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247,000 | turicas/rows | rows/utils.py | csv_to_sqlite | def csv_to_sqlite(
input_filename,
output_filename,
samples=None,
dialect=None,
batch_size=10000,
encoding="utf-8",
callback=None,
force_types=None,
chunk_size=8388608,
table_name="table1",
schema=None,
):
"Export a CSV file to SQLite, based on field type detection from samples"
# TODO: automatically detect encoding if encoding == `None`
# TODO: should be able to specify fields
# TODO: if table_name is "2019" the final name will be "field_2019" - must
# be "table_2019"
# TODO: if schema is provided and the names are in uppercase, this function
# will fail
if dialect is None: # Get a sample to detect dialect
fobj = open_compressed(input_filename, mode="rb")
sample = fobj.read(chunk_size)
dialect = rows.plugins.csv.discover_dialect(sample, encoding=encoding)
elif isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
if schema is None: # Identify data types
fobj = open_compressed(input_filename, encoding=encoding)
data = list(islice(csv.DictReader(fobj, dialect=dialect), samples))
schema = rows.import_from_dicts(data).fields
if force_types is not None:
schema.update(force_types)
# Create lazy table object to be converted
# TODO: this lazyness feature will be incorported into the library soon so
# we can call here `rows.import_from_csv` instead of `csv.reader`.
reader = csv.reader(
open_compressed(input_filename, encoding=encoding), dialect=dialect
)
header = make_header(next(reader)) # skip header
table = rows.Table(fields=OrderedDict([(field, schema[field]) for field in header]))
table._rows = reader
# Export to SQLite
return rows.export_to_sqlite(
table,
output_filename,
table_name=table_name,
batch_size=batch_size,
callback=callback,
) | python | def csv_to_sqlite(
input_filename,
output_filename,
samples=None,
dialect=None,
batch_size=10000,
encoding="utf-8",
callback=None,
force_types=None,
chunk_size=8388608,
table_name="table1",
schema=None,
):
"Export a CSV file to SQLite, based on field type detection from samples"
# TODO: automatically detect encoding if encoding == `None`
# TODO: should be able to specify fields
# TODO: if table_name is "2019" the final name will be "field_2019" - must
# be "table_2019"
# TODO: if schema is provided and the names are in uppercase, this function
# will fail
if dialect is None: # Get a sample to detect dialect
fobj = open_compressed(input_filename, mode="rb")
sample = fobj.read(chunk_size)
dialect = rows.plugins.csv.discover_dialect(sample, encoding=encoding)
elif isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
if schema is None: # Identify data types
fobj = open_compressed(input_filename, encoding=encoding)
data = list(islice(csv.DictReader(fobj, dialect=dialect), samples))
schema = rows.import_from_dicts(data).fields
if force_types is not None:
schema.update(force_types)
# Create lazy table object to be converted
# TODO: this lazyness feature will be incorported into the library soon so
# we can call here `rows.import_from_csv` instead of `csv.reader`.
reader = csv.reader(
open_compressed(input_filename, encoding=encoding), dialect=dialect
)
header = make_header(next(reader)) # skip header
table = rows.Table(fields=OrderedDict([(field, schema[field]) for field in header]))
table._rows = reader
# Export to SQLite
return rows.export_to_sqlite(
table,
output_filename,
table_name=table_name,
batch_size=batch_size,
callback=callback,
) | [
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247,001 | turicas/rows | rows/utils.py | sqlite_to_csv | def sqlite_to_csv(
input_filename,
table_name,
output_filename,
dialect=csv.excel,
batch_size=10000,
encoding="utf-8",
callback=None,
query=None,
):
"""Export a table inside a SQLite database to CSV"""
# TODO: should be able to specify fields
# TODO: should be able to specify custom query
if isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
if query is None:
query = "SELECT * FROM {}".format(table_name)
connection = sqlite3.Connection(input_filename)
cursor = connection.cursor()
result = cursor.execute(query)
header = [item[0] for item in cursor.description]
fobj = open_compressed(output_filename, mode="w", encoding=encoding)
writer = csv.writer(fobj, dialect=dialect)
writer.writerow(header)
total_written = 0
for batch in rows.plugins.utils.ipartition(result, batch_size):
writer.writerows(batch)
written = len(batch)
total_written += written
if callback:
callback(written, total_written)
fobj.close() | python | def sqlite_to_csv(
input_filename,
table_name,
output_filename,
dialect=csv.excel,
batch_size=10000,
encoding="utf-8",
callback=None,
query=None,
):
# TODO: should be able to specify fields
# TODO: should be able to specify custom query
if isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
if query is None:
query = "SELECT * FROM {}".format(table_name)
connection = sqlite3.Connection(input_filename)
cursor = connection.cursor()
result = cursor.execute(query)
header = [item[0] for item in cursor.description]
fobj = open_compressed(output_filename, mode="w", encoding=encoding)
writer = csv.writer(fobj, dialect=dialect)
writer.writerow(header)
total_written = 0
for batch in rows.plugins.utils.ipartition(result, batch_size):
writer.writerows(batch)
written = len(batch)
total_written += written
if callback:
callback(written, total_written)
fobj.close() | [
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] | c74da41ae9ed091356b803a64f8a30c641c5fc45 | https://github.com/turicas/rows/blob/c74da41ae9ed091356b803a64f8a30c641c5fc45/rows/utils.py#L616-L650 |
247,002 | turicas/rows | rows/utils.py | execute_command | def execute_command(command):
"""Execute a command and return its output"""
command = shlex.split(command)
try:
process = subprocess.Popen(
command,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
except FileNotFoundError:
raise RuntimeError("Command not found: {}".format(repr(command)))
process.wait()
# TODO: may use another codec to decode
if process.returncode > 0:
stderr = process.stderr.read().decode("utf-8")
raise ValueError("Error executing command: {}".format(repr(stderr)))
return process.stdout.read().decode("utf-8") | python | def execute_command(command):
command = shlex.split(command)
try:
process = subprocess.Popen(
command,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
except FileNotFoundError:
raise RuntimeError("Command not found: {}".format(repr(command)))
process.wait()
# TODO: may use another codec to decode
if process.returncode > 0:
stderr = process.stderr.read().decode("utf-8")
raise ValueError("Error executing command: {}".format(repr(stderr)))
return process.stdout.read().decode("utf-8") | [
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247,003 | turicas/rows | rows/utils.py | uncompressed_size | def uncompressed_size(filename):
"""Return the uncompressed size for a file by executing commands
Note: due to a limitation in gzip format, uncompressed files greather than
4GiB will have a wrong value.
"""
quoted_filename = shlex.quote(filename)
# TODO: get filetype from file-magic, if available
if str(filename).lower().endswith(".xz"):
output = execute_command('xz --list "{}"'.format(quoted_filename))
compressed, uncompressed = regexp_sizes.findall(output)
value, unit = uncompressed.split()
value = float(value.replace(",", ""))
return int(value * MULTIPLIERS[unit])
elif str(filename).lower().endswith(".gz"):
# XXX: gzip only uses 32 bits to store uncompressed size, so if the
# uncompressed size is greater than 4GiB, the value returned will be
# incorrect.
output = execute_command('gzip --list "{}"'.format(quoted_filename))
lines = [line.split() for line in output.splitlines()]
header, data = lines[0], lines[1]
gzip_data = dict(zip(header, data))
return int(gzip_data["uncompressed"])
else:
raise ValueError('Unrecognized file type for "{}".'.format(filename)) | python | def uncompressed_size(filename):
quoted_filename = shlex.quote(filename)
# TODO: get filetype from file-magic, if available
if str(filename).lower().endswith(".xz"):
output = execute_command('xz --list "{}"'.format(quoted_filename))
compressed, uncompressed = regexp_sizes.findall(output)
value, unit = uncompressed.split()
value = float(value.replace(",", ""))
return int(value * MULTIPLIERS[unit])
elif str(filename).lower().endswith(".gz"):
# XXX: gzip only uses 32 bits to store uncompressed size, so if the
# uncompressed size is greater than 4GiB, the value returned will be
# incorrect.
output = execute_command('gzip --list "{}"'.format(quoted_filename))
lines = [line.split() for line in output.splitlines()]
header, data = lines[0], lines[1]
gzip_data = dict(zip(header, data))
return int(gzip_data["uncompressed"])
else:
raise ValueError('Unrecognized file type for "{}".'.format(filename)) | [
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247,004 | turicas/rows | rows/utils.py | pgimport | def pgimport(
filename,
database_uri,
table_name,
encoding="utf-8",
dialect=None,
create_table=True,
schema=None,
callback=None,
timeout=0.1,
chunk_size=8388608,
max_samples=10000,
):
"""Import data from CSV into PostgreSQL using the fastest method
Required: psql command
"""
fobj = open_compressed(filename, mode="r", encoding=encoding)
sample = fobj.read(chunk_size)
if dialect is None: # Detect dialect
dialect = rows.plugins.csv.discover_dialect(
sample.encode(encoding), encoding=encoding
)
elif isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
if schema is None:
# Detect field names
reader = csv.reader(io.StringIO(sample), dialect=dialect)
field_names = [slug(field_name) for field_name in next(reader)]
else:
field_names = list(schema.keys())
if create_table:
if schema is None:
data = [
dict(zip(field_names, row))
for row in itertools.islice(reader, max_samples)
]
table = rows.import_from_dicts(data)
field_types = [table.fields[field_name] for field_name in field_names]
else:
field_types = list(schema.values())
columns = [
"{} {}".format(name, POSTGRESQL_TYPES.get(type_, DEFAULT_POSTGRESQL_TYPE))
for name, type_ in zip(field_names, field_types)
]
create_table = SQL_CREATE_TABLE.format(
table_name=table_name, field_types=", ".join(columns)
)
execute_command(get_psql_command(create_table, database_uri=database_uri))
# Prepare the `psql` command to be executed based on collected metadata
command = get_psql_copy_command(
database_uri=database_uri,
dialect=dialect,
direction="FROM",
encoding=encoding,
header=field_names,
table_name=table_name,
)
rows_imported, error = 0, None
fobj = open_compressed(filename, mode="rb")
try:
process = subprocess.Popen(
shlex.split(command),
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
data = fobj.read(chunk_size)
total_written = 0
while data != b"":
written = process.stdin.write(data)
total_written += written
if callback:
callback(written, total_written)
data = fobj.read(chunk_size)
stdout, stderr = process.communicate()
if stderr != b"":
raise RuntimeError(stderr.decode("utf-8"))
rows_imported = int(stdout.replace(b"COPY ", b"").strip())
except FileNotFoundError:
raise RuntimeError("Command `psql` not found")
except BrokenPipeError:
raise RuntimeError(process.stderr.read().decode("utf-8"))
return {"bytes_written": total_written, "rows_imported": rows_imported} | python | def pgimport(
filename,
database_uri,
table_name,
encoding="utf-8",
dialect=None,
create_table=True,
schema=None,
callback=None,
timeout=0.1,
chunk_size=8388608,
max_samples=10000,
):
fobj = open_compressed(filename, mode="r", encoding=encoding)
sample = fobj.read(chunk_size)
if dialect is None: # Detect dialect
dialect = rows.plugins.csv.discover_dialect(
sample.encode(encoding), encoding=encoding
)
elif isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
if schema is None:
# Detect field names
reader = csv.reader(io.StringIO(sample), dialect=dialect)
field_names = [slug(field_name) for field_name in next(reader)]
else:
field_names = list(schema.keys())
if create_table:
if schema is None:
data = [
dict(zip(field_names, row))
for row in itertools.islice(reader, max_samples)
]
table = rows.import_from_dicts(data)
field_types = [table.fields[field_name] for field_name in field_names]
else:
field_types = list(schema.values())
columns = [
"{} {}".format(name, POSTGRESQL_TYPES.get(type_, DEFAULT_POSTGRESQL_TYPE))
for name, type_ in zip(field_names, field_types)
]
create_table = SQL_CREATE_TABLE.format(
table_name=table_name, field_types=", ".join(columns)
)
execute_command(get_psql_command(create_table, database_uri=database_uri))
# Prepare the `psql` command to be executed based on collected metadata
command = get_psql_copy_command(
database_uri=database_uri,
dialect=dialect,
direction="FROM",
encoding=encoding,
header=field_names,
table_name=table_name,
)
rows_imported, error = 0, None
fobj = open_compressed(filename, mode="rb")
try:
process = subprocess.Popen(
shlex.split(command),
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
data = fobj.read(chunk_size)
total_written = 0
while data != b"":
written = process.stdin.write(data)
total_written += written
if callback:
callback(written, total_written)
data = fobj.read(chunk_size)
stdout, stderr = process.communicate()
if stderr != b"":
raise RuntimeError(stderr.decode("utf-8"))
rows_imported = int(stdout.replace(b"COPY ", b"").strip())
except FileNotFoundError:
raise RuntimeError("Command `psql` not found")
except BrokenPipeError:
raise RuntimeError(process.stderr.read().decode("utf-8"))
return {"bytes_written": total_written, "rows_imported": rows_imported} | [
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Required: psql command | [
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247,005 | turicas/rows | rows/utils.py | pgexport | def pgexport(
database_uri,
table_name,
filename,
encoding="utf-8",
dialect=csv.excel,
callback=None,
timeout=0.1,
chunk_size=8388608,
):
"""Export data from PostgreSQL into a CSV file using the fastest method
Required: psql command
"""
if isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
# Prepare the `psql` command to be executed to export data
command = get_psql_copy_command(
database_uri=database_uri,
direction="TO",
encoding=encoding,
header=None, # Needed when direction = 'TO'
table_name=table_name,
dialect=dialect,
)
fobj = open_compressed(filename, mode="wb")
try:
process = subprocess.Popen(
shlex.split(command),
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
total_written = 0
data = process.stdout.read(chunk_size)
while data != b"":
written = fobj.write(data)
total_written += written
if callback:
callback(written, total_written)
data = process.stdout.read(chunk_size)
stdout, stderr = process.communicate()
if stderr != b"":
raise RuntimeError(stderr.decode("utf-8"))
except FileNotFoundError:
raise RuntimeError("Command `psql` not found")
except BrokenPipeError:
raise RuntimeError(process.stderr.read().decode("utf-8"))
return {"bytes_written": total_written} | python | def pgexport(
database_uri,
table_name,
filename,
encoding="utf-8",
dialect=csv.excel,
callback=None,
timeout=0.1,
chunk_size=8388608,
):
if isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
# Prepare the `psql` command to be executed to export data
command = get_psql_copy_command(
database_uri=database_uri,
direction="TO",
encoding=encoding,
header=None, # Needed when direction = 'TO'
table_name=table_name,
dialect=dialect,
)
fobj = open_compressed(filename, mode="wb")
try:
process = subprocess.Popen(
shlex.split(command),
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
total_written = 0
data = process.stdout.read(chunk_size)
while data != b"":
written = fobj.write(data)
total_written += written
if callback:
callback(written, total_written)
data = process.stdout.read(chunk_size)
stdout, stderr = process.communicate()
if stderr != b"":
raise RuntimeError(stderr.decode("utf-8"))
except FileNotFoundError:
raise RuntimeError("Command `psql` not found")
except BrokenPipeError:
raise RuntimeError(process.stderr.read().decode("utf-8"))
return {"bytes_written": total_written} | [
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Required: psql command | [
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247,006 | turicas/rows | rows/utils.py | load_schema | def load_schema(filename, context=None):
"""Load schema from file in any of the supported formats
The table must have at least the fields `field_name` and `field_type`.
`context` is a `dict` with field_type as key pointing to field class, like:
{"text": rows.fields.TextField, "value": MyCustomField}
"""
table = import_from_uri(filename)
field_names = table.field_names
assert "field_name" in field_names
assert "field_type" in field_names
context = context or {
key.replace("Field", "").lower(): getattr(rows.fields, key)
for key in dir(rows.fields)
if "Field" in key and key != "Field"
}
return OrderedDict(
[
(row.field_name, context[row.field_type])
for row in table
]
) | python | def load_schema(filename, context=None):
table = import_from_uri(filename)
field_names = table.field_names
assert "field_name" in field_names
assert "field_type" in field_names
context = context or {
key.replace("Field", "").lower(): getattr(rows.fields, key)
for key in dir(rows.fields)
if "Field" in key and key != "Field"
}
return OrderedDict(
[
(row.field_name, context[row.field_type])
for row in table
]
) | [
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The table must have at least the fields `field_name` and `field_type`.
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247,007 | turicas/rows | rows/fields.py | slug | def slug(text, separator="_", permitted_chars=SLUG_CHARS):
"""Generate a slug for the `text`.
