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0k/kids.cache
src/kids/cache/__init__.py
undecorate
def undecorate(func): """Returns the decorator and the undecorated function of given object.""" orig_call_wrapper = lambda x: x for call_wrapper, unwrap in SUPPORTED_DECORATOR.items(): if isinstance(func, call_wrapper): func = unwrap(func) orig_call_wrapper = call_wrapper break return orig_call_wrapper, func
python
def undecorate(func): """Returns the decorator and the undecorated function of given object.""" orig_call_wrapper = lambda x: x for call_wrapper, unwrap in SUPPORTED_DECORATOR.items(): if isinstance(func, call_wrapper): func = unwrap(func) orig_call_wrapper = call_wrapper break return orig_call_wrapper, func
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668f3b966877c4a0855d60e05cc3706cf37e4570
https://github.com/0k/kids.cache/blob/668f3b966877c4a0855d60e05cc3706cf37e4570/src/kids/cache/__init__.py#L82-L90
train
idlesign/steampak
steampak/cli.py
item
def item(ctx, appid, title): """Market-related commands.""" ctx.obj['appid'] = appid ctx.obj['title'] = title
python
def item(ctx, appid, title): """Market-related commands.""" ctx.obj['appid'] = appid ctx.obj['title'] = title
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Market-related commands.
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/cli.py#L111-L114
train
idlesign/steampak
steampak/cli.py
get_price
def get_price(ctx, currency): """Prints out market item price.""" appid = ctx.obj['appid'] title = ctx.obj['title'] item_ = Item(appid, title) item_.get_price_data(currency) click.secho('Lowest price: %s %s' % (item_.price_lowest, item_.price_currency), fg='green')
python
def get_price(ctx, currency): """Prints out market item price.""" appid = ctx.obj['appid'] title = ctx.obj['title'] item_ = Item(appid, title) item_.get_price_data(currency) click.secho('Lowest price: %s %s' % (item_.price_lowest, item_.price_currency), fg='green')
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/cli.py#L120-L128
train
idlesign/steampak
steampak/cli.py
get_cards
def get_cards(ctx): """Prints out cards available for application.""" appid = ctx.obj['appid'] app = Application(appid) click.secho('Cards for `%s` [appid: %s]' % (app.title, appid), fg='green') if not app.has_cards: click.secho('This app has no cards.', fg='red', err=True) return cards, booster = app.get_cards() def get_line(card): return '%s [market hash: `%s`]' % (card.title, card.market_hash) for card in cards.values(): click.echo(get_line(card)) if booster: click.secho('* Booster pack: `%s`' % get_line(booster), fg='yellow') click.secho('* Total cards: %d' % len(cards), fg='green')
python
def get_cards(ctx): """Prints out cards available for application.""" appid = ctx.obj['appid'] app = Application(appid) click.secho('Cards for `%s` [appid: %s]' % (app.title, appid), fg='green') if not app.has_cards: click.secho('This app has no cards.', fg='red', err=True) return cards, booster = app.get_cards() def get_line(card): return '%s [market hash: `%s`]' % (card.title, card.market_hash) for card in cards.values(): click.echo(get_line(card)) if booster: click.secho('* Booster pack: `%s`' % get_line(booster), fg='yellow') click.secho('* Total cards: %d' % len(cards), fg='green')
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/cli.py#L141-L164
train
idlesign/steampak
steampak/cli.py
get_card_prices
def get_card_prices(ctx, currency): """Prints out lowest card prices for an application. Comma-separated list of application IDs is supported. """ appid = ctx.obj['appid'] detailed = True appids = [appid] if ',' in appid: appids = [appid.strip() for appid in appid.split(',')] detailed = False for appid in appids: print_card_prices(appid, currency, detailed=detailed) click.echo('')
python
def get_card_prices(ctx, currency): """Prints out lowest card prices for an application. Comma-separated list of application IDs is supported. """ appid = ctx.obj['appid'] detailed = True appids = [appid] if ',' in appid: appids = [appid.strip() for appid in appid.split(',')] detailed = False for appid in appids: print_card_prices(appid, currency, detailed=detailed) click.echo('')
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/cli.py#L170-L186
train
idlesign/steampak
steampak/cli.py
get_gems
def get_gems(ctx): """Prints out total gems count for a Steam user.""" username = ctx.obj['username'] click.secho( 'Total gems owned by `%s`: %d' % (username, User(username).gems_total), fg='green')
python
def get_gems(ctx): """Prints out total gems count for a Steam user.""" username = ctx.obj['username'] click.secho( 'Total gems owned by `%s`: %d' % (username, User(username).gems_total), fg='green')
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Prints out total gems count for a Steam user.
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/cli.py#L199-L205
train
idlesign/steampak
steampak/cli.py
get_games
def get_games(ctx): """Prints out games owned by a Steam user.""" username = ctx.obj['username'] games = User(username).get_games_owned() for game in sorted(games.values(), key=itemgetter('title')): click.echo('%s [appid: %s]' % (game['title'], game['appid'])) click.secho('Total gems owned by `%s`: %d' % (username, len(games)), fg='green')
python
def get_games(ctx): """Prints out games owned by a Steam user.""" username = ctx.obj['username'] games = User(username).get_games_owned() for game in sorted(games.values(), key=itemgetter('title')): click.echo('%s [appid: %s]' % (game['title'], game['appid'])) click.secho('Total gems owned by `%s`: %d' % (username, len(games)), fg='green')
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/cli.py#L210-L219
train
idlesign/steampak
steampak/cli.py
get_booster_stats
def get_booster_stats(ctx, currency): """Prints out price stats for booster packs available in Steam user inventory.""" username = ctx.obj['username'] inventory = User(username)._get_inventory_raw() boosters = {} for item in inventory['rgDescriptions'].values(): is_booster = False tags = item['tags'] for tag in tags: if tag['internal_name'] == TAG_ITEM_CLASS_BOOSTER: is_booster = True break if not is_booster: continue appid = item['market_fee_app'] title = item['name'] boosters[appid] = title if not boosters: click.secho('User `%s` has no booster packs' % username, fg='red', err=True) return for appid, title in boosters.items(): click.secho('Found booster: `%s`' % title, fg='blue') print_card_prices(appid, currency)
python
def get_booster_stats(ctx, currency): """Prints out price stats for booster packs available in Steam user inventory.""" username = ctx.obj['username'] inventory = User(username)._get_inventory_raw() boosters = {} for item in inventory['rgDescriptions'].values(): is_booster = False tags = item['tags'] for tag in tags: if tag['internal_name'] == TAG_ITEM_CLASS_BOOSTER: is_booster = True break if not is_booster: continue appid = item['market_fee_app'] title = item['name'] boosters[appid] = title if not boosters: click.secho('User `%s` has no booster packs' % username, fg='red', err=True) return for appid, title in boosters.items(): click.secho('Found booster: `%s`' % title, fg='blue') print_card_prices(appid, currency)
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Prints out price stats for booster packs available in Steam user inventory.
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/cli.py#L225-L255
train
idlesign/steampak
steampak/cli.py
get_cards_stats
def get_cards_stats(ctx, currency, skip_owned, appid, foil): """Prints out price stats for cards available in Steam user inventory.""" username = ctx.obj['username'] cards_by_app = defaultdict(list) inventory = User(username).traverse_inventory(item_filter=TAG_ITEM_CLASS_CARD) for item in inventory: appid_ = item.app.appid if not appid or appid_ in appid: cards_by_app[appid_].append(item) if not cards_by_app: click.secho('User `%s` has no cards' % username, fg='red', err=True) return for appid_, cards in cards_by_app.items(): app = cards[0].app print_card_prices( app.appid, currency, owned_cards=[card.title for card in cards], skip_owned=skip_owned, foil=foil, )
python
def get_cards_stats(ctx, currency, skip_owned, appid, foil): """Prints out price stats for cards available in Steam user inventory.""" username = ctx.obj['username'] cards_by_app = defaultdict(list) inventory = User(username).traverse_inventory(item_filter=TAG_ITEM_CLASS_CARD) for item in inventory: appid_ = item.app.appid if not appid or appid_ in appid: cards_by_app[appid_].append(item) if not cards_by_app: click.secho('User `%s` has no cards' % username, fg='red', err=True) return for appid_, cards in cards_by_app.items(): app = cards[0].app print_card_prices( app.appid, currency, owned_cards=[card.title for card in cards], skip_owned=skip_owned, foil=foil, )
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/cli.py#L264-L287
train
BD2KGenomics/protect
src/protect/mutation_calling/radia.py
run_radia_with_merge
def run_radia_with_merge(job, rna_bam, tumor_bam, normal_bam, univ_options, radia_options): """ A wrapper for the the entire RADIA sub-graph. :param dict rna_bam: Dict dicts of bam and bai for tumor RNA-Seq obtained by running STAR within ProTECT. :param dict tumor_bam: Dict of bam and bai for tumor DNA-Seq :param dict normal_bam: Dict of bam and bai for normal DNA-Seq :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :return: fsID to the merged RADIA calls :rtype: toil.fileStore.FileID """ spawn = job.wrapJobFn(run_radia, rna_bam['rna_genome'], tumor_bam, normal_bam, univ_options, radia_options, disk='100M', memory='100M').encapsulate() merge = job.wrapJobFn(merge_perchrom_vcfs, spawn.rv(), univ_options, disk='100M', memory='100M') job.addChild(spawn) spawn.addChild(merge) return merge.rv()
python
def run_radia_with_merge(job, rna_bam, tumor_bam, normal_bam, univ_options, radia_options): """ A wrapper for the the entire RADIA sub-graph. :param dict rna_bam: Dict dicts of bam and bai for tumor RNA-Seq obtained by running STAR within ProTECT. :param dict tumor_bam: Dict of bam and bai for tumor DNA-Seq :param dict normal_bam: Dict of bam and bai for normal DNA-Seq :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :return: fsID to the merged RADIA calls :rtype: toil.fileStore.FileID """ spawn = job.wrapJobFn(run_radia, rna_bam['rna_genome'], tumor_bam, normal_bam, univ_options, radia_options, disk='100M', memory='100M').encapsulate() merge = job.wrapJobFn(merge_perchrom_vcfs, spawn.rv(), univ_options, disk='100M', memory='100M') job.addChild(spawn) spawn.addChild(merge) return merge.rv()
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/radia.py#L40-L59
train
BD2KGenomics/protect
src/protect/mutation_calling/radia.py
run_radia
def run_radia(job, rna_bam, tumor_bam, normal_bam, univ_options, radia_options): """ Spawn a RADIA job for each chromosome on the input bam trios. :param dict rna_bam: Dict of bam and bai for tumor DNA-Seq. It can be one of two formats rna_bam: # Just the genomic bam and bai |- 'rna_genome_sorted.bam': fsID +- 'rna_genome_sorted.bam.bai': fsID OR rna_bam: # The output from run_star |- 'rna_transcriptome.bam': fsID |- 'rna_genome': # Only this part will be used |- 'rna_genome_sorted.bam': fsID +- 'rna_genome_sorted.bam.bai': fsID :param dict tumor_bam: Dict of bam and bai for tumor DNA-Seq :param dict normal_bam: Dict of bam and bai for normal DNA-Seq :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :return: Dict of results from running RADIA on every chromosome perchrom_radia: |- 'chr1': fsID |- 'chr2' fsID | |-... | +- 'chrM': fsID :rtype: dict """ if 'rna_genome' in rna_bam.keys(): rna_bam = rna_bam['rna_genome'] elif set(rna_bam.keys()) == {'rna_genome_sorted.bam', 'rna_genome_sorted.bam.bai'}: pass else: raise RuntimeError('An improperly formatted dict was passed to rna_bam.') bams = {'tumor_rna': rna_bam['rna_genome_sorted.bam'], 'tumor_rnai': rna_bam['rna_genome_sorted.bam.bai'], 'tumor_dna': tumor_bam['tumor_dna_fix_pg_sorted.bam'], 'tumor_dnai': tumor_bam['tumor_dna_fix_pg_sorted.bam.bai'], 'normal_dna': normal_bam['normal_dna_fix_pg_sorted.bam'], 'normal_dnai': normal_bam['normal_dna_fix_pg_sorted.bam.bai']} # Get a list of chromosomes to process if radia_options['chromosomes']: chromosomes = radia_options['chromosomes'] else: chromosomes = sample_chromosomes(job, radia_options['genome_fai']) perchrom_radia = defaultdict() for chrom in chromosomes: radia = job.addChildJobFn(run_radia_perchrom, bams, univ_options, radia_options, chrom, memory='6G', disk=PromisedRequirement( radia_disk, tumor_bam['tumor_dna_fix_pg_sorted.bam'], normal_bam['normal_dna_fix_pg_sorted.bam'], rna_bam['rna_genome_sorted.bam'], radia_options['genome_fasta'])) filter_radia = radia.addChildJobFn(run_filter_radia, bams, radia.rv(), univ_options, radia_options, chrom, memory='6G', disk=PromisedRequirement( radia_disk, tumor_bam['tumor_dna_fix_pg_sorted.bam'], normal_bam['normal_dna_fix_pg_sorted.bam'], rna_bam['rna_genome_sorted.bam'], radia_options['genome_fasta'])) perchrom_radia[chrom] = filter_radia.rv() job.fileStore.logToMaster('Ran spawn_radia on %s successfully' % univ_options['patient']) return perchrom_radia
python
def run_radia(job, rna_bam, tumor_bam, normal_bam, univ_options, radia_options): """ Spawn a RADIA job for each chromosome on the input bam trios. :param dict rna_bam: Dict of bam and bai for tumor DNA-Seq. It can be one of two formats rna_bam: # Just the genomic bam and bai |- 'rna_genome_sorted.bam': fsID +- 'rna_genome_sorted.bam.bai': fsID OR rna_bam: # The output from run_star |- 'rna_transcriptome.bam': fsID |- 'rna_genome': # Only this part will be used |- 'rna_genome_sorted.bam': fsID +- 'rna_genome_sorted.bam.bai': fsID :param dict tumor_bam: Dict of bam and bai for tumor DNA-Seq :param dict normal_bam: Dict of bam and bai for normal DNA-Seq :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :return: Dict of results from running RADIA on every chromosome perchrom_radia: |- 'chr1': fsID |- 'chr2' fsID | |-... | +- 'chrM': fsID :rtype: dict """ if 'rna_genome' in rna_bam.keys(): rna_bam = rna_bam['rna_genome'] elif set(rna_bam.keys()) == {'rna_genome_sorted.bam', 'rna_genome_sorted.bam.bai'}: pass else: raise RuntimeError('An improperly formatted dict was passed to rna_bam.') bams = {'tumor_rna': rna_bam['rna_genome_sorted.bam'], 'tumor_rnai': rna_bam['rna_genome_sorted.bam.bai'], 'tumor_dna': tumor_bam['tumor_dna_fix_pg_sorted.bam'], 'tumor_dnai': tumor_bam['tumor_dna_fix_pg_sorted.bam.bai'], 'normal_dna': normal_bam['normal_dna_fix_pg_sorted.bam'], 'normal_dnai': normal_bam['normal_dna_fix_pg_sorted.bam.bai']} # Get a list of chromosomes to process if radia_options['chromosomes']: chromosomes = radia_options['chromosomes'] else: chromosomes = sample_chromosomes(job, radia_options['genome_fai']) perchrom_radia = defaultdict() for chrom in chromosomes: radia = job.addChildJobFn(run_radia_perchrom, bams, univ_options, radia_options, chrom, memory='6G', disk=PromisedRequirement( radia_disk, tumor_bam['tumor_dna_fix_pg_sorted.bam'], normal_bam['normal_dna_fix_pg_sorted.bam'], rna_bam['rna_genome_sorted.bam'], radia_options['genome_fasta'])) filter_radia = radia.addChildJobFn(run_filter_radia, bams, radia.rv(), univ_options, radia_options, chrom, memory='6G', disk=PromisedRequirement( radia_disk, tumor_bam['tumor_dna_fix_pg_sorted.bam'], normal_bam['normal_dna_fix_pg_sorted.bam'], rna_bam['rna_genome_sorted.bam'], radia_options['genome_fasta'])) perchrom_radia[chrom] = filter_radia.rv() job.fileStore.logToMaster('Ran spawn_radia on %s successfully' % univ_options['patient']) return perchrom_radia
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Spawn a RADIA job for each chromosome on the input bam trios. :param dict rna_bam: Dict of bam and bai for tumor DNA-Seq. It can be one of two formats rna_bam: # Just the genomic bam and bai |- 'rna_genome_sorted.bam': fsID +- 'rna_genome_sorted.bam.bai': fsID OR rna_bam: # The output from run_star |- 'rna_transcriptome.bam': fsID |- 'rna_genome': # Only this part will be used |- 'rna_genome_sorted.bam': fsID +- 'rna_genome_sorted.bam.bai': fsID :param dict tumor_bam: Dict of bam and bai for tumor DNA-Seq :param dict normal_bam: Dict of bam and bai for normal DNA-Seq :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :return: Dict of results from running RADIA on every chromosome perchrom_radia: |- 'chr1': fsID |- 'chr2' fsID | |-... | +- 'chrM': fsID :rtype: dict
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/radia.py#L62-L126
train
BD2KGenomics/protect
src/protect/mutation_calling/radia.py
run_radia_perchrom
def run_radia_perchrom(job, bams, univ_options, radia_options, chrom): """ Run RADIA call on a single chromosome in the input bams. :param dict bams: Dict of bam and bai for tumor DNA-Seq, normal DNA-Seq and tumor RNA-Seq :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :param str chrom: Chromosome to process :return: fsID for the chromsome vcf :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() input_files = { 'rna.bam': bams['tumor_rna'], 'rna.bam.bai': bams['tumor_rnai'], 'tumor.bam': bams['tumor_dna'], 'tumor.bam.bai': bams['tumor_dnai'], 'normal.bam': bams['normal_dna'], 'normal.bam.bai': bams['normal_dnai'], 'genome.fa.tar.gz': radia_options['genome_fasta'], 'genome.fa.fai.tar.gz': radia_options['genome_fai']} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) for key in ('genome.fa', 'genome.fa.fai'): input_files[key] = untargz(input_files[key + '.tar.gz'], work_dir) input_files = {key: docker_path(path) for key, path in input_files.items()} radia_output = ''.join([work_dir, '/radia_', chrom, '.vcf']) radia_log = ''.join([work_dir, '/radia_', chrom, '_radia.log']) parameters = [univ_options['patient'], # shortID chrom, '-n', input_files['normal.bam'], '-t', input_files['tumor.bam'], '-r', input_files['rna.bam'], ''.join(['--rnaTumorFasta=', input_files['genome.fa']]), '-f', input_files['genome.fa'], '-o', docker_path(radia_output), '-i', univ_options['ref'], '-m', input_files['genome.fa'], '-d', '[email protected]', '-q', 'Illumina', '--disease', 'CANCER', '-l', 'INFO', '-g', docker_path(radia_log)] docker_call(tool='radia', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=radia_options['version']) output_file = job.fileStore.writeGlobalFile(radia_output) job.fileStore.logToMaster('Ran radia on %s:%s successfully' % (univ_options['patient'], chrom)) return output_file
python
def run_radia_perchrom(job, bams, univ_options, radia_options, chrom): """ Run RADIA call on a single chromosome in the input bams. :param dict bams: Dict of bam and bai for tumor DNA-Seq, normal DNA-Seq and tumor RNA-Seq :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :param str chrom: Chromosome to process :return: fsID for the chromsome vcf :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() input_files = { 'rna.bam': bams['tumor_rna'], 'rna.bam.bai': bams['tumor_rnai'], 'tumor.bam': bams['tumor_dna'], 'tumor.bam.bai': bams['tumor_dnai'], 'normal.bam': bams['normal_dna'], 'normal.bam.bai': bams['normal_dnai'], 'genome.fa.tar.gz': radia_options['genome_fasta'], 'genome.fa.fai.tar.gz': radia_options['genome_fai']} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) for key in ('genome.fa', 'genome.fa.fai'): input_files[key] = untargz(input_files[key + '.tar.gz'], work_dir) input_files = {key: docker_path(path) for key, path in input_files.items()} radia_output = ''.join([work_dir, '/radia_', chrom, '.vcf']) radia_log = ''.join([work_dir, '/radia_', chrom, '_radia.log']) parameters = [univ_options['patient'], # shortID chrom, '-n', input_files['normal.bam'], '-t', input_files['tumor.bam'], '-r', input_files['rna.bam'], ''.join(['--rnaTumorFasta=', input_files['genome.fa']]), '-f', input_files['genome.fa'], '-o', docker_path(radia_output), '-i', univ_options['ref'], '-m', input_files['genome.fa'], '-d', '[email protected]', '-q', 'Illumina', '--disease', 'CANCER', '-l', 'INFO', '-g', docker_path(radia_log)] docker_call(tool='radia', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=radia_options['version']) output_file = job.fileStore.writeGlobalFile(radia_output) job.fileStore.logToMaster('Ran radia on %s:%s successfully' % (univ_options['patient'], chrom)) return output_file
