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algotom
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AlgotomData processing (ALGO)rithms for (TOM)ography.Algotomis a Python package that implements data processing methods for tomography.
It offers a comprehensive pipeline for data processing; including reading and writing data,
pre-processing, tomographic reconstruction, post-processing, and data simulation.
The package provides numerous utility methods to assist users in rapidly developing
prototype methods or constructing a pipeline for processing their own data.
Starting from version 1.1, methods for speckle-based phase-contrast tomography
have been incorporated into the package.FeaturesAlgotom is a lightweight package. The software is built on top of a few core
Python libraries to ensure its ease-of-installation. Methods distributed in
Algotom have been developed and tested at synchrotron beamlines where massive
datasets are produced. This factor drives the methods developed to be easy-to-use,
robust, and practical. Algotom can be used on a normal computer to process large
tomographic data. Some featuring methods in Algotom are as follows:Methods in a full data processing pipeline: reading-writing data,
pre-processing, tomographic reconstruction, and post-processing.Methods for processing grid scans (or tiled scans) with the offset rotation-axis
to multiply double the field-of-view (FOV) of a parallel-beam tomography system.
These techniques enable high-resolution tomographic scanning of large samples.Methods for processing helical scans (with/without the offset rotation-axis).Methods for determining the center-of-rotation (COR) and auto-stitching images
in half-acquisition scans (360-degree acquisition with the offset COR).Some practical methods developed and implemented for the package:
zinger removal, tilted sinogram generation, sinogram distortion correction,
beam hardening correction, DFI (direct Fourier inversion) reconstruction, FBP reconstruction,
and double-wedge filter for removing sample parts larger than the FOV in
a sinogram.Utility methods forcustomizing ring/stripe artifact removal methodsand parallelizing computational work.Calibration methods for determining pixel-size in helical scans.Methods for generating simulation data: phantom creation, sinogram calculation
based on the Fourier slice theorem, and artifact generation.Methods for phase-contrast imaging: phase unwrapping, speckle-based phase retrieval, image correlation, and image alignment.Methods for downsampling, rescaling, and reslicing (+rotating, cropping)
3D reconstructed image without large memory usage.Installationhttps://algotom.readthedocs.io/en/latest/toc/section3.htmlIf users install Algotom to an existing environment and Numba fails to install due to the latest Numpy:Downgrade Numpy and install Algotom/Numba again.Create a new environment and install Algotom first, then other packages.Use conda instead of pip.Avoid using the latest version of Python or Numpy as the Python ecosystem taking time to keep up with these twos.Usagehttps://algotom.readthedocs.io/en/latest/toc/section4/section4_5.htmlhttps://algotom.readthedocs.io/en/latest/toc/section1/section1_4.htmlhttps://algotom.readthedocs.io/en/latest/toc/section4.htmlhttps://github.com/algotom/algotom/tree/master/examplesDevelopment principlesWhile Algotom offers a comprehensive range of tools for tomographic data processing covering raw-data reading,
pre-processing, reconstruction, post-processing, and data saving; its development primarily focuses on
pre-processing techniques. This distinction makes it a prominent feature among other tomographic software.To ensure that the software can work across platforms and is easy-to-install; dependencies are minimized, and only
well-maintainedPython librariesare used.To achieve high-performance computing and leverage GPU utilization while ensuring ease of understanding, usage, and software
maintenance, Numba is used instead of Cupy or PyCuda.Methods are structured into modules and functions rather than classes to enhance usability, debugging, and maintenance.Algotom is highly practical as it can run on computers with or without a GPU, multicore CPUs; and accommodates both small
and large memory capacities.Update noteshttps://algotom.readthedocs.io/en/latest/toc/section6.htmlAuthorNghia T. Vo -NSLS-II, Brookhaven National Lab, USA;Diamond Light Source, UK.HighlightsAlgotom was used for some experiments featured on media:ScanningMoon rocks and Martian meteoritesusing helical scans with offset rotation-axis. Featured onReuters.ScanningHerculaneum Scrollsusing grid scans with offset rotation-axis respect to the grid's FOV (pixel size of 7.9 micron;
total size of 11.3 TB). Featured onBBC.
The latest updates on the scroll's reading progress arehere.Scanning'Little Foot' fossilusing two-camera detector with offset rotation-axis. Featured onBBC.
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algotools
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No description available on PyPI.
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algotoolsshiridi
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No description available on PyPI.
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algotrade
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# algotrade
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algo-trade
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Algorithmic Portfolio ManagementDISCLAIMER: This is a personal project of mine to create a library that facilitates portfolio management using the TDAmeritrade platform. I am not a professional software engineer and cannot attest to robust testing of this library. Additionally, stock trading is an inherently risky practice and is subject to substantial losses. I am not responsible for any losses incurred through use of this library nor any edge cases/bugs that may occur. You have been warned.Overviewalgo_tradeis designed to facilitate the creation and implementation of a portfolio management strategy. There exists free Python packages that either facilitate getting financial data, backtesting trading strategies, or connecting to trading accounts to place trades. This package is specifically created with the intent to combine those features of other financial Python tools.algo_tradeutilizes other financial Python packages and serves as a wrapper to provide an end-to-end trading experience.How Does It Work?Install the package viapip install [INSERT PACKAGE NAME HERE]Asalgo_tradeis designed to integrate features of existing Python packages, usage of the package to define and implement trading strategies requires subclassing as well as knowledge of integrated Python packages. The two main classes used areAccountClientandPortfolio.AccountClientserves as a connection to trading accounts - currently, the only supported client is TDAmeritrade due to their public API and leverages thetda-apiPython package. A sample instantiation of theAccountClientclass can be seen below:fromtdaimportauth,clientfromalgo_trade.accountimportAccountClienttda_client=auth.easy_client(api_key=API_KEY,redirect_uri=REDIRECT_URI,token_path=TOKEN_PATH,)account=AccountClient(client=tda_client,ACC_ID=ACC_ID)Portfoliois the container for algorithmic strategies and can be considered where all the logic, documentation, and indicators the user wants to establish should be placed. A sample definition and instantiation of thePortfolioclass can be seen below, implementing a dollar-cost-averaging of SPY and IWM using a 75:25 weighting:fromalgo_trade.portfolioimportPortfolioimportpandasaspdclassSpyIwmStrategy(Portfolio):population=['SPY','IWM']defstrategy(self):returnpd.DataFrame(data={'ticker':population,'weight':[0.75,0.25]})port_strat=SpyIwmStrategy()print(port_strat.run())An important but not strictly needed class (depending on how you intend to set up your strategy and whether you need data) is theDataBuilderclass, also present in theportfolio.pymodule.DataBuilderallows you to get data, using eitheryfinanceortda-api, to perform necessary calculations in your strategy. A sample instantiation ofDataBuilderto get data via TDAmeritrade can be seen below:fromtdaimportauth,clientfromalgo_trade.portfolioimportDataBuilderdata_builder=DataBuilder(client=tda_client)# tda_client created in above code sampledata_builder.TDAmeritrade(port_strat,port_strat.population,)print(port_strat.holdings)Stock level data are all added to thePortfolioobject asStockobjects which contain their symbol as well as historical price data stored as a dataframe.Trade orders are created by theAccountClientby comparing the current account portfolio weights against target portfolio weights, selling and buying stocks as necessary to get as close to the target portfolio weights as possible. Below is an example of aPortfoliostrategy returning target portfolio weights to theAccountClientwhich calculates the difference, creates the orders, and submits the order onto the TDAmeritrade platform:target_weights=port_strat.run()account.buildOrder(target_weights)account.placeOrderTDAmeritrade()Lastly, theindicator.pymodule contains a series of pre-defined calculations that a use can use within a strategy to calculate metrics such as volatility, sharpe ratio, mean, geometric mean, etc. This module provides a toolset that users can leverage but is not strictly necessary. Most calculations are done on dataframes, so it is relatively simple to create a personal library of indicators if desired.FAQIs there a built in way to designate frequency of the strategy trades?No, though it was considered for a time. A workaround would be to set up a cron job to run the strategy at the appropriate frequency.Can this library be used for day-trading or high-frequency trading?Similar to the above answer, you could use the package for day-trading by setting up a strategy and a related cron job to run every minute or half-hour, though if you have a day-trading account there would be other platforms that provide the tool to do so already. Additionally, this package leverages thetda-apilibrary specifically for HTTP clients - there is an additionally feature in that library used for streaming data that would be better suited for day-trading, but that is out of the scope of this projectFor high-frequency trading, and depending on the trading strategy, some would argue that Python would not be the best language to do this and that a faster programming language (such as C++ or Golang) is better. Again, this too is out of the scope of the project, but even if it were in-scope, Python would probably not be the best approach.Will there be additional APIs/clients incorporated into this project besides TDAmeritrade?Perhaps if other clients that both the API and account administration fees are free, I would consider it. However, there are also other features generally that I would like to implement, so this library will probably be limited to TDAmeritrade for the time being.
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algotradepy
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Copyright (c) 2020, Petio PetrovPermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the โSoftwareโ), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED โAS ISโ, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Description: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.7
Provides-Extra: ibapi
Provides-Extra: polygon
Provides-Extra: dev
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algotrader
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AlgoTradingPython Implementations of popular Algorithmic Trading Strategies, along with genetic algorithms for tuning parameters based on historical data.Algorithms -CCI Correction (Done)Stochastic Pop and Drop (Done)Percent Above 50-day SMA (Done)Moving Momentum (Done)Exponential Moving Averages (Done)Double Exponential Moving Averages (Done)Triple Exponential Moving Averages (Done)Six-Month Cycle MACD (Done)Gap Trading StrategiesHarmonic PatternsThe Last Stochastic TechniquePercent B Money FlowPre-Holiday EffectRSI2Faberโs Sector rotation Trading StrategyCVR3 VIX Market TimingSlope Performance TrendSwing ChartingIchimoku CloudTrend Quantification and Asset Allocation
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algo-trader
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No description available on PyPI.
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algotrade-utils
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Failed to fetch description. HTTP Status Code: 404
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algotrading-api
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algo_tradingThis package allows you test trading algorithms.
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algotradingPythonSalem
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My first Python package with a slightly longer description
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algo-trading-utils
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Algo Trading UtilsA library full of utilities for algorithmic trading and data analysis.
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algotype
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Algotype manualAlgorythmic font creation system.Version 0.2.39Status: AlphaAuthorsMarek Ryฤko (system design and most of Python programming)Bogusลaw Jackowski (design consulting and Metapost programming)Piotr Strzelczyk (Python 2 Metatype1 programming, partially used in Algotype)IntroductionAlgotype is a system for creating fonts using algorythmic means, by programming
the shapes of characters (glyphs), metric information and their relationships.ThealgotypePython package is a Python part of the entire Algotype
system. The other parts, not included on the Python Package Index, PyPI, are:program files in the Metapost language, defining the shapes of font glyphs, their relationships and general font data,configuration files, defining both the installation instance and the paramteters of a particular run of the Algotype system,templates of font feature files (definitions),GOADB file or files (Glyph Order and Alias DataBase), defining the renaming of glyphs for certain types of output fonts,renaming definition files, defining the renaminig of fonts both for OTF format and for Type 1 (PFB) format, including the definitions of names of files in 256-character fonts with various encodings.Algotype is a successor of the Metatype1 system created in the years 2000โ2018 by Bogusลaw Jackowski and Piotr Strzelczyk. The original Metatype1 system has been used to create several font families, including Latin Modern fonts and a series of TeX Gyre fonts (all of them are freele available and also included in most Linux distribiutions).The nameThe name โAgotypeโ reflects the fact that the purpose of the system is algorythmic type (fonts) design.The project web page is planned to be:http://algotype.org.InstallationThe installation steps are the following:install Python 3, version at least 3.6,install t1utils (t1asm,t1disasmprograms; must be available in operating system program search path),install Fontforge (a font manipulation program, available for major operating systems),install Fontforge Python support (Python >= 2.7 in 2.x line or >= 3.7 in 3.x line),usepipcommand in Python 3 to install Algotype, namely the packagealgotypepip install-ihttps://test.pypi.org/simple/algotypeThe command in your operating system may be also calledpip3orpip3.8, or similarly,install Metapost (probably as a part of TeXLive installation),install the Metapost Algotype files (for LM and TG fonts),insltall other input Algotype files (feature templates, goadb files etc),create (or edit) Algotype configuration files,create (or edit) scripts or batch files running/calling the algotype program, with config file paths and file names parameters.
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algoutils
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algoutils
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algovanity
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algovanitygenerate vanity addresses for the Algorand blockchainThe software supports matching multiple patterns at once, and that is in fact the suggested operation mode: generate once, match many.This design also facilitates attempts in finding longer matches in a potentially shorter timespan, giving the user control in reducing the precision and diverging from the initial desired outcome.The script spawns multiple subprocesses which will run indefinitely, with a main loop printing to console some basic statistics and any new matches as they're found, waiting for a keyboard interrupt.InstallationfrompipTo install the script from the packaged release onpip, runpip3installalgovanityfrom sourceTo install the script from source, rungitclonehttps://github.com/nxet/algovanitycdalgovanity# optionally change branchgitcheckoutdev-0.1# install requirements and librarypip3install-rrequirements.txt
pip3install.Pattern formatsAddresses are formed by 58 characters in the uppercaseA-Zrange and the2-7range, user can pick any combination of these.The numbers0,1,8and9are not valid characters in Algorand addressesMatching is supported with four different pattern formats:startmatches at the beginning of the addressdefined with patterns likeADDR...orMYNAME...endmatches at the end of the addressdefined with patterns like...ADDRor...MYNAMEedgesmatches at both start and end of the addressdefined with patterns likeCOOL...ADDRorABC...XYZregexcompiles the provided pattern as is and attempts tore.fullmatchdefined with patterns like^AB[.]*CD[.]*YZ$or^NAME[2-7][A-Z2-7]+$NB: the longer the pattern, the longer the run time.Anything over 6 characters will be running for averylong time.File outputThe script creates a new file if none is available, but will always try to append new matches to the provided file instead of overwriting.Matches are dumped to file at each status update, and finally once the main loop is terminated.The file is opened/closed on-demand, allowing totail -fit for example.Examples# install packagepip3installalgovanity# match addresses starting with MYNAMEalgovanityMYNAME...# or either starting or ending with MYNAMEalgovanityMYNAME......MYNAME# but limiting to only 2 subprocessesalgovanityMYNAME......MYNAME--procs-max2# dump results to filealgovanityMYNAME...--output~/algovanity.txt# match addresses starting with COOL and ending with ADDRalgovanityCOOL...ADDR# match addresses starting with NAME plus one exact number (either 5 or 7)algovanityNAME5...NAME7...--output~/algovanity.txt# match addresses starting with NAME plus one random number from range [2-7]algovanity'^NAME[2-7][A-Z2-7]+$'--output~/algovanity.txt# match addresses starting with NAME plus two random numbers from range [2-7]algovanity'^NAME[2-7]{2}[A-Z2-7]+$'--output~/algovanity.txtLicenseThis project is licensed under GPL 3.0 - see LICENSE for details.Support this projectIf this software has been helpful please consider donating to support future development.Algorand address: NXET... -view on algoexplorer.io
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algovault
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algovaultExperimentation trackingTesti
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algovent_utils
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No description available on PyPI.