>>> slug(' ÁLVARO justen% ')
'alvaro_justen'
>>> slug(' ÁLVARO justen% ', separator='-')
'alvaro-justen'
"""
text = six.text_type(text or "")
# Strip non-ASCII characters
# Example: u' ÁLVARO justen% ' -> ' ALVARO justen% '
text = normalize("NFKD", text.strip()).encode("ascii", "ignore").decode("ascii")
# Replace word boundaries with separator
text = REGEXP_WORD_BOUNDARY.sub("\\1" + re.escape(separator), text)
# Remove non-permitted characters and put everything to lowercase
# Example: u'_ALVARO__justen%_' -> u'_alvaro__justen_'
allowed_chars = list(permitted_chars) + [separator]
text = "".join(char for char in text if char in allowed_chars).lower()
# Remove double occurrencies of separator
# Example: u'_alvaro__justen_' -> u'_alvaro_justen_'
text = (
REGEXP_SEPARATOR
if separator == "_"
else re.compile("(" + re.escape(separator) + "+)")
).sub(separator, text)
# Strip separators
# Example: u'_alvaro_justen_' -> u'alvaro_justen'
return text.strip(separator) | python | def slug(text, separator="_", permitted_chars=SLUG_CHARS):
text = six.text_type(text or "")
# Strip non-ASCII characters
# Example: u' ÁLVARO justen% ' -> ' ALVARO justen% '
text = normalize("NFKD", text.strip()).encode("ascii", "ignore").decode("ascii")
# Replace word boundaries with separator
text = REGEXP_WORD_BOUNDARY.sub("\\1" + re.escape(separator), text)
# Remove non-permitted characters and put everything to lowercase
# Example: u'_ALVARO__justen%_' -> u'_alvaro__justen_'
allowed_chars = list(permitted_chars) + [separator]
text = "".join(char for char in text if char in allowed_chars).lower()
# Remove double occurrencies of separator
# Example: u'_alvaro__justen_' -> u'_alvaro_justen_'
text = (
REGEXP_SEPARATOR
if separator == "_"
else re.compile("(" + re.escape(separator) + "+)")
).sub(separator, text)
# Strip separators
# Example: u'_alvaro_justen_' -> u'alvaro_justen'
return text.strip(separator) | [
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>>> slug(' ÁLVARO justen% ')
'alvaro_justen'
>>> slug(' ÁLVARO justen% ', separator='-')
'alvaro-justen' | [
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247,008 | turicas/rows | rows/fields.py | make_unique_name | def make_unique_name(name, existing_names, name_format="{name}_{index}", start=2):
"""Return a unique name based on `name_format` and `name`."""
index = start
new_name = name
while new_name in existing_names:
new_name = name_format.format(name=name, index=index)
index += 1
return new_name | python | def make_unique_name(name, existing_names, name_format="{name}_{index}", start=2):
index = start
new_name = name
while new_name in existing_names:
new_name = name_format.format(name=name, index=index)
index += 1
return new_name | [
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247,009 | turicas/rows | rows/fields.py | make_header | def make_header(field_names, permit_not=False):
"""Return unique and slugged field names."""
slug_chars = SLUG_CHARS if not permit_not else SLUG_CHARS + "^"
header = [
slug(field_name, permitted_chars=slug_chars) for field_name in field_names
]
result = []
for index, field_name in enumerate(header):
if not field_name:
field_name = "field_{}".format(index)
elif field_name[0].isdigit():
field_name = "field_{}".format(field_name)
if field_name in result:
field_name = make_unique_name(
name=field_name, existing_names=result, start=2
)
result.append(field_name)
return result | python | def make_header(field_names, permit_not=False):
slug_chars = SLUG_CHARS if not permit_not else SLUG_CHARS + "^"
header = [
slug(field_name, permitted_chars=slug_chars) for field_name in field_names
]
result = []
for index, field_name in enumerate(header):
if not field_name:
field_name = "field_{}".format(index)
elif field_name[0].isdigit():
field_name = "field_{}".format(field_name)
if field_name in result:
field_name = make_unique_name(
name=field_name, existing_names=result, start=2
)
result.append(field_name)
return result | [
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247,010 | turicas/rows | rows/fields.py | Field.deserialize | def deserialize(cls, value, *args, **kwargs):
"""Deserialize a value just after importing it
`cls.deserialize` should always return a value of type `cls.TYPE` or
`None`.
"""
if isinstance(value, cls.TYPE):
return value
elif is_null(value):
return None
else:
return value | python | def deserialize(cls, value, *args, **kwargs):
if isinstance(value, cls.TYPE):
return value
elif is_null(value):
return None
else:
return value | [
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247,011 | turicas/rows | rows/plugins/plugin_pdf.py | ExtractionAlgorithm.selected_objects | def selected_objects(self):
"""Filter out objects outside table boundaries"""
return [
obj
for obj in self.text_objects
if contains_or_overlap(self.table_bbox, obj.bbox)
] | python | def selected_objects(self):
return [
obj
for obj in self.text_objects
if contains_or_overlap(self.table_bbox, obj.bbox)
] | [
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247,012 | turicas/rows | examples/library/extract_links.py | transform | def transform(row, table):
'Extract links from "project" field and remove HTML from all'
data = row._asdict()
data["links"] = " ".join(extract_links(row.project))
for key, value in data.items():
if isinstance(value, six.text_type):
data[key] = extract_text(value)
return data | python | def transform(row, table):
'Extract links from "project" field and remove HTML from all'
data = row._asdict()
data["links"] = " ".join(extract_links(row.project))
for key, value in data.items():
if isinstance(value, six.text_type):
data[key] = extract_text(value)
return data | [
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247,013 | turicas/rows | examples/library/brazilian_cities_wikipedia.py | transform | def transform(row, table):
'Transform row "link" into full URL and add "state" based on "name"'
data = row._asdict()
data["link"] = urljoin("https://pt.wikipedia.org", data["link"])
data["name"], data["state"] = regexp_city_state.findall(data["name"])[0]
return data | python | def transform(row, table):
'Transform row "link" into full URL and add "state" based on "name"'
data = row._asdict()
data["link"] = urljoin("https://pt.wikipedia.org", data["link"])
data["name"], data["state"] = regexp_city_state.findall(data["name"])[0]
return data | [
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247,014 | turicas/rows | rows/plugins/plugin_parquet.py | import_from_parquet | def import_from_parquet(filename_or_fobj, *args, **kwargs):
"""Import data from a Parquet file and return with rows.Table."""
source = Source.from_file(filename_or_fobj, plugin_name="parquet", mode="rb")
# TODO: should look into `schema.converted_type` also
types = OrderedDict(
[
(schema.name, PARQUET_TO_ROWS[schema.type])
for schema in parquet._read_footer(source.fobj).schema
if schema.type is not None
]
)
header = list(types.keys())
table_rows = list(parquet.reader(source.fobj)) # TODO: be lazy
meta = {"imported_from": "parquet", "source": source}
return create_table(
[header] + table_rows, meta=meta, force_types=types, *args, **kwargs
) | python | def import_from_parquet(filename_or_fobj, *args, **kwargs):
source = Source.from_file(filename_or_fobj, plugin_name="parquet", mode="rb")
# TODO: should look into `schema.converted_type` also
types = OrderedDict(
[
(schema.name, PARQUET_TO_ROWS[schema.type])
for schema in parquet._read_footer(source.fobj).schema
if schema.type is not None
]
)
header = list(types.keys())
table_rows = list(parquet.reader(source.fobj)) # TODO: be lazy
meta = {"imported_from": "parquet", "source": source}
return create_table(
[header] + table_rows, meta=meta, force_types=types, *args, **kwargs
) | [
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247,015 | turicas/rows | rows/plugins/dicts.py | import_from_dicts | def import_from_dicts(data, samples=None, *args, **kwargs):
"""Import data from a iterable of dicts
The algorithm will use the `samples` first `dict`s to determine the field
names (if `samples` is `None` all `dict`s will be used).
"""
data = iter(data)
cached_rows, headers = [], []
for index, row in enumerate(data, start=1):
cached_rows.append(row)
for key in row.keys():
if key not in headers:
headers.append(key)
if samples and index == samples:
break
data_rows = (
[row.get(header, None) for header in headers]
for row in chain(cached_rows, data)
)
kwargs["samples"] = samples
meta = {"imported_from": "dicts"}
return create_table(chain([headers], data_rows), meta=meta, *args, **kwargs) | python | def import_from_dicts(data, samples=None, *args, **kwargs):
data = iter(data)
cached_rows, headers = [], []
for index, row in enumerate(data, start=1):
cached_rows.append(row)
for key in row.keys():
if key not in headers:
headers.append(key)
if samples and index == samples:
break
data_rows = (
[row.get(header, None) for header in headers]
for row in chain(cached_rows, data)
)
kwargs["samples"] = samples
meta = {"imported_from": "dicts"}
return create_table(chain([headers], data_rows), meta=meta, *args, **kwargs) | [
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247,016 | turicas/rows | rows/plugins/dicts.py | export_to_dicts | def export_to_dicts(table, *args, **kwargs):
"""Export a `rows.Table` to a list of dicts"""
field_names = table.field_names
return [{key: getattr(row, key) for key in field_names} for row in table] | python | def export_to_dicts(table, *args, **kwargs):
field_names = table.field_names
return [{key: getattr(row, key) for key in field_names} for row in table] | [
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247,017 | turicas/rows | rows/plugins/xls.py | cell_value | def cell_value(sheet, row, col):
"""Return the cell value of the table passed by argument, based in row and column."""
cell = sheet.cell(row, col)
field_type = CELL_TYPES[cell.ctype]
# TODO: this approach will not work if using locale
value = cell.value
if field_type is None:
return None
elif field_type is fields.TextField:
if cell.ctype != xlrd.XL_CELL_BLANK:
return value
else:
return ""
elif field_type is fields.DatetimeField:
if value == 0.0:
return None
try:
time_tuple = xlrd.xldate_as_tuple(value, sheet.book.datemode)
except xlrd.xldate.XLDateTooLarge:
return None
value = field_type.serialize(datetime.datetime(*time_tuple))
return value.split("T00:00:00")[0]
elif field_type is fields.BoolField:
if value == 0:
return False
elif value == 1:
return True
elif cell.xf_index is None:
return value # TODO: test
else:
book = sheet.book
xf = book.xf_list[cell.xf_index]
fmt = book.format_map[xf.format_key]
if fmt.format_str.endswith("%"):
# TODO: we may optimize this approach: we're converting to string
# and the library is detecting the type when we could just say to
# the library this value is PercentField
if value is not None:
try:
decimal_places = len(fmt.format_str[:-1].split(".")[-1])
except IndexError:
decimal_places = 2
return "{}%".format(str(round(value * 100, decimal_places)))
else:
return None
elif type(value) == float and int(value) == value:
return int(value)
else:
return value | python | def cell_value(sheet, row, col):
cell = sheet.cell(row, col)
field_type = CELL_TYPES[cell.ctype]
# TODO: this approach will not work if using locale
value = cell.value
if field_type is None:
return None
elif field_type is fields.TextField:
if cell.ctype != xlrd.XL_CELL_BLANK:
return value
else:
return ""
elif field_type is fields.DatetimeField:
if value == 0.0:
return None
try:
time_tuple = xlrd.xldate_as_tuple(value, sheet.book.datemode)
except xlrd.xldate.XLDateTooLarge:
return None
value = field_type.serialize(datetime.datetime(*time_tuple))
return value.split("T00:00:00")[0]
elif field_type is fields.BoolField:
if value == 0:
return False
elif value == 1:
return True
elif cell.xf_index is None:
return value # TODO: test
else:
book = sheet.book
xf = book.xf_list[cell.xf_index]
fmt = book.format_map[xf.format_key]
if fmt.format_str.endswith("%"):
# TODO: we may optimize this approach: we're converting to string
# and the library is detecting the type when we could just say to
# the library this value is PercentField
if value is not None:
try:
decimal_places = len(fmt.format_str[:-1].split(".")[-1])
except IndexError:
decimal_places = 2
return "{}%".format(str(round(value * 100, decimal_places)))
else:
return None
elif type(value) == float and int(value) == value:
return int(value)
else:
return value | [
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247,018 | turicas/rows | rows/plugins/xls.py | import_from_xls | def import_from_xls(
filename_or_fobj,
sheet_name=None,
sheet_index=0,
start_row=None,
start_column=None,
end_row=None,
end_column=None,
*args,
**kwargs
):
"""Return a rows.Table created from imported XLS file."""
source = Source.from_file(filename_or_fobj, mode="rb", plugin_name="xls")
source.fobj.close()
book = xlrd.open_workbook(
source.uri, formatting_info=True, logfile=open(os.devnull, mode="w")
)
if sheet_name is not None:
sheet = book.sheet_by_name(sheet_name)
else:
sheet = book.sheet_by_index(sheet_index)
# TODO: may re-use Excel data types
# Get header and rows
# xlrd library reads rows and columns starting from 0 and ending on
# sheet.nrows/ncols - 1. rows accepts the same pattern
# The xlrd library reads rows and columns starting from 0 and ending on
# sheet.nrows/ncols - 1. rows also uses 0-based indexes, so no
# transformation is needed
min_row, min_column = get_table_start(sheet)
max_row, max_column = sheet.nrows - 1, sheet.ncols - 1
# TODO: consider adding a parameter `ignore_padding=True` and when it's
# True, consider `start_row` starting from `min_row` and `start_column`
# starting from `min_col`.
start_row = max(start_row if start_row is not None else min_row, min_row)
end_row = min(end_row if end_row is not None else max_row, max_row)
start_column = max(
start_column if start_column is not None else min_column, min_column
)
end_column = min(end_column if end_column is not None else max_column, max_column)
table_rows = [
[
cell_value(sheet, row_index, column_index)
for column_index in range(start_column, end_column + 1)
]
for row_index in range(start_row, end_row + 1)
]
meta = {"imported_from": "xls", "source": source, "name": sheet.name}
return create_table(table_rows, meta=meta, *args, **kwargs) | python | def import_from_xls(
filename_or_fobj,
sheet_name=None,
sheet_index=0,
start_row=None,
start_column=None,
end_row=None,
end_column=None,
*args,
**kwargs
):
source = Source.from_file(filename_or_fobj, mode="rb", plugin_name="xls")
source.fobj.close()
book = xlrd.open_workbook(
source.uri, formatting_info=True, logfile=open(os.devnull, mode="w")
)
if sheet_name is not None:
sheet = book.sheet_by_name(sheet_name)
else:
sheet = book.sheet_by_index(sheet_index)
# TODO: may re-use Excel data types
# Get header and rows
# xlrd library reads rows and columns starting from 0 and ending on
# sheet.nrows/ncols - 1. rows accepts the same pattern
# The xlrd library reads rows and columns starting from 0 and ending on
# sheet.nrows/ncols - 1. rows also uses 0-based indexes, so no
# transformation is needed
min_row, min_column = get_table_start(sheet)
max_row, max_column = sheet.nrows - 1, sheet.ncols - 1
# TODO: consider adding a parameter `ignore_padding=True` and when it's
# True, consider `start_row` starting from `min_row` and `start_column`
# starting from `min_col`.
start_row = max(start_row if start_row is not None else min_row, min_row)
end_row = min(end_row if end_row is not None else max_row, max_row)
start_column = max(
start_column if start_column is not None else min_column, min_column
)
end_column = min(end_column if end_column is not None else max_column, max_column)
table_rows = [
[
cell_value(sheet, row_index, column_index)
for column_index in range(start_column, end_column + 1)
]
for row_index in range(start_row, end_row + 1)
]
meta = {"imported_from": "xls", "source": source, "name": sheet.name}
return create_table(table_rows, meta=meta, *args, **kwargs) | [
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247,019 | turicas/rows | rows/plugins/xls.py | export_to_xls | def export_to_xls(table, filename_or_fobj=None, sheet_name="Sheet1", *args, **kwargs):
"""Export the rows.Table to XLS file and return the saved file."""