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Run RADIA call on a single chromosome in the input bams. :param dict bams: Dict of bam and bai for tumor DNA-Seq, normal DNA-Seq and tumor RNA-Seq :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :param str chrom: Chromosome to process :return: fsID for the chromsome vcf :rtype: toil.fileStore.FileID
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/radia.py#L129-L178
train
BD2KGenomics/protect
src/protect/mutation_calling/radia.py
run_filter_radia
def run_filter_radia(job, bams, radia_file, univ_options, radia_options, chrom): """ Run filterradia on the RADIA output. :param dict bams: Dict of bam and bai for tumor DNA-Seq, normal DNA-Seq and tumor RNA-Seq :param toil.fileStore.FileID radia_file: The vcf from runnning RADIA :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :param str chrom: Chromosome to process :return: fsID for the filtered chromsome vcf :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() input_files = { 'rna.bam': bams['tumor_rna'], 'rna.bam.bai': bams['tumor_rnai'], 'tumor.bam': bams['tumor_dna'], 'tumor.bam.bai': bams['tumor_dnai'], 'normal.bam': bams['normal_dna'], 'normal.bam.bai': bams['normal_dnai'], 'radia.vcf': radia_file, 'genome.fa.tar.gz': radia_options['genome_fasta'], 'genome.fa.fai.tar.gz': radia_options['genome_fai'], 'cosmic_beds': radia_options['cosmic_beds'], 'dbsnp_beds': radia_options['dbsnp_beds'], 'retrogene_beds': radia_options['retrogene_beds'], 'pseudogene_beds': radia_options['pseudogene_beds'], 'gencode_beds': radia_options['gencode_beds'] } input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) for key in ('genome.fa', 'genome.fa.fai'): input_files[key] = untargz(input_files[key + '.tar.gz'], work_dir) for key in ('cosmic_beds', 'dbsnp_beds', 'retrogene_beds', 'pseudogene_beds', 'gencode_beds'): input_files[key] = untargz(input_files[key], work_dir) input_files = {key: docker_path(path) for key, path in input_files.items()} filterradia_log = ''.join([work_dir, '/radia_filtered_', chrom, '_radia.log']) parameters = [univ_options['patient'], # shortID chrom.lstrip('chr'), input_files['radia.vcf'], '/data', '/home/radia/scripts', '-d', input_files['dbsnp_beds'], '-r', input_files['retrogene_beds'], '-p', input_files['pseudogene_beds'], '-c', input_files['cosmic_beds'], '-t', input_files['gencode_beds'], '--noSnpEff', '--noBlacklist', '--noTargets', '--noRnaBlacklist', '-f', input_files['genome.fa'], '--log=INFO', '-g', docker_path(filterradia_log)] docker_call(tool='filterradia', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=radia_options['version']) output_file = ''.join([work_dir, '/', chrom, '.vcf']) os.rename(''.join([work_dir, '/', univ_options['patient'], '_', chrom, '.vcf']), output_file) output_fsid = job.fileStore.writeGlobalFile(output_file) export_results(job, output_fsid, output_file, univ_options, subfolder='mutations/radia') job.fileStore.logToMaster('Ran filter-radia on %s:%s successfully' % (univ_options['patient'], chrom)) return output_fsid
python
def run_filter_radia(job, bams, radia_file, univ_options, radia_options, chrom): """ Run filterradia on the RADIA output. :param dict bams: Dict of bam and bai for tumor DNA-Seq, normal DNA-Seq and tumor RNA-Seq :param toil.fileStore.FileID radia_file: The vcf from runnning RADIA :param dict univ_options: Dict of universal options used by almost all tools :param dict radia_options: Options specific to RADIA :param str chrom: Chromosome to process :return: fsID for the filtered chromsome vcf :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() input_files = { 'rna.bam': bams['tumor_rna'], 'rna.bam.bai': bams['tumor_rnai'], 'tumor.bam': bams['tumor_dna'], 'tumor.bam.bai': bams['tumor_dnai'], 'normal.bam': bams['normal_dna'], 'normal.bam.bai': bams['normal_dnai'], 'radia.vcf': radia_file, 'genome.fa.tar.gz': radia_options['genome_fasta'], 'genome.fa.fai.tar.gz': radia_options['genome_fai'], 'cosmic_beds': radia_options['cosmic_beds'], 'dbsnp_beds': radia_options['dbsnp_beds'], 'retrogene_beds': radia_options['retrogene_beds'], 'pseudogene_beds': radia_options['pseudogene_beds'], 'gencode_beds': radia_options['gencode_beds'] } input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) for key in ('genome.fa', 'genome.fa.fai'): input_files[key] = untargz(input_files[key + '.tar.gz'], work_dir) for key in ('cosmic_beds', 'dbsnp_beds', 'retrogene_beds', 'pseudogene_beds', 'gencode_beds'): input_files[key] = untargz(input_files[key], work_dir) input_files = {key: docker_path(path) for key, path in input_files.items()} filterradia_log = ''.join([work_dir, '/radia_filtered_', chrom, '_radia.log']) parameters = [univ_options['patient'], # shortID chrom.lstrip('chr'), input_files['radia.vcf'], '/data', '/home/radia/scripts', '-d', input_files['dbsnp_beds'], '-r', input_files['retrogene_beds'], '-p', input_files['pseudogene_beds'], '-c', input_files['cosmic_beds'], '-t', input_files['gencode_beds'], '--noSnpEff', '--noBlacklist', '--noTargets', '--noRnaBlacklist', '-f', input_files['genome.fa'], '--log=INFO', '-g', docker_path(filterradia_log)] docker_call(tool='filterradia', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=radia_options['version']) output_file = ''.join([work_dir, '/', chrom, '.vcf']) os.rename(''.join([work_dir, '/', univ_options['patient'], '_', chrom, '.vcf']), output_file) output_fsid = job.fileStore.writeGlobalFile(output_file) export_results(job, output_fsid, output_file, univ_options, subfolder='mutations/radia') job.fileStore.logToMaster('Ran filter-radia on %s:%s successfully' % (univ_options['patient'], chrom)) return output_fsid
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/radia.py#L181-L246
train
BD2KGenomics/protect
src/protect/alignment/common.py
index_bamfile
def index_bamfile(job, bamfile, sample_type, univ_options, samtools_options, sample_info=None, export=True): """ Index `bamfile` using samtools :param toil.fileStore.FileID bamfile: fsID for the bam file :param str sample_type: Description of the sample to inject into the filename :param dict univ_options: Dict of universal options used by almost all tools :param dict samtools_options: Options specific to samtools :param str sample_info: Information regarding the sample that will beinjected into the filename as `sample_type`_`sample_info`.bam(.bai) :param bool export: Should the bam and bai be exported to the output directory? :return: Dict containing input bam and the generated index (.bam.bai) output_files: |- '<sample_type>(_<sample_info>).bam': fsID +- '<sample_type>(_<sample_info>).bam.bai': fsID :rtype: dict """ work_dir = os.getcwd() in_bamfile = sample_type if sample_info is not None: assert isinstance(sample_info, str) in_bamfile = '_'.join([in_bamfile, sample_info]) in_bamfile += '.bam' input_files = { in_bamfile: bamfile} input_files = get_files_from_filestore(job, input_files, work_dir, docker=True) parameters = ['index', input_files[in_bamfile]] docker_call(tool='samtools', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=samtools_options['version']) out_bai = '/'.join([work_dir, in_bamfile + '.bai']) output_files = {in_bamfile: bamfile, in_bamfile + '.bai': job.fileStore.writeGlobalFile(out_bai)} if export: export_results(job, bamfile, os.path.splitext(out_bai)[0], univ_options, subfolder='alignments') export_results(job, output_files[in_bamfile + '.bai'], out_bai, univ_options, subfolder='alignments') job.fileStore.logToMaster('Ran samtools-index on %s:%s successfully' % (univ_options['patient'], sample_type)) return output_files
python
def index_bamfile(job, bamfile, sample_type, univ_options, samtools_options, sample_info=None, export=True): """ Index `bamfile` using samtools :param toil.fileStore.FileID bamfile: fsID for the bam file :param str sample_type: Description of the sample to inject into the filename :param dict univ_options: Dict of universal options used by almost all tools :param dict samtools_options: Options specific to samtools :param str sample_info: Information regarding the sample that will beinjected into the filename as `sample_type`_`sample_info`.bam(.bai) :param bool export: Should the bam and bai be exported to the output directory? :return: Dict containing input bam and the generated index (.bam.bai) output_files: |- '<sample_type>(_<sample_info>).bam': fsID +- '<sample_type>(_<sample_info>).bam.bai': fsID :rtype: dict """ work_dir = os.getcwd() in_bamfile = sample_type if sample_info is not None: assert isinstance(sample_info, str) in_bamfile = '_'.join([in_bamfile, sample_info]) in_bamfile += '.bam' input_files = { in_bamfile: bamfile} input_files = get_files_from_filestore(job, input_files, work_dir, docker=True) parameters = ['index', input_files[in_bamfile]] docker_call(tool='samtools', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=samtools_options['version']) out_bai = '/'.join([work_dir, in_bamfile + '.bai']) output_files = {in_bamfile: bamfile, in_bamfile + '.bai': job.fileStore.writeGlobalFile(out_bai)} if export: export_results(job, bamfile, os.path.splitext(out_bai)[0], univ_options, subfolder='alignments') export_results(job, output_files[in_bamfile + '.bai'], out_bai, univ_options, subfolder='alignments') job.fileStore.logToMaster('Ran samtools-index on %s:%s successfully' % (univ_options['patient'], sample_type)) return output_files
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[ "Index", "bamfile", "using", "samtools" ]
06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/alignment/common.py#L33-L74
train
BD2KGenomics/protect
src/protect/alignment/common.py
sort_bamfile
def sort_bamfile(job, bamfile, sample_type, univ_options, samtools_options): """ Sort `bamfile` using samtools :param toil.fileStore.FileID bamfile: fsID for the bam file :param str sample_type: Description of the sample to inject into the filename :param dict univ_options: Dict of universal options used by almost all tools :param dict samtools_options: Options specific to samtools :return: fsID for the sorted bamfile :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() in_bamfile = ''.join([sample_type, '.bam']) out_bamfile = '_'.join([sample_type, 'sorted.bam']) input_files = { in_bamfile: bamfile} input_files = get_files_from_filestore(job, input_files, work_dir, docker=True) parameters = ['sort', '-o', docker_path(out_bamfile), '-O', 'bam', '-T', 'temp_sorted', '-@', str(samtools_options['n']), input_files[in_bamfile]] docker_call(tool='samtools', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=samtools_options['version']) job.fileStore.deleteGlobalFile(bamfile) job.fileStore.logToMaster('Ran samtools-sort on %s:%s successfully' % (univ_options['patient'], sample_type)) return job.fileStore.writeGlobalFile(out_bamfile)
python
def sort_bamfile(job, bamfile, sample_type, univ_options, samtools_options): """ Sort `bamfile` using samtools :param toil.fileStore.FileID bamfile: fsID for the bam file :param str sample_type: Description of the sample to inject into the filename :param dict univ_options: Dict of universal options used by almost all tools :param dict samtools_options: Options specific to samtools :return: fsID for the sorted bamfile :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() in_bamfile = ''.join([sample_type, '.bam']) out_bamfile = '_'.join([sample_type, 'sorted.bam']) input_files = { in_bamfile: bamfile} input_files = get_files_from_filestore(job, input_files, work_dir, docker=True) parameters = ['sort', '-o', docker_path(out_bamfile), '-O', 'bam', '-T', 'temp_sorted', '-@', str(samtools_options['n']), input_files[in_bamfile]] docker_call(tool='samtools', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=samtools_options['version']) job.fileStore.deleteGlobalFile(bamfile) job.fileStore.logToMaster('Ran samtools-sort on %s:%s successfully' % (univ_options['patient'], sample_type)) return job.fileStore.writeGlobalFile(out_bamfile)
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[ "Sort", "bamfile", "using", "samtools" ]
06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/alignment/common.py#L77-L105
train
inveniosoftware/invenio-access
invenio_access/utils.py
get_identity
def get_identity(user): """Create an identity for a given user instance. Primarily useful for testing. """ identity = Identity(user.id) if hasattr(user, 'id'): identity.provides.add(UserNeed(user.id)) for role in getattr(user, 'roles', []): identity.provides.add(RoleNeed(role.name)) identity.user = user return identity
python
def get_identity(user): """Create an identity for a given user instance. Primarily useful for testing. """ identity = Identity(user.id) if hasattr(user, 'id'): identity.provides.add(UserNeed(user.id)) for role in getattr(user, 'roles', []): identity.provides.add(RoleNeed(role.name)) identity.user = user return identity
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Create an identity for a given user instance. Primarily useful for testing.
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3b033a4bdc110eb2f7e9f08f0744a780884bfc80
https://github.com/inveniosoftware/invenio-access/blob/3b033a4bdc110eb2f7e9f08f0744a780884bfc80/invenio_access/utils.py#L16-L30
train
adfinis-sygroup/freeze
freeze/xfreeze.py
object_to_items
def object_to_items(data_structure): """Converts a object to a items list respecting also slots. Use dict(object_to_items(obj)) to get a dictionary.""" items = [] # Get all items from dict try: items = list(data_structure.__dict__.items()) except: pass # Get all slots hierarchy = [data_structure] try: hierarchy += inspect.getmro(data_structure) except: pass slots = [] try: for b in hierarchy: try: slots += b.__slots__ except: # pragma: no cover pass except: # pragma: no cover pass # Get attrs from slots for x in slots: items.append((x, getattr(data_structure, x))) return items
python
def object_to_items(data_structure): """Converts a object to a items list respecting also slots. Use dict(object_to_items(obj)) to get a dictionary.""" items = [] # Get all items from dict try: items = list(data_structure.__dict__.items()) except: pass # Get all slots hierarchy = [data_structure] try: hierarchy += inspect.getmro(data_structure) except: pass slots = [] try: for b in hierarchy: try: slots += b.__slots__ except: # pragma: no cover pass except: # pragma: no cover pass # Get attrs from slots for x in slots: items.append((x, getattr(data_structure, x))) return items
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Converts a object to a items list respecting also slots. Use dict(object_to_items(obj)) to get a dictionary.
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61b4fab8a90ed76d685448723baaa57e2bbd5ef9
https://github.com/adfinis-sygroup/freeze/blob/61b4fab8a90ed76d685448723baaa57e2bbd5ef9/freeze/xfreeze.py#L251-L279
train
adfinis-sygroup/freeze
freeze/xfreeze.py
recursive_sort
def recursive_sort(data_structure): """Sort a recursive data_structure. :param data_structure: The structure to convert. data_structure must be already sortable or you must use freeze() or dump(). The function will work with many kinds of input. Dictionaries will be converted to lists of tuples. >>> _py2_to_py3(vformat(recursive_sort(dump( ... [3, 1, {'c' : 'c', 'a' : 'b', 'b' : 'a'}] ... )))) (["<class 'dict'>", (('a', 'b'), ('b', 'a'), ('c', 'c'))], 1, 3) >>> recursive_sort([3, 1, {'c' : 'c', 'a' : 'b', 'b' : 'a'}]) ((('a', 'b'), ('b', 'a'), ('c', 'c')), 1, 3) >>> recursive_sort(_TestClass()) (('a', 'huhu'),) """ # We don't sory primitve types if not isinstance(data_structure, _primitive_types): is_meta = isinstance(data_structure, Meta) was_dict = isinstance(data_structure, WasDict) if not (is_meta or was_dict): was_dict = isinstance(data_structure, dict) if not was_dict: # Dictize if possible (support objects) try: data_structure = data_structure.__dict__ was_dict = True except: pass # Itemize if possible try: data_structure = data_structure.items() except: pass tlen = -1 # If item has a length we sort it try: tlen = len(data_structure) except: # pragma: no cover pass if tlen != -1: # Well there are classes out in the wild that answer to len # but have no indexer. try: if was_dict: return tuple(sorted( [ ( recursive_sort(x[0]), recursive_sort(x[1]), ) for x in data_structure ], key=TraversalBasedReprCompare )) elif is_meta: return data_structure[0:-1] + [ recursive_sort( data_structure[-1] ) ] else: return tuple(sorted( [recursive_sort( x, ) for x in data_structure], key=TraversalBasedReprCompare, )) except: # pragma: no cover pass return data_structure
python
def recursive_sort(data_structure): """Sort a recursive data_structure. :param data_structure: The structure to convert. data_structure must be already sortable or you must use freeze() or dump(). The function will work with many kinds of input. Dictionaries will be converted to lists of tuples. >>> _py2_to_py3(vformat(recursive_sort(dump( ... [3, 1, {'c' : 'c', 'a' : 'b', 'b' : 'a'}] ... )))) (["<class 'dict'>", (('a', 'b'), ('b', 'a'), ('c', 'c'))], 1, 3) >>> recursive_sort([3, 1, {'c' : 'c', 'a' : 'b', 'b' : 'a'}]) ((('a', 'b'), ('b', 'a'), ('c', 'c')), 1, 3) >>> recursive_sort(_TestClass()) (('a', 'huhu'),) """ # We don't sory primitve types if not isinstance(data_structure, _primitive_types): is_meta = isinstance(data_structure, Meta) was_dict = isinstance(data_structure, WasDict) if not (is_meta or was_dict): was_dict = isinstance(data_structure, dict) if not was_dict: # Dictize if possible (support objects) try: data_structure = data_structure.__dict__ was_dict = True except: pass # Itemize if possible try: data_structure = data_structure.items() except: pass tlen = -1 # If item has a length we sort it try: tlen = len(data_structure) except: # pragma: no cover pass if tlen != -1: # Well there are classes out in the wild that answer to len # but have no indexer. try: if was_dict: return tuple(sorted( [ ( recursive_sort(x[0]), recursive_sort(x[1]), ) for x in data_structure ], key=TraversalBasedReprCompare )) elif is_meta: return data_structure[0:-1] + [ recursive_sort( data_structure[-1] ) ] else: return tuple(sorted( [recursive_sort( x, ) for x in data_structure], key=TraversalBasedReprCompare, )) except: # pragma: no cover pass return data_structure
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Sort a recursive data_structure. :param data_structure: The structure to convert. data_structure must be already sortable or you must use freeze() or dump(). The function will work with many kinds of input. Dictionaries will be converted to lists of tuples. >>> _py2_to_py3(vformat(recursive_sort(dump( ... [3, 1, {'c' : 'c', 'a' : 'b', 'b' : 'a'}] ... )))) (["<class 'dict'>", (('a', 'b'), ('b', 'a'), ('c', 'c'))], 1, 3) >>> recursive_sort([3, 1, {'c' : 'c', 'a' : 'b', 'b' : 'a'}]) ((('a', 'b'), ('b', 'a'), ('c', 'c')), 1, 3) >>> recursive_sort(_TestClass()) (('a', 'huhu'),)
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61b4fab8a90ed76d685448723baaa57e2bbd5ef9
https://github.com/adfinis-sygroup/freeze/blob/61b4fab8a90ed76d685448723baaa57e2bbd5ef9/freeze/xfreeze.py#L531-L611
train
adfinis-sygroup/freeze
freeze/xfreeze.py
traverse_frozen_data
def traverse_frozen_data(data_structure): """Yields the leaves of the frozen data-structure pre-order. It will produce the same order as one would write the data-structure.""" parent_stack = [data_structure] while parent_stack: node = parent_stack.pop(0) # We don't iterate strings tlen = -1 if not isinstance(node, _string_types): # If item has a length we freeze it try: tlen = len(node) except: pass if tlen == -1: yield node else: parent_stack = list(node) + parent_stack
python
def traverse_frozen_data(data_structure): """Yields the leaves of the frozen data-structure pre-order. It will produce the same order as one would write the data-structure.""" parent_stack = [data_structure] while parent_stack: node = parent_stack.pop(0) # We don't iterate strings tlen = -1 if not isinstance(node, _string_types): # If item has a length we freeze it try: tlen = len(node) except: pass if tlen == -1: yield node else: parent_stack = list(node) + parent_stack
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Yields the leaves of the frozen data-structure pre-order. It will produce the same order as one would write the data-structure.
