Saravanan666/pypi-org huggingface dataset:
Package: pyexecutors
PyExecutors - A simple multi-threading task management libraryAre you great with multi-threading?PyExecutors is a utility module which provides straight-forward, powerful functions for working with asynchronous python functions.This runs an array of functions in series. You can program the functions to run synchronously or asynchronously in the order you desire.Installationpip install pyexecutorsThen, from a python interpreterfrom pyexecutors.executors.Executors import SyncTasks, AsyncTasks, Executors

def execute_method(exec_thread_number):
    // your function

Executors() \
    .enqueue(AsyncTasks(execute_method, args=(1,))) \
    .enqueue(AsyncTasks(execute_method, args=(2,))) \
    .enqueue(SyncTasks(execute_method, args=(3,))) \
    .enqueue(AsyncTasks(execute_method, args=(4,))) \
    .execute()How does it workSynchronous FunctionsA synchronous functions runs by encapsulating itself withRLocks. The lock is released after the functions' execution is completeAsynchronous FunctionsAsynchronous takes the help ofBarriers. The idea is to create a barrier with the  limit being the number of consecutive async functions.
A new barrier is created when a Sync function comes in between.Running Testspip install pytest
pytestThetest functionsimply matches the thread number with the argument passed to the functions.
The argument has been given to match the order of thread executionCode & IssuesIf you are a developer and you wish to contribute to the library please fork the project and submit a pull request.
FollowGithub Flowfor collaboration! If you have any questions, feel free to askmeabout whatever you want.Project MaintainersThis project is founded and actively maintained byTanmay Majumdar.
For any sort of queries feel free to mail attanmay.majumdar@hotmail.comLicenseThis project is licensed under the MIT License - see the LICENSE.md file for details
Package: pyexhange-r3ne
PyExhangeThis code is a Python implementation of a basic wallet system that allows users to buy, sell, and transfer currencies. It includes a JSON database to store user information and currency balances. The code is licensed under the MIT license.Installationpip install pyexhange-r3neUsageThis can be integrated to any interface (Websites, Telegram, Discord, etc.) with ease.Example:importpyexhange#Buy 1 Ethereumprint(pyexhange.handle_command("trade 1 1 eth"))#Sell 1 Ethereumprint(pyexhange.handle_command("trade 1 -1 eth"))#As user 1 send 100 dollars to user 2print(pyexhange.handle_command("send 1 2 100 USD This_Is_A_Message"))
Package: pyexifinfo
PyExifInfo===================Yet Another python wrapper for Phil Harvey' ExiftoolExifTool is the corner stone library to look for when you need to extract Exif or other types of metadata whithin a picture.ExifTool est la package de référence quand il s'agit d'analyser l'Exif ou les métadonnées d'une photohttps://github.com/guinslym/pyexifinfoInstallation------------To install pyexifinfo, simply:.. code:: sh$ pip install pyexifinfoUsage-----.. code:: pythonimport pyexifinfo as pp.ver() #retrieve your ExifTool versionfilename = 'python-logo.png'p.get_json(filename) #retrieve a json representation of this file exif=>[{u'File:FilePermissions': u'rw-rw-r--', u'PNG:Interlace': u'Noninterlaced', u'SourceFile': u'/home/laptop/python-logo.png', u'PNG:ColorType': u'RGB with Alpha', u'File:MIMEType': u'image/png',u'File:FileAccessDate': u'2015:07:20 16:37:22-04:00', u'File:FileModifyDate': u'2014:12:12 20:55:59-05:00', u'File:FileSize': u'9.9 kB', u'PNG:ImageWidth': 290, u'File:FileType': u'PNG', u'File:FileName': u'python-logo.png', u'PNG:Compression': u'Deflate/Inflate', u'PNG:PixelsPerUnitY': 2835, u'PNG:PixelsPerUnitX': 2835, u'PNG:ImageHeight': 82, u'PNG:PixelUnits': u'Meters', u'File:Directory': u'/home/laptop', u'File:FileInodeChangDate': u'2015:07:20 16:37:22-04:00', u'PNG:Filter': u'Adaptive', u'PNG:BitDepth': 8, u'Composite:ImageSize': u'290x82', u'ExifTool:ExifToolVersion': 9.46}]Other useful functions-----.. code:: pythonfrom pyexifinfo get_csv, get_xml, fileType, mimeType, imageSize, imageWidth, imageHeightfilename = 'python-logo.png'result = get_csv(filename)result = get_xml(filename)result = fileType(filename)result = mimeType(filename)
Package: pyexifwrangle
Wrangle EXIF Data in PythonA Python package for wrangling EXIF data extracted from images using Phil Harvey's EXIFTool.Set-upInstall pyexifwrangle with pip$pipinstallpyexifwrangleInstall Phil Harvey's EXIFToolInstall Phil Harvey's EXIFTool fromhttps://exiftool.org/. This site has installation instructions if you need them.UsageGet EXIF dataAfter installing EXIFTool, you can extract EXIF data from every image in a folder, including subdirectories, save the
results in a csv file, and return the results in a Pandas DataFrame.importpyexifwrangle.wrangleaswrdf=wr.get_exif(input_dir='path/to/images',output_csv='path/to/output.csv')Load the EXIF dataIf you already used get_exif() to save the EXIF to a csv file, you can use read_exif() to
load the csv file into a Pandas data frame. In this case, the output of get_exif() is the same as the output
from read_exif().importpyexifwrangle.wrangleaswrdf=wr.read_exif('path/to/output.csv',filename_col='SourceFile')The functionwrangle.read_exifuses the Pandas package to load the csv into a data frame. The parameterfilename_colis the name of the column that contains the filenames of the images.  The absolute file paths are
included with the filenames in thefilename_col. After reading the EXIF data into a Pandas data frame, this function removes any images whose filename starts with '.'.Make columns from folder namesI often organize my images into folders and sub-folders. For example one of my projects has the following folder tree:├── Samsung_phones  # main directory
│   ├── s21  # model
│   │   ├── s21_1  # phone name
│   │   │ 	├── blank  # scene type
│   │   │	│	├── front  # camera
│   │   │	│	│	├──image1.jpg
│   │   │	│	│	├──image2.jpg
│   │   │	│	│	├──...