workbook = xlwt.Workbook()
sheet = workbook.add_sheet(sheet_name)
prepared_table = prepare_to_export(table, *args, **kwargs)
field_names = next(prepared_table)
for column_index, field_name in enumerate(field_names):
sheet.write(0, column_index, field_name)
_convert_row = _python_to_xls([table.fields.get(field) for field in field_names])
for row_index, row in enumerate(prepared_table, start=1):
for column_index, (value, data) in enumerate(_convert_row(row)):
sheet.write(row_index, column_index, value, **data)
return_result = False
if filename_or_fobj is None:
filename_or_fobj = BytesIO()
return_result = True
source = Source.from_file(filename_or_fobj, mode="wb", plugin_name="xls")
workbook.save(source.fobj)
source.fobj.flush()
if return_result:
source.fobj.seek(0)
result = source.fobj.read()
else:
result = source.fobj
if source.should_close:
source.fobj.close()
return result | python | def export_to_xls(table, filename_or_fobj=None, sheet_name="Sheet1", *args, **kwargs):
workbook = xlwt.Workbook()
sheet = workbook.add_sheet(sheet_name)
prepared_table = prepare_to_export(table, *args, **kwargs)
field_names = next(prepared_table)
for column_index, field_name in enumerate(field_names):
sheet.write(0, column_index, field_name)
_convert_row = _python_to_xls([table.fields.get(field) for field in field_names])
for row_index, row in enumerate(prepared_table, start=1):
for column_index, (value, data) in enumerate(_convert_row(row)):
sheet.write(row_index, column_index, value, **data)
return_result = False
if filename_or_fobj is None:
filename_or_fobj = BytesIO()
return_result = True
source = Source.from_file(filename_or_fobj, mode="wb", plugin_name="xls")
workbook.save(source.fobj)
source.fobj.flush()
if return_result:
source.fobj.seek(0)
result = source.fobj.read()
else:
result = source.fobj
if source.should_close:
source.fobj.close()
return result | [
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247,020 | turicas/rows | rows/plugins/postgresql.py | _valid_table_name | def _valid_table_name(name):
"""Verify if a given table name is valid for `rows`
Rules:
- Should start with a letter or '_'
- Letters can be capitalized or not
- Accepts letters, numbers and _
"""
if name[0] not in "_" + string.ascii_letters or not set(name).issubset(
"_" + string.ascii_letters + string.digits
):
return False
else:
return True | python | def _valid_table_name(name):
if name[0] not in "_" + string.ascii_letters or not set(name).issubset(
"_" + string.ascii_letters + string.digits
):
return False
else:
return True | [
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247,021 | turicas/rows | rows/plugins/txt.py | _parse_col_positions | def _parse_col_positions(frame_style, header_line):
"""Find the position for each column separator in the given line
If frame_style is 'None', this won work
for column names that _start_ with whitespace
(which includes non-lefthand aligned column titles)
"""
separator = re.escape(FRAMES[frame_style.lower()]["VERTICAL"])
if frame_style == "None":
separator = r"[\s]{2}[^\s]"
# Matches two whitespaces followed by a non-whitespace.
# Our column headers are serated by 3 spaces by default.
col_positions = []
# Abuse regexp engine to anotate vertical-separator positions:
re.sub(separator, lambda group: col_positions.append(group.start()), header_line)
if frame_style == "None":
col_positions.append(len(header_line) - 1)
return col_positions | python | def _parse_col_positions(frame_style, header_line):
separator = re.escape(FRAMES[frame_style.lower()]["VERTICAL"])
if frame_style == "None":
separator = r"[\s]{2}[^\s]"
# Matches two whitespaces followed by a non-whitespace.
# Our column headers are serated by 3 spaces by default.
col_positions = []
# Abuse regexp engine to anotate vertical-separator positions:
re.sub(separator, lambda group: col_positions.append(group.start()), header_line)
if frame_style == "None":
col_positions.append(len(header_line) - 1)
return col_positions | [
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If frame_style is 'None', this won work
for column names that _start_ with whitespace
(which includes non-lefthand aligned column titles) | [
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247,022 | turicas/rows | rows/plugins/txt.py | import_from_txt | def import_from_txt(
filename_or_fobj, encoding="utf-8", frame_style=FRAME_SENTINEL, *args, **kwargs
):
"""Return a rows.Table created from imported TXT file."""
# TODO: (maybe)
# enable parsing of non-fixed-width-columns
# with old algorithm - that would just split columns
# at the vertical separator character for the frame.
# (if doing so, include an optional parameter)
# Also, this fixes an outstanding unreported issue:
# trying to parse tables which fields values
# included a Pipe char - "|" - would silently
# yield bad results.
source = Source.from_file(filename_or_fobj, mode="rb", plugin_name="txt", encoding=encoding)
raw_contents = source.fobj.read().decode(encoding).rstrip("\n")
if frame_style is FRAME_SENTINEL:
frame_style = _guess_frame_style(raw_contents)
else:
frame_style = _parse_frame_style(frame_style)
contents = raw_contents.splitlines()
del raw_contents
if frame_style != "None":
contents = contents[1:-1]
del contents[1]
else:
# the table is possibly generated from other source.
# check if the line we reserve as a separator is realy empty.
if not contents[1].strip():
del contents[1]
col_positions = _parse_col_positions(frame_style, contents[0])
table_rows = [
[
row[start + 1 : end].strip()
for start, end in zip(col_positions, col_positions[1:])
]
for row in contents
]
meta = {
"imported_from": "txt",
"source": source,
"frame_style": frame_style,
}
return create_table(table_rows, meta=meta, *args, **kwargs) | python | def import_from_txt(
filename_or_fobj, encoding="utf-8", frame_style=FRAME_SENTINEL, *args, **kwargs
):
# TODO: (maybe)
# enable parsing of non-fixed-width-columns
# with old algorithm - that would just split columns
# at the vertical separator character for the frame.
# (if doing so, include an optional parameter)
# Also, this fixes an outstanding unreported issue:
# trying to parse tables which fields values
# included a Pipe char - "|" - would silently
# yield bad results.
source = Source.from_file(filename_or_fobj, mode="rb", plugin_name="txt", encoding=encoding)
raw_contents = source.fobj.read().decode(encoding).rstrip("\n")
if frame_style is FRAME_SENTINEL:
frame_style = _guess_frame_style(raw_contents)
else:
frame_style = _parse_frame_style(frame_style)
contents = raw_contents.splitlines()
del raw_contents
if frame_style != "None":
contents = contents[1:-1]
del contents[1]
else:
# the table is possibly generated from other source.
# check if the line we reserve as a separator is realy empty.
if not contents[1].strip():
del contents[1]
col_positions = _parse_col_positions(frame_style, contents[0])
table_rows = [
[
row[start + 1 : end].strip()
for start, end in zip(col_positions, col_positions[1:])
]
for row in contents
]
meta = {
"imported_from": "txt",
"source": source,
"frame_style": frame_style,
}
return create_table(table_rows, meta=meta, *args, **kwargs) | [
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247,023 | turicas/rows | rows/plugins/txt.py | export_to_txt | def export_to_txt(
table,
filename_or_fobj=None,
encoding=None,
frame_style="ASCII",
safe_none_frame=True,
*args,
**kwargs
):
"""Export a `rows.Table` to text.
This function can return the result as a string or save into a file (via
filename or file-like object).
`encoding` could be `None` if no filename/file-like object is specified,
then the return type will be `six.text_type`.
`frame_style`: will select the frame style to be printed around data.
Valid values are: ('None', 'ASCII', 'single', 'double') - ASCII is default.
Warning: no checks are made to check the desired encoding allows the
characters needed by single and double frame styles.
`safe_none_frame`: bool, defaults to True. Affects only output with
frame_style == "None":
column titles are left-aligned and have
whitespace replaced for "_". This enables
the output to be parseable. Otherwise, the generated table will look
prettier but can not be imported back.
"""
# TODO: will work only if table.fields is OrderedDict
frame_style = _parse_frame_style(frame_style)
frame = FRAMES[frame_style.lower()]
serialized_table = serialize(table, *args, **kwargs)
field_names = next(serialized_table)
table_rows = list(serialized_table)
max_sizes = _max_column_sizes(field_names, table_rows)
dashes = [frame["HORIZONTAL"] * (max_sizes[field] + 2) for field in field_names]
if frame_style != "None" or not safe_none_frame:
header = [field.center(max_sizes[field]) for field in field_names]
else:
header = [
field.replace(" ", "_").ljust(max_sizes[field]) for field in field_names
]
header = "{0} {1} {0}".format(
frame["VERTICAL"], " {} ".format(frame["VERTICAL"]).join(header)
)
top_split_line = (
frame["DOWN AND RIGHT"]
+ frame["DOWN AND HORIZONTAL"].join(dashes)
+ frame["DOWN AND LEFT"]
)
body_split_line = (
frame["VERTICAL AND RIGHT"]
+ frame["VERTICAL AND HORIZONTAL"].join(dashes)
+ frame["VERTICAL AND LEFT"]
)
botton_split_line = (
frame["UP AND RIGHT"]
+ frame["UP AND HORIZONTAL"].join(dashes)
+ frame["UP AND LEFT"]
)
result = []
if frame_style != "None":
result += [top_split_line]
result += [header, body_split_line]
for row in table_rows:
values = [
value.rjust(max_sizes[field_name])
for field_name, value in zip(field_names, row)
]
row_data = " {} ".format(frame["VERTICAL"]).join(values)
result.append("{0} {1} {0}".format(frame["VERTICAL"], row_data))
if frame_style != "None":
result.append(botton_split_line)
result.append("")
data = "\n".join(result)
if encoding is not None:
data = data.encode(encoding)
return export_data(filename_or_fobj, data, mode="wb") | python | def export_to_txt(
table,
filename_or_fobj=None,
encoding=None,
frame_style="ASCII",
safe_none_frame=True,
*args,
**kwargs
):
# TODO: will work only if table.fields is OrderedDict
frame_style = _parse_frame_style(frame_style)
frame = FRAMES[frame_style.lower()]
serialized_table = serialize(table, *args, **kwargs)
field_names = next(serialized_table)
table_rows = list(serialized_table)
max_sizes = _max_column_sizes(field_names, table_rows)
dashes = [frame["HORIZONTAL"] * (max_sizes[field] + 2) for field in field_names]
if frame_style != "None" or not safe_none_frame:
header = [field.center(max_sizes[field]) for field in field_names]
else:
header = [
field.replace(" ", "_").ljust(max_sizes[field]) for field in field_names
]
header = "{0} {1} {0}".format(
frame["VERTICAL"], " {} ".format(frame["VERTICAL"]).join(header)
)
top_split_line = (
frame["DOWN AND RIGHT"]
+ frame["DOWN AND HORIZONTAL"].join(dashes)
+ frame["DOWN AND LEFT"]
)
body_split_line = (
frame["VERTICAL AND RIGHT"]
+ frame["VERTICAL AND HORIZONTAL"].join(dashes)
+ frame["VERTICAL AND LEFT"]
)
botton_split_line = (
frame["UP AND RIGHT"]
+ frame["UP AND HORIZONTAL"].join(dashes)
+ frame["UP AND LEFT"]
)
result = []
if frame_style != "None":
result += [top_split_line]
result += [header, body_split_line]
for row in table_rows:
values = [
value.rjust(max_sizes[field_name])
for field_name, value in zip(field_names, row)
]
row_data = " {} ".format(frame["VERTICAL"]).join(values)
result.append("{0} {1} {0}".format(frame["VERTICAL"], row_data))
if frame_style != "None":
result.append(botton_split_line)
result.append("")
data = "\n".join(result)
if encoding is not None:
data = data.encode(encoding)
return export_data(filename_or_fobj, data, mode="wb") | [
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This function can return the result as a string or save into a file (via
filename or file-like object).
`encoding` could be `None` if no filename/file-like object is specified,
then the return type will be `six.text_type`.
`frame_style`: will select the frame style to be printed around data.
Valid values are: ('None', 'ASCII', 'single', 'double') - ASCII is default.
Warning: no checks are made to check the desired encoding allows the
characters needed by single and double frame styles.
`safe_none_frame`: bool, defaults to True. Affects only output with
frame_style == "None":
column titles are left-aligned and have
whitespace replaced for "_". This enables
the output to be parseable. Otherwise, the generated table will look
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247,024 | turicas/rows | rows/plugins/sqlite.py | import_from_sqlite | def import_from_sqlite(
filename_or_connection,
table_name="table1",
query=None,
query_args=None,
*args,
**kwargs
):
"""Return a rows.Table with data from SQLite database."""
source = get_source(filename_or_connection)
connection = source.fobj
cursor = connection.cursor()
if query is None:
if not _valid_table_name(table_name):
raise ValueError("Invalid table name: {}".format(table_name))
query = SQL_SELECT_ALL.format(table_name=table_name)
if query_args is None:
query_args = tuple()
table_rows = list(cursor.execute(query, query_args)) # TODO: may be lazy
header = [six.text_type(info[0]) for info in cursor.description]
cursor.close()
# TODO: should close connection also?
meta = {"imported_from": "sqlite", "source": source}
return create_table([header] + table_rows, meta=meta, *args, **kwargs) | python | def import_from_sqlite(
filename_or_connection,
table_name="table1",
query=None,
query_args=None,
*args,
**kwargs
):
source = get_source(filename_or_connection)
connection = source.fobj
cursor = connection.cursor()
if query is None:
if not _valid_table_name(table_name):
raise ValueError("Invalid table name: {}".format(table_name))
query = SQL_SELECT_ALL.format(table_name=table_name)
if query_args is None:
query_args = tuple()
table_rows = list(cursor.execute(query, query_args)) # TODO: may be lazy
header = [six.text_type(info[0]) for info in cursor.description]
cursor.close()
# TODO: should close connection also?
meta = {"imported_from": "sqlite", "source": source}
return create_table([header] + table_rows, meta=meta, *args, **kwargs) | [
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247,025 | turicas/rows | rows/plugins/xlsx.py | _cell_to_python | def _cell_to_python(cell):
"""Convert a PyOpenXL's `Cell` object to the corresponding Python object."""
data_type, value = cell.data_type, cell.value
if type(cell) is EmptyCell:
return None
elif data_type == "f" and value == "=TRUE()":
return True
elif data_type == "f" and value == "=FALSE()":
return False
elif cell.number_format.lower() == "yyyy-mm-dd":
return str(value).split(" 00:00:00")[0]
elif cell.number_format.lower() == "yyyy-mm-dd hh:mm:ss":
return str(value).split(".")[0]
elif cell.number_format.endswith("%") and isinstance(value, Number):
value = Decimal(str(value))
return "{:%}".format(value)
elif value is None:
return ""
else:
return value | python | def _cell_to_python(cell):
data_type, value = cell.data_type, cell.value
if type(cell) is EmptyCell:
return None
elif data_type == "f" and value == "=TRUE()":
return True
elif data_type == "f" and value == "=FALSE()":
return False
elif cell.number_format.lower() == "yyyy-mm-dd":
return str(value).split(" 00:00:00")[0]
elif cell.number_format.lower() == "yyyy-mm-dd hh:mm:ss":
return str(value).split(".")[0]
elif cell.number_format.endswith("%") and isinstance(value, Number):
value = Decimal(str(value))
return "{:%}".format(value)
elif value is None:
return ""
else:
return value | [
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247,026 | turicas/rows | rows/plugins/xlsx.py | import_from_xlsx | def import_from_xlsx(
filename_or_fobj,
sheet_name=None,
sheet_index=0,
start_row=None,
start_column=None,
end_row=None,
end_column=None,
workbook_kwargs=None,
*args,
**kwargs
):
"""Return a rows.Table created from imported XLSX file.