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algovera
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๐ Algovera LibraryThe Algovera Library currently comprises of a Jupyter Lab extension for using MetaMask within Jupyter Lab to interact with theOcean market, and store on decentralized storage with decentralized access control (lit protocol for decentralized access control, Estuary/Filecoin for decentralized storage)AlgoveraAlgovera is a community of individuals working to facilitate and accelerate the development of decentralised AI products and research.Website|Notion|Discord|Calendar|Twitter|YouTube๐ SetupTo start using the extension, simply run these commands in your terminal::conda create -n algolab -c conda-forge jupyterlab
conda activate algolab
pip install algovera
jupyter lab๐ง Contributing to the LibraryThere are currently two ways to contribute to the Algovera Library: adding more functionality to the python package or improving the jupyter lab extension.First, clone the repository by runninggit clone https://github.com/AlgoveraAI/jupyterlab_extensions.git
cd jupyterlab_extensions/To start contributing, follow the commands below to set up a development environment.conda create -n algolab-dev -c conda-forge jupyterlab ipylab jupyter-packaging nodejs ipytree bqplot ipywidgets numpy
conda activate algolab-dev
python -m pip install -e ".[dev]"
jupyter labextension develop . --overwrite
jlpm
jlpm run buildAfter any changes, runjlpm run buildto see them in Jupyter Lab. Note that you might need to runjlpmorpython -m pip install -e ".[dev]"depending on whether you add new dependencies to the project.
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algovera-ocean-lib
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ocean.pyPython library to privately & securely publish, exchange, and consume data.With ocean.py, you can:Publishdata services: downloadable files or compute-to-data. Create an ERC721data NFTfor each service, and ERC20datatokenfor access (1.0 datatokens to access).Selldatatokens via for a fixed price. Sell data NFTs.Transferdata NFTs & datatokens to another owner, andall other ERC721 & ERC20 actionsusingweb3.py,Brownie, etc.ocean.py is part of theOcean Protocoltoolset.This is in beta state. If you run into problems, please open up anew issue.๐ Installation๐ Quickstart: simple flow, marketplace, compute-to-data, more๐ฆ Development๐ License๐ Installation#Installtheocean.pylibrary.Allowpre-releasesforthelatestv4version.Installwheelfirsttoavoiderrors.pip install wheelpip install --pre ocean-libโ ๏ธ Mac users: if you encounter an "Unsupported Architecture" issue, then install including ARCHFLAGS:ARCHFLAGS="-arch x86_64" pip install ocean-lib. [Details.]๐ QuickstartHere are flows to try out, from simple to specific detailed variants.Simple flow- the essence of Ocean - creating a data NFT & datatoken.Publish flow- a dataset is published.Consume flow- a published dataset is consumed (downloaded).Marketplace flow- a data asset is posted for sale at fixed rate, then purchased.Dispenser flow- here, a datatoken dispenser is created and datatokens are dispensed for free.Compute-to-data flow- uses C2D to build an AI model a dataset that never leaves the premises.Key-value database- use data NFTs to store arbitrary key-value pairs on-chain.Profile NFTs- enable "login with Web3" where Dapp can access private user profile data.Learn moreGet test OCEAN- from rinkebyUnderstand config parameters- envvars vs filesLearn about off-chain services- Ocean Provider for data services, Aquarius metadata storeLearn about wallets- on generating, storing, and accessing private keysGet an overview of ocean.py- key modules and functions๐ฆ DevelopmentDevelopers flow- to further develop ocean.pyRelease process- to do a new release of ocean.py๐ LicenseCopyright ((C)) 2022 Ocean Protocol Foundation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
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algovis
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Algovis is a python library made for visualizing algorithms. Refer to thedocumentationfor more info.Currently the library has these algorithmsSortingBubble SortInsertion SortSelection SortMerge SortQuick SortSearchingLinear SearchBinary SearchGetting StartedPrerequisitesI would highly suggest making a virtual environment. The main purpose of a Python virtual environments is to create an isolated environment for Python projects. You can read more about themhere.# making a test folder$mkdirtest_algovis# make it the current directory$cdtest_algovis# making a virtual environment (you can replace envname with whatever name you like)$python3-mvenvenvname# activating it$sourceenvname/bin/activateYou can only access algovis inside this virtual environment. To leave this virtual env when you're done trying out the library, type$deactivateInstalling$pip3installalgovisUsing the sorting packageVisualize method# import the sorting package from libraryfromalgovisimportsorting# importing random module to shuffle the listimportrandom# Making a list of 100 integers from 1-100# using list comprehensionmy_list=[i+1foriinrange(100)]# shuffling the listrandom.shuffle(my_list)# making a BubbleSort class object by passing the shuffled listbs_object=sorting.BubbleSort(my_list)# calling the visualize methodbs_object.visualize(interval=100)Outputsort method# lets work on a shorter example nowmy_list=[i+1foriinrange(10)]# shuffling the list using random modulerandom.shuffle(my_list)#making a quicksort objectqs_object=sorting.QuickSort(my_list)#sorting in reverse with stepsqs_object.sort(pivot="first",steps=True,reverse=True)evaluate method# calling the evaluate method and passing the optional parameter 'iterations'# the list is sorted 'iterations' number of times and the min, max and average time taken#to sort the list is returned in form of a formatted tablebs_object.evaluate(iterations=100)info method# This method gives us information about the algorithmbs_object.info()code method# It prints out the function for the algorithmbs_object.code()My terminal config is iTerm2 + ohmyzsh + powerlevel10k with dark backgroud. Colors may appear different in your terminal output. It's recommended to change the terminal color to something darkerUsing the searching packageThe searching package has the same methods as sorting, just instead of 'sort' you have 'search'
Refer to thedocumentationfor more infosearch method#importing searching packagefromalgovisimportsearching# making a list of integers from 1 to 100# using list comprehensionmy_list=[i+1foriinrange(100)]#making binary search objectbin_search=searching.BinarySearch(my_list)#calling the search methodbin_search.search(42,steps=True)visualize method# calling the visualize method# interval is the time between two different frames of the animationbin_search.visualize(42,interval=1000)# or if you want to linear search 42lin_search=searching.LinearSearch(my_list)# setting a less interval to make a much faster animationlin_search.visualize(42,interval=100)DoumentationThe documentation is built withMKdocsusingmaterialtheme and is hosted on netlify. You can read ithereAuthorMayank Arora(hotshot07)LicenseThis project is licensed under the GNU Affero General Public License v3 (AGPL-3.0) - see theLICENSEfile for details
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algovision
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AlgoVision - A Framework for Differentiable Algorithms and Algorithmic SupervisionThis repository includes the official implementation of our NeurIPS 2021 Paper "Learning with Algorithmic Supervision via Continuous Relaxations"
(Paper @ArXiv,
Video @Youtube).algovisionis a Python 3.6+ and PyTorch 1.9.0+ based library for making algorithms differentiable. It can be installed via:pipinstallalgovisionApplications include smoothly integrating algorithms into neural networks for algorithmic supervision, problem-specific optimization within an algorithm, and whatever your imagination allows.
Asalgovisionrelies on PyTorch it also supports CUDA, etc.Check out the Documentation!๐ฑ IntroDeriving a loss from a smooth algorithm can be as easy asfromexamplesimportget_bubble_sortimporttorch# Get an array (the first dimension is the batch dimension, which is always required)array=torch.randn(1,8,requires_grad=True)bubble_sort=get_bubble_sort(beta=5)result,loss=bubble_sort(array)loss.backward()print(array)print(result)print(array.grad)Here, the loss is a sorting loss corresponding to the number of swaps in the bubble sort algorithm.
But we can also define this algorithm from scratch:fromalgovisionimport(Algorithm,Input,Output,Var,VarInt,# coreLet,LetInt,Print,# instructionsEq,NEq,LT,LEq,GT,GEq,CatProbEq,CosineSimilarity,IsTrue,IsFalse,# conditionsIf,While,For,# control_structuresMin,ArgMin,Max,ArgMax,# functions)importtorchbubble_sort=Algorithm(# Define the variables the input corresponds toInput('array'),# Declare and initialize all differentiable variablesVar('a',torch.tensor(0.)),Var('b',torch.tensor(0.)),Var('swapped',torch.tensor(1.)),Var('loss',torch.tensor(0.)),# Declare and initialize a hard integer variable (VarInt) for the control flow.# It can be defined in terms of a lambda expression. The required variables# are automatically inferred from the signature of the lambda expression.VarInt('n',lambdaarray:array.shape[1]-1),# Start a relaxed While loop:While(IsTrue('swapped'),# Set `swapped` to 0 / FalseLet('swapped',0),# Start an unrolled For loop. Corresponds to `for i in range(n):`For('i','n',# Set `a` to the `i`th element of `array`Let('a','array',['i']),# Using an inplace lambda expression, we can include computations# based on variables to obtain the element at position i+1.Let('b','array',[lambdai:i+1]),# An If-Else statement with the condition a > bIf(GT('a','b'),if_true=[# Set the i+1 th element of array to aLet('array',[lambdai:i+1],'a'),# Set the i th element of array to bLet('array',['i'],'b'),# Set swapped to 1 / TrueLet('swapped',1.),# Increment the loss by 1 using a lambda expressionLet('loss',lambdaloss:loss+1.),]),),# Decrement the hard integer variable n by 1LetInt('n',lambdan:n-1),),# Define what the algorithm should returnOutput('array'),Output('loss'),# Set the inverse temperature betabeta=5,)๐พ Full Instruction Set(click to expand)The full set of modules is:fromalgovisionimport(Algorithm,Input,Output,Var,VarInt,# coreLet,LetInt,Print,# instructionsEq,NEq,LT,LEq,GT,GEq,CatProbEq,CosineSimilarity,IsTrue,IsFalse,# conditionsIf,While,For,# control_structuresMin,ArgMin,Max,ArgMax,# functions)Algorithmis the main class,InputandOutputdefine arguments and return values,Vardefines differentiable variables andVarIntdefines non-differentiable integer variables.Eq,LT, etc. are relaxed conditions forIfandWhile, which are respective control structures.Forbounded loops of fixed length that are unrolled.Letsets a differentiable variable,LetIntsets a hard integer variable.
Note that hard integer variables should only be used if they are independent of the input values, but they may depend on the input shape (e.g., for reducing the number of iterations after each traversal of a For loop).Printprints for debug purposes.Min,ArgMin,Max, andArgMaxreturn the element-wise min/max/argmin/argmax of a list of tensors (of equal shape).ฮป Lambda ExpressionsKey to defining an algorithm arelambdaexpressions (seeherefor a reference).
They allow defining anonymous functions and therefore allow expressing computations in-place.
In most cases inalgovision, it is possible to write a value in terms of a lambda expressions.
The name of the used variable will be inferred from the signature of the expression.
For example,lambda x: x**2will take the variable namedxand return the square of it at the location where the expression is written.Let('z', lambda x, y: x**2 + y)corresponds to the regular line of codez = x**2 + y.
This also allows inserting complex external functions including neural networks as part of the lambda expression.
Assumingnetis a neural networks, one can writeLet('y', lambda x: net(x))(corresponding toy = net(x)).LetLetis a very flexible instruction. The following table shows the use cases of it.AlgoVisionPythonDescriptionLet('a', 'x')a = xVariableais set to the value of variablex.Let('a', lambda x: x**2)a = x**2As soon as we compute anything on the right hand side of the equation, we need to write it as alambdaexpression.Let('a', 'array', ['i'])a = array[i]Indexing on the right hand requires an additional list parameter after the second argument.Let('a', lambda array, i: array[:, i])a = array[i]Equivalent to the row above: indexing can also be manually done inside of alambdaexpression. Note that in this case, the batch dimension has to be written explicitly.Let('a', 'array', ['i', lambda j: j+1])a = array[i, j+1]Multiple indices andlambdaexpressions are also supported.Let('a', 'array', [None, slice(0, None, 2)])a = array[:, 0::2]Noneandslices are also supported.Let('a', ['i'], 'x')a[i] = xIndexing can also be done on the left hand side of the equation.Let('a', ['i'], 'x', ['j'])a[i] = x['j']...or on both sides.Let(['a', 'b'], lamba x, y: (x+y, x-y))a, b = x+y, x-yMultiple return values are supported.In its most simple formLetobtains two arguments, a string naming the variable where the result is written, and the value that may be expressed via alambdaexpression.If the lambda expression returns multiple values, e.g., because a complex function is called and has two return values, the left argument can be a list of strings.
That is,Let(['a', 'b'], lamba x, y: (x+y, x-y))corresponds toa, b = x+y, x-y.Letalso supports indexing. This is denoted by an additional list argument after the left and/or the right argument.
For example,Let('a', 'array', ['i'])corresponds toa = array[i], whileLet('array', ['i'], 'b')corresponds toarray[i] = b.Let('array', ['i'], 'array', ['j'])corresponding toarray[i] = array[j]is also supported.Note that indexing can also be expressed throughlambdaexpressions.
For example,Let('a', 'array', ['i'])is equivalent toLet('a', lambda array, i: array[:, i]). Note how in this case the batch dimension has to be explicitly taken into account ([:, ]).
Relaxed indexing on the right-hand side is only supported throughlambdaexpressions due to its complexity.
Relaxed indexing on the left-hand side is supported if exactly one probability weight tensor is in the list (e.g.,Let('array', [lambda x: get_weights(x)], 'a')).LetIntonly supports setting the variable to an integer (Pythonint) or list of integers (as well as the same type via lambda expressions).
Note that hard integer variables should only be used if they are independent of the input values, but they may depend on the input shape.If you need help implementing your differentiable algorithm, you mayschedule an appointment. This will also help me improve the documentation and usability.๐งช ExperimentsThe experiments can be found in theexperimentsfolder. Additional experiments will be added soon.๐ฌ Sorting SupervisionThe sorting supervision experiment can be run withpythonexperiments/train_sort.pyor by checking outthis Colab notebook.๐ CitingIf you used our library, please cite it as@inproceedings{petersen2021learning,title={{Learning with Algorithmic Supervision via Continuous Relaxations}},author={Petersen, Felix and Borgelt, Christian and Kuehne, Hilde and Deussen, Oliver},booktitle={Conference on Neural Information Processing Systems (NeurIPS)},year={2021}}๐ Licensealgovisionis released under the MIT license. SeeLICENSEfor additional details.
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algoviz
|
AlgoVizCreates table for python list and highlights indexes on index access.Installationpip install algovizExamplesExample 1 : Coin Change Problemfrom algoviz.vizlist import VizList
def coinChange(coins, amount):
dp = [0] * (amount + 1)
dp[0] = 1
dp = VizList(dp, title_name='Coin Change')
for coin in coins:
for val in range(amount + 1):
if coin <= val:
dp.print(f'Coin = {coin} | dp[{val}] += dp[{val} - {coin}] =', f'#[{val}] + #[{val} - {coin}]')
'''
dp.print :
Param 1 : Normal Print
Param 2: eval is run on this string. Replace array name with # to access original array.