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61b4fab8a90ed76d685448723baaa57e2bbd5ef9
https://github.com/adfinis-sygroup/freeze/blob/61b4fab8a90ed76d685448723baaa57e2bbd5ef9/freeze/xfreeze.py#L665-L683
train
adfinis-sygroup/freeze
freeze/xfreeze.py
tree_diff
def tree_diff(a, b, n=5, sort=False): """Dump any data-structure or object, traverse it depth-first in-order and apply a unified diff. Depth-first in-order is just like structure would be printed. :param a: data_structure a :param b: data_structure b :param n: lines of context :type n: int :param sort: sort the data-structure ATTENTION: Sorting means changing the data-structure. The test-result may differ. But in case of dictionaries the results become comparable because the sorting negates the hash-algorithms "de-sorting". >>> a = recursive_sort(freeze([ ... 'a', ... [3, 4], ... {'a': [3, {'w' : set([4, '3', frozenset([3,5,2])])}]}, ... [] ... ])) >>> b = recursive_sort(freeze([ ... 'a', ... [7, 3], ... {'a': [3, {'w' : set([4, '3', frozenset([2,5,3])])}]}, ... [] ... ])) >>> transparent_repr("\\n".join(tree_diff(a, b).split("\\n")[2:])) @@ -7,6 +7,6 @@ 'w'),), 3), 'a'),), 'a', (3, - 4)) + 7)) >>> a = [ ... 'a', ... [3, 4], ... {'a': [3, {'w' : set([4, '3', frozenset([3,5,2])])}]}, ... [] ... ] >>> b = [ ... 'a', ... [7, 3], ... {'a': [3, {'w' : set([4, '3', frozenset([2,5,3])])}]}, ... [] ... ] >>> transparent_repr("\\n".join( ... tree_diff(a, b, sort=True ... ).split("\\n")[2:])) @@ -11,6 +11,6 @@ '3', 4)]),)], 3)),)], 'a', (3, - 4)) + 7)) """ a = dump(a) b = dump(b) if not sort: a = vformat(a).split("\n") b = vformat(b).split("\n") else: a = vformat(recursive_sort(a)).split("\n") b = vformat(recursive_sort(b)).split("\n") return "\n".join(difflib.unified_diff(a, b, n=n, lineterm=""))
python
def tree_diff(a, b, n=5, sort=False): """Dump any data-structure or object, traverse it depth-first in-order and apply a unified diff. Depth-first in-order is just like structure would be printed. :param a: data_structure a :param b: data_structure b :param n: lines of context :type n: int :param sort: sort the data-structure ATTENTION: Sorting means changing the data-structure. The test-result may differ. But in case of dictionaries the results become comparable because the sorting negates the hash-algorithms "de-sorting". >>> a = recursive_sort(freeze([ ... 'a', ... [3, 4], ... {'a': [3, {'w' : set([4, '3', frozenset([3,5,2])])}]}, ... [] ... ])) >>> b = recursive_sort(freeze([ ... 'a', ... [7, 3], ... {'a': [3, {'w' : set([4, '3', frozenset([2,5,3])])}]}, ... [] ... ])) >>> transparent_repr("\\n".join(tree_diff(a, b).split("\\n")[2:])) @@ -7,6 +7,6 @@ 'w'),), 3), 'a'),), 'a', (3, - 4)) + 7)) >>> a = [ ... 'a', ... [3, 4], ... {'a': [3, {'w' : set([4, '3', frozenset([3,5,2])])}]}, ... [] ... ] >>> b = [ ... 'a', ... [7, 3], ... {'a': [3, {'w' : set([4, '3', frozenset([2,5,3])])}]}, ... [] ... ] >>> transparent_repr("\\n".join( ... tree_diff(a, b, sort=True ... ).split("\\n")[2:])) @@ -11,6 +11,6 @@ '3', 4)]),)], 3)),)], 'a', (3, - 4)) + 7)) """ a = dump(a) b = dump(b) if not sort: a = vformat(a).split("\n") b = vformat(b).split("\n") else: a = vformat(recursive_sort(a)).split("\n") b = vformat(recursive_sort(b)).split("\n") return "\n".join(difflib.unified_diff(a, b, n=n, lineterm=""))
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61b4fab8a90ed76d685448723baaa57e2bbd5ef9
https://github.com/adfinis-sygroup/freeze/blob/61b4fab8a90ed76d685448723baaa57e2bbd5ef9/freeze/xfreeze.py#L752-L823
train
idlesign/steampak
steampak/libsteam/resources/groups.py
Group.stats
def stats(self): """Basic group statistics. Returned dict has the following keys: 'online' - users online count 'ingame' - users currently in game count 'chatting' - users chatting count :return: dict """ stats_online = CRef.cint() stats_ingame = CRef.cint() stats_chatting = CRef.cint() self._iface.get_clan_stats( self.group_id, stats_online, stats_ingame, stats_chatting, ) return { 'online': int(stats_online), 'ingame': int(stats_ingame), 'chatting': int(stats_chatting), }
python
def stats(self): """Basic group statistics. Returned dict has the following keys: 'online' - users online count 'ingame' - users currently in game count 'chatting' - users chatting count :return: dict """ stats_online = CRef.cint() stats_ingame = CRef.cint() stats_chatting = CRef.cint() self._iface.get_clan_stats( self.group_id, stats_online, stats_ingame, stats_chatting, ) return { 'online': int(stats_online), 'ingame': int(stats_ingame), 'chatting': int(stats_chatting), }
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Basic group statistics. Returned dict has the following keys: 'online' - users online count 'ingame' - users currently in game count 'chatting' - users chatting count :return: dict
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/libsteam/resources/groups.py#L24-L50
train
budacom/trading-bots
trading_bots/core/management/__init__.py
startproject
def startproject(name, directory, verbosity): """ Creates a Trading-Bots project directory structure for the given project NAME in the current directory or optionally in the given DIRECTORY. """ handle_template('project', name, target=directory, verbosity=verbosity) click.echo(f"Success: '{name}' project was successfully created on '{directory}'")
python
def startproject(name, directory, verbosity): """ Creates a Trading-Bots project directory structure for the given project NAME in the current directory or optionally in the given DIRECTORY. """ handle_template('project', name, target=directory, verbosity=verbosity) click.echo(f"Success: '{name}' project was successfully created on '{directory}'")
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Creates a Trading-Bots project directory structure for the given project NAME in the current directory or optionally in the given DIRECTORY.
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8cb68bb8d0b5f822108db1cc5dae336e3d3c3452
https://github.com/budacom/trading-bots/blob/8cb68bb8d0b5f822108db1cc5dae336e3d3c3452/trading_bots/core/management/__init__.py#L101-L107
train
budacom/trading-bots
trading_bots/core/management/__init__.py
createbot
def createbot(name, directory, verbosity): """ Creates a Bot's directory structure for the given bot NAME in the current directory or optionally in the given DIRECTORY. """ handle_template('bot', name, target=directory, verbosity=verbosity) click.echo(f"Success: '{name}' bot was successfully created on '{directory}'")
python
def createbot(name, directory, verbosity): """ Creates a Bot's directory structure for the given bot NAME in the current directory or optionally in the given DIRECTORY. """ handle_template('bot', name, target=directory, verbosity=verbosity) click.echo(f"Success: '{name}' bot was successfully created on '{directory}'")
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Creates a Bot's directory structure for the given bot NAME in the current directory or optionally in the given DIRECTORY.
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8cb68bb8d0b5f822108db1cc5dae336e3d3c3452
https://github.com/budacom/trading-bots/blob/8cb68bb8d0b5f822108db1cc5dae336e3d3c3452/trading_bots/core/management/__init__.py#L114-L120
train
idlesign/steampak
steampak/libsteam/resources/user.py
User.get_state
def get_state(self, as_str=False): """Returns user state. See ``UserState``. :param bool as_str: Return human-friendly state name instead of an ID. :rtype: int|str """ uid = self.user_id if self._iface_user.get_id() == uid: result = self._iface.get_my_state() else: result = self._iface.get_state(uid) if as_str: return UserState.get_alias(result) return result
python
def get_state(self, as_str=False): """Returns user state. See ``UserState``. :param bool as_str: Return human-friendly state name instead of an ID. :rtype: int|str """ uid = self.user_id if self._iface_user.get_id() == uid: result = self._iface.get_my_state() else: result = self._iface.get_state(uid) if as_str: return UserState.get_alias(result) return result
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Returns user state. See ``UserState``. :param bool as_str: Return human-friendly state name instead of an ID. :rtype: int|str
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/libsteam/resources/user.py#L95-L113
train
inveniosoftware/invenio-access
invenio_access/loaders.py
load_permissions_on_identity_loaded
def load_permissions_on_identity_loaded(sender, identity): """Add system roles "Needs" to users' identities. Every user gets the **any_user** Need. Authenticated users get in addition the **authenticated_user** Need. """ identity.provides.add( any_user ) # if the user is not anonymous if current_user.is_authenticated: # Add the need provided to authenticated users identity.provides.add( authenticated_user )
python
def load_permissions_on_identity_loaded(sender, identity): """Add system roles "Needs" to users' identities. Every user gets the **any_user** Need. Authenticated users get in addition the **authenticated_user** Need. """ identity.provides.add( any_user ) # if the user is not anonymous if current_user.is_authenticated: # Add the need provided to authenticated users identity.provides.add( authenticated_user )
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Add system roles "Needs" to users' identities. Every user gets the **any_user** Need. Authenticated users get in addition the **authenticated_user** Need.
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3b033a4bdc110eb2f7e9f08f0744a780884bfc80
https://github.com/inveniosoftware/invenio-access/blob/3b033a4bdc110eb2f7e9f08f0744a780884bfc80/invenio_access/loaders.py#L15-L29
train
HEPData/hepdata-validator
hepdata_validator/__init__.py
Validator.print_errors
def print_errors(self, file_name): """ Prints the errors observed for a file """ for error in self.get_messages(file_name): print('\t', error.__unicode__())
python
def print_errors(self, file_name): """ Prints the errors observed for a file """ for error in self.get_messages(file_name): print('\t', error.__unicode__())
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Prints the errors observed for a file
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d0b0cab742a009c8f0e8aac9f8c8e434a524d43c
https://github.com/HEPData/hepdata-validator/blob/d0b0cab742a009c8f0e8aac9f8c8e434a524d43c/hepdata_validator/__init__.py#L98-L103
train
bkg/django-spillway
spillway/forms/forms.py
RasterQueryForm.clean
def clean(self): """Return cleaned fields as a dict, determine which geom takes precedence. """ data = super(RasterQueryForm, self).clean() geom = data.pop('upload', None) or data.pop('bbox', None) if geom: data['g'] = geom return data
python
def clean(self): """Return cleaned fields as a dict, determine which geom takes precedence. """ data = super(RasterQueryForm, self).clean() geom = data.pop('upload', None) or data.pop('bbox', None) if geom: data['g'] = geom return data
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Return cleaned fields as a dict, determine which geom takes precedence.
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c488a62642430b005f1e0d4a19e160d8d5964b67
https://github.com/bkg/django-spillway/blob/c488a62642430b005f1e0d4a19e160d8d5964b67/spillway/forms/forms.py#L125-L133
train
drslump/pyshould
pyshould/matchers.py
register
def register(matcher, *aliases): """ Register a matcher associated to one or more aliases. Each alias given is also normalized. """ docstr = matcher.__doc__ if matcher.__doc__ is not None else '' helpmatchers[matcher] = docstr.strip() for alias in aliases: matchers[alias] = matcher # Map a normalized version of the alias norm = normalize(alias) normalized[norm] = alias # Map a version without snake case norm = norm.replace('_', '') normalized[norm] = alias
python
def register(matcher, *aliases): """ Register a matcher associated to one or more aliases. Each alias given is also normalized. """ docstr = matcher.__doc__ if matcher.__doc__ is not None else '' helpmatchers[matcher] = docstr.strip() for alias in aliases: matchers[alias] = matcher # Map a normalized version of the alias norm = normalize(alias) normalized[norm] = alias # Map a version without snake case norm = norm.replace('_', '') normalized[norm] = alias
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Register a matcher associated to one or more aliases. Each alias given is also normalized.
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7210859d4c84cfbaa64f91b30c2a541aea788ddf
https://github.com/drslump/pyshould/blob/7210859d4c84cfbaa64f91b30c2a541aea788ddf/pyshould/matchers.py#L54-L68
train
drslump/pyshould
pyshould/matchers.py
normalize
def normalize(alias): """ Normalizes an alias by removing adverbs defined in IGNORED_WORDS """ # Convert from CamelCase to snake_case alias = re.sub(r'([a-z])([A-Z])', r'\1_\2', alias) # Ignore words words = alias.lower().split('_') words = filter(lambda w: w not in IGNORED_WORDS, words) return '_'.join(words)
python
def normalize(alias): """ Normalizes an alias by removing adverbs defined in IGNORED_WORDS """ # Convert from CamelCase to snake_case alias = re.sub(r'([a-z])([A-Z])', r'\1_\2', alias) # Ignore words words = alias.lower().split('_') words = filter(lambda w: w not in IGNORED_WORDS, words) return '_'.join(words)
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Normalizes an alias by removing adverbs defined in IGNORED_WORDS
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7210859d4c84cfbaa64f91b30c2a541aea788ddf
https://github.com/drslump/pyshould/blob/7210859d4c84cfbaa64f91b30c2a541aea788ddf/pyshould/matchers.py#L94-L102
train
drslump/pyshould
pyshould/matchers.py
lookup
def lookup(alias): """ Tries to find a matcher callable associated to the given alias. If an exact match does not exists it will try normalizing it and even removing underscores to find one. """ if alias in matchers: return matchers[alias] else: norm = normalize(alias) if norm in normalized: alias = normalized[norm] return matchers[alias] # Check without snake case if -1 != alias.find('_'): norm = normalize(alias).replace('_', '') return lookup(norm) return None
python
def lookup(alias): """ Tries to find a matcher callable associated to the given alias. If an exact match does not exists it will try normalizing it and even removing underscores to find one. """ if alias in matchers: return matchers[alias] else: norm = normalize(alias) if norm in normalized: alias = normalized[norm] return matchers[alias] # Check without snake case if -1 != alias.find('_'): norm = normalize(alias).replace('_', '') return lookup(norm) return None
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Tries to find a matcher callable associated to the given alias. If an exact match does not exists it will try normalizing it and even removing underscores to find one.
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7210859d4c84cfbaa64f91b30c2a541aea788ddf
https://github.com/drslump/pyshould/blob/7210859d4c84cfbaa64f91b30c2a541aea788ddf/pyshould/matchers.py#L105-L124
train
drslump/pyshould
pyshould/matchers.py
suggest
def suggest(alias, max=3, cutoff=0.5): """ Suggest a list of aliases which are similar enough """ aliases = matchers.keys() similar = get_close_matches(alias, aliases, n=max, cutoff=cutoff) return similar
python
def suggest(alias, max=3, cutoff=0.5): """ Suggest a list of aliases which are similar enough """ aliases = matchers.keys() similar = get_close_matches(alias, aliases, n=max, cutoff=cutoff) return similar
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Suggest a list of aliases which are similar enough
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7210859d4c84cfbaa64f91b30c2a541aea788ddf
https://github.com/drslump/pyshould/blob/7210859d4c84cfbaa64f91b30c2a541aea788ddf/pyshould/matchers.py#L127-L134
train
BD2KGenomics/protect
src/protect/mutation_calling/common.py
sample_chromosomes
def sample_chromosomes(job, genome_fai_file): """ Get a list of chromosomes in the input data. :param toil.fileStore.FileID genome_fai_file: Job store file ID for the genome fai file :return: Chromosomes in the sample :rtype: list[str] """ work_dir = os.getcwd() genome_fai = untargz(job.fileStore.readGlobalFile(genome_fai_file), work_dir) return chromosomes_from_fai(genome_fai)
python
def sample_chromosomes(job, genome_fai_file): """ Get a list of chromosomes in the input data. :param toil.fileStore.FileID genome_fai_file: Job store file ID for the genome fai file :return: Chromosomes in the sample :rtype: list[str] """ work_dir = os.getcwd() genome_fai = untargz(job.fileStore.readGlobalFile(genome_fai_file), work_dir) return chromosomes_from_fai(genome_fai)
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Get a list of chromosomes in the input data. :param toil.fileStore.FileID genome_fai_file: Job store file ID for the genome fai file :return: Chromosomes in the sample :rtype: list[str]
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/common.py#L25-L35
train
BD2KGenomics/protect
src/protect/mutation_calling/common.py
run_mutation_aggregator
def run_mutation_aggregator(job, mutation_results, univ_options): """ Aggregate all the called mutations. :param dict mutation_results: Dict of dicts of the various mutation callers in a per chromosome format :param dict univ_options: Dict of universal options used by almost all tools :returns: fsID for the merged mutations file :rtype: toil.fileStore.FileID """ # Setup an input data structure for the merge function out = {} for chrom in mutation_results['mutect'].keys(): out[chrom] = job.addChildJobFn(merge_perchrom_mutations, chrom, mutation_results, univ_options).rv() merged_snvs = job.addFollowOnJobFn(merge_perchrom_vcfs, out, 'merged', univ_options) job.fileStore.logToMaster('Aggregated mutations for %s successfully' % univ_options['patient']) return merged_snvs.rv()
python
def run_mutation_aggregator(job, mutation_results, univ_options): """ Aggregate all the called mutations. :param dict mutation_results: Dict of dicts of the various mutation callers in a per chromosome format :param dict univ_options: Dict of universal options used by almost all tools :returns: fsID for the merged mutations file :rtype: toil.fileStore.FileID """ # Setup an input data structure for the merge function out = {} for chrom in mutation_results['mutect'].keys(): out[chrom] = job.addChildJobFn(merge_perchrom_mutations, chrom, mutation_results, univ_options).rv() merged_snvs = job.addFollowOnJobFn(merge_perchrom_vcfs, out, 'merged', univ_options) job.fileStore.logToMaster('Aggregated mutations for %s successfully' % univ_options['patient']) return merged_snvs.rv()
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Aggregate all the called mutations. :param dict mutation_results: Dict of dicts of the various mutation callers in a per chromosome format :param dict univ_options: Dict of universal options used by almost all tools :returns: fsID for the merged mutations file :rtype: toil.fileStore.FileID
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/common.py#L54-L71
train
BD2KGenomics/protect
src/protect/mutation_calling/common.py
merge_perchrom_mutations
def merge_perchrom_mutations(job, chrom, mutations, univ_options): """ Merge the mutation calls for a single chromosome. :param str chrom: Chromosome to process :param dict mutations: dict of dicts of the various mutation caller names as keys, and a dict of per chromosome job store ids for vcfs as value :param dict univ_options: Dict of universal options used by almost all tools :returns fsID for vcf contaning merged calls for the given chromosome :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() from protect.mutation_calling.muse import process_muse_vcf from protect.mutation_calling.mutect import process_mutect_vcf from protect.mutation_calling.radia import process_radia_vcf from protect.mutation_calling.somaticsniper import process_somaticsniper_vcf from protect.mutation_calling.strelka import process_strelka_vcf mutations.pop('indels') mutations['strelka_indels'] = mutations['strelka']['indels'] mutations['strelka_snvs'] = mutations['strelka']['snvs'] vcf_processor = {'snvs': {'mutect': process_mutect_vcf, 'muse': process_muse_vcf, 'radia': process_radia_vcf, 'somaticsniper': process_somaticsniper_vcf, 'strelka_snvs': process_strelka_vcf }, 'indels': {'strelka_indels': process_strelka_vcf } } # 'fusions': lambda x: None, # 'indels': lambda x: None} # For now, let's just say 2 out of n need to call it. # num_preds = len(mutations) # majority = int((num_preds + 0.5) / 2) majority = {'snvs': 2, 'indels': 1} accepted_hits = defaultdict(dict) for mut_type in vcf_processor.keys(): # Get input files perchrom_mutations = {caller: vcf_processor[mut_type][caller](job, mutations[caller][chrom], work_dir, univ_options) for caller in vcf_processor[mut_type]} # Process the strelka key perchrom_mutations['strelka'] = perchrom_mutations['strelka_' + mut_type] perchrom_mutations.pop('strelka_' + mut_type) # Read in each file to a dict vcf_lists = {caller: read_vcf(vcf_file) for caller, vcf_file in perchrom_mutations.items()} all_positions = list(set(itertools.chain(*vcf_lists.values()))) for position in sorted(all_positions): hits = {caller: position in vcf_lists[caller] for caller in perchrom_mutations.keys()} if sum(hits.values()) >= majority[mut_type]: callers = ','.join([caller for caller, hit in hits.items() if hit]) assert position[1] not in accepted_hits[position[0]] accepted_hits[position[0]][position[1]] = (position[2], position[3], callers) with open(''.join([work_dir, '/', chrom, '.vcf']), 'w') as outfile: print('##fileformat=VCFv4.0', file=outfile) print('##INFO=<ID=callers,Number=.,Type=String,Description=List of supporting callers.', file=outfile) print('#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO', file=outfile) for chrom in chrom_sorted(accepted_hits.keys()): for position in sorted(accepted_hits[chrom]): print(chrom, position, '.', accepted_hits[chrom][position][0], accepted_hits[chrom][position][1], '.', 'PASS', 'callers=' + accepted_hits[chrom][position][2], sep='\t', file=outfile) fsid = job.fileStore.writeGlobalFile(outfile.name) export_results(job, fsid, outfile.name, univ_options, subfolder='mutations/merged') return fsid
python
def merge_perchrom_mutations(job, chrom, mutations, univ_options): """ Merge the mutation calls for a single chromosome. :param str chrom: Chromosome to process :param dict mutations: dict of dicts of the various mutation caller names as keys, and a dict of per chromosome job store ids for vcfs as value :param dict univ_options: Dict of universal options used by almost all tools :returns fsID for vcf contaning merged calls for the given chromosome :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() from protect.mutation_calling.muse import process_muse_vcf from protect.mutation_calling.mutect import process_mutect_vcf from protect.mutation_calling.radia import process_radia_vcf from protect.mutation_calling.somaticsniper import process_somaticsniper_vcf from protect.mutation_calling.strelka import process_strelka_vcf mutations.pop('indels') mutations['strelka_indels'] = mutations['strelka']['indels'] mutations['strelka_snvs'] = mutations['strelka']['snvs'] vcf_processor = {'snvs': {'mutect': process_mutect_vcf, 'muse': process_muse_vcf, 'radia': process_radia_vcf, 'somaticsniper': process_somaticsniper_vcf, 'strelka_snvs': process_strelka_vcf }, 'indels': {'strelka_indels': process_strelka_vcf } } # 'fusions': lambda x: None, # 'indels': lambda x: None} # For now, let's just say 2 out of n need to call it. # num_preds = len(mutations) # majority = int((num_preds + 0.5) / 2) majority = {'snvs': 2, 'indels': 1} accepted_hits = defaultdict(dict) for mut_type in vcf_processor.keys(): # Get input files perchrom_mutations = {caller: vcf_processor[mut_type][caller](job, mutations[caller][chrom], work_dir, univ_options) for caller in vcf_processor[mut_type]} # Process the strelka key perchrom_mutations['strelka'] = perchrom_mutations['strelka_' + mut_type] perchrom_mutations.pop('strelka_' + mut_type) # Read in each file to a dict vcf_lists = {caller: read_vcf(vcf_file) for caller, vcf_file in perchrom_mutations.items()} all_positions = list(set(itertools.chain(*vcf_lists.values()))) for position in sorted(all_positions): hits = {caller: position in vcf_lists[caller] for caller in perchrom_mutations.keys()} if sum(hits.values()) >= majority[mut_type]: callers = ','.join([caller for caller, hit in hits.items() if hit]) assert position[1] not in accepted_hits[position[0]] accepted_hits[position[0]][position[1]] = (position[2], position[3], callers) with open(''.join([work_dir, '/', chrom, '.vcf']), 'w') as outfile: print('##fileformat=VCFv4.0', file=outfile) print('##INFO=<ID=callers,Number=.,Type=String,Description=List of supporting callers.', file=outfile) print('#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO', file=outfile) for chrom in chrom_sorted(accepted_hits.keys()): for position in sorted(accepted_hits[chrom]): print(chrom, position, '.', accepted_hits[chrom][position][0], accepted_hits[chrom][position][1], '.', 'PASS', 'callers=' + accepted_hits[chrom][position][2], sep='\t', file=outfile) fsid = job.fileStore.writeGlobalFile(outfile.name) export_results(job, fsid, outfile.name, univ_options, subfolder='mutations/merged') return fsid