workbook_kwargs will be passed to openpyxl.load_workbook
"""
workbook_kwargs = workbook_kwargs or {}
if "read_only" not in workbook_kwargs:
workbook_kwargs["read_only"] = True
workbook = load_workbook(filename_or_fobj, **workbook_kwargs)
if sheet_name is None:
sheet_name = workbook.sheetnames[sheet_index]
sheet = workbook[sheet_name]
# The openpyxl library reads rows and columns starting from 1 and ending on
# sheet.max_row/max_col. rows uses 0-based indexes (from 0 to N - 1), so we
# need to adjust the ranges accordingly.
min_row, min_column = sheet.min_row - 1, sheet.min_column - 1
max_row, max_column = sheet.max_row - 1, sheet.max_column - 1
# TODO: consider adding a parameter `ignore_padding=True` and when it's
# True, consider `start_row` starting from `sheet.min_row` and
# `start_column` starting from `sheet.min_col`.
start_row = start_row if start_row is not None else min_row
end_row = end_row if end_row is not None else max_row
start_column = start_column if start_column is not None else min_column
end_column = end_column if end_column is not None else max_column
table_rows = []
is_empty = lambda row: all(cell is None for cell in row)
selected_rows = sheet.iter_rows(
min_row=start_row + 1,
max_row=end_row + 1,
min_col=start_column + 1,
max_col=end_column + 1,
)
for row in selected_rows:
row = [_cell_to_python(cell) for cell in row]
if not is_empty(row):
table_rows.append(row)
source = Source.from_file(filename_or_fobj, plugin_name="xlsx")
source.fobj.close()
# TODO: pass a parameter to Source.from_file so it won't open the file
metadata = {"imported_from": "xlsx", "source": source, "name": sheet_name}
return create_table(table_rows, meta=metadata, *args, **kwargs) | python | def import_from_xlsx(
filename_or_fobj,
sheet_name=None,
sheet_index=0,
start_row=None,
start_column=None,
end_row=None,
end_column=None,
workbook_kwargs=None,
*args,
**kwargs
):
workbook_kwargs = workbook_kwargs or {}
if "read_only" not in workbook_kwargs:
workbook_kwargs["read_only"] = True
workbook = load_workbook(filename_or_fobj, **workbook_kwargs)
if sheet_name is None:
sheet_name = workbook.sheetnames[sheet_index]
sheet = workbook[sheet_name]
# The openpyxl library reads rows and columns starting from 1 and ending on
# sheet.max_row/max_col. rows uses 0-based indexes (from 0 to N - 1), so we
# need to adjust the ranges accordingly.
min_row, min_column = sheet.min_row - 1, sheet.min_column - 1
max_row, max_column = sheet.max_row - 1, sheet.max_column - 1
# TODO: consider adding a parameter `ignore_padding=True` and when it's
# True, consider `start_row` starting from `sheet.min_row` and
# `start_column` starting from `sheet.min_col`.
start_row = start_row if start_row is not None else min_row
end_row = end_row if end_row is not None else max_row
start_column = start_column if start_column is not None else min_column
end_column = end_column if end_column is not None else max_column
table_rows = []
is_empty = lambda row: all(cell is None for cell in row)
selected_rows = sheet.iter_rows(
min_row=start_row + 1,
max_row=end_row + 1,
min_col=start_column + 1,
max_col=end_column + 1,
)
for row in selected_rows:
row = [_cell_to_python(cell) for cell in row]
if not is_empty(row):
table_rows.append(row)
source = Source.from_file(filename_or_fobj, plugin_name="xlsx")
source.fobj.close()
# TODO: pass a parameter to Source.from_file so it won't open the file
metadata = {"imported_from": "xlsx", "source": source, "name": sheet_name}
return create_table(table_rows, meta=metadata, *args, **kwargs) | [
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247,027 | turicas/rows | rows/plugins/xlsx.py | export_to_xlsx | def export_to_xlsx(table, filename_or_fobj=None, sheet_name="Sheet1", *args, **kwargs):
"""Export the rows.Table to XLSX file and return the saved file."""
workbook = Workbook()
sheet = workbook.active
sheet.title = sheet_name
prepared_table = prepare_to_export(table, *args, **kwargs)
# Write header
field_names = next(prepared_table)
for col_index, field_name in enumerate(field_names):
cell = sheet.cell(row=1, column=col_index + 1)
cell.value = field_name
# Write sheet rows
_convert_row = _python_to_cell(list(map(table.fields.get, field_names)))
for row_index, row in enumerate(prepared_table, start=1):
for col_index, (value, number_format) in enumerate(_convert_row(row)):
cell = sheet.cell(row=row_index + 1, column=col_index + 1)
cell.value = value
if number_format is not None:
cell.number_format = number_format
return_result = False
if filename_or_fobj is None:
filename_or_fobj = BytesIO()
return_result = True
source = Source.from_file(filename_or_fobj, mode="wb", plugin_name="xlsx")
workbook.save(source.fobj)
source.fobj.flush()
if return_result:
source.fobj.seek(0)
result = source.fobj.read()
else:
result = source.fobj
if source.should_close:
source.fobj.close()
return result | python | def export_to_xlsx(table, filename_or_fobj=None, sheet_name="Sheet1", *args, **kwargs):
workbook = Workbook()
sheet = workbook.active
sheet.title = sheet_name
prepared_table = prepare_to_export(table, *args, **kwargs)
# Write header
field_names = next(prepared_table)
for col_index, field_name in enumerate(field_names):
cell = sheet.cell(row=1, column=col_index + 1)
cell.value = field_name
# Write sheet rows
_convert_row = _python_to_cell(list(map(table.fields.get, field_names)))
for row_index, row in enumerate(prepared_table, start=1):
for col_index, (value, number_format) in enumerate(_convert_row(row)):
cell = sheet.cell(row=row_index + 1, column=col_index + 1)
cell.value = value
if number_format is not None:
cell.number_format = number_format
return_result = False
if filename_or_fobj is None:
filename_or_fobj = BytesIO()
return_result = True
source = Source.from_file(filename_or_fobj, mode="wb", plugin_name="xlsx")
workbook.save(source.fobj)
source.fobj.flush()
if return_result:
source.fobj.seek(0)
result = source.fobj.read()
else:
result = source.fobj
if source.should_close:
source.fobj.close()
return result | [
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247,028 | turicas/rows | examples/library/organizaciones.py | download_organizations | def download_organizations():
"Download organizations JSON and extract its properties"
response = requests.get(URL)
data = response.json()
organizations = [organization["properties"] for organization in data["features"]]
return rows.import_from_dicts(organizations) | python | def download_organizations():
"Download organizations JSON and extract its properties"
response = requests.get(URL)
data = response.json()
organizations = [organization["properties"] for organization in data["features"]]
return rows.import_from_dicts(organizations) | [
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] | c74da41ae9ed091356b803a64f8a30c641c5fc45 | https://github.com/turicas/rows/blob/c74da41ae9ed091356b803a64f8a30c641c5fc45/examples/library/organizaciones.py#L15-L21 |
247,029 | turicas/rows | rows/plugins/plugin_html.py | import_from_html | def import_from_html(
filename_or_fobj,
encoding="utf-8",
index=0,
ignore_colspan=True,
preserve_html=False,
properties=False,
table_tag="table",
row_tag="tr",
column_tag="td|th",
*args,
**kwargs
):
"""Return rows.Table from HTML file."""
source = Source.from_file(
filename_or_fobj, plugin_name="html", mode="rb", encoding=encoding
)
html = source.fobj.read().decode(source.encoding)
html_tree = document_fromstring(html)
tables = html_tree.xpath("//{}".format(table_tag))
table = tables[index]
# TODO: set meta's "name" from @id or @name (if available)
strip_tags(table, "thead")
strip_tags(table, "tbody")
row_elements = table.xpath(row_tag)
table_rows = [
_get_row(
row,
column_tag=column_tag,
preserve_html=preserve_html,
properties=properties,
)
for row in row_elements
]
if properties:
table_rows[0][-1] = "properties"
if preserve_html and kwargs.get("fields", None) is None:
# The field names will be the first table row, so we need to strip HTML
# from it even if `preserve_html` is `True` (it's `True` only for rows,
# not for the header).
table_rows[0] = list(map(_extract_node_text, row_elements[0]))
if ignore_colspan:
max_columns = max(map(len, table_rows))
table_rows = [row for row in table_rows if len(row) == max_columns]
meta = {"imported_from": "html", "source": source}
return create_table(table_rows, meta=meta, *args, **kwargs) | python | def import_from_html(
filename_or_fobj,
encoding="utf-8",
index=0,
ignore_colspan=True,
preserve_html=False,
properties=False,
table_tag="table",
row_tag="tr",
column_tag="td|th",
*args,
**kwargs
):
source = Source.from_file(
filename_or_fobj, plugin_name="html", mode="rb", encoding=encoding
)
html = source.fobj.read().decode(source.encoding)
html_tree = document_fromstring(html)
tables = html_tree.xpath("//{}".format(table_tag))
table = tables[index]
# TODO: set meta's "name" from @id or @name (if available)
strip_tags(table, "thead")
strip_tags(table, "tbody")
row_elements = table.xpath(row_tag)
table_rows = [
_get_row(
row,
column_tag=column_tag,
preserve_html=preserve_html,
properties=properties,
)
for row in row_elements
]
if properties:
table_rows[0][-1] = "properties"
if preserve_html and kwargs.get("fields", None) is None:
# The field names will be the first table row, so we need to strip HTML
# from it even if `preserve_html` is `True` (it's `True` only for rows,
# not for the header).
table_rows[0] = list(map(_extract_node_text, row_elements[0]))
if ignore_colspan:
max_columns = max(map(len, table_rows))
table_rows = [row for row in table_rows if len(row) == max_columns]
meta = {"imported_from": "html", "source": source}
return create_table(table_rows, meta=meta, *args, **kwargs) | [
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247,030 | turicas/rows | rows/plugins/plugin_html.py | export_to_html | def export_to_html(
table, filename_or_fobj=None, encoding="utf-8", caption=False, *args, **kwargs
):
"""Export and return rows.Table data to HTML file."""
serialized_table = serialize(table, *args, **kwargs)
fields = next(serialized_table)
result = ["<table>\n\n"]
if caption and table.name:
result.extend([" <caption>", table.name, "</caption>\n\n"])
result.extend([" <thead>\n", " <tr>\n"])
# TODO: set @name/@id if self.meta["name"] is set
header = [" <th> {} </th>\n".format(field) for field in fields]
result.extend(header)
result.extend([" </tr>\n", " </thead>\n", "\n", " <tbody>\n", "\n"])
for index, row in enumerate(serialized_table, start=1):
css_class = "odd" if index % 2 == 1 else "even"
result.append(' <tr class="{}">\n'.format(css_class))
for value in row:
result.extend([" <td> ", escape(value), " </td>\n"])
result.append(" </tr>\n\n")
result.append(" </tbody>\n\n</table>\n")
html = "".join(result).encode(encoding)
return export_data(filename_or_fobj, html, mode="wb") | python | def export_to_html(
table, filename_or_fobj=None, encoding="utf-8", caption=False, *args, **kwargs
):
serialized_table = serialize(table, *args, **kwargs)
fields = next(serialized_table)
result = ["<table>\n\n"]
if caption and table.name:
result.extend([" <caption>", table.name, "</caption>\n\n"])
result.extend([" <thead>\n", " <tr>\n"])
# TODO: set @name/@id if self.meta["name"] is set
header = [" <th> {} </th>\n".format(field) for field in fields]
result.extend(header)
result.extend([" </tr>\n", " </thead>\n", "\n", " <tbody>\n", "\n"])
for index, row in enumerate(serialized_table, start=1):
css_class = "odd" if index % 2 == 1 else "even"
result.append(' <tr class="{}">\n'.format(css_class))
for value in row:
result.extend([" <td> ", escape(value), " </td>\n"])
result.append(" </tr>\n\n")
result.append(" </tbody>\n\n</table>\n")
html = "".join(result).encode(encoding)
return export_data(filename_or_fobj, html, mode="wb") | [
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247,031 | turicas/rows | rows/plugins/plugin_html.py | _extract_node_text | def _extract_node_text(node):
"""Extract text from a given lxml node."""
texts = map(
six.text_type.strip, map(six.text_type, map(unescape, node.xpath(".//text()")))
)
return " ".join(text for text in texts if text) | python | def _extract_node_text(node):
texts = map(
six.text_type.strip, map(six.text_type, map(unescape, node.xpath(".//text()")))
)
return " ".join(text for text in texts if text) | [
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247,032 | turicas/rows | rows/plugins/plugin_html.py | count_tables | def count_tables(filename_or_fobj, encoding="utf-8", table_tag="table"):
"""Read a file passed by arg and return your table HTML tag count."""
source = Source.from_file(
filename_or_fobj, plugin_name="html", mode="rb", encoding=encoding
)
html = source.fobj.read().decode(source.encoding)
html_tree = document_fromstring(html)
tables = html_tree.xpath("//{}".format(table_tag))
result = len(tables)
if source.should_close:
source.fobj.close()
return result | python | def count_tables(filename_or_fobj, encoding="utf-8", table_tag="table"):
source = Source.from_file(
filename_or_fobj, plugin_name="html", mode="rb", encoding=encoding
)
html = source.fobj.read().decode(source.encoding)
html_tree = document_fromstring(html)
tables = html_tree.xpath("//{}".format(table_tag))
result = len(tables)
if source.should_close:
source.fobj.close()
return result | [
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247,033 | turicas/rows | rows/plugins/plugin_html.py | tag_to_dict | def tag_to_dict(html):
"""Extract tag's attributes into a `dict`."""
element = document_fromstring(html).xpath("//html/body/child::*")[0]
attributes = dict(element.attrib)
attributes["text"] = element.text_content()
return attributes | python | def tag_to_dict(html):
element = document_fromstring(html).xpath("//html/body/child::*")[0]
attributes = dict(element.attrib)
attributes["text"] = element.text_content()
return attributes | [
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247,034 | turicas/rows | rows/plugins/utils.py | create_table | def create_table(
data,
meta=None,
fields=None,
skip_header=True,
import_fields=None,
samples=None,
force_types=None,
max_rows=None,
*args,
**kwargs
):
"""Create a rows.Table object based on data rows and some configurations
- `skip_header` is only used if `fields` is set
- `samples` is only used if `fields` is `None`. If samples=None, all data
is filled in memory - use with caution.
- `force_types` is only used if `fields` is `None`
- `import_fields` can be used either if `fields` is set or not, the
resulting fields will seek its order
- `fields` must always be in the same order as the data
"""
table_rows = iter(data)
force_types = force_types or {}
if import_fields is not None:
import_fields = make_header(import_fields)
# TODO: test max_rows
if fields is None: # autodetect field types
# TODO: may add `type_hints` parameter so autodetection can be easier
# (plugins may specify some possible field types).
header = make_header(next(table_rows))
if samples is not None:
sample_rows = list(islice(table_rows, 0, samples))
table_rows = chain(sample_rows, table_rows)
else:
if max_rows is not None and max_rows > 0:
sample_rows = table_rows = list(islice(table_rows, max_rows))
else:
sample_rows = table_rows = list(table_rows)
# Detect field types using only the desired columns
detected_fields = detect_types(
header,
sample_rows,
skip_indexes=[
index
for index, field in enumerate(header)
if field in force_types or field not in (import_fields or header)
],
*args,
**kwargs
)
# Check if any field was added during detecting process
new_fields = [
field_name
for field_name in detected_fields.keys()
if field_name not in header
]
# Finally create the `fields` with both header and new field names,
# based on detected fields `and force_types`
fields = OrderedDict(
[
(field_name, detected_fields.get(field_name, TextField))
for field_name in header + new_fields
]
)
fields.update(force_types)
# Update `header` and `import_fields` based on new `fields`
header = list(fields.keys())
if import_fields is None:
import_fields = header
else: # using provided field types
if not isinstance(fields, OrderedDict):
raise ValueError("`fields` must be an `OrderedDict`")
if skip_header:
# If we're skipping the header probably this row is not trustable
# (can be data or garbage).
next(table_rows)
header = make_header(list(fields.keys()))
if import_fields is None:
import_fields = header
fields = OrderedDict(
[(field_name, fields[key]) for field_name, key in zip(header, fields)]
)
diff = set(import_fields) - set(header)
if diff:
field_names = ", ".join('"{}"'.format(field) for field in diff)
raise ValueError("Invalid field names: {}".format(field_names))
fields = OrderedDict(
[(field_name, fields[field_name]) for field_name in import_fields]
)
get_row = get_items(*map(header.index, import_fields))
table = Table(fields=fields, meta=meta)
if max_rows is not None and max_rows > 0:
table_rows = islice(table_rows, max_rows)
table.extend(dict(zip(import_fields, get_row(row))) for row in table_rows)
source = table.meta.get("source", None)
if source is not None:
if source.should_close:
source.fobj.close()
if source.should_delete and Path(source.uri).exists():
unlink(source.uri)
return table | python | def create_table(
data,
meta=None,
fields=None,
skip_header=True,
import_fields=None,
samples=None,
force_types=None,
max_rows=None,
*args,
**kwargs
):
table_rows = iter(data)
force_types = force_types or {}
if import_fields is not None:
import_fields = make_header(import_fields)
# TODO: test max_rows
if fields is None: # autodetect field types
# TODO: may add `type_hints` parameter so autodetection can be easier
# (plugins may specify some possible field types).
header = make_header(next(table_rows))
if samples is not None:
sample_rows = list(islice(table_rows, 0, samples))
table_rows = chain(sample_rows, table_rows)
else:
if max_rows is not None and max_rows > 0:
sample_rows = table_rows = list(islice(table_rows, max_rows))
else:
sample_rows = table_rows = list(table_rows)
# Detect field types using only the desired columns
detected_fields = detect_types(
header,
sample_rows,
skip_indexes=[
index
for index, field in enumerate(header)
if field in force_types or field not in (import_fields or header)
],
*args,
**kwargs
)
# Check if any field was added during detecting process
new_fields = [
field_name
for field_name in detected_fields.keys()
if field_name not in header
]
# Finally create the `fields` with both header and new field names,
# based on detected fields `and force_types`
fields = OrderedDict(
[
(field_name, detected_fields.get(field_name, TextField))
for field_name in header + new_fields
]
)
fields.update(force_types)
# Update `header` and `import_fields` based on new `fields`
header = list(fields.keys())
if import_fields is None:
import_fields = header
else: # using provided field types
if not isinstance(fields, OrderedDict):
raise ValueError("`fields` must be an `OrderedDict`")
if skip_header:
# If we're skipping the header probably this row is not trustable
# (can be data or garbage).
next(table_rows)
header = make_header(list(fields.keys()))
if import_fields is None:
import_fields = header
fields = OrderedDict(
[(field_name, fields[key]) for field_name, key in zip(header, fields)]
)
diff = set(import_fields) - set(header)
if diff:
field_names = ", ".join('"{}"'.format(field) for field in diff)
raise ValueError("Invalid field names: {}".format(field_names))
fields = OrderedDict(
[(field_name, fields[field_name]) for field_name in import_fields]
)
get_row = get_items(*map(header.index, import_fields))
table = Table(fields=fields, meta=meta)
if max_rows is not None and max_rows > 0:
table_rows = islice(table_rows, max_rows)
table.extend(dict(zip(import_fields, get_row(row))) for row in table_rows)
source = table.meta.get("source", None)
if source is not None:
if source.should_close:
source.fobj.close()
if source.should_delete and Path(source.uri).exists():
unlink(source.uri)
return table | [
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] | Create a rows.Table object based on data rows and some configurations
- `skip_header` is only used if `fields` is set
- `samples` is only used if `fields` is `None`. If samples=None, all data
is filled in memory - use with caution.