'''
dp[val] += dp[val - coin]
return dp[-1]
if __name__ == '__main__':
coins = [1, 2]
amount = 3
res = coinChange(coins, amount)
print(f'Output : {res}')Output:Coin Change Init
โโโโโณโโโโณโโโโณโโโโ
โ 0 โ 1 โ 2 โ 3 โ
โกโโโโโโโโโโโโโโโโฉ
โ 1 โ 0 โ 0 โ 0 โ
โโโโโดโโโโดโโโโดโโโโ
Coin = 1 | dp[1] += dp[1 - 1] = 1
Coin Change
โโโโโณโโโโณโโโโณโโโโ
โ 0 โ 1 โ 2 โ 3 โ
โกโโโโโโโโโโโโโโโโฉ
โ 1 โ 1 โ 0 โ 0 โ
โโโโโดโโโโดโโโโดโโโโ
Coin = 1 | dp[2] += dp[2 - 1] = 1
Coin Change
โโโโโณโโโโณโโโโณโโโโ
โ 0 โ 1 โ 2 โ 3 โ
โกโโโโโโโโโโโโโโโโฉ
โ 1 โ 1 โ 1 โ 0 โ
โโโโโดโโโโดโโโโดโโโโ
Coin = 1 | dp[3] += dp[3 - 1] = 1
Coin Change
โโโโโณโโโโณโโโโณโโโโ
โ 0 โ 1 โ 2 โ 3 โ
โกโโโโโโโโโโโโโโโโฉ
โ 1 โ 1 โ 1 โ 1 โ
โโโโโดโโโโดโโโโดโโโโ
Coin = 2 | dp[2] += dp[2 - 2] = 2
Coin Change
โโโโโณโโโโณโโโโณโโโโ
โ 0 โ 1 โ 2 โ 3 โ
โกโโโโโโโโโโโโโโโโฉ
โ 1 โ 1 โ 2 โ 1 โ
โโโโโดโโโโดโโโโดโโโโ
Coin = 2 | dp[3] += dp[3 - 2] = 2
Coin Change
โโโโโณโโโโณโโโโณโโโโ
โ 0 โ 1 โ 2 โ 3 โ
โกโโโโโโโโโโโโโโโโฉ
โ 1 โ 1 โ 2 โ 2 โ
โโโโโดโโโโดโโโโดโโโโ
Output : 2Example 2 : Count number of palindromesdef countSubstrings(s):
n = len(s)
dp = [[0] * n for _ in range(n)]
dp = VizList(dp, column_index=list(s), row_index=list(s), title_name='DP Table', sleep_time=1, set_highlight_color='blue')
res = 0
for i in range(n - 1, -1, -1):
for j in range(i, n):
dp[i][j] = s[i] == s[j] and ((j - i + 1) < 3 or dp[i + 1][j - 1])
res += dp[i][j]
dp.clear_highighlight_data() # Clears highlight tracking data. It's done automatically on list assignment operators
# The second parameter is evaluated using eval and printed.
# Note : to access the internal array, the array name should be replace by a #
return res
if __name__ == '__main__':
s = 'aab'
res = countSubstrings(s)
print('Output : {}'.format(res))The above code will generateDP Table Init
โโโโโโโโโณโโโโโโโโณโโโโโโโโณโโโโโโโโ
โ โ a [0] โ a [1] โ b [2] โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ a [0] โ 0 โ 0 โ 0 โ
โ a [1] โ 0 โ 0 โ 0 โ
โ b [2] โ 0 โ 0 โ 0 โ
โโโโโโโโโดโโโโโโโโดโโโโโโโโดโโโโโโโโ
DP Table
โโโโโโโโโณโโโโโโโโณโโโโโโโโณโโโโโโโโ
โ โ a [0] โ a [1] โ b [2] โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ a [0] โ 0 โ 0 โ 0 โ
โ a [1] โ 0 โ 0 โ 0 โ
โ b [2] โ 0 โ 0 โ True โ
โโโโโโโโโดโโโโโโโโดโโโโโโโโดโโโโโโโโ
DP Table
โโโโโโโโโณโโโโโโโโณโโโโโโโโณโโโโโโโโ
โ โ a [0] โ a [1] โ b [2] โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ a [0] โ 0 โ 0 โ 0 โ
โ a [1] โ 0 โ True โ 0 โ
โ b [2] โ 0 โ 0 โ True โ
โโโโโโโโโดโโโโโโโโดโโโโโโโโดโโโโโโโโ
DP Table
โโโโโโโโโณโโโโโโโโณโโโโโโโโณโโโโโโโโ
โ โ a [0] โ a [1] โ b [2] โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ a [0] โ 0 โ 0 โ 0 โ
โ a [1] โ 0 โ True โ False โ
โ b [2] โ 0 โ 0 โ True โ
โโโโโโโโโดโโโโโโโโดโโโโโโโโดโโโโโโโโ
DP Table
โโโโโโโโโณโโโโโโโโณโโโโโโโโณโโโโโโโโ
โ โ a [0] โ a [1] โ b [2] โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ a [0] โ True โ 0 โ 0 โ
โ a [1] โ 0 โ True โ False โ
โ b [2] โ 0 โ 0 โ True โ
โโโโโโโโโดโโโโโโโโดโโโโโโโโดโโโโโโโโ
DP Table
โโโโโโโโโณโโโโโโโโณโโโโโโโโณโโโโโโโโ
โ โ a [0] โ a [1] โ b [2] โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ a [0] โ True โ True โ 0 โ
โ a [1] โ 0 โ True โ False โ
โ b [2] โ 0 โ 0 โ True โ
โโโโโโโโโดโโโโโโโโดโโโโโโโโดโโโโโโโโ
DP Table
โโโโโโโโโณโโโโโโโโณโโโโโโโโณโโโโโโโโ
โ โ a [0] โ a [1] โ b [2] โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ a [0] โ True โ True โ False โ
โ a [1] โ 0 โ True โ False โ
โ b [2] โ 0 โ 0 โ True โ
โโโโโโโโโดโโโโโโโโดโโโโโโโโดโโโโโโโโ
Output : 4
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algo-wars
|
Investment Strategies Library: algo-warsalgo-warsis Python library for Investment Strategies such as Volatility Modeling, Technical Analysis, and Portfolio Optimization. The goal of this library is to provides cues for strategies to investment or trade stock, bond, or cryptocurrency, based on the statistical machine learning and the deep reignforcement learning. Especialy, this library provides apprication of the Volatility model based on Conditional Generative Adversarial Networks(Conditional GANs) and Portfolio Selection based on Deep Q-Network.Please do note that this library is currently inBETATesting. Please use this libraryat your own risk.InstallationInstall using pip:pipinstallalgo-warsSource codeThe source code is currently hosted on GitHub.accel-brain-code/Algorithm-WarsPython package index(PyPI)Installers for the latest released version are available at the Python package index.algo-wars : Python Package IndexDependenciesnumpy: v1.13.3 or higher.pandas: v0.22.0 or higher.accel-brain-base: v1.0.0 or higher.OptionsyfinanceOnly when usingalgowars/extractablehistoricaldata/facade_yfinance.py.DescriptionThe library is designing a complex of two deep architectures:Generative Adversarial Networks(GAN) that enable the generation of pseudo-historical data.Multi-agent Deep Reinforcement Learning(Multi-agent DRL) that addresses multiple investment strategies such as volatility minimization and Sharpe ratio maximization.For convenience, we named this complex systemAdversarial Generative Deep Reinforcement Learning.Multi-agent DRL can acquire high generalization performance and domain adaptability by learning both the historical data generated by GAN and the true historical data. Multi-agent DRL develops a solution under two problem settings: volatility minimization and Sharpe ratio maximization. Multiple agents are assigned to each problem setting. Finally, the portfolio of agents with the highest cost performance is output as the winning portfolio.This library uses Retrospective encoders from Zhang, K., et al. (2018) as generative models in designing GANs for modeling volatility. This model is also mentioned inAutomatic Summarization Library: pysummarization. The loss/error function and network structure are designed according to Akcay, S., et al. (2018). As used inGenerative Adversarial Networks Library: pygan, This model facilitates manifold learning by adding a re-encoder to the encoder-decoder network structure.The Multi-agent DRL is designed as a Deep Q-network derived from the decentralized partially observable Markov decision process(Dec-POMDP) proposed by Egorov, M. (2016). This model is also mentioned inReinforcement Learning Library: pyqlearning.Setup master data of ticker symbols.Before starting learning, it is necessary to prepare the master data of securities. Demo data is located inmasterdata/ticker_master_demo.csv. This master data is referred to during data preparation and learning.The column definition is as follows.ticker: Ticker Symbol.asset: Asset type.area: If the asset has regionality, write a symbol such as the category.If it's a US stock, for instance, writeUS.detail: It's just a space for notes. The system does not refer to this value.asset_allocation: Weight per asset. This value is referenced when calculating the portfolio percentage.If you want to judge purely by the algorithm, write a constant here.area_allocation: Weight per area. This value is referenced when calculating the portfolio percentage.If you want to judge purely by the algorithm, write a constant here.expense_ratio: ETF expense ratio. Write0.0for individual stocks and crypto assets.yield: Past annual yield.commission: Trading fees.tax: Tax rate on capital gains.Data PreparationHistorical data must be placed in thelogs / historical /directory as a CSV file consisting of the following formats:timestamp:YYYY-MM-DDopen: open.high: high.low: low.close: close.adjusted_close: adjusted close.volume: volume.It is necessary to prepare one CSV file for each Ticker symbols. Also, the file name must be associated with the value in thetickercolumn in the security master data.Historical data can be obtained from various REST (ful) APIs. This library already has a batch program for retrieving data from several APIs. For instance,pythonalgowars/extractablehistoricaldata/facade_yfinance.py\-vTrue\-tmp./masterdata/ticker_master_demo.csvLearning and inference can be performed from the following batch programs.pythonalgowars/portfolio_dqn_controller.py\-vTrue\-sd2013-06-24-ed2020-06-23\-gsd2021-01-01-ged2021-04-27\-df30\-an3\-ep300\-nan3\-lrdqn1e-04-lr1e-10\-in500\-bs20\-sl10\-rpm1.0\-rps0.1\-gppparams/recursive_seq_2_seq_model_re_encoder_model.params\-rppparams/recursive_seq_2_seq_model_model.params\-dppparams/discriminative_model_model.params\-dqnppparams/dqn_model.params\-tmpmasterdata/ticker_master_demo.csv\-scall\-mm120000\-mfm\-ltsl90You can check the interface specifications of the batch program with the following command.pythonalgowars/portfolio_dqn_controller.py-hA demonstration of visualizing the results of pseudo-historical data generation and portfolio optimization is demonstrated in the following notebook.demo-portfolio-optimization.ipynbReferencesAkcay, S., Atapour-Abarghouei, A., & Breckon, T. P. (2018, December). Ganomaly: Semi-supervised anomaly detection via adversarial training. In Asian Conference on Computer Vision (pp. 622-637). Springer, Cham.Donahue, J., Krรคhenbรผhl, P., & Darrell, T. (2016). Adversarial feature learning. arXiv preprint arXiv:1605.09782.Makhzani, A., Shlens, J., Jaitly, N., Goodfellow, I., & Frey, B. (2015). Adversarial autoencoders. arXiv preprint arXiv:1511.05644.Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., & Chen, X. (2016). Improved techniques for training gans. In Advances in neural information processing systems (pp. 2234-2242).Schlegl, T., Seebรถck, P., Waldstein, S. M., Schmidt-Erfurth, U., & Langs, G. (2017, June). Unsupervised anomaly detection with generative adversarial networks to guide marker discovery. In International conference on information processing in medical imaging (pp. 146-157). Springer, Cham.Yeh, R., Chen, C., Lim, T. Y., Hasegawa-Johnson, M., & Do, M. N. (2016). Semantic image inpainting with perceptual and contextual losses. arXiv preprint arXiv:1607.07539, 2(3).Zenati, H., Foo, C. S., Lecouat, B., Manek, G., & Chandrasekhar, V. R. (2018). Efficient gan-based anomaly detection. arXiv preprint arXiv:1802.06222.Zhang, K., Grauman, K., & Sha, F. (2018). Retrospective Encoders for Video Summarization. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 383-399).Authoraccel-brainAuthor URIhttps://accel-brain.co.jp/https://accel-brain.com/LicenseGNU General Public License v2.0
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algoworld-contracts
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๐ AboutThe following repository hosts the source codes for:AlgoWorld Swapper's algorand smart signatures.AlgoWorldExplorer's stateful smart contracts for card auctions and card trading. Modified version ofOpenNFT's smart contracts.โ ๏ธ NOTE: These contracts were created in collaboration with Solution Architect from Algorand (credits @cusma) and audited byTENSET security. Code is provided under MIT license.Prerequisitespoetrypre-commitAlgorand SandboxDocker๐ OverviewAlgoWorld currently offers several smart signatures used for swapping on AlgoWorld Swapper.If you are looking to install algoworld contracts into your project run the following command:pipinstallalgoworld-contractsExample usagefromalgoworld_contractsimportcontracts# Replace inputParams with real valuesasa_to_asa_swap=contracts.get_swapper_teal(inputParams.creator_address,inputParams.offered_asa_id,inputParams.offered_asa_amount,inputParams.requested_asa_id,inputParams.requested_asa_amount,inputParams.incentive_wallet,inputParams.incentive_fee,)# asa_to_asa_swap is a string of TEAL coderesponse=algod.compile(asa_to_asa_swap)...SwapperThere are two main types of smart signatures available:ASA to ASA swap | ๐ดโ๏ธ๐ด: Smart signature that allows performing a swap of any single ASA of specified amount to any other single ASA of specified amount.Swap Configuration Proxy ๐: Smart signature that powers theAlgoWorld Swapperby allowing users to issue certain transactions that contain links to swap configuration files stored as.jsonfiles onipfs. Proxy is then used to obtain thoseipfsfiles by grabbing the latest pay transaction using Algorand Indexer queries.ASAs to ALGO swap | ๐ด๐ด๐ดโ๏ธ๐ฐ: Smart signature that allows performing a swap of multiple ASAs of specified amount to ALGO of specified amount.โ๏ธ InstallationThis section assumes that poetry and pre-commit are installed and executed from the root folder of this repository.Clone the repogitclonehttps://github.com/AlgoWorldNFT/algoworld-contractsInstall python requirementspoetryinstall# install all dependenciespoetryshell# activate virtual env(OPTIONAL) 3. Configurepre-commithookspre-commitinstallIf you are not going to setuppre-commitlocally, there is a Github Actions plugin that will autoformat your branch if you are opening a PR with commits that contain un-formatted code.๐งช TestingTesting assumes that docker-compose is installed and available. Project is relying onpytest-docker-composeplugin that automatically boots up temporary algorand sandbox and destroys the containers after the tests are finished.(.venv)pytestYou can also include[pytest]into your commit message to trigger the test in CI pipeline onpushaction (on pr it is triggered automatically).๐ง Contribution guidelineSeeCONTRIBUTING.mdโญ๏ธ StargazersSpecial thanks to everyone who forked or starred the repository โค๏ธ
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algoworld-contracts-legacy