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Merge the mutation calls for a single chromosome. :param str chrom: Chromosome to process :param dict mutations: dict of dicts of the various mutation caller names as keys, and a dict of per chromosome job store ids for vcfs as value :param dict univ_options: Dict of universal options used by almost all tools :returns fsID for vcf contaning merged calls for the given chromosome :rtype: toil.fileStore.FileID
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/common.py#L74-L143
train
BD2KGenomics/protect
src/protect/mutation_calling/common.py
read_vcf
def read_vcf(vcf_file): """ Read a vcf file to a dict of lists. :param str vcf_file: Path to a vcf file. :return: dict of lists of vcf records :rtype: dict """ vcf_dict = [] with open(vcf_file, 'r') as invcf: for line in invcf: if line.startswith('#'): continue line = line.strip().split() vcf_dict.append((line[0], line[1], line[3], line[4])) return vcf_dict
python
def read_vcf(vcf_file): """ Read a vcf file to a dict of lists. :param str vcf_file: Path to a vcf file. :return: dict of lists of vcf records :rtype: dict """ vcf_dict = [] with open(vcf_file, 'r') as invcf: for line in invcf: if line.startswith('#'): continue line = line.strip().split() vcf_dict.append((line[0], line[1], line[3], line[4])) return vcf_dict
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Read a vcf file to a dict of lists. :param str vcf_file: Path to a vcf file. :return: dict of lists of vcf records :rtype: dict
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/common.py#L146-L161
train
BD2KGenomics/protect
src/protect/mutation_calling/common.py
merge_perchrom_vcfs
def merge_perchrom_vcfs(job, perchrom_vcfs, tool_name, univ_options): """ Merge per-chromosome vcf files into a single genome level vcf. :param dict perchrom_vcfs: Dictionary with chromosome name as key and fsID of the corresponding vcf as value :param str tool_name: Name of the tool that generated the vcfs :returns: fsID for the merged vcf :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() input_files = {''.join([chrom, '.vcf']): jsid for chrom, jsid in perchrom_vcfs.items()} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) first = True with open(''.join([work_dir, '/', 'all_merged.vcf']), 'w') as outvcf: for chromvcfname in chrom_sorted([x.rstrip('.vcf') for x in input_files.keys()]): with open(input_files[chromvcfname + '.vcf'], 'r') as infile: for line in infile: line = line.strip() if line.startswith('#'): if first: print(line, file=outvcf) continue first = False print(line, file=outvcf) output_file = job.fileStore.writeGlobalFile(outvcf.name) export_results(job, output_file, outvcf.name, univ_options, subfolder='mutations/' + tool_name) job.fileStore.logToMaster('Ran merge_perchrom_vcfs for %s successfully' % tool_name) return output_file
python
def merge_perchrom_vcfs(job, perchrom_vcfs, tool_name, univ_options): """ Merge per-chromosome vcf files into a single genome level vcf. :param dict perchrom_vcfs: Dictionary with chromosome name as key and fsID of the corresponding vcf as value :param str tool_name: Name of the tool that generated the vcfs :returns: fsID for the merged vcf :rtype: toil.fileStore.FileID """ work_dir = os.getcwd() input_files = {''.join([chrom, '.vcf']): jsid for chrom, jsid in perchrom_vcfs.items()} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) first = True with open(''.join([work_dir, '/', 'all_merged.vcf']), 'w') as outvcf: for chromvcfname in chrom_sorted([x.rstrip('.vcf') for x in input_files.keys()]): with open(input_files[chromvcfname + '.vcf'], 'r') as infile: for line in infile: line = line.strip() if line.startswith('#'): if first: print(line, file=outvcf) continue first = False print(line, file=outvcf) output_file = job.fileStore.writeGlobalFile(outvcf.name) export_results(job, output_file, outvcf.name, univ_options, subfolder='mutations/' + tool_name) job.fileStore.logToMaster('Ran merge_perchrom_vcfs for %s successfully' % tool_name) return output_file
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Merge per-chromosome vcf files into a single genome level vcf. :param dict perchrom_vcfs: Dictionary with chromosome name as key and fsID of the corresponding vcf as value :param str tool_name: Name of the tool that generated the vcfs :returns: fsID for the merged vcf :rtype: toil.fileStore.FileID
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/common.py#L164-L192
train
BD2KGenomics/protect
src/protect/mutation_calling/common.py
unmerge
def unmerge(job, input_vcf, tool_name, chromosomes, tool_options, univ_options): """ Un-merge a vcf file into per-chromosome vcfs. :param str input_vcf: Input vcf :param str tool_name: The name of the mutation caller :param list chromosomes: List of chromosomes to retain :param dict tool_options: Options specific to the mutation caller :param dict univ_options: Dict of universal options used by almost all tools :return: dict of fsIDs, one for each chromosomal vcf :rtype: dict """ work_dir = os.getcwd() input_files = { 'input.vcf': input_vcf, 'genome.fa.fai.tar.gz': tool_options['genome_fai']} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) input_files['genome.fa.fai'] = untargz(input_files['genome.fa.fai.tar.gz'], work_dir) read_chromosomes = defaultdict() with open(input_files['input.vcf'], 'r') as in_vcf: header = [] for line in in_vcf: if line.startswith('#'): header.append(line) continue line = line.strip() chrom = line.split()[0] if chrom in read_chromosomes: print(line, file=read_chromosomes[chrom]) else: read_chromosomes[chrom] = open(os.path.join(os.getcwd(), chrom + '.vcf'), 'w') print(''.join(header), file=read_chromosomes[chrom], end='') print(line, file=read_chromosomes[chrom]) # Process chromosomes that had no mutations for chrom in set(chromosomes).difference(set(read_chromosomes.keys())): read_chromosomes[chrom] = open(os.path.join(os.getcwd(), chrom + '.vcf'), 'w') print(''.join(header), file=read_chromosomes[chrom], end='') outdict = {} chroms = set(chromosomes).intersection(set(read_chromosomes.keys())) for chrom, chromvcf in read_chromosomes.items(): chromvcf.close() if chrom not in chroms: continue outdict[chrom] = job.fileStore.writeGlobalFile(chromvcf.name) export_results(job, outdict[chrom], chromvcf.name, univ_options, subfolder='mutations/' + tool_name) return outdict
python
def unmerge(job, input_vcf, tool_name, chromosomes, tool_options, univ_options): """ Un-merge a vcf file into per-chromosome vcfs. :param str input_vcf: Input vcf :param str tool_name: The name of the mutation caller :param list chromosomes: List of chromosomes to retain :param dict tool_options: Options specific to the mutation caller :param dict univ_options: Dict of universal options used by almost all tools :return: dict of fsIDs, one for each chromosomal vcf :rtype: dict """ work_dir = os.getcwd() input_files = { 'input.vcf': input_vcf, 'genome.fa.fai.tar.gz': tool_options['genome_fai']} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) input_files['genome.fa.fai'] = untargz(input_files['genome.fa.fai.tar.gz'], work_dir) read_chromosomes = defaultdict() with open(input_files['input.vcf'], 'r') as in_vcf: header = [] for line in in_vcf: if line.startswith('#'): header.append(line) continue line = line.strip() chrom = line.split()[0] if chrom in read_chromosomes: print(line, file=read_chromosomes[chrom]) else: read_chromosomes[chrom] = open(os.path.join(os.getcwd(), chrom + '.vcf'), 'w') print(''.join(header), file=read_chromosomes[chrom], end='') print(line, file=read_chromosomes[chrom]) # Process chromosomes that had no mutations for chrom in set(chromosomes).difference(set(read_chromosomes.keys())): read_chromosomes[chrom] = open(os.path.join(os.getcwd(), chrom + '.vcf'), 'w') print(''.join(header), file=read_chromosomes[chrom], end='') outdict = {} chroms = set(chromosomes).intersection(set(read_chromosomes.keys())) for chrom, chromvcf in read_chromosomes.items(): chromvcf.close() if chrom not in chroms: continue outdict[chrom] = job.fileStore.writeGlobalFile(chromvcf.name) export_results(job, outdict[chrom], chromvcf.name, univ_options, subfolder='mutations/' + tool_name) return outdict
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Un-merge a vcf file into per-chromosome vcfs. :param str input_vcf: Input vcf :param str tool_name: The name of the mutation caller :param list chromosomes: List of chromosomes to retain :param dict tool_options: Options specific to the mutation caller :param dict univ_options: Dict of universal options used by almost all tools :return: dict of fsIDs, one for each chromosomal vcf :rtype: dict
[ "Un", "-", "merge", "a", "vcf", "file", "into", "per", "-", "chromosome", "vcfs", "." ]
06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/mutation_calling/common.py#L195-L243
train
bkg/django-spillway
spillway/collections.py
as_feature
def as_feature(data): """Returns a Feature or FeatureCollection. Arguments: data -- Sequence or Mapping of Feature-like or FeatureCollection-like data """ if not isinstance(data, (Feature, FeatureCollection)): if is_featurelike(data): data = Feature(**data) elif has_features(data): data = FeatureCollection(**data) elif isinstance(data, collections.Sequence): data = FeatureCollection(features=data) elif has_layer(data): data = LayerCollection(data) elif has_coordinates(data): data = Feature(geometry=data) elif isinstance(data, collections.Mapping) and not data: data = Feature() return data
python
def as_feature(data): """Returns a Feature or FeatureCollection. Arguments: data -- Sequence or Mapping of Feature-like or FeatureCollection-like data """ if not isinstance(data, (Feature, FeatureCollection)): if is_featurelike(data): data = Feature(**data) elif has_features(data): data = FeatureCollection(**data) elif isinstance(data, collections.Sequence): data = FeatureCollection(features=data) elif has_layer(data): data = LayerCollection(data) elif has_coordinates(data): data = Feature(geometry=data) elif isinstance(data, collections.Mapping) and not data: data = Feature() return data
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c488a62642430b005f1e0d4a19e160d8d5964b67
https://github.com/bkg/django-spillway/blob/c488a62642430b005f1e0d4a19e160d8d5964b67/spillway/collections.py#L9-L28
train
bkg/django-spillway
spillway/collections.py
has_layer
def has_layer(fcollection): """Returns true for a multi-layer dict of FeatureCollections.""" for val in six.viewvalues(fcollection): if has_features(val): return True return False
python
def has_layer(fcollection): """Returns true for a multi-layer dict of FeatureCollections.""" for val in six.viewvalues(fcollection): if has_features(val): return True return False
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c488a62642430b005f1e0d4a19e160d8d5964b67
https://github.com/bkg/django-spillway/blob/c488a62642430b005f1e0d4a19e160d8d5964b67/spillway/collections.py#L51-L56
train
BD2KGenomics/protect
src/protect/expression_profiling/rsem.py
wrap_rsem
def wrap_rsem(job, star_bams, univ_options, rsem_options): """ A wrapper for run_rsem using the results from run_star as input. :param dict star_bams: dict of results from star :param dict univ_options: Dict of universal options used by almost all tools :param dict rsem_options: Options specific to rsem :return: Dict of gene- and isoform-level expression calls output_files: |- 'rsem.genes.results': fsID +- 'rsem.isoforms.results': fsID :rtype: dict """ rsem = job.addChildJobFn(run_rsem, star_bams['rna_transcriptome.bam'], univ_options, rsem_options, cores=rsem_options['n'], disk=PromisedRequirement(rsem_disk, star_bams, rsem_options['index'])) return rsem.rv()
python
def wrap_rsem(job, star_bams, univ_options, rsem_options): """ A wrapper for run_rsem using the results from run_star as input. :param dict star_bams: dict of results from star :param dict univ_options: Dict of universal options used by almost all tools :param dict rsem_options: Options specific to rsem :return: Dict of gene- and isoform-level expression calls output_files: |- 'rsem.genes.results': fsID +- 'rsem.isoforms.results': fsID :rtype: dict """ rsem = job.addChildJobFn(run_rsem, star_bams['rna_transcriptome.bam'], univ_options, rsem_options, cores=rsem_options['n'], disk=PromisedRequirement(rsem_disk, star_bams, rsem_options['index'])) return rsem.rv()
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/expression_profiling/rsem.py#L36-L54
train
BD2KGenomics/protect
src/protect/expression_profiling/rsem.py
run_rsem
def run_rsem(job, rna_bam, univ_options, rsem_options): """ Run rsem on the input RNA bam. ARGUMENTS :param toil.fileStore.FileID rna_bam: fsID of a transcriptome bam generated by STAR :param dict univ_options: Dict of universal options used by almost all tools :param dict rsem_options: Options specific to rsem :return: Dict of gene- and isoform-level expression calls output_files: |- 'rsem.genes.results': fsID +- 'rsem.isoforms.results': fsID :rtype: dict """ work_dir = os.getcwd() input_files = { 'star_transcriptome.bam': rna_bam, 'rsem_index.tar.gz': rsem_options['index']} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) input_files['rsem_index'] = untargz(input_files['rsem_index.tar.gz'], work_dir) input_files = {key: docker_path(path) for key, path in input_files.items()} parameters = ['--paired-end', '-p', str(rsem_options['n']), '--bam', input_files['star_transcriptome.bam'], '--no-bam-output', '/'.join([input_files['rsem_index'], univ_options['ref']]), 'rsem'] docker_call(tool='rsem', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=rsem_options['version']) output_files = {} for filename in ('rsem.genes.results', 'rsem.isoforms.results'): output_files[filename] = job.fileStore.writeGlobalFile('/'.join([work_dir, filename])) export_results(job, output_files[filename], '/'.join([work_dir, filename]), univ_options, subfolder='expression') job.fileStore.logToMaster('Ran rsem on %s successfully' % univ_options['patient']) return output_files
python
def run_rsem(job, rna_bam, univ_options, rsem_options): """ Run rsem on the input RNA bam. ARGUMENTS :param toil.fileStore.FileID rna_bam: fsID of a transcriptome bam generated by STAR :param dict univ_options: Dict of universal options used by almost all tools :param dict rsem_options: Options specific to rsem :return: Dict of gene- and isoform-level expression calls output_files: |- 'rsem.genes.results': fsID +- 'rsem.isoforms.results': fsID :rtype: dict """ work_dir = os.getcwd() input_files = { 'star_transcriptome.bam': rna_bam, 'rsem_index.tar.gz': rsem_options['index']} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) input_files['rsem_index'] = untargz(input_files['rsem_index.tar.gz'], work_dir) input_files = {key: docker_path(path) for key, path in input_files.items()} parameters = ['--paired-end', '-p', str(rsem_options['n']), '--bam', input_files['star_transcriptome.bam'], '--no-bam-output', '/'.join([input_files['rsem_index'], univ_options['ref']]), 'rsem'] docker_call(tool='rsem', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=rsem_options['version']) output_files = {} for filename in ('rsem.genes.results', 'rsem.isoforms.results'): output_files[filename] = job.fileStore.writeGlobalFile('/'.join([work_dir, filename])) export_results(job, output_files[filename], '/'.join([work_dir, filename]), univ_options, subfolder='expression') job.fileStore.logToMaster('Ran rsem on %s successfully' % univ_options['patient']) return output_files
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/expression_profiling/rsem.py#L57-L95
train
idlesign/steampak
steampak/libsteam/resources/overlay.py
Overlay.activate
def activate(self, page=None): """Activates overlay with browser, optionally opened at a given page. :param str page: Overlay page alias (see OVERLAY_PAGE_*) or a custom URL. """ page = page or '' if '://' in page: self._iface.activate_overlay_url(page) else: self._iface.activate_overlay_game(page)
python
def activate(self, page=None): """Activates overlay with browser, optionally opened at a given page. :param str page: Overlay page alias (see OVERLAY_PAGE_*) or a custom URL. """ page = page or '' if '://' in page: self._iface.activate_overlay_url(page) else: self._iface.activate_overlay_game(page)
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Activates overlay with browser, optionally opened at a given page. :param str page: Overlay page alias (see OVERLAY_PAGE_*) or a custom URL.
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cb3f2c737e272b0360802d947e388df7e34f50f3
https://github.com/idlesign/steampak/blob/cb3f2c737e272b0360802d947e388df7e34f50f3/steampak/libsteam/resources/overlay.py#L30-L43
train
drslump/pyshould
pyshould/dsl.py
any_of
def any_of(value, *args): """ At least one of the items in value should match """ if len(args): value = (value,) + args return ExpectationAny(value)
python
def any_of(value, *args): """ At least one of the items in value should match """ if len(args): value = (value,) + args return ExpectationAny(value)
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7210859d4c84cfbaa64f91b30c2a541aea788ddf
https://github.com/drslump/pyshould/blob/7210859d4c84cfbaa64f91b30c2a541aea788ddf/pyshould/dsl.py#L33-L39
train
drslump/pyshould
pyshould/dsl.py
all_of
def all_of(value, *args): """ All the items in value should match """ if len(args): value = (value,) + args return ExpectationAll(value)
python
def all_of(value, *args): """ All the items in value should match """ if len(args): value = (value,) + args return ExpectationAll(value)
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All the items in value should match
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7210859d4c84cfbaa64f91b30c2a541aea788ddf
https://github.com/drslump/pyshould/blob/7210859d4c84cfbaa64f91b30c2a541aea788ddf/pyshould/dsl.py#L42-L48
train
drslump/pyshould
pyshould/dsl.py
none_of
def none_of(value, *args): """ None of the items in value should match """ if len(args): value = (value,) + args return ExpectationNone(value)
python
def none_of(value, *args): """ None of the items in value should match """ if len(args): value = (value,) + args return ExpectationNone(value)
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None of the items in value should match
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7210859d4c84cfbaa64f91b30c2a541aea788ddf
https://github.com/drslump/pyshould/blob/7210859d4c84cfbaa64f91b30c2a541aea788ddf/pyshould/dsl.py#L51-L57
train
BD2KGenomics/protect
src/protect/qc/rna.py
run_cutadapt
def run_cutadapt(job, fastqs, univ_options, cutadapt_options): """ Runs cutadapt on the input RNA fastq files. :param list fastqs: List of fsIDs for input an RNA-Seq fastq pair :param dict univ_options: Dict of universal options used by almost all tools :param dict cutadapt_options: Options specific to cutadapt :return: List of fsIDs of cutadapted fastqs :rtype: list[toil.fileStore.FileID] """ work_dir = os.getcwd() input_files = { 'rna_1.fastq': fastqs[0], 'rna_2.fastq': fastqs[1]} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) # Handle gzipped file gz = '.gz' if is_gzipfile(input_files['rna_1.fastq']) else '' if gz: for read_file in 'rna_1.fastq', 'rna_2.fastq': os.symlink(read_file, read_file + gz) input_files[read_file + gz] = input_files[read_file] + gz input_files = {key: docker_path(path) for key, path in input_files.items()} parameters = ['-a', cutadapt_options['a'], # Fwd read 3' adapter '-A', cutadapt_options['A'], # Rev read 3' adapter '-m', '35', # Minimum size of read '-o', docker_path('rna_cutadapt_1.fastq.gz'), # Output for R1 '-p', docker_path('rna_cutadapt_2.fastq.gz'), # Output for R2 input_files['rna_1.fastq' + gz], input_files['rna_2.fastq' + gz]] docker_call(tool='cutadapt', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=cutadapt_options['version']) output_files = [] for fastq_file in ['rna_cutadapt_1.fastq.gz', 'rna_cutadapt_2.fastq.gz']: output_files.append(job.fileStore.writeGlobalFile('/'.join([work_dir, fastq_file]))) job.fileStore.logToMaster('Ran cutadapt on %s successfully' % univ_options['patient']) return output_files
python
def run_cutadapt(job, fastqs, univ_options, cutadapt_options): """ Runs cutadapt on the input RNA fastq files. :param list fastqs: List of fsIDs for input an RNA-Seq fastq pair :param dict univ_options: Dict of universal options used by almost all tools :param dict cutadapt_options: Options specific to cutadapt :return: List of fsIDs of cutadapted fastqs :rtype: list[toil.fileStore.FileID] """ work_dir = os.getcwd() input_files = { 'rna_1.fastq': fastqs[0], 'rna_2.fastq': fastqs[1]} input_files = get_files_from_filestore(job, input_files, work_dir, docker=False) # Handle gzipped file gz = '.gz' if is_gzipfile(input_files['rna_1.fastq']) else '' if gz: for read_file in 'rna_1.fastq', 'rna_2.fastq': os.symlink(read_file, read_file + gz) input_files[read_file + gz] = input_files[read_file] + gz input_files = {key: docker_path(path) for key, path in input_files.items()} parameters = ['-a', cutadapt_options['a'], # Fwd read 3' adapter '-A', cutadapt_options['A'], # Rev read 3' adapter '-m', '35', # Minimum size of read '-o', docker_path('rna_cutadapt_1.fastq.gz'), # Output for R1 '-p', docker_path('rna_cutadapt_2.fastq.gz'), # Output for R2 input_files['rna_1.fastq' + gz], input_files['rna_2.fastq' + gz]] docker_call(tool='cutadapt', tool_parameters=parameters, work_dir=work_dir, dockerhub=univ_options['dockerhub'], tool_version=cutadapt_options['version']) output_files = [] for fastq_file in ['rna_cutadapt_1.fastq.gz', 'rna_cutadapt_2.fastq.gz']: output_files.append(job.fileStore.writeGlobalFile('/'.join([work_dir, fastq_file]))) job.fileStore.logToMaster('Ran cutadapt on %s successfully' % univ_options['patient']) return output_files
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Runs cutadapt on the input RNA fastq files. :param list fastqs: List of fsIDs for input an RNA-Seq fastq pair :param dict univ_options: Dict of universal options used by almost all tools :param dict cutadapt_options: Options specific to cutadapt :return: List of fsIDs of cutadapted fastqs :rtype: list[toil.fileStore.FileID]
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/qc/rna.py#L29-L64
train
inveniosoftware/invenio-access
examples/app.py
index
def index(): """Basic test view.""" identity = g.identity actions = {} for action in access.actions.values(): actions[action.value] = DynamicPermission(action).allows(identity) if current_user.is_anonymous: return render_template("invenio_access/open.html", actions=actions, identity=identity) else: return render_template("invenio_access/limited.html", message='', actions=actions, identity=identity)
python
def index(): """Basic test view.""" identity = g.identity actions = {} for action in access.actions.values(): actions[action.value] = DynamicPermission(action).allows(identity) if current_user.is_anonymous: return render_template("invenio_access/open.html", actions=actions, identity=identity) else: return render_template("invenio_access/limited.html", message='', actions=actions, identity=identity)
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Basic test view.