- `force_types` is only used if `fields` is `None`
- `import_fields` can be used either if `fields` is set or not, the
resulting fields will seek its order
- `fields` must always be in the same order as the data | [
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] | c74da41ae9ed091356b803a64f8a30c641c5fc45 | https://github.com/turicas/rows/blob/c74da41ae9ed091356b803a64f8a30c641c5fc45/rows/plugins/utils.py#L75-L189 |
247,035 | turicas/rows | rows/plugins/utils.py | export_data | def export_data(filename_or_fobj, data, mode="w"):
"""Return the object ready to be exported or only data if filename_or_fobj is not passed."""
if filename_or_fobj is None:
return data
_, fobj = get_filename_and_fobj(filename_or_fobj, mode=mode)
source = Source.from_file(filename_or_fobj, mode=mode, plugin_name=None)
source.fobj.write(data)
source.fobj.flush()
return source.fobj | python | def export_data(filename_or_fobj, data, mode="w"):
if filename_or_fobj is None:
return data
_, fobj = get_filename_and_fobj(filename_or_fobj, mode=mode)
source = Source.from_file(filename_or_fobj, mode=mode, plugin_name=None)
source.fobj.write(data)
source.fobj.flush()
return source.fobj | [
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] | c74da41ae9ed091356b803a64f8a30c641c5fc45 | https://github.com/turicas/rows/blob/c74da41ae9ed091356b803a64f8a30c641c5fc45/rows/plugins/utils.py#L236-L246 |
247,036 | turicas/rows | rows/plugins/plugin_csv.py | read_sample | def read_sample(fobj, sample):
"""Read `sample` bytes from `fobj` and return the cursor to where it was."""
cursor = fobj.tell()
data = fobj.read(sample)
fobj.seek(cursor)
return data | python | def read_sample(fobj, sample):
cursor = fobj.tell()
data = fobj.read(sample)
fobj.seek(cursor)
return data | [
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247,037 | turicas/rows | rows/plugins/plugin_csv.py | export_to_csv | def export_to_csv(
table,
filename_or_fobj=None,
encoding="utf-8",
dialect=unicodecsv.excel,
batch_size=100,
callback=None,
*args,
**kwargs
):
"""Export a `rows.Table` to a CSV file.
If a file-like object is provided it MUST be in binary mode, like in
`open(filename, mode='wb')`.
If not filename/fobj is provided, the function returns a string with CSV
contents.
"""
# TODO: will work only if table.fields is OrderedDict
# TODO: should use fobj? What about creating a method like json.dumps?
return_data, should_close = False, None
if filename_or_fobj is None:
filename_or_fobj = BytesIO()
return_data = should_close = True
source = Source.from_file(
filename_or_fobj,
plugin_name="csv",
mode="wb",
encoding=encoding,
should_close=should_close,
)
# TODO: may use `io.BufferedWriter` instead of `ipartition` so user can
# choose the real size (in Bytes) when to flush to the file system, instead
# number of rows
writer = unicodecsv.writer(source.fobj, encoding=encoding, dialect=dialect)
if callback is None:
for batch in ipartition(serialize(table, *args, **kwargs), batch_size):
writer.writerows(batch)
else:
serialized = serialize(table, *args, **kwargs)
writer.writerow(next(serialized)) # First, write the header
total = 0
for batch in ipartition(serialized, batch_size):
writer.writerows(batch)
total += len(batch)
callback(total)
if return_data:
source.fobj.seek(0)
result = source.fobj.read()
else:
source.fobj.flush()
result = source.fobj
if source.should_close:
source.fobj.close()
return result | python | def export_to_csv(
table,
filename_or_fobj=None,
encoding="utf-8",
dialect=unicodecsv.excel,
batch_size=100,
callback=None,
*args,
**kwargs
):
# TODO: will work only if table.fields is OrderedDict
# TODO: should use fobj? What about creating a method like json.dumps?
return_data, should_close = False, None
if filename_or_fobj is None:
filename_or_fobj = BytesIO()
return_data = should_close = True
source = Source.from_file(
filename_or_fobj,
plugin_name="csv",
mode="wb",
encoding=encoding,
should_close=should_close,
)
# TODO: may use `io.BufferedWriter` instead of `ipartition` so user can
# choose the real size (in Bytes) when to flush to the file system, instead
# number of rows
writer = unicodecsv.writer(source.fobj, encoding=encoding, dialect=dialect)
if callback is None:
for batch in ipartition(serialize(table, *args, **kwargs), batch_size):
writer.writerows(batch)
else:
serialized = serialize(table, *args, **kwargs)
writer.writerow(next(serialized)) # First, write the header
total = 0
for batch in ipartition(serialized, batch_size):
writer.writerows(batch)
total += len(batch)
callback(total)
if return_data:
source.fobj.seek(0)
result = source.fobj.read()
else:
source.fobj.flush()
result = source.fobj
if source.should_close:
source.fobj.close()
return result | [
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If a file-like object is provided it MUST be in binary mode, like in
`open(filename, mode='wb')`.
If not filename/fobj is provided, the function returns a string with CSV
contents. | [
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247,038 | turicas/rows | rows/operations.py | join | def join(keys, tables):
"""Merge a list of `Table` objects using `keys` to group rows"""
# Make new (merged) Table fields
fields = OrderedDict()
for table in tables:
fields.update(table.fields)
# TODO: may raise an error if a same field is different in some tables
# Check if all keys are inside merged Table's fields
fields_keys = set(fields.keys())
for key in keys:
if key not in fields_keys:
raise ValueError('Invalid key: "{}"'.format(key))
# Group rows by key, without missing ordering
none_fields = lambda: OrderedDict({field: None for field in fields.keys()})
data = OrderedDict()
for table in tables:
for row in table:
row_key = tuple([getattr(row, key) for key in keys])
if row_key not in data:
data[row_key] = none_fields()
data[row_key].update(row._asdict())
merged = Table(fields=fields)
merged.extend(data.values())
return merged | python | def join(keys, tables):
# Make new (merged) Table fields
fields = OrderedDict()
for table in tables:
fields.update(table.fields)
# TODO: may raise an error if a same field is different in some tables
# Check if all keys are inside merged Table's fields
fields_keys = set(fields.keys())
for key in keys:
if key not in fields_keys:
raise ValueError('Invalid key: "{}"'.format(key))
# Group rows by key, without missing ordering
none_fields = lambda: OrderedDict({field: None for field in fields.keys()})
data = OrderedDict()
for table in tables:
for row in table:
row_key = tuple([getattr(row, key) for key in keys])
if row_key not in data:
data[row_key] = none_fields()
data[row_key].update(row._asdict())
merged = Table(fields=fields)
merged.extend(data.values())
return merged | [
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247,039 | turicas/rows | rows/operations.py | transform | def transform(fields, function, *tables):
"Return a new table based on other tables and a transformation function"
new_table = Table(fields=fields)
for table in tables:
for row in filter(bool, map(lambda row: function(row, table), table)):
new_table.append(row)
return new_table | python | def transform(fields, function, *tables):
"Return a new table based on other tables and a transformation function"
new_table = Table(fields=fields)
for table in tables:
for row in filter(bool, map(lambda row: function(row, table), table)):
new_table.append(row)
return new_table | [
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247,040 | jupyterhub/kubespawner | kubespawner/objects.py | make_pvc | def make_pvc(
name,
storage_class,
access_modes,
storage,
labels=None,
annotations=None,
):
"""
Make a k8s pvc specification for running a user notebook.
Parameters
----------
name:
Name of persistent volume claim. Must be unique within the namespace the object is
going to be created in. Must be a valid DNS label.
storage_class:
String of the name of the k8s Storage Class to use.
access_modes:
A list of specifying what access mode the pod should have towards the pvc
storage:
The ammount of storage needed for the pvc
"""
pvc = V1PersistentVolumeClaim()
pvc.kind = "PersistentVolumeClaim"
pvc.api_version = "v1"
pvc.metadata = V1ObjectMeta()
pvc.metadata.name = name
pvc.metadata.annotations = (annotations or {}).copy()
pvc.metadata.labels = (labels or {}).copy()
pvc.spec = V1PersistentVolumeClaimSpec()
pvc.spec.access_modes = access_modes
pvc.spec.resources = V1ResourceRequirements()
pvc.spec.resources.requests = {"storage": storage}
if storage_class:
pvc.metadata.annotations.update({"volume.beta.kubernetes.io/storage-class": storage_class})
pvc.spec.storage_class_name = storage_class
return pvc | python | def make_pvc(
name,
storage_class,
access_modes,
storage,
labels=None,
annotations=None,
):
pvc = V1PersistentVolumeClaim()
pvc.kind = "PersistentVolumeClaim"
pvc.api_version = "v1"
pvc.metadata = V1ObjectMeta()
pvc.metadata.name = name
pvc.metadata.annotations = (annotations or {}).copy()
pvc.metadata.labels = (labels or {}).copy()
pvc.spec = V1PersistentVolumeClaimSpec()
pvc.spec.access_modes = access_modes
pvc.spec.resources = V1ResourceRequirements()
pvc.spec.resources.requests = {"storage": storage}
if storage_class:
pvc.metadata.annotations.update({"volume.beta.kubernetes.io/storage-class": storage_class})
pvc.spec.storage_class_name = storage_class
return pvc | [
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Parameters
----------
name:
Name of persistent volume claim. Must be unique within the namespace the object is
going to be created in. Must be a valid DNS label.
storage_class:
String of the name of the k8s Storage Class to use.
access_modes:
A list of specifying what access mode the pod should have towards the pvc
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The ammount of storage needed for the pvc | [
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247,041 | jupyterhub/kubespawner | kubespawner/objects.py | make_ingress | def make_ingress(
name,
routespec,
target,
data
):
"""
Returns an ingress, service, endpoint object that'll work for this service
"""
# move beta imports here,
# which are more sensitive to kubernetes version
# and will change when they move out of beta
from kubernetes.client.models import (
V1beta1Ingress, V1beta1IngressSpec, V1beta1IngressRule,
V1beta1HTTPIngressRuleValue, V1beta1HTTPIngressPath,
V1beta1IngressBackend,
)
meta = V1ObjectMeta(
name=name,
annotations={
'hub.jupyter.org/proxy-data': json.dumps(data),
'hub.jupyter.org/proxy-routespec': routespec,
'hub.jupyter.org/proxy-target': target
},
labels={
'heritage': 'jupyterhub',
'component': 'singleuser-server',
'hub.jupyter.org/proxy-route': 'true'
}
)
if routespec.startswith('/'):
host = None
path = routespec
else:
host, path = routespec.split('/', 1)
target_parts = urlparse(target)
target_ip = target_parts.hostname
target_port = target_parts.port
target_is_ip = re.match('^\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$', target_ip) is not None
# Make endpoint object
if target_is_ip:
endpoint = V1Endpoints(
kind='Endpoints',
metadata=meta,
subsets=[
V1EndpointSubset(
addresses=[V1EndpointAddress(ip=target_ip)],
ports=[V1EndpointPort(port=target_port)]
)
]
)
else:
endpoint = None
# Make service object
if target_is_ip:
service = V1Service(
kind='Service',
metadata=meta,
spec=V1ServiceSpec(
type='ClusterIP',
external_name='',
ports=[V1ServicePort(port=target_port, target_port=target_port)]
)
)
else:
service = V1Service(
kind='Service',
metadata=meta,
spec=V1ServiceSpec(
type='ExternalName',
external_name=target_ip,
cluster_ip='',
ports=[V1ServicePort(port=target_port, target_port=target_port)],
),
)
# Make Ingress object
ingress = V1beta1Ingress(
kind='Ingress',
metadata=meta,
spec=V1beta1IngressSpec(
rules=[V1beta1IngressRule(
host=host,
http=V1beta1HTTPIngressRuleValue(
paths=[
V1beta1HTTPIngressPath(
path=path,
backend=V1beta1IngressBackend(
service_name=name,
service_port=target_port
)
)
]
)
)]
)
)
return endpoint, service, ingress | python | def make_ingress(
name,
routespec,
target,
data
):
# move beta imports here,
# which are more sensitive to kubernetes version
# and will change when they move out of beta
from kubernetes.client.models import (
V1beta1Ingress, V1beta1IngressSpec, V1beta1IngressRule,
V1beta1HTTPIngressRuleValue, V1beta1HTTPIngressPath,
V1beta1IngressBackend,
)
meta = V1ObjectMeta(
name=name,
annotations={
'hub.jupyter.org/proxy-data': json.dumps(data),
'hub.jupyter.org/proxy-routespec': routespec,
'hub.jupyter.org/proxy-target': target
},
labels={
'heritage': 'jupyterhub',
'component': 'singleuser-server',
'hub.jupyter.org/proxy-route': 'true'
}
)
if routespec.startswith('/'):
host = None
path = routespec
else:
host, path = routespec.split('/', 1)
target_parts = urlparse(target)
target_ip = target_parts.hostname
target_port = target_parts.port
target_is_ip = re.match('^\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$', target_ip) is not None
# Make endpoint object
if target_is_ip:
endpoint = V1Endpoints(
kind='Endpoints',
metadata=meta,
subsets=[
V1EndpointSubset(
addresses=[V1EndpointAddress(ip=target_ip)],
ports=[V1EndpointPort(port=target_port)]
)
]
)
else:
endpoint = None
# Make service object
if target_is_ip:
service = V1Service(
kind='Service',
metadata=meta,
spec=V1ServiceSpec(
type='ClusterIP',
external_name='',
ports=[V1ServicePort(port=target_port, target_port=target_port)]
)
)
else:
service = V1Service(
kind='Service',
metadata=meta,
spec=V1ServiceSpec(
type='ExternalName',
external_name=target_ip,
cluster_ip='',
ports=[V1ServicePort(port=target_port, target_port=target_port)],
),
)
# Make Ingress object
ingress = V1beta1Ingress(
kind='Ingress',
metadata=meta,
spec=V1beta1IngressSpec(
rules=[V1beta1IngressRule(
host=host,
http=V1beta1HTTPIngressRuleValue(
paths=[
V1beta1HTTPIngressPath(
path=path,
backend=V1beta1IngressBackend(
service_name=name,
service_port=target_port
)
)
]
)
)]
)
)
return endpoint, service, ingress | [
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247,042 | jupyterhub/kubespawner | kubespawner/clients.py | shared_client | def shared_client(ClientType, *args, **kwargs):
"""Return a single shared kubernetes client instance
A weak reference to the instance is cached,
so that concurrent calls to shared_client
will all return the same instance until
all references to the client are cleared.