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๐ AboutThe following repository hosts the source codes for:AlgoWorld Swapper's algorand smart signatures.AlgoWorldExplorer's stateful smart contracts for card auctions and card trading. Modified version ofOpenNFT's smart contracts.โ ๏ธ NOTE: These contracts are not formally audited by accredited third parties. However, contracts are a basis for certain functionality on the AlgoWorldExplorer.io platform and were created in collaboration with Solution Architect from Algorand (credits @cusma). Code is provided under MIT license.Prerequisitespoetrypre-commitAlgorand SandboxDocker๐ OverviewAlgoWorld currently offers stateful contracts used for auction trading on AlgoWorldExplorer and several smart signatures used for swapping on AlgoWorld Swapper.If you are looking to install algoworld contracts into your project run the following command:pipinstallalgoworld-contractsExample usagefromalgoworld_contractsimportcontracts# Replace inputParams with real valuesasa_to_asa_swap=contracts.get_swapper_teal(inputParams.creator_address,inputParams.offered_asa_id,inputParams.offered_asa_amount,inputParams.requested_asa_id,inputParams.requested_asa_amount,inputParams.incentive_wallet,inputParams.incentive_fee,)# asa_to_asa_swap is a string of TEAL coderesponse=algod.compile(asa_to_asa_swap)...SwapperThere are two main types of smart signatures available:ASA to ASA swap | ๐ดโ๏ธ๐ด: Smart signature that allows performing a swap of any single ASA of specified amount to any other single ASA of specified amount.Swap Configuration Proxy ๐: Smart signature that powers theAlgoWorld Swapperby allowing users to issue certain transactions that contain links to swap configuration files stored as.jsonfiles onipfs. Proxy is then used to obtain thoseipfsfiles by grabbing the latest pay transaction using Algorand Indexer queries.ASAs to ALGO swap | ๐ด๐ด๐ดโ๏ธ๐ฐ: Smart signature that allows performing a swap of multiple ASAs of specified amount to ALGO of specified amount.AuctionA set of stateful smart contracts for card auctions and card trading:ASAs for ALGO with trades and bidding | ๐ด๐ฐ๐จ:Allows trading ASA via auctions, selling or purchasing directly.โ๏ธ InstallationThis section assumes that poetry and pre-commit are installed and executed from the root folder of this repository.Clone the repogitclonehttps://github.com/AlgoWorldNFT/algoworld-contractsInstall python requirementspoetryinstall# install all dependenciespoetryshell# activate virtual env(OPTIONAL) 3. Configurepre-commithookspre-commitinstallIf you are not going to setuppre-commitlocally, there is a Github Actions plugin that will autoformat your branch if you are opening a PR with commits that contain un-formatted code.๐งช TestingTesting assumes that docker-compose is installed and available. Project is relying onpytest-docker-composeplugin that automatically boots up temporary algorand sandbox and destroys the containers after the tests are finished.(.venv)pytestYou can also include[pytest]into your commit message to trigger the test in CI pipeline onpushaction (on pr it is triggered automatically).๐ง Contribution guidelineSeeCONTRIBUTING.mdโญ๏ธ StargazersSpecial thanks to everyone who forked or starred the repository โค๏ธ
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algoxtools
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algoxtoolsA practical implementation of Donald Knuth's Algorithm X in Python using Numpy and Numba.Open sourced implementations ofAlgorithm Xin Python are plentiful.Justification of creating algoxtools is that although existing packages are compact and elegantly coded in object oriented PythonA drawback is that for more complex exact cover problems processing the Python interpreted node objects used in the NP-complete algorithm becomes slow. Since use of classes in Python has a poor relation with source to source compilers such as Numba, resulting speed gains of running them through a compiler are discouraging.In algoxtools the web of dr. Knuth's Dancing Links is embedded in a numpy array. Since numpy arrays are homogeneous by design and boast high performance libraries, algoxtools aims to come more close to machine level than existing Python solutions by densifying the actual process.The array space used by algoxtools is 3d, arranged in rows, columns, the third dimension being used for substitutes of class attributes such as pointers and index values. Headers for rows and columns as well as meta data such as current row, column, level and solution at hand are all embedded in the array as well, making the variables as easy to pass such as a conventional object.Algoxtools facilitates unlinking and relinking of rows and columns at once by eleborate indexing which avoids handling each individual node chain*.Moreover the indexing used shakes off the need for recursion, which allows for effortless returns to caller level from a single function.The array organisation is sparse and uses 16 bit ints. If needed, int size can be easily adapted.Dynamic allocation of nodes could further optimize use of memory and squeeze out a bit of performance gain, but remains to be implemented.Installationpip install algoxtoolsApi exampleData taken fromWikipediaimport algoxtools as axt
import numpy as np
INDEX, META, SOLUTIONCOUNT,SOLUTION, VALUE = 0, -1, 0, 1, -1
dt = np.int16
# Initialize array
array = axt.init( 6, 7 )
# Assign nodes. Rows and cols start from 1!
axt.annex_row( array, 1, np.array([ 1, 4, 7 ], dt ) )
axt.annex_row( array, 2, np.array([ 1, 4 ], dt ) )
axt.annex_row( array, 3, np.array([ 4, 5, 7 ], dt ) )
axt.annex_row( array, 4, np.array([ 3, 5, 6 ], dt ) )
axt.annex_row( array, 5, np.array([ 2, 3, 6, 7 ], dt ) )
axt.annex_row( array, 6, np.array([ 2, 7 ], dt ) )
# Get result
ii = array[ INDEX, INDEX ]
print('Solution:')
while axt.exact_cover( array ):
print( array[ META, SOLUTION : ii[VALUE], VALUE ] )Solution:
[2 4 6]Above example is enclosed in jupyter notebook format in theexamples folderQuick api reference guide:array = init( rows, columns )Initializes algoxtools array.Internally the number of columns is one higher than the given value and is used for indexing.The internal number of rows is two higher than the given value and is used for indexing and storing meta dataRows and columns values cannot exceed the np.int16 maximum value - 1 (+32,766)Example:import algoxtools as axt
array = axt.init( 6, 7 )annex_row( array, row_number, numpy.array( column 1, column 2, .. column n , numpy.int16) )Assigns linked nodes to the specified columns in a specific row.row and col values should be higher than 1 and cannot exceed numpy.int16 maximum value - 1In order to solve an exact cover, all rows must contain at least one node.Example:axt.annex_row( array, 4, np.array([ 3, 5, 6 ], np.int16 ) )bool exact_cover( array )This is the main function allowing to flip through the exact covers, it returns a boolean True if an exact cover solution is reached and returns a boolean False if finished.Example:while axt.exact_cover( array )
print( array[ -1, 1 : array[ 0,0,-1 ], -1 ] )Miscellaneous functions used internallybool isempty( array )Returns boolean True if an exact cover is reached else returns a FalseExample:if axt.isempty( array ):
## Exact cover found
level = array[ 0, 0, -1 ]
print( array[ -1, 1:level, -1 ]bool mcr_cover( array )Minimum column rows cover (Or Most-constrained column rows cover) is a composite of the internal min_col() and cover() functions.Initialy it selects the first column with the least number of nodes and the first row in that column as an entry, after which it covers the nodes linked to that entry.In subsequent calls mcr_cover selects a next row entry in that column and covers it until all rows are depleted.Returns a boolean False if no more rows are available, else returns a TrueBalanced by Uncover, this function can be used recurively as well as in a flat loop.void uncover( array )Uncover the nodes previously linked to current row and colum entry in the array (selected by mcr_cover)Internal organisation of algoxtools array:0,0 Index,Index------------- Column Indices ----------------------- 0,-1
| Node 1,1 Node 1,2 Node 1,Columns
| Node 2,1 Node 2,2 Node 2,Columns
Row
indices | | |
| | | |
|
| Node Rows,1 Node Rows,2 Node Rows,Columns
-1,0 --------------------------- Meta data ---------------------- -1, -1NB The row and column indices are basically unlinked nodes keeping track of entry positions and node countSpecific array locations used in api'sLevel: array[ 0, 0,-1 ]
Solution count: array[-1, 0, 0 ]
Solution row numbers: array[-1, 1: level, -1 ]Node attributesName Description Value
---------------------------------------
L Left link pointer 0
R Right link pointer 1
U Up link pointer 2
D Down link pointer 3
LINKED Node or index link status 4
VALUE Stores miscellaneous values 5 (-1)Usage examples of internal functions:1. Recursive solver:import algoxtools as axt
INDEX, META, SOLUTIONCOUNT, VALUE, SOLUTION = 0, -1, 0, -1, 1
ii = array[ INDEX, INDEX ]
def search(array): # Level up
ii[VALUE] += 1
if axt.isempty(array):
print( array[ META, SOLUTION : ii[VALUE], VALUE ] )
else:
while axt.mcr_cover(array):
search(array)
axt.uncover(array)
ii[VALUE] -= 1 # Level down
search( array )2. Flat loop solver:This example of an exact_cover function is taken from the source code of algoxtools
Note that this function can be compiled while still being able to hop in and out to interpreter level with resultsimport algoxtools as axt
from numba import njit
INDEX, META, SOLUTIONCOUNT, VALUE, SOLUTION = 0, -1, 0, -1, 1
@njit
def exact_cover( array ):
INDEX, VALUE, META, SOLUTIONCOUNT = 0, -1, -1, 0
ii = array[ INDEX, INDEX ]
if ii[VALUE] == 0:
# First time:
# Reset solution counter
array[ META, SOLUTIONCOUNT, VALUE ] = 0
# Level up
ii[VALUE] += 1
else:
# Consecutive time, Level down
ii[VALUE] -= 1
if ii[VALUE] == 0:
return False
# Uncover preceding exact cover
uncover(array)
while True:
# If any left, get next row in column with minimum node count and cover it
if mcr_cover(array):
# Level up
ii[VALUE] += 1
# If exact cover found, hop in and out with result
if isempty(array):
return True
# Else backtrack
else:
# Level down
ii[VALUE] -= 1
if ii[VALUE] == 0:
# Exit loop
return False
# Uncover preceding trivial cover
uncover(array)
ii = array[ INDEX, INDEX ]
while exact_cover( array ):
print( array[ META, SOLUTION : ii[VALUE], VALUE ] )* Unlinking and relinking nodes:The illustration below which is taken fromWikipediashows how nodes are covered in algoxtools:In the example the entry at column 1, row 1 is heuristically chosen to be covered.Since the nodes at the red ones in Columns (1,4,7) and rows (A,B,C,E,F) are not linked to any other outside nodes, they are unlinked just by row and column index without unlinking each individual node.In the example the remaining ones in the red boxes, (C5,E2,E3,E6 and F2) are what I call 'loose nodes'.They are situated in an unlinked row but not in an unlinked column and are possibly attached to external nodes. So, unlike the other nodes which are left untouched, loose nodes are handled individually ie. unlinked and relinked one by one.NB common in most other implementations of Algorithm X only the down link of the upper node and the up link of the down nodes are changed, right and left links do not need to be modified since the row being made inactive they are not externally referenced.
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algoz
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algozMake use of 3za from within Algorithmia
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algpred2
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AlgPred2.0IntroductionAlgPred2.0 is developed for predicting, mapping and scanning allergen peptides. More information on AlgPred2.0 is available from its web serverhttp://webs.iiitd.edu.in/raghava/. This page provides information about standalone version of AlgPred2.0.Minimum USAGE: Minimum ussage is "algpred2 -i peptide.fa" where peptide.fa is an input fasta file. This will predict Allergenic peptides in fasta format. It will use other parameters by default. It will save output in "outfile.csv" in CSV (comma seperated variables).Full Usage: Following is complete list of all options, you may get these options by "algpred2 -h"algpred2 [-h] -i INPUT [-o OUTPUT] [-t THRESHOLD] [-m {1,2}] [-d {1,2}]Please provide following argumentsoptional arguments:-h, --help show this help message and exit
-i INPUT, --input INPUT
Input: protein or peptide sequence in FASTA format or
single sequence per line in single letter code
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-t THRESHOLD, --threshold THRESHOLD
Threshold: Value between 0 to 1 by default 0.3
-m {1,2}, -- model Model
Model: 1: AAC based RF, 2: Hybrid, by default 1
-d {1,2}, --display {1,2}
Display: 1:Allergen peptide, 2: All peptides, by
default 1Input File: It allows users to provide input in two formats; i) FASTA format (standard) (e.g. peptide.fa) and ii) Simple Format. In case of simple format, file should have one one peptide sequence in a single line in single letter code (eg. peptide.seq).Output File: Program will save result in CSV format, in case user do not provide output file name, it will be stored in outfile.csv.Threshold: User should provide threshold between 0 and 1, please note score is proportional to allergenic potential of peptide.Models: In this program, two models have beeen incorporated; i) Model1 for predicting given input peptide/protein sequence as Allergenic and Non-allergenic peptide/proteins using Random Forest based on amino-acid composition of the peptide/proteins;ii) Model2 for predicting given input peptide/protein sequence as Allergenic and Non-allergenic peptide/proteins using Hybrid approach, which is the ensemble of Random Forest+ BLAST+ MERCI. It combines the scores generated from machine learning (RF), MERCI, and BLAST as Hybrid Score, and the prediction is based on Hybrid Score.
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algpro
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ๅบไป็ป่ฟๆฏ็ฑALGๅทฅไฝๅฎค็ ๅ็ไธไธชๅฝๆฐๅบ๏ผ่ฟ้ๆไธๅฐ้ซๆๆจกๅ๏ผๆฌข่ฟๆจ็ไฝฟ็จๅผๅๆนALGๅทฅไฝๅฎคLanpasbyๅทฅไฝๅฎคไฝ่
๏ผไบๆณฝๅๅธ่
๏ผHuiBuBu
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algpromax
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Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content.