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3b033a4bdc110eb2f7e9f08f0744a780884bfc80
https://github.com/inveniosoftware/invenio-access/blob/3b033a4bdc110eb2f7e9f08f0744a780884bfc80/examples/app.py#L109-L124
train
inveniosoftware/invenio-access
examples/app.py
role_admin
def role_admin(): """View only allowed to admin role.""" identity = g.identity actions = {} for action in access.actions.values(): actions[action.value] = DynamicPermission(action).allows(identity) message = 'You are opening a page requiring the "admin-access" permission' return render_template("invenio_access/limited.html", message=message, actions=actions, identity=identity)
python
def role_admin(): """View only allowed to admin role.""" identity = g.identity actions = {} for action in access.actions.values(): actions[action.value] = DynamicPermission(action).allows(identity) message = 'You are opening a page requiring the "admin-access" permission' return render_template("invenio_access/limited.html", message=message, actions=actions, identity=identity)
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View only allowed to admin role.
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3b033a4bdc110eb2f7e9f08f0744a780884bfc80
https://github.com/inveniosoftware/invenio-access/blob/3b033a4bdc110eb2f7e9f08f0744a780884bfc80/examples/app.py#L134-L145
train
BD2KGenomics/protect
src/protect/binding_prediction/common.py
read_fastas
def read_fastas(input_files): """ Read the tumor and normal fastas into a joint dict. :param dict input_files: A dict containing filename: filepath for T_ and N_ transgened files. :return: The read fastas in a dictionary of tuples :rtype: dict """ tumor_file = [y for x, y in input_files.items() if x.startswith('T')][0] normal_file = [y for x, y in input_files.items() if x.startswith('N')][0] output_files = defaultdict(list) output_files = _read_fasta(tumor_file, output_files) num_entries = len(output_files) output_files = _read_fasta(normal_file, output_files) assert len(output_files) == num_entries return output_files
python
def read_fastas(input_files): """ Read the tumor and normal fastas into a joint dict. :param dict input_files: A dict containing filename: filepath for T_ and N_ transgened files. :return: The read fastas in a dictionary of tuples :rtype: dict """ tumor_file = [y for x, y in input_files.items() if x.startswith('T')][0] normal_file = [y for x, y in input_files.items() if x.startswith('N')][0] output_files = defaultdict(list) output_files = _read_fasta(tumor_file, output_files) num_entries = len(output_files) output_files = _read_fasta(normal_file, output_files) assert len(output_files) == num_entries return output_files
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/binding_prediction/common.py#L140-L155
train
BD2KGenomics/protect
src/protect/binding_prediction/common.py
_read_fasta
def _read_fasta(fasta_file, output_dict): """ Read the peptide fasta into an existing dict. :param str fasta_file: The peptide file :param dict output_dict: The dict to appends results to. :return: output_dict :rtype: dict """ read_name = None with open(fasta_file, 'r') as f: for line in f: line = line.strip() if not line: continue if line.startswith('>'): read_name = line.lstrip('>') else: assert read_name is not None, line output_dict[read_name].append(line.strip()) return output_dict
python
def _read_fasta(fasta_file, output_dict): """ Read the peptide fasta into an existing dict. :param str fasta_file: The peptide file :param dict output_dict: The dict to appends results to. :return: output_dict :rtype: dict """ read_name = None with open(fasta_file, 'r') as f: for line in f: line = line.strip() if not line: continue if line.startswith('>'): read_name = line.lstrip('>') else: assert read_name is not None, line output_dict[read_name].append(line.strip()) return output_dict
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/binding_prediction/common.py#L158-L178
train
BD2KGenomics/protect
src/protect/binding_prediction/common.py
_process_consensus_mhcii
def _process_consensus_mhcii(mhc_file, normal=False): """ Process the results from running IEDB MHCII binding predictions using the consensus method into a pandas dataframe. :param str mhc_file: Output file containing consensus mhcii:peptide binding predictions :param bool normal: Is this processing the results of a normal? :return: Results in a tabular format :rtype: pandas.DataFrame """ core_col = None # Variable to hold the column number with the core results = pandas.DataFrame(columns=['allele', 'pept', 'tumor_pred', 'core']) with open(mhc_file, 'r') as mf: peptides = set() for line in mf: # Skip header lines if not line.startswith('HLA'): continue line = line.strip().split('\t') allele = line[0] pept = line[4] pred = line[6] if core_col: core = line[core_col] else: methods = line[5].lstrip('Consensus(').rstrip(')') methods = methods.split(',') if 'NN' in methods: core_col = 13 elif 'netMHCIIpan' in methods: core_col = 17 elif 'Sturniolo' in methods: core_col = 19 elif 'SMM' in methods: core_col = 10 core = line[core_col] if core_col else 'NOCORE' if float(pred) > 5.00 and not normal: continue results.loc[len(results)] = [allele, pept, pred, core] results.drop_duplicates(inplace=True) return results
python
def _process_consensus_mhcii(mhc_file, normal=False): """ Process the results from running IEDB MHCII binding predictions using the consensus method into a pandas dataframe. :param str mhc_file: Output file containing consensus mhcii:peptide binding predictions :param bool normal: Is this processing the results of a normal? :return: Results in a tabular format :rtype: pandas.DataFrame """ core_col = None # Variable to hold the column number with the core results = pandas.DataFrame(columns=['allele', 'pept', 'tumor_pred', 'core']) with open(mhc_file, 'r') as mf: peptides = set() for line in mf: # Skip header lines if not line.startswith('HLA'): continue line = line.strip().split('\t') allele = line[0] pept = line[4] pred = line[6] if core_col: core = line[core_col] else: methods = line[5].lstrip('Consensus(').rstrip(')') methods = methods.split(',') if 'NN' in methods: core_col = 13 elif 'netMHCIIpan' in methods: core_col = 17 elif 'Sturniolo' in methods: core_col = 19 elif 'SMM' in methods: core_col = 10 core = line[core_col] if core_col else 'NOCORE' if float(pred) > 5.00 and not normal: continue results.loc[len(results)] = [allele, pept, pred, core] results.drop_duplicates(inplace=True) return results
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/binding_prediction/common.py#L181-L221
train
BD2KGenomics/protect
src/protect/binding_prediction/common.py
_process_net_mhcii
def _process_net_mhcii(mhc_file, normal=False): """ Process the results from running NetMHCIIpan binding predictions into a pandas dataframe. :param str mhc_file: Output file containing netmhciipan mhcii:peptide binding predictions :param bool normal: Is this processing the results of a normal? :return: Results in a tabular format :rtype: pandas.DataFrame """ results = pandas.DataFrame(columns=['allele', 'pept', 'tumor_pred', 'core', 'peptide_name']) with open(mhc_file, 'r') as mf: peptides = set() # Get the allele from the first line and skip the second line allele = re.sub('-DQB', '/DQB', mf.readline().strip()) _ = mf.readline() for line in mf: line = line.strip().split('\t') pept = line[1] pred = line[5] core = 'NOCORE' peptide_name = line[2] if float(pred) > 5.00 and not normal: continue results.loc[len(results)] = [allele, pept, pred, core, peptide_name] results.drop_duplicates(inplace=True) return results
python
def _process_net_mhcii(mhc_file, normal=False): """ Process the results from running NetMHCIIpan binding predictions into a pandas dataframe. :param str mhc_file: Output file containing netmhciipan mhcii:peptide binding predictions :param bool normal: Is this processing the results of a normal? :return: Results in a tabular format :rtype: pandas.DataFrame """ results = pandas.DataFrame(columns=['allele', 'pept', 'tumor_pred', 'core', 'peptide_name']) with open(mhc_file, 'r') as mf: peptides = set() # Get the allele from the first line and skip the second line allele = re.sub('-DQB', '/DQB', mf.readline().strip()) _ = mf.readline() for line in mf: line = line.strip().split('\t') pept = line[1] pred = line[5] core = 'NOCORE' peptide_name = line[2] if float(pred) > 5.00 and not normal: continue results.loc[len(results)] = [allele, pept, pred, core, peptide_name] results.drop_duplicates(inplace=True) return results
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/binding_prediction/common.py#L253-L278
train
BD2KGenomics/protect
src/protect/binding_prediction/common.py
_process_mhci
def _process_mhci(mhc_file, normal=False): """ Process the results from running IEDB MHCI binding predictions into a pandas dataframe. :param str mhc_file: Output file containing netmhciipan mhci:peptide binding predictions :param bool normal: Is this processing the results of a normal? :return: Results in a tabular format :rtype: pandas.DataFrame """ results = pandas.DataFrame(columns=['allele', 'pept', 'tumor_pred', 'core']) with open(mhc_file, 'r') as mf: peptides = set() for line in mf: # Skip header lines if not line.startswith('HLA'): continue line = line.strip().split('\t') allele = line[0] pept = line[5] pred = line[7] if float(pred) > 5.00 and not normal: continue results.loc[len(results)] = [allele, pept, pred, pept] results.drop_duplicates(inplace=True) return results
python
def _process_mhci(mhc_file, normal=False): """ Process the results from running IEDB MHCI binding predictions into a pandas dataframe. :param str mhc_file: Output file containing netmhciipan mhci:peptide binding predictions :param bool normal: Is this processing the results of a normal? :return: Results in a tabular format :rtype: pandas.DataFrame """ results = pandas.DataFrame(columns=['allele', 'pept', 'tumor_pred', 'core']) with open(mhc_file, 'r') as mf: peptides = set() for line in mf: # Skip header lines if not line.startswith('HLA'): continue line = line.strip().split('\t') allele = line[0] pept = line[5] pred = line[7] if float(pred) > 5.00 and not normal: continue results.loc[len(results)] = [allele, pept, pred, pept] results.drop_duplicates(inplace=True) return results
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/binding_prediction/common.py#L281-L305
train
BD2KGenomics/protect
src/protect/binding_prediction/common.py
pept_diff
def pept_diff(p1, p2): """ Return the number of differences betweeen 2 peptides :param str p1: Peptide 1 :param str p2: Peptide 2 :return: The number of differences between the pepetides :rtype: int >>> pept_diff('ABCDE', 'ABCDF') 1 >>> pept_diff('ABCDE', 'ABDFE') 2 >>> pept_diff('ABCDE', 'EDCBA') 4 >>> pept_diff('ABCDE', 'ABCDE') 0 """ if len(p1) != len(p2): return -1 else: return sum([p1[i] != p2[i] for i in range(len(p1))])
python
def pept_diff(p1, p2): """ Return the number of differences betweeen 2 peptides :param str p1: Peptide 1 :param str p2: Peptide 2 :return: The number of differences between the pepetides :rtype: int >>> pept_diff('ABCDE', 'ABCDF') 1 >>> pept_diff('ABCDE', 'ABDFE') 2 >>> pept_diff('ABCDE', 'EDCBA') 4 >>> pept_diff('ABCDE', 'ABCDE') 0 """ if len(p1) != len(p2): return -1 else: return sum([p1[i] != p2[i] for i in range(len(p1))])
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Return the number of differences betweeen 2 peptides :param str p1: Peptide 1 :param str p2: Peptide 2 :return: The number of differences between the pepetides :rtype: int >>> pept_diff('ABCDE', 'ABCDF') 1 >>> pept_diff('ABCDE', 'ABDFE') 2 >>> pept_diff('ABCDE', 'EDCBA') 4 >>> pept_diff('ABCDE', 'ABCDE') 0
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/binding_prediction/common.py#L308-L329
train
BD2KGenomics/protect
src/protect/binding_prediction/common.py
print_mhc_peptide
def print_mhc_peptide(neoepitope_info, peptides, pepmap, outfile, netmhc=False): """ Accept data about one neoepitope from merge_mhc_peptide_calls and print it to outfile. This is a generic module to reduce code redundancy. :param pandas.core.frame neoepitope_info: object containing with allele, pept, pred, core, normal_pept, normal_pred :param dict peptides: Dict of pepname: pep sequence for all IARS considered :param dict pepmap: Dict containing teh contents from the peptide map file. :param file outfile: An open file descriptor to the output file :param bool netmhc: Does this record correspond to a netmhcIIpan record? These are processed differently. """ if netmhc: peptide_names = [neoepitope_info.peptide_name] else: peptide_names = [x for x, y in peptides.items() if neoepitope_info.pept in y] # Convert named tuple to dict so it can be modified neoepitope_info = neoepitope_info._asdict() # Handle fusion peptides (They are characterized by having all N's as the normal partner) if neoepitope_info['normal_pept'] == 'N' * len(neoepitope_info['pept']): neoepitope_info['normal_pept'] = neoepitope_info['normal_pred'] = 'NA' # For each peptide, append the ensembl gene for peptide_name in peptide_names: print('{ni[allele]}\t' '{ni[pept]}\t' '{ni[normal_pept]}\t' '{pname}\t' '{ni[core]}\t' '0\t' '{ni[tumor_pred]}\t' '{ni[normal_pred]}\t' '{pmap}'.format(ni=neoepitope_info, pname=peptide_name, pmap=pepmap[peptide_name]), file=outfile) return None
python
def print_mhc_peptide(neoepitope_info, peptides, pepmap, outfile, netmhc=False): """ Accept data about one neoepitope from merge_mhc_peptide_calls and print it to outfile. This is a generic module to reduce code redundancy. :param pandas.core.frame neoepitope_info: object containing with allele, pept, pred, core, normal_pept, normal_pred :param dict peptides: Dict of pepname: pep sequence for all IARS considered :param dict pepmap: Dict containing teh contents from the peptide map file. :param file outfile: An open file descriptor to the output file :param bool netmhc: Does this record correspond to a netmhcIIpan record? These are processed differently. """ if netmhc: peptide_names = [neoepitope_info.peptide_name] else: peptide_names = [x for x, y in peptides.items() if neoepitope_info.pept in y] # Convert named tuple to dict so it can be modified neoepitope_info = neoepitope_info._asdict() # Handle fusion peptides (They are characterized by having all N's as the normal partner) if neoepitope_info['normal_pept'] == 'N' * len(neoepitope_info['pept']): neoepitope_info['normal_pept'] = neoepitope_info['normal_pred'] = 'NA' # For each peptide, append the ensembl gene for peptide_name in peptide_names: print('{ni[allele]}\t' '{ni[pept]}\t' '{ni[normal_pept]}\t' '{pname}\t' '{ni[core]}\t' '0\t' '{ni[tumor_pred]}\t' '{ni[normal_pred]}\t' '{pmap}'.format(ni=neoepitope_info, pname=peptide_name, pmap=pepmap[peptide_name]), file=outfile) return None
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Accept data about one neoepitope from merge_mhc_peptide_calls and print it to outfile. This is a generic module to reduce code redundancy. :param pandas.core.frame neoepitope_info: object containing with allele, pept, pred, core, normal_pept, normal_pred :param dict peptides: Dict of pepname: pep sequence for all IARS considered :param dict pepmap: Dict containing teh contents from the peptide map file. :param file outfile: An open file descriptor to the output file :param bool netmhc: Does this record correspond to a netmhcIIpan record? These are processed differently.
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06310682c50dcf8917b912c8e551299ff7ee41ce
https://github.com/BD2KGenomics/protect/blob/06310682c50dcf8917b912c8e551299ff7ee41ce/src/protect/binding_prediction/common.py#L581-L615
train
rs/domcheck
domcheck/__init__.py
check
def check(domain, prefix, code, strategies='*'): """ Check the ownership of a domain by going thru a serie of strategies. If at least one strategy succeed, the domain is considered verified, and this methods returns true. The prefix is a fixed DNS safe string like "yourservice-domain-verification" and the code is a random value associated to this domain. It is advised to prefix the code by a fixed value that is unique to your service like "yourservice2k3dWdk9dwz". By default all available strategies are tested. You can limit the check to a limited set of strategies by passing a comma separated list of strategy names like "nds_txt,dns_cname". See the "strategies" module for a full list of avaialble strategies. """ if strategies == '*' or 'dns_txt' in strategies: if check_dns_txt(domain, prefix, code): return True if strategies == '*' or 'dns_cname' in strategies: if check_dns_cname(domain, prefix, code): return True if strategies == '*' or 'meta_tag' in strategies: if check_meta_tag(domain, prefix, code): return True if strategies == '*' or 'html_file' in strategies: if check_html_file(domain, prefix, code): return True return False
python
def check(domain, prefix, code, strategies='*'): """ Check the ownership of a domain by going thru a serie of strategies. If at least one strategy succeed, the domain is considered verified, and this methods returns true. The prefix is a fixed DNS safe string like "yourservice-domain-verification" and the code is a random value associated to this domain. It is advised to prefix the code by a fixed value that is unique to your service like "yourservice2k3dWdk9dwz". By default all available strategies are tested. You can limit the check to a limited set of strategies by passing a comma separated list of strategy names like "nds_txt,dns_cname". See the "strategies" module for a full list of avaialble strategies. """ if strategies == '*' or 'dns_txt' in strategies: if check_dns_txt(domain, prefix, code): return True if strategies == '*' or 'dns_cname' in strategies: if check_dns_cname(domain, prefix, code): return True if strategies == '*' or 'meta_tag' in strategies: if check_meta_tag(domain, prefix, code): return True if strategies == '*' or 'html_file' in strategies: if check_html_file(domain, prefix, code): return True return False
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Check the ownership of a domain by going thru a serie of strategies. If at least one strategy succeed, the domain is considered verified, and this methods returns true. The prefix is a fixed DNS safe string like "yourservice-domain-verification" and the code is a random value associated to this domain. It is advised to prefix the code by a fixed value that is unique to your service like "yourservice2k3dWdk9dwz". By default all available strategies are tested. You can limit the check to a limited set of strategies by passing a comma separated list of strategy names like "nds_txt,dns_cname". See the "strategies" module for a full list of avaialble strategies.