"""
kwarg_key = tuple((key, kwargs[key]) for key in sorted(kwargs))
cache_key = (ClientType, args, kwarg_key)
client = None
if cache_key in _client_cache:
# resolve cached weakref
# client can still be None after this!
client = _client_cache[cache_key]()
if client is None:
Client = getattr(kubernetes.client, ClientType)
client = Client(*args, **kwargs)
# cache weakref so that clients can be garbage collected
_client_cache[cache_key] = weakref.ref(client)
return client | python | def shared_client(ClientType, *args, **kwargs):
kwarg_key = tuple((key, kwargs[key]) for key in sorted(kwargs))
cache_key = (ClientType, args, kwarg_key)
client = None
if cache_key in _client_cache:
# resolve cached weakref
# client can still be None after this!
client = _client_cache[cache_key]()
if client is None:
Client = getattr(kubernetes.client, ClientType)
client = Client(*args, **kwargs)
# cache weakref so that clients can be garbage collected
_client_cache[cache_key] = weakref.ref(client)
return client | [
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247,043 | jupyterhub/kubespawner | kubespawner/utils.py | generate_hashed_slug | def generate_hashed_slug(slug, limit=63, hash_length=6):
"""
Generate a unique name that's within a certain length limit
Most k8s objects have a 63 char name limit. We wanna be able to compress
larger names down to that if required, while still maintaining some
amount of legibility about what the objects really are.
If the length of the slug is shorter than the limit - hash_length, we just
return slug directly. If not, we truncate the slug to (limit - hash_length)
characters, hash the slug and append hash_length characters from the hash
to the end of the truncated slug. This ensures that these names are always
unique no matter what.
"""
if len(slug) < (limit - hash_length):
return slug
slug_hash = hashlib.sha256(slug.encode('utf-8')).hexdigest()
return '{prefix}-{hash}'.format(
prefix=slug[:limit - hash_length - 1],
hash=slug_hash[:hash_length],
).lower() | python | def generate_hashed_slug(slug, limit=63, hash_length=6):
if len(slug) < (limit - hash_length):
return slug
slug_hash = hashlib.sha256(slug.encode('utf-8')).hexdigest()
return '{prefix}-{hash}'.format(
prefix=slug[:limit - hash_length - 1],
hash=slug_hash[:hash_length],
).lower() | [
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247,044 | jupyterhub/kubespawner | kubespawner/utils.py | get_k8s_model | def get_k8s_model(model_type, model_dict):
"""
Returns an instance of type specified model_type from an model instance or
represantative dictionary.
"""
model_dict = copy.deepcopy(model_dict)
if isinstance(model_dict, model_type):
return model_dict
elif isinstance(model_dict, dict):
# convert the dictionaries camelCase keys to snake_case keys
model_dict = _map_dict_keys_to_model_attributes(model_type, model_dict)
# use the dictionary keys to initialize a model of given type
return model_type(**model_dict)
else:
raise AttributeError("Expected object of type 'dict' (or '{}') but got '{}'.".format(model_type.__name__, type(model_dict).__name__)) | python | def get_k8s_model(model_type, model_dict):
model_dict = copy.deepcopy(model_dict)
if isinstance(model_dict, model_type):
return model_dict
elif isinstance(model_dict, dict):
# convert the dictionaries camelCase keys to snake_case keys
model_dict = _map_dict_keys_to_model_attributes(model_type, model_dict)
# use the dictionary keys to initialize a model of given type
return model_type(**model_dict)
else:
raise AttributeError("Expected object of type 'dict' (or '{}') but got '{}'.".format(model_type.__name__, type(model_dict).__name__)) | [
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247,045 | jupyterhub/kubespawner | kubespawner/utils.py | _get_k8s_model_dict | def _get_k8s_model_dict(model_type, model):
"""
Returns a dictionary representation of a provided model type
"""
model = copy.deepcopy(model)
if isinstance(model, model_type):
return model.to_dict()
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else:
raise AttributeError("Expected object of type '{}' (or 'dict') but got '{}'.".format(model_type.__name__, type(model).__name__)) | python | def _get_k8s_model_dict(model_type, model):
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247,046 | jupyterhub/kubespawner | kubespawner/reflector.py | NamespacedResourceReflector._list_and_update | def _list_and_update(self):
"""
Update current list of resources by doing a full fetch.
Overwrites all current resource info.
"""
initial_resources = getattr(self.api, self.list_method_name)(
self.namespace,
label_selector=self.label_selector,
field_selector=self.field_selector,
_request_timeout=self.request_timeout,
)
# This is an atomic operation on the dictionary!
self.resources = {p.metadata.name: p for p in initial_resources.items}
# return the resource version so we can hook up a watch
return initial_resources.metadata.resource_version | python | def _list_and_update(self):
initial_resources = getattr(self.api, self.list_method_name)(
self.namespace,
label_selector=self.label_selector,
field_selector=self.field_selector,
_request_timeout=self.request_timeout,
)
# This is an atomic operation on the dictionary!
self.resources = {p.metadata.name: p for p in initial_resources.items}
# return the resource version so we can hook up a watch
return initial_resources.metadata.resource_version | [
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247,047 | jupyterhub/kubespawner | kubespawner/reflector.py | NamespacedResourceReflector._watch_and_update | def _watch_and_update(self):
"""
Keeps the current list of resources up-to-date
This method is to be run not on the main thread!
We first fetch the list of current resources, and store that. Then we
register to be notified of changes to those resources, and keep our
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We also perform exponential backoff, giving up after we hit 32s
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Note that we're playing a bit with fire here, by updating a dictionary
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without using locks! However, dictionary access itself is atomic,
and as long as we don't try to mutate them (do a 'fetch / modify /
update' cycle on them), we should be ok!
"""
selectors = []
log_name = ""
if self.label_selector:
selectors.append("label selector=%r" % self.label_selector)
if self.field_selector:
selectors.append("field selector=%r" % self.field_selector)
log_selector = ', '.join(selectors)
cur_delay = 0.1
self.log.info(
"watching for %s with %s in namespace %s",
self.kind, log_selector, self.namespace,
)
while True:
self.log.debug("Connecting %s watcher", self.kind)
start = time.monotonic()
w = watch.Watch()
try:
resource_version = self._list_and_update()
if not self.first_load_future.done():
# signal that we've loaded our initial data
self.first_load_future.set_result(None)
watch_args = {
'namespace': self.namespace,
'label_selector': self.label_selector,
'field_selector': self.field_selector,
'resource_version': resource_version,
}
if self.request_timeout:
# set network receive timeout
watch_args['_request_timeout'] = self.request_timeout
if self.timeout_seconds:
# set watch timeout
watch_args['timeout_seconds'] = self.timeout_seconds
# in case of timeout_seconds, the w.stream just exits (no exception thrown)
# -> we stop the watcher and start a new one
for ev in w.stream(
getattr(self.api, self.list_method_name),
**watch_args
):
cur_delay = 0.1
resource = ev['object']
if ev['type'] == 'DELETED':
# This is an atomic delete operation on the dictionary!
self.resources.pop(resource.metadata.name, None)
else:
# This is an atomic operation on the dictionary!
self.resources[resource.metadata.name] = resource
if self._stop_event.is_set():
self.log.info("%s watcher stopped", self.kind)
break
watch_duration = time.monotonic() - start
if watch_duration >= self.restart_seconds:
self.log.debug(
"Restarting %s watcher after %i seconds",
self.kind, watch_duration,
)
break
except ReadTimeoutError:
# network read time out, just continue and restart the watch
# this could be due to a network problem or just low activity
self.log.warning("Read timeout watching %s, reconnecting", self.kind)
continue
except Exception:
cur_delay = cur_delay * 2
if cur_delay > 30:
self.log.exception("Watching resources never recovered, giving up")
if self.on_failure:
self.on_failure()
return
self.log.exception("Error when watching resources, retrying in %ss", cur_delay)
time.sleep(cur_delay)
continue
else:
# no events on watch, reconnect
self.log.debug("%s watcher timeout", self.kind)
finally:
w.stop()
if self._stop_event.is_set():
self.log.info("%s watcher stopped", self.kind)
break
self.log.warning("%s watcher finished", self.kind) | python | def _watch_and_update(self):
selectors = []
log_name = ""
if self.label_selector:
selectors.append("label selector=%r" % self.label_selector)
if self.field_selector:
selectors.append("field selector=%r" % self.field_selector)
log_selector = ', '.join(selectors)
cur_delay = 0.1
self.log.info(
"watching for %s with %s in namespace %s",
self.kind, log_selector, self.namespace,
)
while True:
self.log.debug("Connecting %s watcher", self.kind)
start = time.monotonic()
w = watch.Watch()
try:
resource_version = self._list_and_update()
if not self.first_load_future.done():
# signal that we've loaded our initial data
self.first_load_future.set_result(None)
watch_args = {
'namespace': self.namespace,
'label_selector': self.label_selector,
'field_selector': self.field_selector,
'resource_version': resource_version,
}
if self.request_timeout:
# set network receive timeout
watch_args['_request_timeout'] = self.request_timeout
if self.timeout_seconds:
# set watch timeout
watch_args['timeout_seconds'] = self.timeout_seconds
# in case of timeout_seconds, the w.stream just exits (no exception thrown)
# -> we stop the watcher and start a new one
for ev in w.stream(
getattr(self.api, self.list_method_name),
**watch_args
):
cur_delay = 0.1
resource = ev['object']
if ev['type'] == 'DELETED':
# This is an atomic delete operation on the dictionary!
self.resources.pop(resource.metadata.name, None)
else:
# This is an atomic operation on the dictionary!
self.resources[resource.metadata.name] = resource
if self._stop_event.is_set():
self.log.info("%s watcher stopped", self.kind)
break
watch_duration = time.monotonic() - start
if watch_duration >= self.restart_seconds:
self.log.debug(
"Restarting %s watcher after %i seconds",
self.kind, watch_duration,
)
break
except ReadTimeoutError:
# network read time out, just continue and restart the watch
# this could be due to a network problem or just low activity
self.log.warning("Read timeout watching %s, reconnecting", self.kind)
continue
except Exception:
cur_delay = cur_delay * 2
if cur_delay > 30:
self.log.exception("Watching resources never recovered, giving up")
if self.on_failure:
self.on_failure()
return
self.log.exception("Error when watching resources, retrying in %ss", cur_delay)
time.sleep(cur_delay)
continue
else:
# no events on watch, reconnect
self.log.debug("%s watcher timeout", self.kind)
finally:
w.stop()
if self._stop_event.is_set():
self.log.info("%s watcher stopped", self.kind)
break
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247,048 | jupyterhub/kubespawner | kubespawner/reflector.py | NamespacedResourceReflector.start | def start(self):
"""
Start the reflection process!
We'll do a blocking read of all resources first, so that we don't
race with any operations that are checking the state of the pod
store - such as polls. This should be called only once at the
start of program initialization (when the singleton is being created),
and not afterwards!
"""
if hasattr(self, 'watch_thread'):
raise ValueError('Thread watching for resources is already running')
self._list_and_update()
self.watch_thread = threading.Thread(target=self._watch_and_update)
# If the watch_thread is only thread left alive, exit app
self.watch_thread.daemon = True
self.watch_thread.start() | python | def start(self):
if hasattr(self, 'watch_thread'):
raise ValueError('Thread watching for resources is already running')
self._list_and_update()
self.watch_thread = threading.Thread(target=self._watch_and_update)
# If the watch_thread is only thread left alive, exit app
self.watch_thread.daemon = True
self.watch_thread.start() | [
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247,049 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner.get_pod_manifest | def get_pod_manifest(self):
"""
Make a pod manifest that will spawn current user's notebook pod.
"""
if callable(self.uid):
uid = yield gen.maybe_future(self.uid(self))
else:
uid = self.uid
if callable(self.gid):
gid = yield gen.maybe_future(self.gid(self))
else:
gid = self.gid
if callable(self.fs_gid):
fs_gid = yield gen.maybe_future(self.fs_gid(self))
else:
fs_gid = self.fs_gid
if callable(self.supplemental_gids):
supplemental_gids = yield gen.maybe_future(self.supplemental_gids(self))
else:
supplemental_gids = self.supplemental_gids
if self.cmd:
real_cmd = self.cmd + self.get_args()
else:
real_cmd = None
labels = self._build_pod_labels(self._expand_all(self.extra_labels))
annotations = self._build_common_annotations(self._expand_all(self.extra_annotations))
return make_pod(
name=self.pod_name,
cmd=real_cmd,
port=self.port,
image=self.image,
image_pull_policy=self.image_pull_policy,
image_pull_secret=self.image_pull_secrets,
node_selector=self.node_selector,
run_as_uid=uid,
run_as_gid=gid,
fs_gid=fs_gid,
supplemental_gids=supplemental_gids,
run_privileged=self.privileged,
env=self.get_env(),
volumes=self._expand_all(self.volumes),
volume_mounts=self._expand_all(self.volume_mounts),
working_dir=self.working_dir,
labels=labels,
annotations=annotations,
cpu_limit=self.cpu_limit,
cpu_guarantee=self.cpu_guarantee,
mem_limit=self.mem_limit,
mem_guarantee=self.mem_guarantee,
extra_resource_limits=self.extra_resource_limits,
extra_resource_guarantees=self.extra_resource_guarantees,
lifecycle_hooks=self.lifecycle_hooks,
init_containers=self._expand_all(self.init_containers),
service_account=self.service_account,
extra_container_config=self.extra_container_config,
extra_pod_config=self.extra_pod_config,
extra_containers=self._expand_all(self.extra_containers),
scheduler_name=self.scheduler_name,
tolerations=self.tolerations,
node_affinity_preferred=self.node_affinity_preferred,
node_affinity_required=self.node_affinity_required,
pod_affinity_preferred=self.pod_affinity_preferred,
pod_affinity_required=self.pod_affinity_required,
pod_anti_affinity_preferred=self.pod_anti_affinity_preferred,
pod_anti_affinity_required=self.pod_anti_affinity_required,
priority_class_name=self.priority_class_name,
logger=self.log,
) | python | def get_pod_manifest(self):
if callable(self.uid):
uid = yield gen.maybe_future(self.uid(self))
else:
uid = self.uid
if callable(self.gid):
gid = yield gen.maybe_future(self.gid(self))
else:
gid = self.gid
if callable(self.fs_gid):
fs_gid = yield gen.maybe_future(self.fs_gid(self))
else:
fs_gid = self.fs_gid
if callable(self.supplemental_gids):
supplemental_gids = yield gen.maybe_future(self.supplemental_gids(self))
else:
supplemental_gids = self.supplemental_gids
if self.cmd:
real_cmd = self.cmd + self.get_args()
else:
real_cmd = None
labels = self._build_pod_labels(self._expand_all(self.extra_labels))
annotations = self._build_common_annotations(self._expand_all(self.extra_annotations))
return make_pod(
name=self.pod_name,
cmd=real_cmd,
port=self.port,
image=self.image,
image_pull_policy=self.image_pull_policy,
image_pull_secret=self.image_pull_secrets,
node_selector=self.node_selector,
run_as_uid=uid,
run_as_gid=gid,
fs_gid=fs_gid,
supplemental_gids=supplemental_gids,
run_privileged=self.privileged,
env=self.get_env(),
volumes=self._expand_all(self.volumes),
volume_mounts=self._expand_all(self.volume_mounts),
working_dir=self.working_dir,
labels=labels,
annotations=annotations,
cpu_limit=self.cpu_limit,
cpu_guarantee=self.cpu_guarantee,
mem_limit=self.mem_limit,
mem_guarantee=self.mem_guarantee,
extra_resource_limits=self.extra_resource_limits,
extra_resource_guarantees=self.extra_resource_guarantees,
lifecycle_hooks=self.lifecycle_hooks,
init_containers=self._expand_all(self.init_containers),
service_account=self.service_account,
extra_container_config=self.extra_container_config,
extra_pod_config=self.extra_pod_config,
extra_containers=self._expand_all(self.extra_containers),
scheduler_name=self.scheduler_name,
tolerations=self.tolerations,
node_affinity_preferred=self.node_affinity_preferred,
node_affinity_required=self.node_affinity_required,
pod_affinity_preferred=self.pod_affinity_preferred,
pod_affinity_required=self.pod_affinity_required,
pod_anti_affinity_preferred=self.pod_anti_affinity_preferred,
pod_anti_affinity_required=self.pod_anti_affinity_required,
priority_class_name=self.priority_class_name,
logger=self.log,
) | [
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247,050 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner.get_pvc_manifest | def get_pvc_manifest(self):
"""
Make a pvc manifest that will spawn current user's pvc.