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algpros
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ๅฅฅๅฉ็ป้ซๆ็ผ็จๅบpycharm็๏ผ่ฟ้ๆฑ้ไบ่ฎธๅค้ซๆๆจกๅ๏ผ็ฑๅฅฅๅฉ็ป็กฌไปถ็งๆๅทฅไฝๅฎคๅถไฝ๏ผไธป่ฆไฝ่
๏ผไบๆณฝ
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algpros30
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ๅฅฅๅฉ็ป้ซๆ็ผ็จๅบ30ๆต่ฏ็๏ผ๏ผ๏ผ
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algpygame
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ๅฅฅๅฉ็ป็กฌไปถ็งๆๅทฅไฝๅฎคpygameๅฝๆฐๅบ
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algs4
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OverviewThis repository contains the Python source code for the algorithms in the textbookAlgorithms, 4th Editionby Robert Sedgewick and Kevin Wayne.The official Java source code ishere.GoalsMake a Python implementation of the library so that a Python programmer can follow this book easily or prefer to demonstrate the algorithms using Python.Try to keep the interface and variable name consistent with the original book while writing idiomatic Python code.Installpipinstallalgs4fromalgs4.stackimportStackIndex1 FUNDAMENTALSBagQueueStackUnionFind2 SORTINGSelectionInsertionShellMergeQuickQuick3WayMaxPQTopMIndexMinPQMultiwayHeap3 SEARCHINGFrequencyCounterSequentialSearchSTBinarySearchSTBSTRedBlackBSTSeparateChainingHashSTLinearProbingHashST4 GRAPHSGraphGraphDepthFirstSearchDepthFirstPathsBreadthFirstPathsCCCycleSymbolGraphDegreesOfSeparationDigraphDigraphDirectedDFSDirectedCycleDepthFirstOrderTopologicalKosarajuSCCMSTEdgeWeightedGraphLazyPrimMSTPrimMSTKruskalMSTShortest PathsEdgeWeightedDigraphDijkstraSPAcyclicSPBellmanFordSP5 STRINGLSDMSDQuick3stringTrieSTTSTKMPNFAHuffmanLZWLicenseThis code is released under MIT.Contribute to this repositoryIssue reports and code fixes are welcome. please follow the same style as the code in the repository and add test for your
code.contributing guide
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algs-ixi
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Example PyPI (Python Package Index) Package & Tutorial / Instruction / Workflow for 2021This is an examplePyPI(Python Package Index) package set up with automated tests and package publishing workflow using GitHub Actions CI/CD. It is made primarily for GitHub + VS Code (Windows / Mac / Linux) users who are about to write and publish their first PyPI package. The package could serve as a starter / boilerplate / demo and the tutorial could give you a quick and concise explaination to solve some small but annoying problems you might encounter, such as package / module name confusion, and VS Code test configuration issues.Differences from pypa/sampleproject (click to show/hide)This example package is inspired by / based on theofficial sample project pypa/sampleproject, but this package:is a simplified version of pypa/sampleproject (and theofficial Python Packaging User Guide)uses GitHub Actions for both testing and publishing, instead of Travis CIis tested when pushingmasterormainbranch, and is published when create a releaseincludes test files in the source distributionusessetup.cfgforversion single-sourcing(setuptools 46.4.0+)has.vscode\settings.jsonandvscode.envwhich addssrc/folder toPYTHONPATH, so that test files don't have linting errors and may run with pytest in VS Codedoes not use flake8 for automated linting - it is sometimes too strict and inflexible, you may use pylint locally insteadhas this tutorial that covers everything you need to know in one page. Everything that might not be very useful, is hidden in collapsible sections that you can click to showhas.editorconfigfileMake necessary changesUse as a template(Click the above button to use this example package as a template for your new GitHub repo, this will initialize a new repository and my commits will not be in your git history)(If you do not use GitHub, you candownload the archive of the example package)Package, module nameMany use a same package and module name, you could definitely do that. But this example package and its module's names are different:example_pypi_packageandexamplepy.Openexample_pypi_packagefolder with Visual Studio Code,Ctrl+Shift+F(Windows / Linux) orCmd+Shift+F(MacOS) to find all occurrences of both names and replace them with your package and module's names. Also remember to change the name of the foldersrc/examplepy.Simply and very roughly speaking, package name is used inpip install <PACKAGENAME>and module name is used inimport <MODULENAME>. Both names should consist of lowercase basic letters (a-z). They may have underscores (_) if you really need them. Hyphen-minus (-) should not be used.You'll also need to make sure the URL "https://pypi.org/project/example-pypi-package/" (replaceexample-pypi-packageby your package name, with all_becoming-) is not occupied.Details on naming convention (click to show/hide)Underscores (_) can be used but such use is discouraged. Numbers can be used if the name does not start with a number, but such use is also discouraged.Name starting with a number and/or containing hyphen-minus (-) should not be used: although technically legal, such name causes a lot of trouble โ users have to useimportlibto import it.Don't be fooled by the URL "pypi.org/project/example-pypi-package/" and the name "example-pypi-package" on pypi.org. pypi.org and pip system convert all_to-and use the latter on the website / inpipcommand, but the real name is still with_, which users should use when importing the package.There's alsonamespaceto use if you need sub-packages.Other changesMake necessary changes insetup.py.The package's version number__version__is insrc/examplepy/__init__.py. You may want to change that.The example package is designed to be compatible with Python 3.6, 3.7, 3.8, 3.9, and will be tested against these versions. If you need to change the version range, you should change:classifiers,python_requiresinsetup.pyenvlistintox.inimatrix: python:in.github/workflows/test.ymlIf you plan to upload toTestPyPIwhich is a playground ofPyPIfor testing purpose, changetwine upload --repository pypi dist/*totwine upload --repository testpypi dist/*in the file.github/workflows/release.yml.Developmentpippip is a Python package manager. You already have pip if you use Python 3.4 and later version which include it by default. Readthisto know how to check whether pip is installed. Readthisif you need to install it.Use VS CodeVisual Studio Code is the most popular code editor today, our example package is configured to work with VS Code.Install VS Code extension "Python"."Python" VS Code extension will suggest you install pylint. Also, the example package is configured to use pytest with VS Code + Python extensions, so, install pylint and pytest:pipinstallpylintpytest(It's likely you will be prompted to install them, if that's the case, you don't need to type and execute the command)vscode.env's content is nowPYTHONPATH=/;src/;${PYTHONPATH}which is good for Windows. If you use Linux or MacOS, you need to change it toPYTHONPATH=/:src/:${PYTHONPATH}(replacing;with:). If the PATH is not properly set, you'll see linting errors in test files and pytest won't be able to runtests/test_*.pyfiles correctly.Close and reopen VS Code. You can now click the lab flask icon in the left menu and run all tests there, with pytest. pytest seems better than the standard unittest framework, it supportsunittestthus you can keep usingimport unittestin your test files.The example package also has a.editorconfigfile. You may install VS Code extension "EditorConfig for VS Code" that uses the file. With current configuration, the EditorConfig tool can automatically use spaces (4 spaces for .py, 2 for others) for indentation, setUTF-8encoding,LFend of lines, trim trailing whitespaces in non Markdown files, etc.In VS Code, you can go to File -> Preferences -> Settings, type "Python Formatting Provider" in the search box, and choose one of the three Python code formatting tools (autopep8, black and yapf), you'll be prompted to install it. The shortcuts for formatting of a code file areShift+Alt+F(Windows);Shift+Option (Alt)+F(MacOS);Ctrl+Shift+I(Linux).Write your packageInsrc/examplepy/(examplepyshould have been replaced by your module name) folder, renamemodule1.pyand write your code in it. Add more module .py files if you need to.Write your testsIntests/folder, renametest_module1.py(totest_*.py) and write your unit test code (withunittest) in it. Add moretest_*.pyfiles if you need to.The testing tool `tox` will be used in the automation with GitHub Actions CI/CD. If you want to use `tox` locally, click to read the "Use tox locally" sectionUse tox locallyInstall tox and run it:pipinstalltox
toxIn our configuration, tox runs a check of source distribution usingcheck-manifest(which requires your repo to be git-initialized (git init) and added (git add .) at least), setuptools's check, and unit tests using pytest. You don't need to install check-manifest and pytest though, tox will install them in a separate environment.The automated tests are run against several Python versions, but on your machine, you might be using only one version of Python, if that is Python 3.9, then run:tox-epy39If you add more files to the root directory (example_pypi_package/), you'll need to add your file tocheck-manifest --ignorelist intox.ini.Thanks to GitHub Actions' automated process, you don't need to generate distribution files locally. But if you insist, click to read the "Generate distribution files" sectionGenerate distribution filesInstall toolsInstall or upgradesetuptoolsandwheel:python-mpipinstall--user--upgradesetuptoolswheel(Ifpython3is the command on your machine, changepythontopython3in the above command, or add a linealias python=python3to~/.bashrcor~/.bash_aliasesfile if you use bash on Linux)GeneratedistFromexample_pypi_packagedirectory, run the following command, in order to generate production version for source distribution (sdist) indistfolder:pythonsetup.pysdistbdist_wheelInstall locallyOptionally, you can install dist version of your package locally before uploading toPyPIorTestPyPI:pipinstalldist/example_pypi_package-0.1.0.tar.gz(You may need to uninstall existing package first:pipuninstallexample_pypi_packageThere may be several installed packages with the same name, so runpip uninstallmultiple times until it says no more package to remove.)Upload to PyPIRegister on PyPI and get tokenRegister an account onPyPI, go toAccount settings ยง API tokens, "Add API token". The PyPI token only appears once, copy it somewhere. If you missed it, delete the old and add a new token.(Register aTestPyPIaccount if you are uploading to TestPyPI)Set secret in GitHub repoOn the page of your newly created or existing GitHub repo, clickSettings->Secrets->New repository secret, theNameshould bePYPI_API_TOKENand theValueshould be your PyPI token (which starts withpypi-).Push or releaseThe example package has automated tests and upload (publishing) already set up with GitHub Actions:Every time yougit pushor a pull request is submitted on yourmasterormainbranch, the package is automatically tested against the desired Python versions with GitHub Actions.Every time a new release (either the initial version or an updated version) is created, the latest version of the package is automatically uploaded to PyPI with GitHub Actions.View it on pypi.orgAfter your package is published on PyPI, go tohttps://pypi.org/project/example-pypi-package/(_becomes-). Copy the command on the page, execute it to download and install your package from PyPI. (or test.pypi.org if you use that)If you want to modify the description / README of your package on pypi.org, you have to publish a new version.If you publish your package to PyPI manually, click to readInstall TwineInstall or upgrade Twine:python-mpipinstall--user--upgradetwineCreate a.pypircfile in your$HOME(~) directory, its content should be:[pypi]username=__token__password=<PyPI token>(Use[testpypi]instead of[pypi]if you are uploading toTestPyPI)Replace<PyPI token>with your real PyPI token (which starts withpypi-).(if you don't manually create$HOME/.pypirc, you will be prompted for a username (which should be__token__) and password (which should be your PyPI token) when you run Twine)UploadRun Twine to upload all of the archives underdistfolder:python-mtwineupload--repositorypypidist/*(usetestpypiinstead ofpypiif you are uploading toTestPyPI)UpdateWhen you finished developing a newer version of your package, do the following things.Modify the version number__version__insrc\examplepy__init__.py.Delete all old versions indist.Run the following command again to regeneratedist:pythonsetup.pysdistbdist_wheelRun the following command again to uploaddist:python-mtwineupload--repositorypypidist/*(usetestpypiinstead ofpypiif needed)ReferencesPython Packaging Authority (PyPA)'s sample projectPyPA's Python Packaging User GuideStackoverflow questions and answersGitHub Actions Guides: Building and testing PythonBtw, if you want to publish TypeScript (JavaScript) package to the npm registry, go toExample TypeScript Package ready to be published on npm for 2021.
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algtestprocess
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Algtest pyProcessA tool for simple visualizations of gathered TPM and JavaCard smart card data collected by tpm2-algtest and JCAlgtest tools respectively.Getting startedDependenciesPython 3 (see.requirements.txt)InstallingSetup virtual environmentpython -m venv venv
source venv/bin/activateInstall package usingpipor runsetup.pypip install -e .NOTEIf you are an user of fish shell, right command issource venv/bin/activate.fishUsagepyprocess commandAn entry point to the command line interface, which is used mostly to preprocess the datasets which are then analysed in jupyter notebooks.Commands:
tpm A collection of commands for processing of results from tpm2-algtest
javacard NOT YET IMPLEMENTEDtpm commandsmetadata-updateCommand which is used to find all measurements on a given path, and group them by exact firmware. The output ismetadata.jsonwhich contains these aggregated paths. Latter part of this file contains directory hashes, to prevent duplicate inclusion of the same measurement. An example ofmetadata.jsonfile is shown below.If you have already created ametadata.jsonfile and just want to add more measurements, you may use-ioption which takes path to oldmetadata.jsonfile.pyprocess tpm metadata-update ./results/tpmalgtest_results_2022
pyprocess tpm metadata-update -i metadata.json ./results/tpmalgtest_results_2023An example ofmetadata.jsonfile.{
"entries": {
"STM 73.4.17568.4452": {
"TPM name": "STM 73.4.17568.4452",
"vendor": "STM",
"title": "",
"measurement paths": [
"/home/tjaros/storage/research/tpm/tpmalgtest_results/out4/out",
"/home/tjaros/storage/research/tpm/tpmalgtest_results/algtest_result_8d400ec7-122c-498f-b141-733d359ad78f_STM",
"/home/tjaros/storage/research/tpm/tpmalgtest_results/algtest_result_9fdfdf94-3a4a-4cd3-9a92-86642f9f4f6c"
]
},
"AMD AMD 3.37.0.5": {
"TPM name": "AMD AMD 3.37.0.5",
"vendor": "AMD",
"title": "",
"measurement paths": [
"/home/tjaros/storage/research/tpm/tpmalgtest_results/algtest_result_70de7ce0-de7c-42bc-9f86-708d8304ad48"
]
},
},
"hashes": [
"862ad83383339467dbd687f3ebb2d075",
"7f78e96bd4fc47299cdbaa7cf1a1c1e3",
"3d6f2c211f00245d2a7b2c6458b3626a",
"2b3242fc08c73b608a227eea563f1531",
],
}LicenseThis project is licensed underMIT License- see the LICENSE file for details
|
alguiloop
|
AlGUILoopAlGUILoop allows to use while and for loops alongside without obstructing the GUI. This is currently for tkinter, PyQt5, PyQt6, wxPython, PyForms-GUI and PySide2.InstallationYou can install AlGUILoop fromPyPI:pip install alguiloop.The AlGUILoop supports Python 3.6 and above.UsageThere are following examples to use while and for loops alongside without obstructing the GUI using AlGUILoop :-"""
This script uses a while loop that lets to toggle switch while the GUI(tkinter) is still
responsive. After running the script -
ON: Switch 1
ON: Switch 2
ON: Switch 3
OFF: Switch 1
OFF: Switch 2
OFF: Switch 3
ON: Switch 1
ON: Switch 2
ON: Switch 3
CLICKED
OFF: Switch 1
OFF: Switch 2
OFF: Switch 3
CLICKED
"""
from tkinter import *
from AlGUILoop.AlGUILoop import AlGUILoop
@AlGUILoop
def toggleSwitch(argument):
while 1:
print("ON: " + argument)
yield 0.5 # time to wait
print("OFF: " + argument)
yield 0.5
root = Tk()
# you can run several loops at once:
toggleSwitch(root, 'Switch 1')
toggleSwitch(root, 'Switch 2')
toggleSwitch(root, 'Switch 3')
# add a responsive button
def click():
print('CLICKED')
Button(root, command = click, text = 'CLICK HERE').pack(fill=X)
# start the GUI loop
root.mainloop()"""
This script uses a while loop that lets to toggle switch while the GUI(tkinter) is still
responsive. It shows how loops can be started and stopped when GUI is responsive.