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43e10c345320564a1236778e8577e2b8ef825925
https://github.com/rs/domcheck/blob/43e10c345320564a1236778e8577e2b8ef825925/domcheck/__init__.py#L6-L34
train
daxlab/Flask-Cache-Buster
flask_cache_buster/__init__.py
CacheBuster.register_cache_buster
def register_cache_buster(self, app, config=None): """ Register `app` in cache buster so that `url_for` adds a unique prefix to URLs generated for the `'static'` endpoint. Also make the app able to serve cache-busted static files. This allows setting long cache expiration values on static resources because whenever the resource changes, so does its URL. """ if not (config is None or isinstance(config, dict)): raise ValueError("`config` must be an instance of dict or None") bust_map = {} # map from an unbusted filename to a busted one unbust_map = {} # map from a busted filename to an unbusted one # http://flask.pocoo.org/docs/0.12/api/#flask.Flask.static_folder app.logger.debug('Starting computing hashes for static assets') # compute (un)bust tables. for dirpath, dirnames, filenames in os.walk(app.static_folder): for filename in filenames: # compute version component rooted_filename = os.path.join(dirpath, filename) if not self.__is_file_to_be_busted(rooted_filename): continue app.logger.debug(f'Computing hashes for {rooted_filename}') with open(rooted_filename, 'rb') as f: version = hashlib.md5( f.read() ).hexdigest()[:self.hash_size] # add version unbusted = os.path.relpath(rooted_filename, app.static_folder) # busted = os.path.join(version, unbusted) busted = f"{unbusted}?q={version}" # save computation to map bust_map[unbusted] = busted unbust_map[busted] = unbusted app.logger.debug('Finished Starting computing hashes for static assets') def bust_filename(file): return bust_map.get(file, file) def unbust_filename(file): return unbust_map.get(file, file) @app.url_defaults def reverse_to_cache_busted_url(endpoint, values): """ Make `url_for` produce busted filenames when using the 'static' endpoint. """ if endpoint == 'static': values['filename'] = bust_filename(values['filename']) def debusting_static_view(*args, **kwargs): """ Serve a request for a static file having a busted name. """ kwargs['filename'] = unbust_filename(kwargs.get('filename')) return original_static_view(*args, **kwargs) # Replace the default static file view with our debusting view. original_static_view = app.view_functions['static'] app.view_functions['static'] = debusting_static_view
python
def register_cache_buster(self, app, config=None): """ Register `app` in cache buster so that `url_for` adds a unique prefix to URLs generated for the `'static'` endpoint. Also make the app able to serve cache-busted static files. This allows setting long cache expiration values on static resources because whenever the resource changes, so does its URL. """ if not (config is None or isinstance(config, dict)): raise ValueError("`config` must be an instance of dict or None") bust_map = {} # map from an unbusted filename to a busted one unbust_map = {} # map from a busted filename to an unbusted one # http://flask.pocoo.org/docs/0.12/api/#flask.Flask.static_folder app.logger.debug('Starting computing hashes for static assets') # compute (un)bust tables. for dirpath, dirnames, filenames in os.walk(app.static_folder): for filename in filenames: # compute version component rooted_filename = os.path.join(dirpath, filename) if not self.__is_file_to_be_busted(rooted_filename): continue app.logger.debug(f'Computing hashes for {rooted_filename}') with open(rooted_filename, 'rb') as f: version = hashlib.md5( f.read() ).hexdigest()[:self.hash_size] # add version unbusted = os.path.relpath(rooted_filename, app.static_folder) # busted = os.path.join(version, unbusted) busted = f"{unbusted}?q={version}" # save computation to map bust_map[unbusted] = busted unbust_map[busted] = unbusted app.logger.debug('Finished Starting computing hashes for static assets') def bust_filename(file): return bust_map.get(file, file) def unbust_filename(file): return unbust_map.get(file, file) @app.url_defaults def reverse_to_cache_busted_url(endpoint, values): """ Make `url_for` produce busted filenames when using the 'static' endpoint. """ if endpoint == 'static': values['filename'] = bust_filename(values['filename']) def debusting_static_view(*args, **kwargs): """ Serve a request for a static file having a busted name. """ kwargs['filename'] = unbust_filename(kwargs.get('filename')) return original_static_view(*args, **kwargs) # Replace the default static file view with our debusting view. original_static_view = app.view_functions['static'] app.view_functions['static'] = debusting_static_view
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4c10bed9ab46020904df565a9c0014a7f2e4f6b3
https://github.com/daxlab/Flask-Cache-Buster/blob/4c10bed9ab46020904df565a9c0014a7f2e4f6b3/flask_cache_buster/__init__.py#L29-L93
train
theherk/figgypy
figgypy/utils.py
env_or_default
def env_or_default(var, default=None): """Get environment variable or provide default. Args: var (str): environment variable to search for default (optional(str)): default to return """ if var in os.environ: return os.environ[var] return default
python
def env_or_default(var, default=None): """Get environment variable or provide default. Args: var (str): environment variable to search for default (optional(str)): default to return """ if var in os.environ: return os.environ[var] return default
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Get environment variable or provide default. Args: var (str): environment variable to search for default (optional(str)): default to return
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324d1b281a8df20a26b92f42bf7fda0cca892116
https://github.com/theherk/figgypy/blob/324d1b281a8df20a26b92f42bf7fda0cca892116/figgypy/utils.py#L11-L20
train
theherk/figgypy
figgypy/utils.py
kms_encrypt
def kms_encrypt(value, key, aws_config=None): """Encrypt and value with KMS key. Args: value (str): value to encrypt key (str): key id or alias aws_config (optional[dict]): aws credentials dict of arguments passed into boto3 session example: aws_creds = {'aws_access_key_id': aws_access_key_id, 'aws_secret_access_key': aws_secret_access_key, 'region_name': 'us-east-1'} Returns: str: encrypted cipher text """ aws_config = aws_config or {} aws = boto3.session.Session(**aws_config) client = aws.client('kms') enc_res = client.encrypt(KeyId=key, Plaintext=value) return n(b64encode(enc_res['CiphertextBlob']))
python
def kms_encrypt(value, key, aws_config=None): """Encrypt and value with KMS key. Args: value (str): value to encrypt key (str): key id or alias aws_config (optional[dict]): aws credentials dict of arguments passed into boto3 session example: aws_creds = {'aws_access_key_id': aws_access_key_id, 'aws_secret_access_key': aws_secret_access_key, 'region_name': 'us-east-1'} Returns: str: encrypted cipher text """ aws_config = aws_config or {} aws = boto3.session.Session(**aws_config) client = aws.client('kms') enc_res = client.encrypt(KeyId=key, Plaintext=value) return n(b64encode(enc_res['CiphertextBlob']))
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324d1b281a8df20a26b92f42bf7fda0cca892116
https://github.com/theherk/figgypy/blob/324d1b281a8df20a26b92f42bf7fda0cca892116/figgypy/utils.py#L23-L44
train
theherk/figgypy
figgypy/__init__.py
get_value
def get_value(*args, **kwargs): """Get from config object by exposing Config.get_value method. dict.get() method on Config.values """ global _config if _config is None: raise ValueError('configuration not set; must run figgypy.set_config first') return _config.get_value(*args, **kwargs)
python
def get_value(*args, **kwargs): """Get from config object by exposing Config.get_value method. dict.get() method on Config.values """ global _config if _config is None: raise ValueError('configuration not set; must run figgypy.set_config first') return _config.get_value(*args, **kwargs)
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Get from config object by exposing Config.get_value method. dict.get() method on Config.values
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324d1b281a8df20a26b92f42bf7fda0cca892116
https://github.com/theherk/figgypy/blob/324d1b281a8df20a26b92f42bf7fda0cca892116/figgypy/__init__.py#L27-L35
train
theherk/figgypy
figgypy/__init__.py
set_value
def set_value(*args, **kwargs): """Set value in the global Config object.""" global _config if _config is None: raise ValueError('configuration not set; must run figgypy.set_config first') return _config.set_value(*args, **kwargs)
python
def set_value(*args, **kwargs): """Set value in the global Config object.""" global _config if _config is None: raise ValueError('configuration not set; must run figgypy.set_config first') return _config.set_value(*args, **kwargs)
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Set value in the global Config object.
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324d1b281a8df20a26b92f42bf7fda0cca892116
https://github.com/theherk/figgypy/blob/324d1b281a8df20a26b92f42bf7fda0cca892116/figgypy/__init__.py#L73-L78
train
Grk0/python-libconf
libconf.py
decode_escapes
def decode_escapes(s): '''Unescape libconfig string literals''' def decode_match(match): return codecs.decode(match.group(0), 'unicode-escape') return ESCAPE_SEQUENCE_RE.sub(decode_match, s)
python
def decode_escapes(s): '''Unescape libconfig string literals''' def decode_match(match): return codecs.decode(match.group(0), 'unicode-escape') return ESCAPE_SEQUENCE_RE.sub(decode_match, s)
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Unescape libconfig string literals
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9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L50-L55
train
Grk0/python-libconf
libconf.py
loads
def loads(string, filename=None, includedir=''): '''Load the contents of ``string`` to a Python object The returned object is a subclass of ``dict`` that exposes string keys as attributes as well. Example: >>> config = libconf.loads('window: { title: "libconfig example"; };') >>> config['window']['title'] 'libconfig example' >>> config.window.title 'libconfig example' ''' try: f = io.StringIO(string) except TypeError: raise TypeError("libconf.loads() input string must by unicode") return load(f, filename=filename, includedir=includedir)
python
def loads(string, filename=None, includedir=''): '''Load the contents of ``string`` to a Python object The returned object is a subclass of ``dict`` that exposes string keys as attributes as well. Example: >>> config = libconf.loads('window: { title: "libconfig example"; };') >>> config['window']['title'] 'libconfig example' >>> config.window.title 'libconfig example' ''' try: f = io.StringIO(string) except TypeError: raise TypeError("libconf.loads() input string must by unicode") return load(f, filename=filename, includedir=includedir)
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Load the contents of ``string`` to a Python object The returned object is a subclass of ``dict`` that exposes string keys as attributes as well. Example: >>> config = libconf.loads('window: { title: "libconfig example"; };') >>> config['window']['title'] 'libconfig example' >>> config.window.title 'libconfig example'
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9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L501-L521
train
Grk0/python-libconf
libconf.py
dump_string
def dump_string(s): '''Stringize ``s``, adding double quotes and escaping as necessary Backslash escape backslashes, double quotes, ``\f``, ``\n``, ``\r``, and ``\t``. Escape all remaining unprintable characters in ``\xFF``-style. The returned string will be surrounded by double quotes. ''' s = (s.replace('\\', '\\\\') .replace('"', '\\"') .replace('\f', r'\f') .replace('\n', r'\n') .replace('\r', r'\r') .replace('\t', r'\t')) s = UNPRINTABLE_CHARACTER_RE.sub( lambda m: r'\x{:02x}'.format(ord(m.group(0))), s) return '"' + s + '"'
python
def dump_string(s): '''Stringize ``s``, adding double quotes and escaping as necessary Backslash escape backslashes, double quotes, ``\f``, ``\n``, ``\r``, and ``\t``. Escape all remaining unprintable characters in ``\xFF``-style. The returned string will be surrounded by double quotes. ''' s = (s.replace('\\', '\\\\') .replace('"', '\\"') .replace('\f', r'\f') .replace('\n', r'\n') .replace('\r', r'\r') .replace('\t', r'\t')) s = UNPRINTABLE_CHARACTER_RE.sub( lambda m: r'\x{:02x}'.format(ord(m.group(0))), s) return '"' + s + '"'
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Stringize ``s``, adding double quotes and escaping as necessary Backslash escape backslashes, double quotes, ``\f``, ``\n``, ``\r``, and ``\t``. Escape all remaining unprintable characters in ``\xFF``-style. The returned string will be surrounded by double quotes.
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9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L555-L572
train
Grk0/python-libconf
libconf.py
get_dump_type
def get_dump_type(value): '''Get the libconfig datatype of a value Return values: ``'d'`` (dict), ``'l'`` (list), ``'a'`` (array), ``'i'`` (integer), ``'i64'`` (long integer), ``'b'`` (bool), ``'f'`` (float), or ``'s'`` (string). Produces the proper type for LibconfList, LibconfArray, LibconfInt64 instances. ''' if isinstance(value, dict): return 'd' if isinstance(value, tuple): return 'l' if isinstance(value, list): return 'a' # Test bool before int since isinstance(True, int) == True. if isinstance(value, bool): return 'b' if isint(value): if is_long_int(value): return 'i64' else: return 'i' if isinstance(value, float): return 'f' if isstr(value): return 's' return None
python
def get_dump_type(value): '''Get the libconfig datatype of a value Return values: ``'d'`` (dict), ``'l'`` (list), ``'a'`` (array), ``'i'`` (integer), ``'i64'`` (long integer), ``'b'`` (bool), ``'f'`` (float), or ``'s'`` (string). Produces the proper type for LibconfList, LibconfArray, LibconfInt64 instances. ''' if isinstance(value, dict): return 'd' if isinstance(value, tuple): return 'l' if isinstance(value, list): return 'a' # Test bool before int since isinstance(True, int) == True. if isinstance(value, bool): return 'b' if isint(value): if is_long_int(value): return 'i64' else: return 'i' if isinstance(value, float): return 'f' if isstr(value): return 's' return None
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Get the libconfig datatype of a value Return values: ``'d'`` (dict), ``'l'`` (list), ``'a'`` (array), ``'i'`` (integer), ``'i64'`` (long integer), ``'b'`` (bool), ``'f'`` (float), or ``'s'`` (string). Produces the proper type for LibconfList, LibconfArray, LibconfInt64 instances.
[ "Get", "the", "libconfig", "datatype", "of", "a", "value" ]
9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L575-L606
train
Grk0/python-libconf
libconf.py
get_array_value_dtype
def get_array_value_dtype(lst): '''Return array value type, raise ConfigSerializeError for invalid arrays Libconfig arrays must only contain scalar values and all elements must be of the same libconfig data type. Raises ConfigSerializeError if these invariants are not met. Returns the value type of the array. If an array contains both int and long int data types, the return datatype will be ``'i64'``. ''' array_value_type = None for value in lst: dtype = get_dump_type(value) if dtype not in {'b', 'i', 'i64', 'f', 's'}: raise ConfigSerializeError( "Invalid datatype in array (may only contain scalars):" "%r of type %s" % (value, type(value))) if array_value_type is None: array_value_type = dtype continue if array_value_type == dtype: continue if array_value_type == 'i' and dtype == 'i64': array_value_type = 'i64' continue if array_value_type == 'i64' and dtype == 'i': continue raise ConfigSerializeError( "Mixed types in array (all elements must have same type):" "%r of type %s" % (value, type(value))) return array_value_type
python
def get_array_value_dtype(lst): '''Return array value type, raise ConfigSerializeError for invalid arrays Libconfig arrays must only contain scalar values and all elements must be of the same libconfig data type. Raises ConfigSerializeError if these invariants are not met. Returns the value type of the array. If an array contains both int and long int data types, the return datatype will be ``'i64'``. ''' array_value_type = None for value in lst: dtype = get_dump_type(value) if dtype not in {'b', 'i', 'i64', 'f', 's'}: raise ConfigSerializeError( "Invalid datatype in array (may only contain scalars):" "%r of type %s" % (value, type(value))) if array_value_type is None: array_value_type = dtype continue if array_value_type == dtype: continue if array_value_type == 'i' and dtype == 'i64': array_value_type = 'i64' continue if array_value_type == 'i64' and dtype == 'i': continue raise ConfigSerializeError( "Mixed types in array (all elements must have same type):" "%r of type %s" % (value, type(value))) return array_value_type
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Return array value type, raise ConfigSerializeError for invalid arrays Libconfig arrays must only contain scalar values and all elements must be of the same libconfig data type. Raises ConfigSerializeError if these invariants are not met. Returns the value type of the array. If an array contains both int and long int data types, the return datatype will be ``'i64'``.
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9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L609-L646
train
Grk0/python-libconf
libconf.py
dump_value
def dump_value(key, value, f, indent=0): '''Save a value of any libconfig type This function serializes takes ``key`` and ``value`` and serializes them into ``f``. If ``key`` is ``None``, a list-style output is produced. Otherwise, output has ``key = value`` format. ''' spaces = ' ' * indent if key is None: key_prefix = '' key_prefix_nl = '' else: key_prefix = key + ' = ' key_prefix_nl = key + ' =\n' + spaces dtype = get_dump_type(value) if dtype == 'd': f.write(u'{}{}{{\n'.format(spaces, key_prefix_nl)) dump_dict(value, f, indent + 4) f.write(u'{}}}'.format(spaces)) elif dtype == 'l': f.write(u'{}{}(\n'.format(spaces, key_prefix_nl)) dump_collection(value, f, indent + 4) f.write(u'\n{})'.format(spaces)) elif dtype == 'a': f.write(u'{}{}[\n'.format(spaces, key_prefix_nl)) value_dtype = get_array_value_dtype(value) # If int array contains one or more Int64, promote all values to i64. if value_dtype == 'i64': value = [LibconfInt64(v) for v in value] dump_collection(value, f, indent + 4) f.write(u'\n{}]'.format(spaces)) elif dtype == 's': f.write(u'{}{}{}'.format(spaces, key_prefix, dump_string(value))) elif dtype == 'i' or dtype == 'i64': f.write(u'{}{}{}'.format(spaces, key_prefix, dump_int(value))) elif dtype == 'f' or dtype == 'b': f.write(u'{}{}{}'.format(spaces, key_prefix, value)) else: raise ConfigSerializeError("Can not serialize object %r of type %s" % (value, type(value)))
python
def dump_value(key, value, f, indent=0): '''Save a value of any libconfig type This function serializes takes ``key`` and ``value`` and serializes them into ``f``. If ``key`` is ``None``, a list-style output is produced. Otherwise, output has ``key = value`` format. ''' spaces = ' ' * indent if key is None: key_prefix = '' key_prefix_nl = '' else: key_prefix = key + ' = ' key_prefix_nl = key + ' =\n' + spaces dtype = get_dump_type(value) if dtype == 'd': f.write(u'{}{}{{\n'.format(spaces, key_prefix_nl)) dump_dict(value, f, indent + 4) f.write(u'{}}}'.format(spaces)) elif dtype == 'l': f.write(u'{}{}(\n'.format(spaces, key_prefix_nl)) dump_collection(value, f, indent + 4) f.write(u'\n{})'.format(spaces)) elif dtype == 'a': f.write(u'{}{}[\n'.format(spaces, key_prefix_nl)) value_dtype = get_array_value_dtype(value) # If int array contains one or more Int64, promote all values to i64. if value_dtype == 'i64': value = [LibconfInt64(v) for v in value] dump_collection(value, f, indent + 4) f.write(u'\n{}]'.format(spaces)) elif dtype == 's': f.write(u'{}{}{}'.format(spaces, key_prefix, dump_string(value))) elif dtype == 'i' or dtype == 'i64': f.write(u'{}{}{}'.format(spaces, key_prefix, dump_int(value))) elif dtype == 'f' or dtype == 'b': f.write(u'{}{}{}'.format(spaces, key_prefix, value)) else: raise ConfigSerializeError("Can not serialize object %r of type %s" % (value, type(value)))
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Save a value of any libconfig type This function serializes takes ``key`` and ``value`` and serializes them into ``f``. If ``key`` is ``None``, a list-style output is produced. Otherwise, output has ``key = value`` format.
[ "Save", "a", "value", "of", "any", "libconfig", "type" ]
9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L649-L692
train
Grk0/python-libconf
libconf.py
dump_collection
def dump_collection(cfg, f, indent=0): '''Save a collection of attributes''' for i, value in enumerate(cfg): dump_value(None, value, f, indent) if i < len(cfg) - 1: f.write(u',\n')
python
def dump_collection(cfg, f, indent=0): '''Save a collection of attributes''' for i, value in enumerate(cfg): dump_value(None, value, f, indent) if i < len(cfg) - 1: f.write(u',\n')
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Save a collection of attributes
[ "Save", "a", "collection", "of", "attributes" ]
9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L695-L701
train
Grk0/python-libconf
libconf.py
dump_dict
def dump_dict(cfg, f, indent=0): '''Save a dictionary of attributes''' for key in cfg: if not isstr(key): raise ConfigSerializeError("Dict keys must be strings: %r" % (key,)) dump_value(key, cfg[key], f, indent) f.write(u';\n')
python
def dump_dict(cfg, f, indent=0): '''Save a dictionary of attributes''' for key in cfg: if not isstr(key): raise ConfigSerializeError("Dict keys must be strings: %r" % (key,)) dump_value(key, cfg[key], f, indent) f.write(u';\n')
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Save a dictionary of attributes
[ "Save", "a", "dictionary", "of", "attributes" ]
9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L704-L712
train
Grk0/python-libconf
libconf.py
dumps
def dumps(cfg): '''Serialize ``cfg`` into a libconfig-formatted ``str`` ``cfg`` must be a ``dict`` with ``str`` keys and libconf-supported values (numbers, strings, booleans, possibly nested dicts, lists, and tuples). Returns the formatted string. ''' str_file = io.StringIO() dump(cfg, str_file) return str_file.getvalue()
python
def dumps(cfg): '''Serialize ``cfg`` into a libconfig-formatted ``str`` ``cfg`` must be a ``dict`` with ``str`` keys and libconf-supported values (numbers, strings, booleans, possibly nested dicts, lists, and tuples). Returns the formatted string. ''' str_file = io.StringIO() dump(cfg, str_file) return str_file.getvalue()
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Serialize ``cfg`` into a libconfig-formatted ``str`` ``cfg`` must be a ``dict`` with ``str`` keys and libconf-supported values (numbers, strings, booleans, possibly nested dicts, lists, and tuples). Returns the formatted string.
[ "Serialize", "cfg", "into", "a", "libconfig", "-", "formatted", "str" ]
9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L715-L726
train
Grk0/python-libconf
libconf.py
dump
def dump(cfg, f): '''Serialize ``cfg`` as a libconfig-formatted stream into ``f`` ``cfg`` must be a ``dict`` with ``str`` keys and libconf-supported values (numbers, strings, booleans, possibly nested dicts, lists, and tuples). ``f`` must be a ``file``-like object with a ``write()`` method. ''' if not isinstance(cfg, dict): raise ConfigSerializeError( 'dump() requires a dict as input, not %r of type %r' % (cfg, type(cfg))) dump_dict(cfg, f, 0)
python
def dump(cfg, f): '''Serialize ``cfg`` as a libconfig-formatted stream into ``f`` ``cfg`` must be a ``dict`` with ``str`` keys and libconf-supported values (numbers, strings, booleans, possibly nested dicts, lists, and tuples). ``f`` must be a ``file``-like object with a ``write()`` method. ''' if not isinstance(cfg, dict): raise ConfigSerializeError( 'dump() requires a dict as input, not %r of type %r' % (cfg, type(cfg))) dump_dict(cfg, f, 0)
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Serialize ``cfg`` as a libconfig-formatted stream into ``f`` ``cfg`` must be a ``dict`` with ``str`` keys and libconf-supported values (numbers, strings, booleans, possibly nested dicts, lists, and tuples). ``f`` must be a ``file``-like object with a ``write()`` method.