"""
labels = self._build_common_labels(self._expand_all(self.storage_extra_labels))
labels.update({
'component': 'singleuser-storage'
})
annotations = self._build_common_annotations({})
return make_pvc(
name=self.pvc_name,
storage_class=self.storage_class,
access_modes=self.storage_access_modes,
storage=self.storage_capacity,
labels=labels,
annotations=annotations
) | python | def get_pvc_manifest(self):
labels = self._build_common_labels(self._expand_all(self.storage_extra_labels))
labels.update({
'component': 'singleuser-storage'
})
annotations = self._build_common_annotations({})
return make_pvc(
name=self.pvc_name,
storage_class=self.storage_class,
access_modes=self.storage_access_modes,
storage=self.storage_capacity,
labels=labels,
annotations=annotations
) | [
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247,051 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner.is_pod_running | def is_pod_running(self, pod):
"""
Check if the given pod is running
pod must be a dictionary representing a Pod kubernetes API object.
"""
# FIXME: Validate if this is really the best way
is_running = (
pod is not None and
pod.status.phase == 'Running' and
pod.status.pod_ip is not None and
pod.metadata.deletion_timestamp is None and
all([cs.ready for cs in pod.status.container_statuses])
)
return is_running | python | def is_pod_running(self, pod):
# FIXME: Validate if this is really the best way
is_running = (
pod is not None and
pod.status.phase == 'Running' and
pod.status.pod_ip is not None and
pod.metadata.deletion_timestamp is None and
all([cs.ready for cs in pod.status.container_statuses])
)
return is_running | [
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247,052 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner.get_env | def get_env(self):
"""Return the environment dict to use for the Spawner.
See also: jupyterhub.Spawner.get_env
"""
env = super(KubeSpawner, self).get_env()
# deprecate image
env['JUPYTER_IMAGE_SPEC'] = self.image
env['JUPYTER_IMAGE'] = self.image
return env | python | def get_env(self):
env = super(KubeSpawner, self).get_env()
# deprecate image
env['JUPYTER_IMAGE_SPEC'] = self.image
env['JUPYTER_IMAGE'] = self.image
return env | [
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247,053 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner.poll | def poll(self):
"""
Check if the pod is still running.
Uses the same interface as subprocess.Popen.poll(): if the pod is
still running, returns None. If the pod has exited, return the
exit code if we can determine it, or 1 if it has exited but we
don't know how. These are the return values JupyterHub expects.
Note that a clean exit will have an exit code of zero, so it is
necessary to check that the returned value is None, rather than
just Falsy, to determine that the pod is still running.
"""
# have to wait for first load of data before we have a valid answer
if not self.pod_reflector.first_load_future.done():
yield self.pod_reflector.first_load_future
data = self.pod_reflector.pods.get(self.pod_name, None)
if data is not None:
if data.status.phase == 'Pending':
return None
ctr_stat = data.status.container_statuses
if ctr_stat is None: # No status, no container (we hope)
# This seems to happen when a pod is idle-culled.
return 1
for c in ctr_stat:
# return exit code if notebook container has terminated
if c.name == 'notebook':
if c.state.terminated:
# call self.stop to delete the pod
if self.delete_stopped_pods:
yield self.stop(now=True)
return c.state.terminated.exit_code
break
# None means pod is running or starting up
return None
# pod doesn't exist or has been deleted
return 1 | python | def poll(self):
# have to wait for first load of data before we have a valid answer
if not self.pod_reflector.first_load_future.done():
yield self.pod_reflector.first_load_future
data = self.pod_reflector.pods.get(self.pod_name, None)
if data is not None:
if data.status.phase == 'Pending':
return None
ctr_stat = data.status.container_statuses
if ctr_stat is None: # No status, no container (we hope)
# This seems to happen when a pod is idle-culled.
return 1
for c in ctr_stat:
# return exit code if notebook container has terminated
if c.name == 'notebook':
if c.state.terminated:
# call self.stop to delete the pod
if self.delete_stopped_pods:
yield self.stop(now=True)
return c.state.terminated.exit_code
break
# None means pod is running or starting up
return None
# pod doesn't exist or has been deleted
return 1 | [
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247,054 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner.events | def events(self):
"""Filter event-reflector to just our events
Returns list of all events that match our pod_name
since our ._last_event (if defined).
._last_event is set at the beginning of .start().
"""
if not self.event_reflector:
return []
events = []
for event in self.event_reflector.events:
if event.involved_object.name != self.pod_name:
# only consider events for my pod name
continue
if self._last_event and event.metadata.uid == self._last_event:
# saw last_event marker, ignore any previous events
# and only consider future events
# only include events *after* our _last_event marker
events = []
else:
events.append(event)
return events | python | def events(self):
if not self.event_reflector:
return []
events = []
for event in self.event_reflector.events:
if event.involved_object.name != self.pod_name:
# only consider events for my pod name
continue
if self._last_event and event.metadata.uid == self._last_event:
# saw last_event marker, ignore any previous events
# and only consider future events
# only include events *after* our _last_event marker
events = []
else:
events.append(event)
return events | [
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247,055 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner._start_reflector | def _start_reflector(self, key, ReflectorClass, replace=False, **kwargs):
"""Start a shared reflector on the KubeSpawner class
key: key for the reflector (e.g. 'pod' or 'events')
Reflector: Reflector class to be instantiated
kwargs: extra keyword-args to be relayed to ReflectorClass
If replace=False and the pod reflector is already running,
do nothing.
If replace=True, a running pod reflector will be stopped
and a new one started (for recovering from possible errors).
"""
main_loop = IOLoop.current()
def on_reflector_failure():
self.log.critical(
"%s reflector failed, halting Hub.",
key.title(),
)
sys.exit(1)
previous_reflector = self.__class__.reflectors.get(key)
if replace or not previous_reflector:
self.__class__.reflectors[key] = ReflectorClass(
parent=self,
namespace=self.namespace,
on_failure=on_reflector_failure,
**kwargs,
)
if replace and previous_reflector:
# we replaced the reflector, stop the old one
previous_reflector.stop()
# return the current reflector
return self.__class__.reflectors[key] | python | def _start_reflector(self, key, ReflectorClass, replace=False, **kwargs):
main_loop = IOLoop.current()
def on_reflector_failure():
self.log.critical(
"%s reflector failed, halting Hub.",
key.title(),
)
sys.exit(1)
previous_reflector = self.__class__.reflectors.get(key)
if replace or not previous_reflector:
self.__class__.reflectors[key] = ReflectorClass(
parent=self,
namespace=self.namespace,
on_failure=on_reflector_failure,
**kwargs,
)
if replace and previous_reflector:
# we replaced the reflector, stop the old one
previous_reflector.stop()
# return the current reflector
return self.__class__.reflectors[key] | [
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247,056 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner._start_watching_events | def _start_watching_events(self, replace=False):
"""Start the events reflector
If replace=False and the event reflector is already running,
do nothing.
If replace=True, a running pod reflector will be stopped
and a new one started (for recovering from possible errors).
"""
return self._start_reflector(
"events",
EventReflector,
fields={"involvedObject.kind": "Pod"},
replace=replace,
) | python | def _start_watching_events(self, replace=False):
return self._start_reflector(
"events",
EventReflector,
fields={"involvedObject.kind": "Pod"},
replace=replace,
) | [
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247,057 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner._options_form_default | def _options_form_default(self):
'''
Build the form template according to the `profile_list` setting.
Returns:
'' when no `profile_list` has been defined
The rendered template (using jinja2) when `profile_list` is defined.
'''
if not self.profile_list:
return ''
if callable(self.profile_list):
return self._render_options_form_dynamically
else:
return self._render_options_form(self.profile_list) | python | def _options_form_default(self):
'''
Build the form template according to the `profile_list` setting.
Returns:
'' when no `profile_list` has been defined
The rendered template (using jinja2) when `profile_list` is defined.
'''
if not self.profile_list:
return ''
if callable(self.profile_list):
return self._render_options_form_dynamically
else:
return self._render_options_form(self.profile_list) | [
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247,058 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner.options_from_form | def options_from_form(self, formdata):
"""get the option selected by the user on the form
This only constructs the user_options dict,
it should not actually load any options.
That is done later in `.load_user_options()`
Args:
formdata: user selection returned by the form
To access to the value, you can use the `get` accessor and the name of the html element,
for example::
formdata.get('profile',[0])
to get the value of the form named "profile", as defined in `form_template`::
<select class="form-control" name="profile"...>
</select>
Returns:
user_options (dict): the selected profile in the user_options form,
e.g. ``{"profile": "8 CPUs"}``
"""
if not self.profile_list or self._profile_list is None:
return formdata
# Default to first profile if somehow none is provided
try:
selected_profile = int(formdata.get('profile', [0])[0])
options = self._profile_list[selected_profile]
except (TypeError, IndexError, ValueError):
raise web.HTTPError(400, "No such profile: %i", formdata.get('profile', None))
return {
'profile': options['display_name']
} | python | def options_from_form(self, formdata):
if not self.profile_list or self._profile_list is None:
return formdata
# Default to first profile if somehow none is provided
try:
selected_profile = int(formdata.get('profile', [0])[0])
options = self._profile_list[selected_profile]
except (TypeError, IndexError, ValueError):
raise web.HTTPError(400, "No such profile: %i", formdata.get('profile', None))
return {
'profile': options['display_name']
} | [
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<select class="form-control" name="profile"...>
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247,059 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner._load_profile | def _load_profile(self, profile_name):
"""Load a profile by name
Called by load_user_options
"""
# find the profile
default_profile = self._profile_list[0]
for profile in self._profile_list:
if profile.get('default', False):
# explicit default, not the first
default_profile = profile
if profile['display_name'] == profile_name:
break
else:
if profile_name:
# name specified, but not found
raise ValueError("No such profile: %s. Options include: %s" % (
profile_name, ', '.join(p['display_name'] for p in self._profile_list)
))
else:
# no name specified, use the default
profile = default_profile
self.log.debug("Applying KubeSpawner override for profile '%s'", profile['display_name'])
kubespawner_override = profile.get('kubespawner_override', {})
for k, v in kubespawner_override.items():
if callable(v):
v = v(self)
self.log.debug(".. overriding KubeSpawner value %s=%s (callable result)", k, v)
else:
self.log.debug(".. overriding KubeSpawner value %s=%s", k, v)
setattr(self, k, v) | python | def _load_profile(self, profile_name):
# find the profile
default_profile = self._profile_list[0]
for profile in self._profile_list:
if profile.get('default', False):
# explicit default, not the first
default_profile = profile
if profile['display_name'] == profile_name:
break
else:
if profile_name:
# name specified, but not found
raise ValueError("No such profile: %s. Options include: %s" % (
profile_name, ', '.join(p['display_name'] for p in self._profile_list)
))
else:
# no name specified, use the default
profile = default_profile
self.log.debug("Applying KubeSpawner override for profile '%s'", profile['display_name'])
kubespawner_override = profile.get('kubespawner_override', {})
for k, v in kubespawner_override.items():
if callable(v):
v = v(self)
self.log.debug(".. overriding KubeSpawner value %s=%s (callable result)", k, v)
else:
self.log.debug(".. overriding KubeSpawner value %s=%s", k, v)
setattr(self, k, v) | [
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247,060 | jupyterhub/kubespawner | kubespawner/spawner.py | KubeSpawner.load_user_options | def load_user_options(self):
"""Load user options from self.user_options dict
This can be set via POST to the API or via options_from_form
Only supported argument by default is 'profile'.
Override in subclasses to support other options.
"""
if self._profile_list is None:
if callable(self.profile_list):
self._profile_list = yield gen.maybe_future(self.profile_list(self))
else:
self._profile_list = self.profile_list
if self._profile_list:
yield self._load_profile(self.user_options.get('profile', None)) | python | def load_user_options(self):
if self._profile_list is None:
if callable(self.profile_list):
self._profile_list = yield gen.maybe_future(self.profile_list(self))
else:
self._profile_list = self.profile_list
if self._profile_list:
yield self._load_profile(self.user_options.get('profile', None)) | [
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247,061 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | list_motors | def list_motors(name_pattern=Motor.SYSTEM_DEVICE_NAME_CONVENTION, **kwargs):
"""
This is a generator function that enumerates all tacho motors that match
the provided arguments.
Parameters:
name_pattern: pattern that device name should match.
For example, 'motor*'. Default value: '*'.
keyword arguments: used for matching the corresponding device
attributes. For example, driver_name='lego-ev3-l-motor', or
address=['outB', 'outC']. When argument value
is a list, then a match against any entry of the list is
enough.
"""
class_path = abspath(Device.DEVICE_ROOT_PATH + '/' + Motor.SYSTEM_CLASS_NAME)
return (Motor(name_pattern=name, name_exact=True)
for name in list_device_names(class_path, name_pattern, **kwargs)) | python | def list_motors(name_pattern=Motor.SYSTEM_DEVICE_NAME_CONVENTION, **kwargs):
class_path = abspath(Device.DEVICE_ROOT_PATH + '/' + Motor.SYSTEM_CLASS_NAME)
return (Motor(name_pattern=name, name_exact=True)
for name in list_device_names(class_path, name_pattern, **kwargs)) | [
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247,062 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | SpeedRPS.to_native_units | def to_native_units(self, motor):
"""
Return the native speed measurement required to achieve desired rotations-per-second
"""
assert abs(self.rotations_per_second) <= motor.max_rps,\
"invalid rotations-per-second: {} max RPS is {}, {} was requested".format(
motor, motor.max_rps, self.rotations_per_second)
return self.rotations_per_second/motor.max_rps * motor.max_speed | python | def to_native_units(self, motor):
assert abs(self.rotations_per_second) <= motor.max_rps,\
"invalid rotations-per-second: {} max RPS is {}, {} was requested".format(
motor, motor.max_rps, self.rotations_per_second)
return self.rotations_per_second/motor.max_rps * motor.max_speed | [
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247,063 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | SpeedRPM.to_native_units | def to_native_units(self, motor):
"""
Return the native speed measurement required to achieve desired rotations-per-minute
"""
assert abs(self.rotations_per_minute) <= motor.max_rpm,\
"invalid rotations-per-minute: {} max RPM is {}, {} was requested".format(
motor, motor.max_rpm, self.rotations_per_minute)
return self.rotations_per_minute/motor.max_rpm * motor.max_speed | python | def to_native_units(self, motor):
assert abs(self.rotations_per_minute) <= motor.max_rpm,\
"invalid rotations-per-minute: {} max RPM is {}, {} was requested".format(
motor, motor.max_rpm, self.rotations_per_minute)
return self.rotations_per_minute/motor.max_rpm * motor.max_speed | [
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247,064 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | SpeedDPS.to_native_units | def to_native_units(self, motor):
"""
Return the native speed measurement required to achieve desired degrees-per-second
"""
assert abs(self.degrees_per_second) <= motor.max_dps,\
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motor, motor.max_dps, self.degrees_per_second)
return self.degrees_per_second/motor.max_dps * motor.max_speed | python | def to_native_units(self, motor):
assert abs(self.degrees_per_second) <= motor.max_dps,\
"invalid degrees-per-second: {} max DPS is {}, {} was requested".format(
motor, motor.max_dps, self.degrees_per_second)
return self.degrees_per_second/motor.max_dps * motor.max_speed | [
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247,065 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | SpeedDPM.to_native_units | def to_native_units(self, motor):
"""
Return the native speed measurement required to achieve desired degrees-per-minute
"""
assert abs(self.degrees_per_minute) <= motor.max_dpm,\
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motor, motor.max_dpm, self.degrees_per_minute)
return self.degrees_per_minute/motor.max_dpm * motor.max_speed | python | def to_native_units(self, motor):
assert abs(self.degrees_per_minute) <= motor.max_dpm,\
"invalid degrees-per-minute: {} max DPM is {}, {} was requested".format(
motor, motor.max_dpm, self.degrees_per_minute)
return self.degrees_per_minute/motor.max_dpm * motor.max_speed | [
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247,066 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.address | def address(self):
"""
Returns the name of the port that this motor is connected to.
"""
self._address, value = self.get_attr_string(self._address, 'address')
return value | python | def address(self):
self._address, value = self.get_attr_string(self._address, 'address')
return value | [
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247,067 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.commands | def commands(self):
"""
Returns a list of commands that are supported by the motor
controller. Possible values are `run-forever`, `run-to-abs-pos`, `run-to-rel-pos`,
`run-timed`, `run-direct`, `stop` and `reset`. Not all commands may be supported.
- `run-forever` will cause the motor to run until another command is sent.
- `run-to-abs-pos` will run to an absolute position specified by `position_sp`
and then stop using the action specified in `stop_action`.
- `run-to-rel-pos` will run to a position relative to the current `position` value.
The new position will be current `position` + `position_sp`. When the new
position is reached, the motor will stop using the action specified by `stop_action`.
- `run-timed` will run the motor for the amount of time specified in `time_sp`
and then stop the motor using the action specified by `stop_action`.