After running the script -
Switch ON
Switch OFF
Switch ON
Switch OFF
"""
from tkinter import *
from AlGUILoop.AlGUILoop import AlGUILoop, stopLoop
class StartAndStoopLoop():
def __init__(self):
root = Tk()
@AlGUILoop
def toggleSwitch():
while 1:
print("Switch ON")
yield 0.5 # time to wait
print("Switch OFF")
yield 0.5
def start():
self.generator = toggleSwitch(root)
def stop():
stopLoop(self.generator)
# This button will start the loop
b1 = Button(root, command = start, text = 'START')
b1.pack(fill=X)
# This button will stop the loop
b2 = Button(root, command = stop, text = 'STOP')
b2.pack(fill=X)
root.mainloop()
if __name__ == "__main__":
StartAndStoopLoop()"""
This script uses a while loop that lets to toggle switch while the GUI(PyQt5) is still
responsive. After running the script -
ON: Switch 1
ON: Switch 2
ON: Switch 3
OFF: Switch 1
OFF: Switch 2
OFF: Switch 3
CLICKED
ON: Switch 1
ON: Switch 2
ON: Switch 3
"""
from PyQt5 import QtWidgets
import sys
from AlGUILoop.AlGUILoop import AlGUILoop
@AlGUILoop
def toggleSwitch(argument):
while 1:
print("ON: " + argument)
yield 0.5 # time to wait
print("OFF: " + argument)
yield 0.5
app = QtWidgets.QApplication(sys.argv)
# add a responsive button
def click():
print('CLICKED')
window = QtWidgets.QPushButton()
window.setText('CLICK')
window.clicked.connect(click)
window.show()
# you can run several loops at once:
toggleSwitch(window, 'Switch 1')
toggleSwitch(window, 'Switch 2')
toggleSwitch(window, 'Switch 3')
sys.exit(app.exec_())"""
This script uses a while loop that lets to toggle switch while the GUI(PyQt5) is still
responsive. It shows how loops can be started and stopped when GUI is responsive.
After running the script -
Switch ON
Switch OFF
Switch ON
Switch OFF
"""
from PyQt5.QtWidgets import *
import sys
from AlGUILoop.AlGUILoop import AlGUILoop, stopLoop
class StartAndStoopLoop(QWidget):
def __init__(self):
super().__init__()
self.w = QVBoxLayout(self)
self.w.setContentsMargins(2, 2, 2, 2)
self.w.setSpacing(0)
self.w1 = QPushButton()
self.w2 = QPushButton()
self.w1.setText('START')
self.w2.setText('STOP')
self.w.addWidget(self.w1)
self.w.addWidget(self.w2)
self.w1.clicked.connect(self.start)
self.w2.clicked.connect(self.stop)
self.show()
@AlGUILoop
def toggleSwitch(self):
while 1:
print("Switch ON")
yield 0.5 # time to wait
print("Switch OFF")
yield 0.5
def start(self):
self.generator = self.toggleSwitch()
def stop(self):
stopLoop(self.generator)
if __name__ == "__main__" :
App = QApplication(sys.argv)
window = StartAndStoopLoop()
sys.exit(App.exec())"""
This script uses a while loop that lets to toggle switch while the GUI(PyQt6) is still
responsive. After running the script -
ON: Switch 1
ON: Switch 2
ON: Switch 3
OFF: Switch 1
OFF: Switch 2
OFF: Switch 3
CLICKED
ON: Switch 1
ON: Switch 2
ON: Switch 3
"""
from PyQt6 import QtWidgets
import sys
from AlGUILoop.AlGUILoop import AlGUILoop
@AlGUILoop
def toggleSwitch(argument):
while 1:
print("ON: " + argument)
yield 0.5 # time to wait
print("OFF: " + argument)
yield 0.5
app = QtWidgets.QApplication(sys.argv)
# add a responsive button
def click():
print('CLICKED')
window = QtWidgets.QPushButton()
window.setText('CLICK')
window.clicked.connect(click)
window.show()
# you can run several loops at once:
toggleSwitch(window, 'Switch 1')
toggleSwitch(window, 'Switch 2')
toggleSwitch(window, 'Switch 3')
sys.exit(app.exec_())"""
This script uses a while loop that lets to toggle switch while the GUI(PyQt6) is still
responsive. It shows how loops can be started and stopped when GUI is responsive.
After running the script -
Switch ON
Switch OFF
Switch ON
Switch OFF
"""
from PyQt6.QtWidgets import *
import sys
from AlGUILoop.AlGUILoop import AlGUILoop, stopLoop
class StartAndStoopLoop(QWidget):
def __init__(self):
super().__init__()
self.w = QVBoxLayout(self)
self.w.setContentsMargins(2, 2, 2, 2)
self.w.setSpacing(0)
self.w1 = QPushButton()
self.w2 = QPushButton()
self.w1.setText('START')
self.w2.setText('STOP')
self.w.addWidget(self.w1)
self.w.addWidget(self.w2)
self.w1.clicked.connect(self.start)
self.w2.clicked.connect(self.stop)
self.show()
@AlGUILoop
def toggleSwitch(self):
while 1:
print("Switch ON")
yield 0.5 # time to wait
print("Switch OFF")
yield 0.5
def start(self):
self.generator = self.toggleSwitch()
def stop(self):
stopLoop(self.generator)
if __name__ == "__main__" :
App = QApplication(sys.argv)
window = StartAndStoopLoop()
sys.exit(App.exec())"""
This script uses a while loop that lets to toggle switch while the GUI(wxPython) is still
responsive. After running the script -
ON: Switch 1
ON: Switch 2
ON: Switch 3
OFF: Switch 3
OFF: Switch 2
OFF: Switch 1
ON: Switch 2
ON: Switch 3
ON: Switch 1
CLICKED
OFF: Switch 3
OFF: Switch 2
OFF: Switch 1
"""
import wx
from AlGUILoop.AlGUILoop import AlGUILoop
@AlGUILoop
def toggleSwitch(argument):
while 1:
print("ON: " + argument)
yield 0.5 # time to wait
print("OFF: " + argument)
yield 0.5
def click(event):
print('CLICKED')
app = wx.App()
frame = wx.Frame(None, size = (50,60))
panel = wx.Panel(frame)
gridSizer = wx.GridSizer(1, 1, 0, 0)
button = wx.Button(panel, label = 'CLICK')
button.Bind(wx.EVT_BUTTON, click)
gridSizer.Add(button, 0, wx.EXPAND)
panel.SetSizer(gridSizer)
frame.Show()
# you can run several loops at once:
toggleSwitch(frame, 'Switch 1')
toggleSwitch(frame, 'Switch 2')
toggleSwitch(frame, 'Switch 3')
app.MainLoop()"""
This script uses a while loop that lets to toggle switch while the GUI(wxPython) is still
responsive. It shows how loops can be started and stopped when GUI is responsive.
After running the script -
Switch ON
Switch OFF
Switch ON
Switch OFF
"""
import wx
from AlGUILoop.AlGUILoop import AlGUILoop, stopLoop
class StartAndStoopLoop(wx.Frame):
def __init__(self, parent):
super(StartAndStoopLoop, self).__init__(parent, size = (50,100))
panel = wx.Panel(self)
gridSizer = wx.GridSizer(2,1,0,0)
b1 = wx.Button(panel, label='START')
b2 = wx.Button(panel, label='STOP')
b1.Bind(wx.EVT_BUTTON, self.start)
b2.Bind(wx.EVT_BUTTON, self.stop)
gridSizer.Add(b1,0,wx.EXPAND)
gridSizer.Add(b2,0,wx.EXPAND)
panel.SetSizer(gridSizer)
self.Centre()
self.Show()
@AlGUILoop
def toggleSwitch(self):
while 1:
print("Switch ON")
yield 0.5 # time to wait
print("Switch OFF")
yield 0.5
def start(self,event):
self.generator = self.toggleSwitch()
def stop(self,event):
stopLoop(self.generator)
app = wx.App()
StartAndStoopLoop(None)
app.MainLoop()"""
This script uses a while loop that lets to toggle switch while the GUI(PyForms-GUI) is
still responsive. After running the script -
ON: Switch 1
ON: Switch 2
ON: Switch 3
OFF: Switch 1
OFF: Switch 2
OFF: Switch 3
CLICKED
ON: Switch 1
ON: Switch 2
ON: Switch 3
OFF: Switch 1
OFF: Switch 2
OFF: Switch 3
"""
from pyforms import start_app
from pyforms.basewidget import BaseWidget
from pyforms.controls import ControlButton
from AlGUILoop.AlGUILoop import AlGUILoop
class Toggle(BaseWidget):
def __init__(self, *args, **kwargs):
super().__init__('Computer vision algorithm example')
self.button = ControlButton('CLICK')
self.button.value = self.click
self._formset = [ 'button']
self.toggleSwitch('Switch 1')
self.toggleSwitch('Switch 2')
self.toggleSwitch('Switch 3')
def click(self):
print('CLICKED')
@AlGUILoop
def toggleSwitch(self,argument):
while 1:
print("ON: " + argument)
yield 0.5
print("OFF: " + argument)
yield 0.5
if __name__ == '__main__':
start_app(Toggle, geometry=(50, 70, 50, 20))"""
This script uses a while loop that lets to toggle switch while the GUI(PyForms-GUI) is
still responsive. It shows how loops can be started and stopped when GUI is responsive.
After running the script -
Switch ON
Switch OFF
Switch ON
Switch OFF
"""
from pyforms import start_app
from pyforms.basewidget import BaseWidget
from pyforms.controls import ControlButton
from AlGUILoop.AlGUILoop import AlGUILoop, stopLoop
class StartAndStoopLoop(BaseWidget):
def __init__(self, *args, **kwargs):
super().__init__('Computer vision algorithm example')
self.b1 = ControlButton('START')
self.b2 = ControlButton('STOP')
self.b1.value = self.start
self.b2.value = self.stop
self._formset = [
'b1',
'b2'
]
@AlGUILoop
def toggleSwitch(self):
while 1:
print("Switch ON")
yield 0.5 # time to wait
print("Switch OFF")
yield 0.5
def start(self):
self.generator = self.toggleSwitch()
def stop(self):
stopLoop(self.generator)
if __name__ == '__main__':
start_app(StartAndStoopLoop, geometry=(50, 70, 50, 40))"""
This script uses a while loop that lets to toggle switch while the GUI(PySide2) is still
responsive. After running the script -
ON: Switch 1
ON: Switch 2
ON: Switch 3
OFF: Switch 1
OFF: Switch 2
OFF: Switch 3
CLICKED
ON: Switch 1
ON: Switch 2
ON: Switch 3
"""
from PySide2 import QtWidgets
import sys
from AlGUILoop.AlGUILoop import AlGUILoop
@AlGUILoop
def toggleSwitch(argument):
while 1:
print("ON: " + argument)
yield 0.5 # time to wait
print("OFF: " + argument)
yield 0.5
app = QtWidgets.QApplication(sys.argv)
# add a responsive button
def click():
print('CLICKED')
window = QtWidgets.QPushButton()
window.setText('CLICK')
window.clicked.connect(click)
window.show()
# you can run several loops at once:
toggleSwitch(window, 'Switch 1')
toggleSwitch(window, 'Switch 2')
toggleSwitch(window, 'Switch 3')
sys.exit(app.exec_())"""
This script uses a while loop that lets to toggle switch while the GUI(PySide2) is still
responsive. It shows how loops can be started and stopped when GUI is responsive.
After running the script -
Switch ON
Switch OFF
Switch ON
Switch OFF
"""
from PySide2.QtWidgets import *
import sys
from AlGUILoop.AlGUILoop import AlGUILoop, stopLoop
class StartAndStoopLoop(QWidget):
def __init__(self):
super().__init__()
self.w = QVBoxLayout(self)
self.w.setContentsMargins(2, 2, 2, 2)
self.w.setSpacing(0)
self.w1 = QPushButton()
self.w2 = QPushButton()
self.w1.setText('START')
self.w2.setText('STOP')
self.w.addWidget(self.w1)
self.w.addWidget(self.w2)
self.w1.clicked.connect(self.start)
self.w2.clicked.connect(self.stop)
self.show()
@AlGUILoop
def toggleSwitch(self):
while 1:
print("Switch ON")
yield 0.5 # time to wait
print("Switch OFF")
yield 0.5
def start(self):
self.generator = self.toggleSwitch()
def stop(self):
stopLoop(self.generator)
if __name__ == "__main__" :
App = QApplication(sys.argv)
window = StartAndStoopLoop()
sys.exit(App.exec_())Licenseยฉ 2021 Alankar SinghThis repository is licensed under the MIT license. See LICENSE for details.
|
alguns
|
AlgunsAlguns is a symmetric encryption method that contains 2 keys, without which decryption of the message is impossible.Alguns also uses 128-bit AES in CBC mode and PKCS7 padding.Letters and symbols are encrypted using the replacement method generate_replacement. A replacement character for a letter consists of [randomSymbol, randomNumber(0,99), randomSymbol, randomNumber(0,99)].
A Alguns key as returned by the generate_key actually contains two 16-byte keys:
A signing key used to sign the HMAC.A private key used by the encryption.
These two values are concatenated to form a 32 byte value. This 32 byte key is then encoded using Base64 encoding. This encodes the binary quantity as string of ASCII characters. The variant of Base64 used is URL and filename safe, meaning that it doesn't contain any characters that aren't permitted in a URL or a valid filename in any major operating system.Supported Languages:RussianEnglishInstallationThe installation method for this module is shown below.pip3 install algunsHow generate keys?key=Alguns.generate_key()replacement=Alguns.generate_replacement()# Put this somewhere safe!How to encrypt a message?mykey=# My key that I created earlier.myreplacement=# My replacement that I created earlier.al=Alguns(key=mykey,replacement=myreplacement)msgcrypt=al.encrypt('Hellow it is my message! ะัะธะฒะตั, ััะพ ะผะพะต ัะพะพะฑัะตะฝะธะต...')print(msgcrypt)# gAAAAABewxb_nE1mbHgN7ma79_XAbh68hLblIFdX3czIEmUDCSFWxMXTTEdIU5...How to decrypt a message?al=Alguns(key=mykey,replacement=myreplacement)msgdecrypt=al.decrypt('gAAAAABewxb_nE1mbHgN7ma79_XAbh68hLblIFdX3czIEmUDCSFWxMXTTEdIU5...')print(msgdecrypt)# Hellow it's my message! ะัะธะฒะตั, ััะพ ะผะพะต ัะพะพะฑัะตะฝะธะต...
|
algviz
|
Algvizไธญๆไป็ปๆๆกฃWhat is algviz?Algvizis an algorithm animation engine for your Python code inJupyter, which supports multiple data structures such asvector,table,linked_list,treeandgraph.VectorTableTreeGraphYou can get live algorithm animation after bringing some algviz interfaces to your algorithm.