[ "Serialize", "cfg", "as", "a", "libconfig", "-", "formatted", "stream", "into", "f" ]
9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L729-L743
train
Grk0/python-libconf
libconf.py
Tokenizer.tokenize
def tokenize(self, string): '''Yield tokens from the input string or throw ConfigParseError''' pos = 0 while pos < len(string): m = SKIP_RE.match(string, pos=pos) if m: skip_lines = m.group(0).split('\n') if len(skip_lines) > 1: self.row += len(skip_lines) - 1 self.column = 1 + len(skip_lines[-1]) else: self.column += len(skip_lines[0]) pos = m.end() continue for cls, type, regex in self.token_map: m = regex.match(string, pos=pos) if m: yield cls(type, m.group(0), self.filename, self.row, self.column) self.column += len(m.group(0)) pos = m.end() break else: raise ConfigParseError( "Couldn't load config in %r row %d, column %d: %r" % (self.filename, self.row, self.column, string[pos:pos+20]))
python
def tokenize(self, string): '''Yield tokens from the input string or throw ConfigParseError''' pos = 0 while pos < len(string): m = SKIP_RE.match(string, pos=pos) if m: skip_lines = m.group(0).split('\n') if len(skip_lines) > 1: self.row += len(skip_lines) - 1 self.column = 1 + len(skip_lines[-1]) else: self.column += len(skip_lines[0]) pos = m.end() continue for cls, type, regex in self.token_map: m = regex.match(string, pos=pos) if m: yield cls(type, m.group(0), self.filename, self.row, self.column) self.column += len(m.group(0)) pos = m.end() break else: raise ConfigParseError( "Couldn't load config in %r row %d, column %d: %r" % (self.filename, self.row, self.column, string[pos:pos+20]))
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Yield tokens from the input string or throw ConfigParseError
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9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L178-L206
train
Grk0/python-libconf
libconf.py
TokenStream.from_file
def from_file(cls, f, filename=None, includedir='', seenfiles=None): '''Create a token stream by reading an input file Read tokens from `f`. If an include directive ('@include "file.cfg"') is found, read its contents as well. The `filename` argument is used for error messages and to detect circular imports. ``includedir`` sets the lookup directory for included files. ``seenfiles`` is used internally to detect circular includes, and should normally not be supplied by users of is function. ''' if filename is None: filename = getattr(f, 'name', '<unknown>') if seenfiles is None: seenfiles = set() if filename in seenfiles: raise ConfigParseError("Circular include: %r" % (filename,)) seenfiles = seenfiles | {filename} # Copy seenfiles, don't alter it. tokenizer = Tokenizer(filename=filename) lines = [] tokens = [] for line in f: m = re.match(r'@include "(.*)"$', line.strip()) if m: tokens.extend(tokenizer.tokenize(''.join(lines))) lines = [re.sub(r'\S', ' ', line)] includefilename = decode_escapes(m.group(1)) includefilename = os.path.join(includedir, includefilename) try: includefile = open(includefilename, "r") except IOError: raise ConfigParseError("Could not open include file %r" % (includefilename,)) with includefile: includestream = cls.from_file(includefile, filename=includefilename, includedir=includedir, seenfiles=seenfiles) tokens.extend(includestream.tokens) else: lines.append(line) tokens.extend(tokenizer.tokenize(''.join(lines))) return cls(tokens)
python
def from_file(cls, f, filename=None, includedir='', seenfiles=None): '''Create a token stream by reading an input file Read tokens from `f`. If an include directive ('@include "file.cfg"') is found, read its contents as well. The `filename` argument is used for error messages and to detect circular imports. ``includedir`` sets the lookup directory for included files. ``seenfiles`` is used internally to detect circular includes, and should normally not be supplied by users of is function. ''' if filename is None: filename = getattr(f, 'name', '<unknown>') if seenfiles is None: seenfiles = set() if filename in seenfiles: raise ConfigParseError("Circular include: %r" % (filename,)) seenfiles = seenfiles | {filename} # Copy seenfiles, don't alter it. tokenizer = Tokenizer(filename=filename) lines = [] tokens = [] for line in f: m = re.match(r'@include "(.*)"$', line.strip()) if m: tokens.extend(tokenizer.tokenize(''.join(lines))) lines = [re.sub(r'\S', ' ', line)] includefilename = decode_escapes(m.group(1)) includefilename = os.path.join(includedir, includefilename) try: includefile = open(includefilename, "r") except IOError: raise ConfigParseError("Could not open include file %r" % (includefilename,)) with includefile: includestream = cls.from_file(includefile, filename=includefilename, includedir=includedir, seenfiles=seenfiles) tokens.extend(includestream.tokens) else: lines.append(line) tokens.extend(tokenizer.tokenize(''.join(lines))) return cls(tokens)
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9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L224-L273
train
Grk0/python-libconf
libconf.py
TokenStream.error
def error(self, msg): '''Raise a ConfigParseError at the current input position''' if self.finished(): raise ConfigParseError("Unexpected end of input; %s" % (msg,)) else: t = self.peek() raise ConfigParseError("Unexpected token %s; %s" % (t, msg))
python
def error(self, msg): '''Raise a ConfigParseError at the current input position''' if self.finished(): raise ConfigParseError("Unexpected end of input; %s" % (msg,)) else: t = self.peek() raise ConfigParseError("Unexpected token %s; %s" % (t, msg))
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Raise a ConfigParseError at the current input position
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9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4
https://github.com/Grk0/python-libconf/blob/9c4cf5f56d56ebbc1fe0e1596807218b7d5d5da4/libconf.py#L321-L327
train
FulcrumTechnologies/pyconfluence
pyconfluence/api.py
load_variables
def load_variables(): """Load variables from environment variables.""" if (not os.environ.get("PYCONFLUENCE_TOKEN") or not os.environ.get("PYCONFLUENCE_USER") or not os.environ.get("PYCONFLUENCE_ORG")): print ("One or more pyconfluence environment variables are not set. " "See README for directions on how to resolve this.") sys.exit("Error") global token global user global base_url token = os.environ["PYCONFLUENCE_TOKEN"] user = os.environ["PYCONFLUENCE_USER"] base_url = ("https://" + os.environ["PYCONFLUENCE_ORG"] + ".atlassian" ".net/wiki/rest/api/content")
python
def load_variables(): """Load variables from environment variables.""" if (not os.environ.get("PYCONFLUENCE_TOKEN") or not os.environ.get("PYCONFLUENCE_USER") or not os.environ.get("PYCONFLUENCE_ORG")): print ("One or more pyconfluence environment variables are not set. " "See README for directions on how to resolve this.") sys.exit("Error") global token global user global base_url token = os.environ["PYCONFLUENCE_TOKEN"] user = os.environ["PYCONFLUENCE_USER"] base_url = ("https://" + os.environ["PYCONFLUENCE_ORG"] + ".atlassian" ".net/wiki/rest/api/content")
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Load variables from environment variables.
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a999726dbc1cbdd3d9062234698eeae799ce84ce
https://github.com/FulcrumTechnologies/pyconfluence/blob/a999726dbc1cbdd3d9062234698eeae799ce84ce/pyconfluence/api.py#L21-L36
train
FulcrumTechnologies/pyconfluence
pyconfluence/api.py
rest
def rest(url, req="GET", data=None): """Main function to be called from this module. send a request using method 'req' and to the url. the _rest() function will add the base_url to this, so 'url' should be something like '/ips'. """ load_variables() return _rest(base_url + url, req, data)
python
def rest(url, req="GET", data=None): """Main function to be called from this module. send a request using method 'req' and to the url. the _rest() function will add the base_url to this, so 'url' should be something like '/ips'. """ load_variables() return _rest(base_url + url, req, data)
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Main function to be called from this module. send a request using method 'req' and to the url. the _rest() function will add the base_url to this, so 'url' should be something like '/ips'.
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a999726dbc1cbdd3d9062234698eeae799ce84ce
https://github.com/FulcrumTechnologies/pyconfluence/blob/a999726dbc1cbdd3d9062234698eeae799ce84ce/pyconfluence/api.py#L39-L47
train
FulcrumTechnologies/pyconfluence
pyconfluence/api.py
_rest
def _rest(url, req, data=None): """Send a rest rest request to the server.""" if url.upper().startswith("HTTPS"): print("Secure connection required: Please use HTTPS or https") return "" req = req.upper() if req != "GET" and req != "PUT" and req != "POST" and req != "DELETE": return "" status, body = _api_action(url, req, data) if (int(status) >= 200 and int(status) <= 226): return body else: return body
python
def _rest(url, req, data=None): """Send a rest rest request to the server.""" if url.upper().startswith("HTTPS"): print("Secure connection required: Please use HTTPS or https") return "" req = req.upper() if req != "GET" and req != "PUT" and req != "POST" and req != "DELETE": return "" status, body = _api_action(url, req, data) if (int(status) >= 200 and int(status) <= 226): return body else: return body
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Send a rest rest request to the server.
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a999726dbc1cbdd3d9062234698eeae799ce84ce
https://github.com/FulcrumTechnologies/pyconfluence/blob/a999726dbc1cbdd3d9062234698eeae799ce84ce/pyconfluence/api.py#L50-L64
train
FulcrumTechnologies/pyconfluence
pyconfluence/api.py
_api_action
def _api_action(url, req, data=None): """Take action based on what kind of request is needed.""" requisite_headers = {'Accept': 'application/json', 'Content-Type': 'application/json'} auth = (user, token) if req == "GET": response = requests.get(url, headers=requisite_headers, auth=auth) elif req == "PUT": response = requests.put(url, headers=requisite_headers, auth=auth, data=data) elif req == "POST": response = requests.post(url, headers=requisite_headers, auth=auth, data=data) elif req == "DELETE": response = requests.delete(url, headers=requisite_headers, auth=auth) return response.status_code, response.text
python
def _api_action(url, req, data=None): """Take action based on what kind of request is needed.""" requisite_headers = {'Accept': 'application/json', 'Content-Type': 'application/json'} auth = (user, token) if req == "GET": response = requests.get(url, headers=requisite_headers, auth=auth) elif req == "PUT": response = requests.put(url, headers=requisite_headers, auth=auth, data=data) elif req == "POST": response = requests.post(url, headers=requisite_headers, auth=auth, data=data) elif req == "DELETE": response = requests.delete(url, headers=requisite_headers, auth=auth) return response.status_code, response.text
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Take action based on what kind of request is needed.
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a999726dbc1cbdd3d9062234698eeae799ce84ce
https://github.com/FulcrumTechnologies/pyconfluence/blob/a999726dbc1cbdd3d9062234698eeae799ce84ce/pyconfluence/api.py#L67-L84
train
kstaniek/condoor
condoor/patterns.py
PatternManager._platform_patterns
def _platform_patterns(self, platform='generic', compiled=False): """Return all the patterns for specific platform.""" patterns = self._dict_compiled.get(platform, None) if compiled else self._dict_text.get(platform, None) if patterns is None: raise KeyError("Unknown platform: {}".format(platform)) return patterns
python
def _platform_patterns(self, platform='generic', compiled=False): """Return all the patterns for specific platform.""" patterns = self._dict_compiled.get(platform, None) if compiled else self._dict_text.get(platform, None) if patterns is None: raise KeyError("Unknown platform: {}".format(platform)) return patterns
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Return all the patterns for specific platform.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/patterns.py#L56-L61
train
kstaniek/condoor
condoor/patterns.py
PatternManager.pattern
def pattern(self, platform, key, compiled=True): """Return the pattern defined by the key string specific to the platform. :param platform: :param key: :param compiled: :return: Pattern string or RE object. """ patterns = self._platform_patterns(platform, compiled=compiled) pattern = patterns.get(key, self._platform_patterns(compiled=compiled).get(key, None)) if pattern is None: raise KeyError("Patterns database corrupted. Platform: {}, Key: {}".format(platform, key)) return pattern
python
def pattern(self, platform, key, compiled=True): """Return the pattern defined by the key string specific to the platform. :param platform: :param key: :param compiled: :return: Pattern string or RE object. """ patterns = self._platform_patterns(platform, compiled=compiled) pattern = patterns.get(key, self._platform_patterns(compiled=compiled).get(key, None)) if pattern is None: raise KeyError("Patterns database corrupted. Platform: {}, Key: {}".format(platform, key)) return pattern
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Return the pattern defined by the key string specific to the platform. :param platform: :param key: :param compiled: :return: Pattern string or RE object.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/patterns.py#L76-L90
train
kstaniek/condoor
condoor/patterns.py
PatternManager.description
def description(self, platform, key): """Return the patter description.""" patterns = self._dict_dscr.get(platform, None) description = patterns.get(key, None) return description
python
def description(self, platform, key): """Return the patter description.""" patterns = self._dict_dscr.get(platform, None) description = patterns.get(key, None) return description
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Return the patter description.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/patterns.py#L92-L96
train
kstaniek/condoor
condoor/patterns.py
PatternManager.platform
def platform(self, with_prompt, platforms=None): """Return the platform name based on the prompt matching.""" if platforms is None: platforms = self._dict['generic']['prompt_detection'] for platform in platforms: pattern = self.pattern(platform, 'prompt') result = re.search(pattern, with_prompt) if result: return platform return None
python
def platform(self, with_prompt, platforms=None): """Return the platform name based on the prompt matching.""" if platforms is None: platforms = self._dict['generic']['prompt_detection'] for platform in platforms: pattern = self.pattern(platform, 'prompt') result = re.search(pattern, with_prompt) if result: return platform return None
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Return the platform name based on the prompt matching.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/patterns.py#L98-L108
train
kstaniek/condoor
condoor/drivers/Calvados.py
Driver.after_connect
def after_connect(self): """Execute after connect.""" # TODO: check if this works. show_users = self.device.send("show users", timeout=120) result = re.search(pattern_manager.pattern(self.platform, 'connected_locally'), show_users) if result: self.log('Locally connected to Calvados. Exiting.') self.device.send('exit') return True return False
python
def after_connect(self): """Execute after connect.""" # TODO: check if this works. show_users = self.device.send("show users", timeout=120) result = re.search(pattern_manager.pattern(self.platform, 'connected_locally'), show_users) if result: self.log('Locally connected to Calvados. Exiting.') self.device.send('exit') return True return False
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Execute after connect.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/drivers/Calvados.py#L47-L56
train
kstaniek/condoor
condoor/drivers/jumphost.py
Driver.get_hostname_text
def get_hostname_text(self): """Return hostname information from the Unix host.""" # FIXME: fix it, too complex logic try: hostname_text = self.device.send('hostname', timeout=10) if hostname_text: self.device.hostname = hostname_text.splitlines()[0] return hostname_text except CommandError: self.log("Non Unix jumphost type detected") return None
python
def get_hostname_text(self): """Return hostname information from the Unix host.""" # FIXME: fix it, too complex logic try: hostname_text = self.device.send('hostname', timeout=10) if hostname_text: self.device.hostname = hostname_text.splitlines()[0] return hostname_text except CommandError: self.log("Non Unix jumphost type detected") return None
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Return hostname information from the Unix host.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/drivers/jumphost.py#L35-L45
train
theherk/figgypy
figgypy/config.py
Config._find_file
def _find_file(f): """Find a config file if possible.""" if os.path.isabs(f): return f else: for d in Config._dirs: _f = os.path.join(d, f) if os.path.isfile(_f): return _f raise FiggypyError( "could not find configuration file {} in dirs {}" .format(f, Config._dirs) )
python
def _find_file(f): """Find a config file if possible.""" if os.path.isabs(f): return f else: for d in Config._dirs: _f = os.path.join(d, f) if os.path.isfile(_f): return _f raise FiggypyError( "could not find configuration file {} in dirs {}" .format(f, Config._dirs) )
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Find a config file if possible.
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324d1b281a8df20a26b92f42bf7fda0cca892116
https://github.com/theherk/figgypy/blob/324d1b281a8df20a26b92f42bf7fda0cca892116/figgypy/config.py#L82-L94
train
theherk/figgypy
figgypy/config.py
Config._load_file
def _load_file(self, f): """Get values from config file""" try: with open(f, 'r') as _fo: _seria_in = seria.load(_fo) _y = _seria_in.dump('yaml') except IOError: raise FiggypyError("could not open configuration file") self.values.update(yaml.load(_y))
python
def _load_file(self, f): """Get values from config file""" try: with open(f, 'r') as _fo: _seria_in = seria.load(_fo) _y = _seria_in.dump('yaml') except IOError: raise FiggypyError("could not open configuration file") self.values.update(yaml.load(_y))
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Get values from config file
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324d1b281a8df20a26b92f42bf7fda0cca892116
https://github.com/theherk/figgypy/blob/324d1b281a8df20a26b92f42bf7fda0cca892116/figgypy/config.py#L96-L104
train
theherk/figgypy
figgypy/config.py
Config.setup
def setup(self, config_file=None, aws_config=None, gpg_config=None, decrypt_gpg=True, decrypt_kms=True): """Make setup easier by providing a constructor method. Move to config_file File can be located with a filename only, relative path, or absolute path. If only name or relative path is provided, look in this order: 1. current directory 2. `~/.config/<file_name>` 3. `/etc/<file_name>` It is a good idea to include you __package__ in the file name. For example, `cfg = Config(os.path.join(__package__, 'config.yaml'))`. This way it will look for your_package/config.yaml, ~/.config/your_package/config.yaml, and /etc/your_package/config.yaml. """ if aws_config is not None: self.aws_config = aws_config if gpg_config is not None: self.gpg_config = gpg_config if decrypt_kms is not None: self.decrypt_kms = decrypt_kms if decrypt_gpg is not None: self.decrypt_gpg = decrypt_gpg # Again, load the file last so that it can rely on other properties. if config_file is not None: self.config_file = config_file return self
python
def setup(self, config_file=None, aws_config=None, gpg_config=None, decrypt_gpg=True, decrypt_kms=True): """Make setup easier by providing a constructor method. Move to config_file File can be located with a filename only, relative path, or absolute path. If only name or relative path is provided, look in this order: 1. current directory 2. `~/.config/<file_name>` 3. `/etc/<file_name>` It is a good idea to include you __package__ in the file name. For example, `cfg = Config(os.path.join(__package__, 'config.yaml'))`. This way it will look for your_package/config.yaml, ~/.config/your_package/config.yaml, and /etc/your_package/config.yaml. """ if aws_config is not None: self.aws_config = aws_config if gpg_config is not None: self.gpg_config = gpg_config if decrypt_kms is not None: self.decrypt_kms = decrypt_kms if decrypt_gpg is not None: self.decrypt_gpg = decrypt_gpg # Again, load the file last so that it can rely on other properties. if config_file is not None: self.config_file = config_file return self
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Make setup easier by providing a constructor method. Move to config_file File can be located with a filename only, relative path, or absolute path. If only name or relative path is provided, look in this order: 1. current directory 2. `~/.config/<file_name>` 3. `/etc/<file_name>` It is a good idea to include you __package__ in the file name. For example, `cfg = Config(os.path.join(__package__, 'config.yaml'))`. This way it will look for your_package/config.yaml, ~/.config/your_package/config.yaml, and /etc/your_package/config.yaml.