- `run-direct` will run the motor at the duty cycle specified by `duty_cycle_sp`.
Unlike other run commands, changing `duty_cycle_sp` while running *will*
take effect immediately.
- `stop` will stop any of the run commands before they are complete using the
action specified by `stop_action`.
- `reset` will reset all of the motor parameter attributes to their default value.
This will also have the effect of stopping the motor.
"""
(self._commands, value) = self.get_cached_attr_set(self._commands, 'commands')
return value | python | def commands(self):
(self._commands, value) = self.get_cached_attr_set(self._commands, 'commands')
return value | [
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247,068 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.driver_name | def driver_name(self):
"""
Returns the name of the driver that provides this tacho motor device.
"""
(self._driver_name, value) = self.get_cached_attr_string(self._driver_name, 'driver_name')
return value | python | def driver_name(self):
(self._driver_name, value) = self.get_cached_attr_string(self._driver_name, 'driver_name')
return value | [
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247,069 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.duty_cycle | def duty_cycle(self):
"""
Returns the current duty cycle of the motor. Units are percent. Values
are -100 to 100.
"""
self._duty_cycle, value = self.get_attr_int(self._duty_cycle, 'duty_cycle')
return value | python | def duty_cycle(self):
self._duty_cycle, value = self.get_attr_int(self._duty_cycle, 'duty_cycle')
return value | [
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247,070 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.duty_cycle_sp | def duty_cycle_sp(self):
"""
Writing sets the duty cycle setpoint. Reading returns the current value.
Units are in percent. Valid values are -100 to 100. A negative value causes
the motor to rotate in reverse.
"""
self._duty_cycle_sp, value = self.get_attr_int(self._duty_cycle_sp, 'duty_cycle_sp')
return value | python | def duty_cycle_sp(self):
self._duty_cycle_sp, value = self.get_attr_int(self._duty_cycle_sp, 'duty_cycle_sp')
return value | [
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247,071 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.polarity | def polarity(self):
"""
Sets the polarity of the motor. With `normal` polarity, a positive duty
cycle will cause the motor to rotate clockwise. With `inversed` polarity,
a positive duty cycle will cause the motor to rotate counter-clockwise.
Valid values are `normal` and `inversed`.
"""
self._polarity, value = self.get_attr_string(self._polarity, 'polarity')
return value | python | def polarity(self):
self._polarity, value = self.get_attr_string(self._polarity, 'polarity')
return value | [
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] | afc98d35004b533dc161a01f7c966e78607d7c1e | https://github.com/ev3dev/ev3dev-lang-python/blob/afc98d35004b533dc161a01f7c966e78607d7c1e/ev3dev2/motor.py#L510-L518 |
247,072 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.position | def position(self):
"""
Returns the current position of the motor in pulses of the rotary
encoder. When the motor rotates clockwise, the position will increase.
Likewise, rotating counter-clockwise causes the position to decrease.
Writing will set the position to that value.
"""
self._position, value = self.get_attr_int(self._position, 'position')
return value | python | def position(self):
self._position, value = self.get_attr_int(self._position, 'position')
return value | [
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247,073 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.position_p | def position_p(self):
"""
The proportional constant for the position PID.
"""
self._position_p, value = self.get_attr_int(self._position_p, 'hold_pid/Kp')
return value | python | def position_p(self):
self._position_p, value = self.get_attr_int(self._position_p, 'hold_pid/Kp')
return value | [
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247,074 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.position_i | def position_i(self):
"""
The integral constant for the position PID.
"""
self._position_i, value = self.get_attr_int(self._position_i, 'hold_pid/Ki')
return value | python | def position_i(self):
self._position_i, value = self.get_attr_int(self._position_i, 'hold_pid/Ki')
return value | [
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247,075 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.position_d | def position_d(self):
"""
The derivative constant for the position PID.
"""
self._position_d, value = self.get_attr_int(self._position_d, 'hold_pid/Kd')
return value | python | def position_d(self):
self._position_d, value = self.get_attr_int(self._position_d, 'hold_pid/Kd')
return value | [
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247,076 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.max_speed | def max_speed(self):
"""
Returns the maximum value that is accepted by the `speed_sp` attribute. This
may be slightly different than the maximum speed that a particular motor can
reach - it's the maximum theoretical speed.
"""
(self._max_speed, value) = self.get_cached_attr_int(self._max_speed, 'max_speed')
return value | python | def max_speed(self):
(self._max_speed, value) = self.get_cached_attr_int(self._max_speed, 'max_speed')
return value | [
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247,077 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.ramp_up_sp | def ramp_up_sp(self):
"""
Writing sets the ramp up setpoint. Reading returns the current value. Units
are in milliseconds and must be positive. When set to a non-zero value, the
motor speed will increase from 0 to 100% of `max_speed` over the span of this
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`speed_sp` and the current `speed` and max_speed multiplied by `ramp_up_sp`.
"""
self._ramp_up_sp, value = self.get_attr_int(self._ramp_up_sp, 'ramp_up_sp')
return value | python | def ramp_up_sp(self):
self._ramp_up_sp, value = self.get_attr_int(self._ramp_up_sp, 'ramp_up_sp')
return value | [
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247,078 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.ramp_down_sp | def ramp_down_sp(self):
"""
Writing sets the ramp down setpoint. Reading returns the current value. Units
are in milliseconds and must be positive. When set to a non-zero value, the
motor speed will decrease from 0 to 100% of `max_speed` over the span of this
setpoint. The actual ramp time is the ratio of the difference between the
`speed_sp` and the current `speed` and max_speed multiplied by `ramp_down_sp`.
"""
self._ramp_down_sp, value = self.get_attr_int(self._ramp_down_sp, 'ramp_down_sp')
return value | python | def ramp_down_sp(self):
self._ramp_down_sp, value = self.get_attr_int(self._ramp_down_sp, 'ramp_down_sp')
return value | [
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247,079 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.speed_p | def speed_p(self):
"""
The proportional constant for the speed regulation PID.
"""
self._speed_p, value = self.get_attr_int(self._speed_p, 'speed_pid/Kp')
return value | python | def speed_p(self):
self._speed_p, value = self.get_attr_int(self._speed_p, 'speed_pid/Kp')
return value | [
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247,080 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.speed_i | def speed_i(self):
"""
The integral constant for the speed regulation PID.
"""
self._speed_i, value = self.get_attr_int(self._speed_i, 'speed_pid/Ki')
return value | python | def speed_i(self):
self._speed_i, value = self.get_attr_int(self._speed_i, 'speed_pid/Ki')
return value | [
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247,081 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.speed_d | def speed_d(self):
"""
The derivative constant for the speed regulation PID.
"""
self._speed_d, value = self.get_attr_int(self._speed_d, 'speed_pid/Kd')
return value | python | def speed_d(self):
self._speed_d, value = self.get_attr_int(self._speed_d, 'speed_pid/Kd')
return value | [
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247,082 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.state | def state(self):
"""
Reading returns a list of state flags. Possible flags are
`running`, `ramping`, `holding`, `overloaded` and `stalled`.
"""
self._state, value = self.get_attr_set(self._state, 'state')
return value | python | def state(self):
self._state, value = self.get_attr_set(self._state, 'state')
return value | [
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247,083 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.stop_action | def stop_action(self):
"""
Reading returns the current stop action. Writing sets the stop action.
The value determines the motors behavior when `command` is set to `stop`.
Also, it determines the motors behavior when a run command completes. See
`stop_actions` for a list of possible values.
"""
self._stop_action, value = self.get_attr_string(self._stop_action, 'stop_action')
return value | python | def stop_action(self):
self._stop_action, value = self.get_attr_string(self._stop_action, 'stop_action')
return value | [
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247,084 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.stop_actions | def stop_actions(self):
"""
Returns a list of stop actions supported by the motor controller.
Possible values are `coast`, `brake` and `hold`. `coast` means that power will
be removed from the motor and it will freely coast to a stop. `brake` means
that power will be removed from the motor and a passive electrical load will
be placed on the motor. This is usually done by shorting the motor terminals
together. This load will absorb the energy from the rotation of the motors and
cause the motor to stop more quickly than coasting. `hold` does not remove
power from the motor. Instead it actively tries to hold the motor at the current
position. If an external force tries to turn the motor, the motor will 'push
back' to maintain its position.
"""
(self._stop_actions, value) = self.get_cached_attr_set(self._stop_actions, 'stop_actions')
return value | python | def stop_actions(self):
(self._stop_actions, value) = self.get_cached_attr_set(self._stop_actions, 'stop_actions')
return value | [
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247,085 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.time_sp | def time_sp(self):
"""
Writing specifies the amount of time the motor will run when using the
`run-timed` command. Reading returns the current value. Units are in
milliseconds.
"""
self._time_sp, value = self.get_attr_int(self._time_sp, 'time_sp')
return value | python | def time_sp(self):
self._time_sp, value = self.get_attr_int(self._time_sp, 'time_sp')
return value | [
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247,086 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.run_forever | def run_forever(self, **kwargs):
"""
Run the motor until another command is sent.
"""
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RUN_FOREVER | python | def run_forever(self, **kwargs):
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RUN_FOREVER | [
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247,087 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.run_to_abs_pos | def run_to_abs_pos(self, **kwargs):
"""
Run to an absolute position specified by `position_sp` and then
stop using the action specified in `stop_action`.
"""
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RUN_TO_ABS_POS | python | def run_to_abs_pos(self, **kwargs):
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RUN_TO_ABS_POS | [
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247,088 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.run_to_rel_pos | def run_to_rel_pos(self, **kwargs):
"""
Run to a position relative to the current `position` value.
The new position will be current `position` + `position_sp`.
When the new position is reached, the motor will stop using
the action specified by `stop_action`.
"""
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RUN_TO_REL_POS | python | def run_to_rel_pos(self, **kwargs):
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RUN_TO_REL_POS | [
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247,089 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.run_timed | def run_timed(self, **kwargs):
"""
Run the motor for the amount of time specified in `time_sp`
and then stop the motor using the action specified by `stop_action`.
"""
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RUN_TIMED | python | def run_timed(self, **kwargs):
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RUN_TIMED | [
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247,090 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.stop | def stop(self, **kwargs):
"""
Stop any of the run commands before they are complete using the
action specified by `stop_action`.
"""
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_STOP | python | def stop(self, **kwargs):
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_STOP | [
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247,091 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.reset | def reset(self, **kwargs):
"""
Reset all of the motor parameter attributes to their default value.
This will also have the effect of stopping the motor.
"""
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RESET | python | def reset(self, **kwargs):
for key in kwargs:
setattr(self, key, kwargs[key])
self.command = self.COMMAND_RESET | [
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247,092 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.on_for_rotations | def on_for_rotations(self, speed, rotations, brake=True, block=True):
"""
Rotate the motor at ``speed`` for ``rotations``
``speed`` can be a percentage or a :class:`ev3dev2.motor.SpeedValue`
object, enabling use of other units.
"""
speed_sp = self._speed_native_units(speed)
self._set_rel_position_degrees_and_speed_sp(rotations * 360, speed_sp)
self._set_brake(brake)
self.run_to_rel_pos()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | python | def on_for_rotations(self, speed, rotations, brake=True, block=True):
speed_sp = self._speed_native_units(speed)
self._set_rel_position_degrees_and_speed_sp(rotations * 360, speed_sp)
self._set_brake(brake)
self.run_to_rel_pos()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | [
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247,093 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.on_for_degrees | def on_for_degrees(self, speed, degrees, brake=True, block=True):
"""
Rotate the motor at ``speed`` for ``degrees``
``speed`` can be a percentage or a :class:`ev3dev2.motor.SpeedValue`
object, enabling use of other units.
"""
speed_sp = self._speed_native_units(speed)
self._set_rel_position_degrees_and_speed_sp(degrees, speed_sp)
self._set_brake(brake)
self.run_to_rel_pos()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | python | def on_for_degrees(self, speed, degrees, brake=True, block=True):
speed_sp = self._speed_native_units(speed)
self._set_rel_position_degrees_and_speed_sp(degrees, speed_sp)
self._set_brake(brake)
self.run_to_rel_pos()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | [
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247,094 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.on_to_position | def on_to_position(self, speed, position, brake=True, block=True):
"""
Rotate the motor at ``speed`` to ``position``
``speed`` can be a percentage or a :class:`ev3dev2.motor.SpeedValue`
object, enabling use of other units.
"""
speed = self._speed_native_units(speed)
self.speed_sp = int(round(speed))
self.position_sp = position
self._set_brake(brake)
self.run_to_abs_pos()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | python | def on_to_position(self, speed, position, brake=True, block=True):
speed = self._speed_native_units(speed)
self.speed_sp = int(round(speed))
self.position_sp = position
self._set_brake(brake)
self.run_to_abs_pos()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
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247,095 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.on_for_seconds | def on_for_seconds(self, speed, seconds, brake=True, block=True):
"""
Rotate the motor at ``speed`` for ``seconds``
``speed`` can be a percentage or a :class:`ev3dev2.motor.SpeedValue`
object, enabling use of other units.
"""
if seconds < 0:
raise ValueError("seconds is negative ({})".format(seconds))
speed = self._speed_native_units(speed)
self.speed_sp = int(round(speed))
self.time_sp = int(seconds * 1000)
self._set_brake(brake)
self.run_timed()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | python | def on_for_seconds(self, speed, seconds, brake=True, block=True):
if seconds < 0:
raise ValueError("seconds is negative ({})".format(seconds))
speed = self._speed_native_units(speed)
self.speed_sp = int(round(speed))
self.time_sp = int(seconds * 1000)
self._set_brake(brake)
self.run_timed()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | [
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247,096 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | Motor.on | def on(self, speed, brake=True, block=False):
"""
Rotate the motor at ``speed`` for forever
``speed`` can be a percentage or a :class:`ev3dev2.motor.SpeedValue`
object, enabling use of other units.
Note that `block` is False by default, this is different from the
other `on_for_XYZ` methods.
"""
speed = self._speed_native_units(speed)
self.speed_sp = int(round(speed))
self._set_brake(brake)
self.run_forever()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | python | def on(self, speed, brake=True, block=False):
speed = self._speed_native_units(speed)
self.speed_sp = int(round(speed))
self._set_brake(brake)
self.run_forever()
if block:
self.wait_until('running', timeout=WAIT_RUNNING_TIMEOUT)
self.wait_until_not_moving() | [
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] | Rotate the motor at ``speed`` for forever
``speed`` can be a percentage or a :class:`ev3dev2.motor.SpeedValue`
object, enabling use of other units.
Note that `block` is False by default, this is different from the
other `on_for_XYZ` methods. | [
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] | afc98d35004b533dc161a01f7c966e78607d7c1e | https://github.com/ev3dev/ev3dev-lang-python/blob/afc98d35004b533dc161a01f7c966e78607d7c1e/ev3dev2/motor.py#L1028-L1045 |
247,097 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | DcMotor.commands | def commands(self):
"""
Returns a list of commands supported by the motor
controller.
"""
self._commands, value = self.get_attr_set(self._commands, 'commands')
return value | python | def commands(self):
self._commands, value = self.get_attr_set(self._commands, 'commands')
return value | [
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247,098 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | DcMotor.stop_actions | def stop_actions(self):
"""
Gets a list of stop actions. Valid values are `coast`
and `brake`.
"""
self._stop_actions, value = self.get_attr_set(self._stop_actions, 'stop_actions')
return value | python | def stop_actions(self):
self._stop_actions, value = self.get_attr_set(self._stop_actions, 'stop_actions')
return value | [
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247,099 | ev3dev/ev3dev-lang-python | ev3dev2/motor.py | ServoMotor.mid_pulse_sp | def mid_pulse_sp(self):
"""
Used to set the pulse size in milliseconds for the signal that tells the
servo to drive to the mid position_sp. Default value is 1500. Valid
values are 1300 to 1700. For example, on a 180 degree servo, this would be
90 degrees. On continuous rotation servo, this is the 'neutral' position_sp
where the motor does not turn. You must write to the position_sp attribute for
changes to this attribute to take effect.
"""
self._mid_pulse_sp, value = self.get_attr_int(self._mid_pulse_sp, 'mid_pulse_sp')
return value | python | def mid_pulse_sp(self):
self._mid_pulse_sp, value = self.get_attr_int(self._mid_pulse_sp, 'mid_pulse_sp')
return value | [
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servo to drive to the mid position_sp. Default value is 1500. Valid
values are 1300 to 1700. For example, on a 180 degree servo, this would be
90 degrees. On continuous rotation servo, this is the 'neutral' position_sp
where the motor does not turn. You must write to the position_sp attribute for
changes to this attribute to take effect. | [
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