For example, this code below shows the bubble sort algorithm:Click to show the code exampleimportalgvizdefbubble_sort(data):viz=algviz.Visualizer(0.5)vector=viz.createVector(data,cell_size=(40,160),histogram=True)foriinrange(len(vector)):forjinrange(len(vector)-i-1):ifvector[j]>vector[j+1]:vector.mark(algviz.cRed,j)vector.mark(algviz.cGreen,j+1)viz.display()vector.swap(j,j+1)else:vector.mark(algviz.cRed,j+1)vector.mark(algviz.cGreen,j)viz.display()vector.mark(algviz.cGray,len(vector)-i-1,hold=True)vector.removeMark(algviz.cGray)viz.display()bubble_sort([5,4,-2,1,-1,3])The rendered animation looks like this:If you are interested in this project, please give me a starโญ, thanks!ExamplesReady to see the magic? Click this button to try more algorithms on Gitpod!Need to login with your github account.InstallationPlease follow thisinstallation guideto setup algviz.TutorialThistutorialgives you a quick start on using algviz.All the API references can be found atalgviz API reference.LicenseAlgviz uses GNU general publicLICENSE. You can use it freely for learning and communication. For the commercial usage, please contact the author.ContributionAny form of contribution is welcomed! Please feel free to report abugor create apull request.If you want to share your algorithms using algviz, you can create aPRfrom this repo: ๐algviz-launch.DiscussionQQ group:334605370Telegram:https://t.me/+mvF8Sivxr3thZWY1
|
alhambra
|
No description available on PyPI.
|
alhambra-mixes
|
For DNA 28, ourposter as a Jupyter notebook is available here.Our documentationis in the process of being written (latest git documentation is here); we also havea tutorial notebook(WIP).This package, alhambra_mixes, is a separate package containing thealhambra.mixeslibrary fromalhambramodified to be more compatible with Python < 3.10. Continued development on
mixes will take place here, and alhambra will be made to depend on this.The
name may change soon to something more unique.The mixes package is a Python library to systematically, efficiently, and safely
design recipes for mixes of many components, intended primarily for DNA
computation experiments. The library recursively tracks individual components
through layers of intermediate mixes, performs checks to ensure those layers of
mixes are possible, and allows verification that final samples will contain the
correct components at the correct concentrations. Incorporating reference
information from files such as DNA synthesis order details, the library
generates recipes for straightforward pipetting, even in mixes with many
components at different concentrations spread across several plates.Changelogv0.5.0An interim version release while larger changes are being made, so that users can make use of several important new features, and the pypi-available version fits well with the latest documentation.Adds anExperimentclass that can hold mixes and components, and keep track of volumes, etc.Adds volume/consumption tracking.Adds master/split mix functions.Fixes numerous minor bugs.
|
alhazen
|
Alhazen is a small, simple framework to facilitate running
experiments, written in Python, using cognitive models, or similar
applications, in multiple, parallel processes. It is only useful on
multi-core machines, though most modern machines are such; the more
cores, the more performance benefit you are likely to get by using it.
It also depends upon the experiment being structured as a large number
of identical, independent runs of the same activity, or of similar
activities. This is a common pattern, each such run usually
corresponding to a distinct virtual participant, or possibly a
collection of interacting participants.There isonline documentation of Alhazen,
and thesourcesare on Bitbucket.Alhazen requires Python version 3.7 or later. Recent versions of Mac OS X and recent Linux distributions
are likely to have a suitable version of Python pre-installed, but it may need to be invoked aspython3instead of justpython, which latter often runs a 2.x version of Python instead. Use of a virtual environment,
which is recommended, often obviates the need for thepython3/pythondistinction.
If it is not already installed, Python, for Windows, Mac OS X, Linux, or other Unices, can bedownloaded from python.org <http://www.python.org/download/>_, for free.Normally, assuming you are connected to the internet, to install Alhazen you should simply have to type at the command linepip install alhazenDepending upon various possible variations in how Python and your machine are configured
you may have to modify the above in various waysyou may need to ensure your virtual environment is activatedyou may need use an alternative scheme your Python IDE supportsyou may need to call itpip3instead of simplypipyou may need to precede the call topipbysudoyou may need to use some combination of the aboveIf you are unable to install Alhazen as above, you can insteaddownload a tarball <https://bitbucket.org/dfmorrison/alhazen/downloads/?tab=tags>_.
The tarball will have a filename something like alhazen-1.3.4.tar.gz.
Assuming this file is at/some/directory/alhazen-1.3.4.tar.gzinstall it by typing at the command linepip install /some/directory/alhazen-1.3.4.tar.gzAlternatively you can untar the tarball withtar -xf /some/directory/alhazen-1.3.4.tar.gzand then change to the resulting directory and typepython setup.py installAlhazen is released under the following MIT style license:Copyright (c) 2020-2022 Carnegie Mellon UniversityPermission is hereby granted, free of charge, to any person obtaining a copy of this
software and associated documentation files (the "Software"), to deal in the Software
without restriction, including without limitation the rights to use, copy, modify,
merge, publish, distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to the following
conditions:The above copyright notice and this permission notice shall be included in all copies
or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE
OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
|
alhazen-py
|
alhazen-pyThis repository contains a complete python implementation of the debugging toolAlhazen,
initially proposed by Kampmann et al. [KHZ2020].
With this reimplementation we not only provide a concise and fast version ofAlhazen,
we also include more machine learning models to explain the circumstances of failing programs.How to useAlhazenTo illustrateAlhazenโs capabilities, we start with a quick motivating example. First, let us introduce our program under test: The Calculator.importmathdefarith_eval(inp)->float:returneval(str(inp),{"sqrt":math.sqrt,"sin":math.sin,"cos":math.cos,"tan":math.tan})This infamous program accepts arithmetic equations, trigonometric functions and allows us to calculate the square root.
To help us determine faulty behavior, i.e., a crash, we implement an evaluation functionfromalhazen.oracleimportOracleResultdefprop(inp:str)->bool:try:arith_eval(inp)returnOracleResult.NO_BUGexceptValueError:returnOracleResult.BUGreturnOracleResult.UNDEFthat takes an input file and returns whether a bug occurred during the evaluation of the mathematical equations (BUG=True,NO_BUG=False).
We can now test the calculator with some sample inputs:inputs=['cos(10)','sqrt(28367)','tan(-12)','sqrt(-3)']print([(x,prop(x))forxininputs])The output looks like this:[('cos(10)', OracleResult.NO_BUG),
('sqrt(28367)', OracleResult.NO_BUG),
('tan(-12)', OracleResult.NO_BUG),
('sqrt(-3)', OracleResult.BUG)]We see thatsqrt(-3)results in the failure of our calculator program.
We can now useAlhazento learn the root causes of the program's failure.First, we need to define the input format of the calculator with a grammar:importstringgrammar={"<start>":["<arith_expr>"],"<arith_expr>":["<function>(<number>)"],"<function>":["sqrt","sin","cos","tan"],"<number>":["<maybe_minus><onenine><maybe_digits>"],"<maybe_minus>":["","-"],"<onenine>":[str(num)fornuminrange(1,10)],"<digit>":list(string.digits),"<maybe_digits>":["","<digits>"],"<digits>":["<digit>","<digit><digits>"],}Then, we can callAlhazenwith the grammar, some sample inputs, and the evaluation function (program under test).fromalhazenimportAlhazenalhazen=Alhazen(initial_inputs=inputs,grammar=grammar,evaluation_function=prop,)trees=alhazen.run()By default,Alhazenwill do10iterations of its refinement process.
Finally,Alhazenreturns the learned decision tree that describes the failure-inducing inputs.For our calculator, the learned decision tree looks something like this:We see that the failure occurs whenever we use thesqrt(x)function and the number x has a negative sign!Project StructureIn this repository, you find:thereimplementationandsource codeofAlhazen-py, anda complete introduction (jupyter-notebook) on how to useAlhazen-pyand how you can add your ownLearnersandGenerators.Install, Development, Testing, BuildInstallIf all external dependencies are available, a simple pip install alhazen-py suffices.
We recommend installingalhazen-pyinside a virtual environment (virtualenv):python3.10 -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install alhazen-pyNow, the alhazen command should be available on the command line within the virtual environment.Development and TestingFor development, we recommend usingalhazen-pyinside a virtual environment (virtualenv).
By thing the following steps in a standard shell (bash), one can run the Alhazen tests:git clone https://github.com/martineberlein/alhazen-py.git
cd alhazen-py/
python3.10 -m venv venv
source venv/bin/activate
pip install --upgrade pip
# Run tests
pip install -e .[dev]
python3 -m pytestBuildalhazen-pyis build locally as follows:git clone https://github.com/martineberlein/alhazen-py.git
cd alhazen-py/
python3.10 -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install --upgrade build
python3 -m buildThen, you will find the built wheel (*.whl) in the dist/ directory.ContributorsThe initial idea for writing the guide was to explain to our students at Humboldt-Universitรคt Zu Berlin how to useAlhazento determine the failure circumstances of a program.
The original notebooks were a joint project with my colleagueHoang Lam Nguyenfrom Humboldt-Universitรคt Zu Berlin.
|
ali50mpdf
|
Failed to fetch description. HTTP Status Code: 404
|
ali88
|
Failed to fetch description. HTTP Status Code: 404
|
alia
|
No description available on PyPI.
|
aliaa-distributions
|
No description available on PyPI.
|
aliad
|
ALiADA Library for Anomaly Detection (ALiAD)
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ali.aj
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No description available on PyPI.
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aliaksandr-custom-serializer
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No description available on PyPI.
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ali-alsofyani-123
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No description available on PyPI.
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alianator
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alianatoralianator is a Discord permission name resolver forPycord.
It takes Discord's API permission flags (e.g.manage_guild) and resolves them to their user-facing aliases (
e.g.Manage Server).Installation$pipinstallalianatorUsagealianator can resolve aliases fromdiscord.Permissionsobjects, integers, strings, tuples, lists of strings, and lists
of tuples.importalianatoralianator.resolve(arg,mode=mode)The optionalmodeflag can be used to specify which permissions should be resolved. IfmodeisTrue, only granted
permissions will be resolved; ifmodeisFalse, only denied permissions will be resolved; ifmodeisNone, all
permissions will be resolved. Ifmodeis not explicitly specified, it will default toTrue.importalianatorimportdiscord# Resolving from a discord.Permissions objectperms=discord.Permissions.general()aliases=alianator.resolve(perms)print(aliases)# ['Manage Channels', 'Manage Server', 'View Audit Log', 'Read Messages', 'View Server Insights', 'Manage Roles', 'Manage Webhooks', 'Manage Emojis and Stickers']# Resolving from an integerperms=3072aliases=alianator.resolve(perms)print(aliases)# ['View Channel', 'Send Messages and Create Posts']# Resolving from a stringperms="send_tts_messages"aliases=alianator.resolve(perms)print(aliases)# ['Send Text-To-Speech Messages']# Resolving from a tupleperms=("moderate_members",True)aliases=alianator.resolve(perms)print(aliases)# ['Timeout Members']# Resolving from a list of stringsperms=["manage_guild","manage_emojis"]aliases=alianator.resolve(perms)print(aliases)# ['Manage Server', 'Manage Emojis and Stickers']# Resolving from a list of tuplesperms=[("use_slash_commands",True),("use_voice_activation",True)]aliases=alianator.resolve(perms)print(aliases)# ['Use Application Commands', 'Use Voice Activity']That's about all there is to it. alianator does one thing and does it well.Licensealianator is released under theMIT License.
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alias
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AliasIdentity Management Container
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aliasanjarani
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This is very simple calculator that takes tow numbers and either add, subtract, multiply or divide them.Change Log0.0.1 (07/17/2023)First Release
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alias-cd
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No description available on PyPI.
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alias-copyi-AngleKMeans
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No description available on PyPI.
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alias-copyi-AnnKMeans
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No description available on PyPI.
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alias-copyi-BallKMeans
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No description available on PyPI.
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alias-copyi-ExpKMeans
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No description available on PyPI.
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alias-copyi-HamKMeans
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No description available on PyPI.
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alias-copyi-module-CDKM
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No description available on PyPI.
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alias-copyi-module-CenterlessClustering
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No description available on PyPI.
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alias-copyi-module-FCDMF
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No description available on PyPI.
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aliasdict
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This module helps users to make multiple keys dict with same value.
In addition to that, this dict automatically gzip-compress values.
So itโs very efficient.I hope this module helps you python programing in your lap-top PC.QuickstartInstall cachelite:pip install aliasdictThen you can use it.importaliasdictfromAliasDictadct=AliasDict()#if you don't need value compression, AliasDict(compress=False)#put a key-valueadct["YOUR_KEY"]="YOUR_VALUE"#set a alias to keyadct.set_alias("YOUR_KEY","YOUR_ALIAS")#get value by aliasadct["YOUR_ALIAS"]#save1withopen("PATH_TO_FILE","wb")asf:adct.dump(f)#save2withopen("PATH_TO_FILE","wb")asf:f.write(adct.dumps())#load1withopen("PATH_TO_FILE","rb")asf:adct=AliasDict.load(f)#load2withopen("PATH_TO_FILE","rb")asf:adct=AliasDict.loads(f.read())
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aliases
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A very small Python package for keeping track of aliases.Installationpip install aliasesDocumentationHere ๐
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aliasfile
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Define your per-directory command aliases in Yaml, to get quick
shortcuts (and avoid having to remember long commands).WARNING:This project is still experimental, and things may change
suddenly. Suggestions are welcome.ConfigurationConfiguration is held in a file, usually named./.aliases, as a
dictionary serialized in YAML format.The main section iscommands, a dict mapping alias names to their
specification.Command specificationcommand: command to be run, as a stringwill be tokenized viashlex.splitstring-format-style placeholders will be replaced:positional arguments ({},{1}) -> variadic arguments to the command..or explicit:{args[1]}environment:{env[USER]}vars (see below):{vars[USER]}extra arguments will be appended to the commandenv: environment for the commandnot considered in string formattingwill go through the same formatting as commandsvars: to be replaced in env/command formattingNoteswe want some way to prevent automatic appending of varargswe might want to use jinja for formatting, so we can have conditionals / defaultswe might want inheritance, rather than having โnestedโ aliasingExamplescommands:test:command:xvfb-run py.test --reuse-db -vvv ./tests/env:DJANGO_SETTINGS_MODULE:fooproject.settings.testingPYTHONPATH:"{env[HOME]}/Projects/fooproject"commands:manage:command:python manage.pyenv:DJANGO_SETTINGS_MODULE:fooproject.settings.testingPYTHONPATH:"{env[HOME]}/Projects/fooproject"LOG_LEVEL:DEBUGrunserver:command:aliasfile manage runservermigrate:command:aliasfile manage migrateshell:command:aliasfile manage shell
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alias-free-torch
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Alias-Free-TorchSimpletorchmodule implementation ofAlias-Free GAN.This repository includingAlias-Free GAN style lowpass sinc filter @filter.pyAlias-Free GAN style up/downsample @resample.pyAlias-Free activation @act.pyand test codes @./testNote: Since this repository is unofficial, filter and upsample could be different withofficial implementation.Still working! If you notice some error or typo, please open new issue!v0.0.8 is TESTEDUPDATE: You can download alias-free-torch frompippython-mpipinstallalias-free-torchRequirementsDue totorch.kaiser_windowandtorch.i0are implemeted after1.7.0, our repository needtorch>=1.7.0.Pytorch>=1.7.0For custom torch users,pipwill not check torch version.TODO2d sinc filter2d resampledevide 1d and 2d modulespip packagingrewrite upsampleUpsample pad size issue(Upsample) support calculation for [B,C,T/(H,W)] (now only supports [B,T/(H,W)] or [B,1,T/(H,W)])set filter as register buffer(Downsample & Filter) support calculation for [B,C,T/(H,W)] (now only supports [B,T/(H,W)] or [B,1,T/(H,W)])provide loadable ckpt for lower version of torchdocumentationTest results 1dFilter sineFilter noiseupsampledownsampleTest results 2dFilter L1 norm sineFilter noiseupsampledownsampleReferencesAlias-Free GANadefossez/juliusA. V. Oppenheim and R. W. Schafer.Discrete-Time Signal Processing. Pearson, International Edition, 3rd edition, 2010AcknowledgementThis work is done atMINDsLab Inc.Thanks to teammates at MINDsLab Inc.Hyoungkyu SongKang-wook KimDongho ChoiSang Hoon Woo
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alias-gen
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ALIAS-GEN ๐Shell aliases are shortcuts or abbreviations for commands that are used in a Unix/Linux shell. They can save you time if you have very long or complex commands that you frequently use. ALIAS-GEN is a script that will create bash/zsh/fish shell aliases automatically to simplify your command-line tasks.This script will create bash/zsh/fish shell aliases automatically. You can generate a new alias file by following the prompts, or use the--stdoutoption to print results directly in your terminal.Two types of aliases are suggested, the default algorithm matches all characters incrementally for each command, while the--use_min_aliasalgorithm aims to minimize the total length of characters per command.