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324d1b281a8df20a26b92f42bf7fda0cca892116
https://github.com/theherk/figgypy/blob/324d1b281a8df20a26b92f42bf7fda0cca892116/figgypy/config.py#L199-L227
train
kstaniek/condoor
condoor/protocols/console.py
Console.authenticate
def authenticate(self, driver): """Authenticate using the Console Server protocol specific FSM.""" # 0 1 2 3 events = [driver.username_re, driver.password_re, self.device.prompt_re, driver.rommon_re, # 4 5 6 7 8 driver.unable_to_connect_re, driver.authentication_error_re, pexpect.TIMEOUT, pexpect.EOF] transitions = [ (driver.username_re, [0], 1, partial(a_send_username, self.username), 10), (driver.username_re, [1], 1, None, 10), (driver.password_re, [0, 1], 2, partial(a_send_password, self._acquire_password()), _C['first_prompt_timeout']), (driver.username_re, [2], -1, a_authentication_error, 0), (driver.password_re, [2], -1, a_authentication_error, 0), (driver.authentication_error_re, [1, 2], -1, a_authentication_error, 0), (self.device.prompt_re, [0, 1, 2], -1, None, 0), (driver.rommon_re, [0], -1, partial(a_send, "\r\n"), 0), (pexpect.TIMEOUT, [0], 1, partial(a_send, "\r\n"), 10), (pexpect.TIMEOUT, [2], -1, None, 0), (pexpect.TIMEOUT, [3, 7], -1, ConnectionTimeoutError("Connection Timeout", self.hostname), 0), (driver.unable_to_connect_re, [0, 1, 2], -1, a_unable_to_connect, 0), ] self.log("EXPECTED_PROMPT={}".format(pattern_to_str(self.device.prompt_re))) fsm = FSM("CONSOLE-SERVER-AUTH", self.device, events, transitions, timeout=_C['connect_timeout'], init_pattern=self.last_pattern) return fsm.run()
python
def authenticate(self, driver): """Authenticate using the Console Server protocol specific FSM.""" # 0 1 2 3 events = [driver.username_re, driver.password_re, self.device.prompt_re, driver.rommon_re, # 4 5 6 7 8 driver.unable_to_connect_re, driver.authentication_error_re, pexpect.TIMEOUT, pexpect.EOF] transitions = [ (driver.username_re, [0], 1, partial(a_send_username, self.username), 10), (driver.username_re, [1], 1, None, 10), (driver.password_re, [0, 1], 2, partial(a_send_password, self._acquire_password()), _C['first_prompt_timeout']), (driver.username_re, [2], -1, a_authentication_error, 0), (driver.password_re, [2], -1, a_authentication_error, 0), (driver.authentication_error_re, [1, 2], -1, a_authentication_error, 0), (self.device.prompt_re, [0, 1, 2], -1, None, 0), (driver.rommon_re, [0], -1, partial(a_send, "\r\n"), 0), (pexpect.TIMEOUT, [0], 1, partial(a_send, "\r\n"), 10), (pexpect.TIMEOUT, [2], -1, None, 0), (pexpect.TIMEOUT, [3, 7], -1, ConnectionTimeoutError("Connection Timeout", self.hostname), 0), (driver.unable_to_connect_re, [0, 1, 2], -1, a_unable_to_connect, 0), ] self.log("EXPECTED_PROMPT={}".format(pattern_to_str(self.device.prompt_re))) fsm = FSM("CONSOLE-SERVER-AUTH", self.device, events, transitions, timeout=_C['connect_timeout'], init_pattern=self.last_pattern) return fsm.run()
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Authenticate using the Console Server protocol specific FSM.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/protocols/console.py#L70-L95
train
kstaniek/condoor
condoor/utils.py
delegate
def delegate(attribute_name, method_names): """Pass the call to the attribute called attribute_name for every method listed in method_names.""" # hack for python 2.7 as nonlocal is not available info = { 'attribute': attribute_name, 'methods': method_names } def decorator(cls): """Decorate class.""" attribute = info['attribute'] if attribute.startswith("__"): attribute = "_" + cls.__name__ + attribute for name in info['methods']: setattr(cls, name, eval("lambda self, *a, **kw: " "self.{0}.{1}(*a, **kw)".format(attribute, name))) return cls return decorator
python
def delegate(attribute_name, method_names): """Pass the call to the attribute called attribute_name for every method listed in method_names.""" # hack for python 2.7 as nonlocal is not available info = { 'attribute': attribute_name, 'methods': method_names } def decorator(cls): """Decorate class.""" attribute = info['attribute'] if attribute.startswith("__"): attribute = "_" + cls.__name__ + attribute for name in info['methods']: setattr(cls, name, eval("lambda self, *a, **kw: " "self.{0}.{1}(*a, **kw)".format(attribute, name))) return cls return decorator
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/utils.py#L12-L29
train
kstaniek/condoor
condoor/utils.py
pattern_to_str
def pattern_to_str(pattern): """Convert regex pattern to string. If pattern is string it returns itself, if pattern is SRE_Pattern then return pattern attribute :param pattern: pattern object or string :return: str: pattern sttring """ if isinstance(pattern, str): return repr(pattern) else: return repr(pattern.pattern) if pattern else None
python
def pattern_to_str(pattern): """Convert regex pattern to string. If pattern is string it returns itself, if pattern is SRE_Pattern then return pattern attribute :param pattern: pattern object or string :return: str: pattern sttring """ if isinstance(pattern, str): return repr(pattern) else: return repr(pattern.pattern) if pattern else None
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Convert regex pattern to string. If pattern is string it returns itself, if pattern is SRE_Pattern then return pattern attribute :param pattern: pattern object or string :return: str: pattern sttring
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/utils.py#L85-L96
train
kstaniek/condoor
condoor/utils.py
levenshtein_distance
def levenshtein_distance(str_a, str_b): """Calculate the Levenshtein distance between string a and b. :param str_a: String - input string a :param str_b: String - input string b :return: Number - Levenshtein Distance between string a and b """ len_a, len_b = len(str_a), len(str_b) if len_a > len_b: str_a, str_b = str_b, str_a len_a, len_b = len_b, len_a current = range(len_a + 1) for i in range(1, len_b + 1): previous, current = current, [i] + [0] * len_a for j in range(1, len_a + 1): add, delete = previous[j] + 1, current[j - 1] + 1 change = previous[j - 1] if str_a[j - 1] != str_b[i - 1]: change += + 1 current[j] = min(add, delete, change) return current[len_a]
python
def levenshtein_distance(str_a, str_b): """Calculate the Levenshtein distance between string a and b. :param str_a: String - input string a :param str_b: String - input string b :return: Number - Levenshtein Distance between string a and b """ len_a, len_b = len(str_a), len(str_b) if len_a > len_b: str_a, str_b = str_b, str_a len_a, len_b = len_b, len_a current = range(len_a + 1) for i in range(1, len_b + 1): previous, current = current, [i] + [0] * len_a for j in range(1, len_a + 1): add, delete = previous[j] + 1, current[j - 1] + 1 change = previous[j - 1] if str_a[j - 1] != str_b[i - 1]: change += + 1 current[j] = min(add, delete, change) return current[len_a]
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Calculate the Levenshtein distance between string a and b. :param str_a: String - input string a :param str_b: String - input string b :return: Number - Levenshtein Distance between string a and b
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/utils.py#L99-L119
train
kstaniek/condoor
condoor/utils.py
parse_inventory
def parse_inventory(inventory_output=None): """Parse the inventory text and return udi dict.""" udi = { "name": "", "description": "", "pid": "", "vid": "", "sn": "" } if inventory_output is None: return udi # find the record with chassis text in name or descr capture_next = False chassis_udi_text = None for line in inventory_output.split('\n'): lc_line = line.lower() if ('chassis' in lc_line or 'switch system' in lc_line or 'rack' in lc_line) and 'name' in lc_line and 'descr': capture_next = True chassis_udi_text = line continue if capture_next: inventory_output = chassis_udi_text + "\n" + line break match = re.search(r"(?i)NAME: (?P<name>.*?),? (?i)DESCR", inventory_output, re.MULTILINE) if match: udi['name'] = match.group('name').strip('" ,') match = re.search(r"(?i)DESCR: (?P<description>.*)", inventory_output, re.MULTILINE) if match: udi['description'] = match.group('description').strip('" ') match = re.search(r"(?i)PID: (?P<pid>.*?),? ", inventory_output, re.MULTILINE) if match: udi['pid'] = match.group('pid') match = re.search(r"(?i)VID: (?P<vid>.*?),? ", inventory_output, re.MULTILINE) if match: udi['vid'] = match.group('vid') match = re.search(r"(?i)SN: (?P<sn>.*)", inventory_output, re.MULTILINE) if match: udi['sn'] = match.group('sn').strip() return udi
python
def parse_inventory(inventory_output=None): """Parse the inventory text and return udi dict.""" udi = { "name": "", "description": "", "pid": "", "vid": "", "sn": "" } if inventory_output is None: return udi # find the record with chassis text in name or descr capture_next = False chassis_udi_text = None for line in inventory_output.split('\n'): lc_line = line.lower() if ('chassis' in lc_line or 'switch system' in lc_line or 'rack' in lc_line) and 'name' in lc_line and 'descr': capture_next = True chassis_udi_text = line continue if capture_next: inventory_output = chassis_udi_text + "\n" + line break match = re.search(r"(?i)NAME: (?P<name>.*?),? (?i)DESCR", inventory_output, re.MULTILINE) if match: udi['name'] = match.group('name').strip('" ,') match = re.search(r"(?i)DESCR: (?P<description>.*)", inventory_output, re.MULTILINE) if match: udi['description'] = match.group('description').strip('" ') match = re.search(r"(?i)PID: (?P<pid>.*?),? ", inventory_output, re.MULTILINE) if match: udi['pid'] = match.group('pid') match = re.search(r"(?i)VID: (?P<vid>.*?),? ", inventory_output, re.MULTILINE) if match: udi['vid'] = match.group('vid') match = re.search(r"(?i)SN: (?P<sn>.*)", inventory_output, re.MULTILINE) if match: udi['sn'] = match.group('sn').strip() return udi
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Parse the inventory text and return udi dict.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/utils.py#L122-L165
train
kstaniek/condoor
condoor/utils.py
normalize_urls
def normalize_urls(urls): """Overload urls and make list of lists of urls.""" _urls = [] if isinstance(urls, list): if urls: if isinstance(urls[0], list): # multiple connections (list of the lists) _urls = urls elif isinstance(urls[0], str): # single connections (make it list of the lists) _urls = [urls] else: raise RuntimeError("No target host url provided.") elif isinstance(urls, str): _urls = [[urls]] return _urls
python
def normalize_urls(urls): """Overload urls and make list of lists of urls.""" _urls = [] if isinstance(urls, list): if urls: if isinstance(urls[0], list): # multiple connections (list of the lists) _urls = urls elif isinstance(urls[0], str): # single connections (make it list of the lists) _urls = [urls] else: raise RuntimeError("No target host url provided.") elif isinstance(urls, str): _urls = [[urls]] return _urls
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Overload urls and make list of lists of urls.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/utils.py#L233-L248
train
kstaniek/condoor
condoor/utils.py
yaml_file_to_dict
def yaml_file_to_dict(script_name, path=None): """Read yaml file and return the dict. It assumes the module file exists with the defaults. If the CONDOOR_{SCRIPT_NAME} env is set then the user file from the env is loaded and merged with the default There can be user file located in ~/.condoor directory with the {script_name}.yaml filename. If exists it is merget with default config. """ def load_yaml(file_path): """Load YAML file from full file path and return dict.""" with open(file_path, 'r') as yamlfile: try: dictionary = yaml.load(yamlfile) except yaml.YAMLError: return {} return dictionary def merge(user, default): """Merge two dicts.""" if isinstance(user, dict) and isinstance(default, dict): for k, v in default.iteritems(): if k not in user: user[k] = v else: user[k] = merge(user[k], v) return user if path is None: path = os.path.abspath('.') config_file_path = os.path.join(path, script_name + '.yaml') if not os.path.exists(config_file_path): raise RuntimeError('Config file does not exist: {}'.format(config_file_path)) default_dict = load_yaml(config_file_path) user_config_file_path = os.path.join(os.path.expanduser('~'), '.condoor', os.path.basename(script_name) + '.yaml') user_config_file_path = os.getenv('CONDOOR_' + os.path.basename(script_name).upper(), user_config_file_path) if os.path.exists(user_config_file_path): user_dict = load_yaml(user_config_file_path) if user_dict: default_dict = merge(user_dict, default_dict) return default_dict
python
def yaml_file_to_dict(script_name, path=None): """Read yaml file and return the dict. It assumes the module file exists with the defaults. If the CONDOOR_{SCRIPT_NAME} env is set then the user file from the env is loaded and merged with the default There can be user file located in ~/.condoor directory with the {script_name}.yaml filename. If exists it is merget with default config. """ def load_yaml(file_path): """Load YAML file from full file path and return dict.""" with open(file_path, 'r') as yamlfile: try: dictionary = yaml.load(yamlfile) except yaml.YAMLError: return {} return dictionary def merge(user, default): """Merge two dicts.""" if isinstance(user, dict) and isinstance(default, dict): for k, v in default.iteritems(): if k not in user: user[k] = v else: user[k] = merge(user[k], v) return user if path is None: path = os.path.abspath('.') config_file_path = os.path.join(path, script_name + '.yaml') if not os.path.exists(config_file_path): raise RuntimeError('Config file does not exist: {}'.format(config_file_path)) default_dict = load_yaml(config_file_path) user_config_file_path = os.path.join(os.path.expanduser('~'), '.condoor', os.path.basename(script_name) + '.yaml') user_config_file_path = os.getenv('CONDOOR_' + os.path.basename(script_name).upper(), user_config_file_path) if os.path.exists(user_config_file_path): user_dict = load_yaml(user_config_file_path) if user_dict: default_dict = merge(user_dict, default_dict) return default_dict
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Read yaml file and return the dict. It assumes the module file exists with the defaults. If the CONDOOR_{SCRIPT_NAME} env is set then the user file from the env is loaded and merged with the default There can be user file located in ~/.condoor directory with the {script_name}.yaml filename. If exists it is merget with default config.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/utils.py#L280-L323
train
kstaniek/condoor
condoor/utils.py
FilteredFile.write
def write(self, text): """Override the standard write method to filter the content.""" index = text.find('\n') if index == -1: self._buffer = self._buffer + text else: self._buffer = self._buffer + text[:index + 1] if self._pattern: # pattern already compiled no need to check result = re.search(self._pattern, self._buffer) if result: for group in result.groups(): if group: self._buffer = self._buffer.replace(group, "***") self._file.write(self._buffer) self._file.flush() self._buffer = text[index + 1:]
python
def write(self, text): """Override the standard write method to filter the content.""" index = text.find('\n') if index == -1: self._buffer = self._buffer + text else: self._buffer = self._buffer + text[:index + 1] if self._pattern: # pattern already compiled no need to check result = re.search(self._pattern, self._buffer) if result: for group in result.groups(): if group: self._buffer = self._buffer.replace(group, "***") self._file.write(self._buffer) self._file.flush() self._buffer = text[index + 1:]
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Override the standard write method to filter the content.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/utils.py#L193-L209
train
ajdavis/GreenletProfiler
_vendorized_yappi/yappi.py
start
def start(builtins=False, profile_threads=True): """ Start profiler. """ if profile_threads: threading.setprofile(_callback) _yappi.start(builtins, profile_threads)
python
def start(builtins=False, profile_threads=True): """ Start profiler. """ if profile_threads: threading.setprofile(_callback) _yappi.start(builtins, profile_threads)
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Start profiler.
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700349864a4f368a8a73a2a60f048c2e818d7cea
https://github.com/ajdavis/GreenletProfiler/blob/700349864a4f368a8a73a2a60f048c2e818d7cea/_vendorized_yappi/yappi.py#L700-L706
train
ajdavis/GreenletProfiler
_vendorized_yappi/yappi.py
set_clock_type
def set_clock_type(type): """ Sets the internal clock type for timing. Profiler shall not have any previous stats. Otherwise an exception is thrown. """ type = type.upper() if type not in CLOCK_TYPES: raise YappiError("Invalid clock type:%s" % (type)) _yappi.set_clock_type(CLOCK_TYPES[type])
python
def set_clock_type(type): """ Sets the internal clock type for timing. Profiler shall not have any previous stats. Otherwise an exception is thrown. """ type = type.upper() if type not in CLOCK_TYPES: raise YappiError("Invalid clock type:%s" % (type)) _yappi.set_clock_type(CLOCK_TYPES[type])
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Sets the internal clock type for timing. Profiler shall not have any previous stats. Otherwise an exception is thrown.
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700349864a4f368a8a73a2a60f048c2e818d7cea
https://github.com/ajdavis/GreenletProfiler/blob/700349864a4f368a8a73a2a60f048c2e818d7cea/_vendorized_yappi/yappi.py#L755-L764
train
hwmrocker/smtplibaio
smtplibaio/streams.py
SMTPStreamReader.read_reply
async def read_reply(self): """ Reads a reply from the server. Raises: ConnectionResetError: If the connection with the server is lost (we can't read any response anymore). Or if the server replies without a proper return code. Returns: (int, str): A (code, full_message) 2-tuple consisting of: - server response code ; - server response string corresponding to response code (multiline responses are returned in a single string). """ code = 500 messages = [] go_on = True while go_on: try: line = await self.readline() except ValueError as e: # ValueError is raised when limit is reached before we could # get an entire line. # We return what we got with a 500 code and we stop to read # the reply to avoid being flooded. code = 500 go_on = False else: try: code = int(line[:3]) except ValueError as e: # We either: # - Got an empty line (connection is probably down), # - Got a line without a valid return code. # In both case, it shouldn't happen, hence: raise ConnectionResetError("Connection lost.") from e else: # Check is we have a multiline response: go_on = line[3:4] == b"-" message = line[4:].strip(b" \t\r\n").decode("ascii") messages.append(message) full_message = "\n".join(messages) return code, full_message
python
async def read_reply(self): """ Reads a reply from the server. Raises: ConnectionResetError: If the connection with the server is lost (we can't read any response anymore). Or if the server replies without a proper return code. Returns: (int, str): A (code, full_message) 2-tuple consisting of: - server response code ; - server response string corresponding to response code (multiline responses are returned in a single string). """ code = 500 messages = [] go_on = True while go_on: try: line = await self.readline() except ValueError as e: # ValueError is raised when limit is reached before we could # get an entire line. # We return what we got with a 500 code and we stop to read # the reply to avoid being flooded. code = 500 go_on = False else: try: code = int(line[:3]) except ValueError as e: # We either: # - Got an empty line (connection is probably down), # - Got a line without a valid return code. # In both case, it shouldn't happen, hence: raise ConnectionResetError("Connection lost.") from e else: # Check is we have a multiline response: go_on = line[3:4] == b"-" message = line[4:].strip(b" \t\r\n").decode("ascii") messages.append(message) full_message = "\n".join(messages) return code, full_message
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Reads a reply from the server. Raises: ConnectionResetError: If the connection with the server is lost (we can't read any response anymore). Or if the server replies without a proper return code. Returns: (int, str): A (code, full_message) 2-tuple consisting of: - server response code ; - server response string corresponding to response code (multiline responses are returned in a single string).
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84ce8e45b7e706476739d0efcb416c18ecabbbb6
https://github.com/hwmrocker/smtplibaio/blob/84ce8e45b7e706476739d0efcb416c18ecabbbb6/smtplibaio/streams.py#L31-L79
train
kstaniek/condoor
condoor/hopinfo.py
make_hop_info_from_url
def make_hop_info_from_url(url, verify_reachability=None): """Build HopInfo object from url. It allows only telnet and ssh as a valid protocols. Args: url (str): The url string describing the node. i.e. telnet://[email protected]. The protocol, username and address portion of url is mandatory. Port and password is optional. If port is missing the standard protocol -> port mapping is done. The password is optional i.e. for TS access directly to console ports. The path part is treated as additional password required for some systems, i.e. enable password for IOS devices.: telnet://<username>:<password>@<host>:<port>/<enable_password> <enable_password> is optional verify_reachability: This is optional callable returning boolean if node is reachable. It can be used to verify reachability of the node before making a connection. It can speedup the connection process when node not reachable especially with telnet having long timeout. Returns: HopInfo object or None if url is invalid or protocol not supported """ parsed = urlparse(url) username = None if parsed.username is None else unquote(parsed.username) # It's None if not exists password = None if parsed.password is None else unquote(parsed.password) # It's None if not exists try: enable_password = parse_qs(parsed.query)["enable_password"][0] except KeyError: enable_password = None hop_info = HopInfo( parsed.scheme, parsed.hostname, username, password, parsed.port, enable_password, verify_reachability=verify_reachability ) if hop_info.is_valid(): return hop_info raise InvalidHopInfoError
python
def make_hop_info_from_url(url, verify_reachability=None): """Build HopInfo object from url. It allows only telnet and ssh as a valid protocols. Args: url (str): The url string describing the node. i.e. telnet://[email protected]. The protocol, username and address portion of url is mandatory. Port and password is optional. If port is missing the standard protocol -> port mapping is done. The password is optional i.e. for TS access directly to console ports. The path part is treated as additional password required for some systems, i.e. enable password for IOS devices.: telnet://<username>:<password>@<host>:<port>/<enable_password> <enable_password> is optional verify_reachability: This is optional callable returning boolean if node is reachable. It can be used to verify reachability of the node before making a connection. It can speedup the connection process when node not reachable especially with telnet having long timeout. Returns: HopInfo object or None if url is invalid or protocol not supported """ parsed = urlparse(url) username = None if parsed.username is None else unquote(parsed.username) # It's None if not exists password = None if parsed.password is None else unquote(parsed.password) # It's None if not exists try: enable_password = parse_qs(parsed.query)["enable_password"][0] except KeyError: enable_password = None hop_info = HopInfo( parsed.scheme, parsed.hostname, username, password, parsed.port, enable_password, verify_reachability=verify_reachability ) if hop_info.is_valid(): return hop_info raise InvalidHopInfoError
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Build HopInfo object from url. It allows only telnet and ssh as a valid protocols. Args: url (str): The url string describing the node. i.e. telnet://[email protected]. The protocol, username and address portion of url is mandatory. Port and password is optional. If port is missing the standard protocol -> port mapping is done. The password is optional i.e. for TS access directly to console ports. The path part is treated as additional password required for some systems, i.e. enable password for IOS devices.: telnet://<username>:<password>@<host>:<port>/<enable_password> <enable_password> is optional verify_reachability: This is optional callable returning boolean if node is reachable. It can be used to verify reachability of the node before making a connection. It can speedup the connection process when node not reachable especially with telnet having long timeout. Returns: HopInfo object or None if url is invalid or protocol not supported
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/hopinfo.py#L16-L63
train
kstaniek/condoor
condoor/hopinfo.py
HopInfo.is_reachable
def is_reachable(self): """Return if host is reachable.""" if self.verify_reachability and \ hasattr(self.verify_reachability, '__call__'): return self.verify_reachability(host=self.hostname, port=self.port) # assume is reachable if can't verify return True
python
def is_reachable(self): """Return if host is reachable.""" if self.verify_reachability and \ hasattr(self.verify_reachability, '__call__'): return self.verify_reachability(host=self.hostname, port=self.port) # assume is reachable if can't verify return True
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Return if host is reachable.
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77c054b29d4e286c1d7aca2c74dff86b805e1fae
https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/hopinfo.py#L118-L124
train