Additionally,--use_min_aliasdoes not necessarily match all characters in the command.The freq (frequency) column shows how often each command was used. For now, this script only generates aliases for the first word in a command.
NOTE: Two character commands or less are not processed.By default, fish shell generates abbr (abbreviations) rather than aliases.RequirementsPython 3.6 or higher.No dependences required for installation.Install from pypipipinstallalias-genhttps://pypi.org/project/alias-gen/CLI UsageFull Help Menu:aliaser -hExample usage to generate the top 40 aliases:aliaser -n 40With stdout and min_alias:aliaser --stdout --use_min_aliasThe-sargument specifies the shell type. In this example,fishshell is used.aliaser -s fishThe-fargument allows you to specify a custom history file path.aliaser -s zsh -f ~/.custom_zsh_historyHow does it work?Thealiascolumn is generated by first sorting the most common commands found
in the history file, then aliases are generated for commands more than two
characters. These aliases just try to match character per character the given
command and will continue with more characters if there is a previous common
alias.Themin_aliascolumn tries to minimize the total length of chars disregarding
the rule of matching the command character per character. It is generated using
the first char of the command always, followed by easy to reach keyboard characters
defined as QUERTY layout middle row, top row, then bottom row.MiscI recommend using this script along with other shell plugins that help you remember
your alias or abbreviation. One example for fish shell isfish-abbreviation-tips.Buy me a coffeeHope you found this project helpful, consider buying a coffee to show your support.
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aliasify
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aliasifySupported environments:This project is in an early state and has only been tested on Windows 10 with Python 3.9 and Python 3.10.Installation:Install aliasify using pip:pip install aliasifyThe required language model for entity detection (~500mb) will automatically be downloaded the first time you run the program.Remove language model (to free up space):The language model is installed as an independent python package. To free up space and remove it again use the following command:pip uninstall en_core_web_trfUsage:Start the program using the command line:aliasifyAlternativelly (e.g. in an environment with blocked executables) start the program from a python session:importaliasifyaliasify.run()Once the program has started, you can use the following workflow:Copy a text into your clipboard.Press F9 to replace all entities in the text with placeholders.Use the text in chatGPT, e.g. ask ChatGPT to shorten it.Copy the response into your clipboard.Press F10 to restore the orginal entities in the modified text.Example:Copy the following text:Subject: Invitation to attend the International Conference on Climate Change
Dear Dr. James Smith,
I hope this email finds you well. My name is Maria Perez, and I am writing to invite you to the International Conference on Climate Change, which will be held in Geneva, Switzerland from May 1-4, 2023.
We have reviewed your research on climate change and the impact of carbon emissions on the environment, and believe that your insights and expertise would make a valuable contribution to our conference. We are particularly interested in your recent paper on the effects of climate change on marine ecosystems, which was published in the Journal of Environmental Science last year.
The conference will bring together leading experts, scientists, and policymakers from around the world to discuss the latest research and innovations in the field of climate change. This year's theme is "Innovative Solutions for a Sustainable Future", and we believe that your research aligns well with this focus.
In addition to presenting your research, you will have the opportunity to network with other experts in your field, attend panel discussions, and participate in workshops. The conference will also feature a keynote address from Dr. Rajesh Sharma, the director of the Climate Change Division at the United Nations.
We would be delighted if you could join us in Geneva for this important event. Please let us know if you are able to attend, and we will provide you with further details and instructions for registration.
Thank you for your consideration, and we look forward to hearing from you soon.
Best regards,
Maria Perez
Conference Coordinator
International Conference on Climate Change
Geneva, SwitzerlandNow, with the running aliasify program, press F9 and paste the text into chatGPT:Subject: Invitation to attend <<EVENT_000018>>
Dear Dr. <<PERSON_000019>>,
I hope this email finds you well. My name is <<PERSON_000020>>, and I am writing to invite you to <<EVENT_000018>>, which will be held in <<GPE_000022>>, <<GPE_000023>> from <<DATE_000024>>.
We have reviewed your research on climate change and the impact of carbon emissions on the environment, and believe that your insights and expertise would make a valuable contribution to our conference. We are particularly interested in your recent paper on the effects of climate change on marine ecosystems, which was published in <<ORG_000025>> <<DATE_000026>>.
The conference will bring together leading experts, scientists, and policymakers from around the world to discuss the latest research and innovations in the field of climate change. This <<DATE_000027>>'s theme is "Innovative Solutions for a Sustainable Future", and we believe that your research aligns well with this focus.
In addition to presenting your research, you will have the opportunity to network with other experts in your field, attend panel discussions, and participate in workshops. The conference will also feature a keynote address from Dr. <<PERSON_000028>>, the director of <<ORG_000029>> at <<ORG_000030>>.
We would be delighted if you could join us in <<GPE_000022>> for this important event. Please let us know if you are able to attend, and we will provide you with further details and instructions for registration.
Thank you for your consideration, and we look forward to hearing from you soon.
Best regards,
<<PERSON_000020>>
Conference Coordinator
<<EVENT_000035>>
<<GPE_000022>>, <<GPE_000023>>Let's have a look at the chatGPT response:Subject: Invitation to <<EVENT_000018>> in <<GPE_000022>>
Dear Dr. <<PERSON_000019>>,
We invite you to attend <<EVENT_000018>> on <<DATE_000024>> in <<GPE_000022>>, <<GPE_000023>>. We're impressed by your research on climate change and carbon emissions' effects on the environment, particularly your recent paper on climate change's impact on marine ecosystems in <<ORG_000025>> <<DATE_000026>>.
As a leading expert, scientist, and policymaker in the field of climate change, we believe your insights would make a valuable contribution to the conference. This year's theme is "Innovative Solutions for a Sustainable Future," aligning with your research.
You'll have the opportunity to present your research, participate in workshops, attend panel discussions, and network with other experts in the field. Our keynote speaker is Dr. <<PERSON_000028>>, the director of <<ORG_000029>> at <<ORG_000030>>.
Please let us know if you're available to join us. We'd be delighted to provide you with further registration instructions and details.
Thank you for your time, and we look forward to your response.
Best regards,
<<PERSON_000020>>
Conference Coordinator
<<EVENT_000035>> in <<GPE_000022>>, <<GPE_000023>>Copy the text into your clipboard and press F10. Then paste the result into your email program:Subject: Invitation to the International Conference on Climate Change in Geneva
Dear Dr. James Smith,
We invite you to attend the International Conference on Climate Change on May 1-4, 2023 in Geneva, Switzerland. We're impressed by your research on climate change and carbon emissions' effects on the environment, particularly your recent paper on climate change's impact on marine ecosystems in the Journal of Environmental Science last year.
As a leading expert, scientist, and policymaker in the field of climate change, we believe your insights would make a valuable contribution to the conference. This year's theme is "Innovative Solutions for a Sustainable Future," aligning with your research.
You'll have the opportunity to present your research, participate in workshops, attend panel discussions, and network with other experts in the field. Our keynote speaker is Dr. Rajesh Sharma, the director of the Climate Change Division at the United Nations.
Please let us know if you're available to join us. We'd be delighted to provide you with further registration instructions and details.
Thank you for your time, and we look forward to your response.
Best regards,
Maria Perez
Conference Coordinator
International Conference on Climate Change in Geneva, Switzerland
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aliasmatching
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Alias matchingaliasmatchingis a python package that provides tools for identifying users that have different aliases.
Tools are designed to support GitHub users ids: username, login, and e-mail.Installationpip install aliasmatchingDocumentationhttps://alias-matching.readthedocs.io/en/latest/overview.htmlMethodsaliasmatching/mathcinghas implementation of currently available matching methods:bird_matching- alias matching based onMining Email Social Networks
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alias_nester
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UNKNOWN
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alias.rc
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No description available on PyPI.
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alias-windows
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aliasManage command aliases in Windows.Installation>pipinstallalias-windowsBy default aliases are stored in%USERPROFILE%\Documents\Scripts\Aliases. You can set the directory to store aliases by changing the environment variable called%ALIASES_DIR%.Managing aliasesGet the list of available aliases:> alias
apktool, gsh, gst
> alias -v
apktool = %SOFTWARE%\apktool\apktool.bat %*
gsh = git show $*
gst = git status --short --branch %*Add an alias:> alias test=dir \b %*
Added testShow the alias:> alias g
gsh, gst
> alias test
dir \b %*Search for a text in alias commands:> alias -s apk
baksmali, smali
> alias -s apk -v
baksmali = %SOFTWARE%\apktool\apktool.bat d %*
smali = %SOFTWARE%\apktool\apktool.bat b %*Delete the alias:> alias -d test
Deleted testEnvironment variablesaliaschanges two variables:%ALIASES_DIR%Directory where aliases are stored.%PATH%Adds%ALIASES_DIR%to%PATH%.LicenseThis project is licensed under theMIT License.
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alib
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Alib provides simple testing without boilerplate. For example, ifmyfile.pycontains the line:7 * 8 == 54 # I'm not sure about this!then running:$ python -m alib.test myfile.pywill, because the test fails, report the test line and the nature of
the failure:line 3: 7 * 8 == 54 # I'm not sure about this!
(['Eq'], [ReturnValue(56), ReturnValue(54)])Exceptions are caught. The input line:(1 + '2') == 3 # Can we add a string to a number?produces:line 4: (1 + '2') == 3 # Can we add a string to a number?
(['Eq'], [ExceptionInstance(TypeError), ReturnValue(3)]This test line succeeds (because the left hand side raises the right
hand side).:(1 + '2') ** TypeError # We can't add a string to a number.To test all Python files in the folderpath/to/mydirrun the command:$ python -m alib.test path/to/mydir
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alib013
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Failed to fetch description. HTTP Status Code: 404
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alib13
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Failed to fetch description. HTTP Status Code: 404
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alibaba
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UNKNOWN
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alibabacloud
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Failed to fetch description. HTTP Status Code: 404
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alibabacloud-abfs20211230
|
English |็ฎไฝไธญๆAlibaba Cloud abfs SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_abfs20211230pipinstallalibabacloud_abfs20211230IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-acm20200206
|
English |็ฎไฝไธญๆAlibaba Cloud acm SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_acm20200206pipinstallalibabacloud_acm20200206IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-actiontrail20150928
|
English |็ฎไฝไธญๆAlibaba Cloud Actiontrail SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_actiontrail20150928pipinstallalibabacloud_actiontrail20150928IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-actiontrail20171204
|
English |็ฎไฝไธญๆAlibaba Cloud Actiontrail SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_actiontrail20171204pipinstallalibabacloud_actiontrail20171204IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-actiontrail20200706
|
English |็ฎไฝไธญๆAlibaba Cloud Actiontrail SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_actiontrail20200706pipinstallalibabacloud_actiontrail20200706IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-actiontrail20200706-py2
|
English |็ฎไฝไธญๆAlibaba Cloud Actiontrail SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_actiontrail20200706_py2pipinstallalibabacloud_actiontrail20200706_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-adb20190315
|
English |็ฎไฝไธญๆAlibaba Cloud adb SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_adb20190315pipinstallalibabacloud_adb20190315IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-adb20190315-py2
|
English |็ฎไฝไธญๆAlibaba Cloud adb SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_adb20190315_py2pipinstallalibabacloud_adb20190315_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-adb20211201
|
English |็ฎไฝไธญๆAlibaba Cloud adb SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_adb20211201pipinstallalibabacloud_adb20211201IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-adb20211201-py2
|
English |็ฎไฝไธญๆAlibaba Cloud adb SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_adb20211201_py2pipinstallalibabacloud_adb20211201_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-adcp20220101
|
English |็ฎไฝไธญๆAlibaba Cloud adcp SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_adcp20220101pipinstallalibabacloud_adcp20220101IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-adcp20220101-py2
|
English |็ฎไฝไธญๆAlibaba Cloud adcp SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_adcp20220101_py2pipinstallalibabacloud_adcp20220101_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-address-purification20191118
|
English |็ฎไฝไธญๆAlibaba Cloud address-purification SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_address_purification20191118pipinstallalibabacloud_address_purification20191118IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-address-purification20191118-py2
|
English |็ฎไฝไธญๆAlibaba Cloud address-purification SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_address_purification20191118_py2pipinstallalibabacloud_address_purification20191118_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-adp20210720
|
English |็ฎไฝไธญๆAlibaba Cloud adp SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_adp20210720pipinstallalibabacloud_adp20210720IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-adp20210720-py2
|
English |็ฎไฝไธญๆAlibaba Cloud adp SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_adp20210720_py2pipinstallalibabacloud_adp20210720_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
|
alibabacloud-advisor20180120
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English |็ฎไฝไธญๆAlibaba Cloud Advisor SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_advisor20180120pipinstallalibabacloud_advisor20180120IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-advisor20180120-py2
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English |็ฎไฝไธญๆAlibaba Cloud Advisor SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_advisor20180120_py2pipinstallalibabacloud_advisor20180120_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-aegis20161111
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English |็ฎไฝไธญๆAlibaba Cloud aegis SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_aegis20161111pipinstallalibabacloud_aegis20161111IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-agency20210609-py2
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English |็ฎไฝไธญๆAlibaba Cloud Agency SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_agency20210609_py2pipinstallalibabacloud_agency20210609_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-agency20221216
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English |็ฎไฝไธญๆAlibaba Cloud Agency SDK for PythonRequirementsPython >= 3.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_agency20221216pipinstallalibabacloud_agency20221216IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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alibabacloud-agency20221216-py2
|
English |็ฎไฝไธญๆAlibaba Cloud Agency SDK for PythonRequirementsPython >= 2.6InstallationInstall with pipPython SDK uses a common package management tool namedpip. If pip is not installed, see thepip user guideto install pip.# Install the alibabacloud_agency20221216_py2pipinstallalibabacloud_agency20221216_py2IssuesOpening an Issue, Issues not conforming to the guidelines may be closed immediately.UsageQuick ExamplesChangelogDetailed changes for each release are documented in therelease notes.ReferencesLatest ReleaseLicenseApache-2.0Copyright (c) 2009-present, Alibaba Cloud All rights reserved.
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