│   │   │	│	├── telephoto
│   │   │	│	│	├──image1.jpg
│   │   │	│	│	├──image2.jpg
│   │   │	│	│	├──...
│   │   │	│	├── ultra
│   │   │	│	│	├──image1.jpg
│   │   │	│	│	├──image2.jpg
│   │   │	│	│	├──...
│   │   │	│	├── wide
│   │   │	│	│	├──image1.jpg
│   │   │	│	│	├──image2.jpg
│   │   │	│	│	├──...
│   │   │ 	├── natural
│   │   │	│	├── front  
│   │   │	│	├── telephoto
│   │   │	│	├── ultra
│   │   │	│	├── wide
│   │   ├── s21_2 
│   │   │ 	├── blank
│   │   │	│	├── front
│   │   │	│	├── telephoto
│   │   │	│	├── ultra
│   │   │	│	├── wide
│   │   │ 	├── natural
│   │   │	│	├── front  
│   │   │	│	├── telephoto
│   │   │	│	├── ultra
│   │   │	│	├── wideExtract the folder names from the images' absolute filepaths and make a new column for each folder.df=wr.filename2columns(df=df,filename_col='SourceFile',columns=['model','phone','scene_type','camera','image'])Search for missing EXIF dataFind images missing EXIF data. For example, search the data frame for images that don't have an Aperture.missing=wr.check_missing_exif(df=df,column='Aperture')Count images per group(s)Group images by column(s) and count the number of images per group.counts=wr.count_images_by_columns(df=df,columns=['model','phone','scene_type','camera'])Optionally, you can sort the output ofcount_images_by_columnscounts_sorted=wr.count_images_by_columns(df=df,columns=['model','phone','scene_type','camera'],sorted=['phone','camera','Aperture'])
Package: pyexistdb
packagedocumentationpyexistdbis a Python 3 module that
provides utilities and classes for interacting with theeXist-db XML
Databasein a
pythonic, object-oriented way, with optionalDjangointegration.pyexistdbis a fork ofeulexistdbwhich was originally
created by the Digital Programs and Systems Software Team ofEmory University Libraries.pyexistdb.queryprovides aQuerySetclass modeled afterDjango QuerySetin
functionality.  This module providesmodelandmanagerclasses
that can be used to connect aneulxmlXmlObjectwith theQuerySetclass, in order to generate XQueries and return the
results as XmlObject instances.  However, configuring the XmlObject
XPaths to make efficent XQueries against eXist and take advantage of
the full-text index does require expertise and familiarity with eXist.When used withDjango,pyexistdbcan pull the database connection configuration from
Django settings, provides a custom management command for working with
the collection index configuration index in the configured eXist
database, and also provides a custom template tag that can be used to
highlight full-text search matches.pyexistdb.dbprovides access to an eXist-db instance through
eXist’sXML-RPC API.Dependenciespyexistdbcurrently depends oneulxml.pyexistdbcan be used withoutDjango, but additional
functionality is available when used with Django.Contact Informationpyexistdbis maintained byThe Research Software Company.Please contact us atcontact@chelem.co.il.Licensepyexistdbis distributed under the Apache 2.0 License.Developer notesTo install dependencies for your local check out of the code, runpip installin thepyexistdbdirectory (the use ofvirtualenvis recommended):pip install -e .If you want to run unit tests or build sphinx documentation, you will also
need to install development dependencies:pip install -e . "pyexistdb[dev]"Running the unit tests requires an eXist-DB database instance.  Before running tests, you will
need to copytest/localsettings.py.disttotest/localsettings.pyand edit the
configuration for your test instance of eXist.To run all unit tests:nosetests test/ # for normal development
nosetests test/ --with-coverage --cover-package=pyexistdb --cover-xml --with-xunit   # for continuous integrationTo run unit tests for a specific module, use syntax like this:nosetests test/test_existdb/test_db.pyTo generate sphinx documentation:cd doc
make html
Package: pyexiv2
pyexiv2Read/Write metadata(includingEXIF,IPTC,XMP),commentandICC Profileembedded in digital images.Install:pip install pyexiv2Source code on GitHubTutorial|中文教程FeaturesBase on C++ API ofExiv2and wrapped withpybind11.Supports running on 64bit Linux, MacOS and Windows, with CPython(≥3.6) interpreter.Supports various image metadataSupports various image formatsSupports opening images based on the file path or from bytes data.Supports Unicode characters that contained in image path or metadata.DefectsCan't read the image larger than 2GB, or modify the image larger than 1GB. (related issue)Not thread safe, because pyexiv2 uses some global variables in C++.Currently, if you use ARM platform, you need to compile exiv2 and pyexiv2 manually, which is troublesome. (related issue)TestsThere are some test cases in folderpyexiv2/tests.ReferencesSimilar projects:exiv2is a C++ library for reading and writing various image metadata, including command-line tools.pyexiv2is a Python2 binding to exiv2, hasn't been updated since 2011.py3exiv2is a Python3 binding to exiv2, wrapped with Boost.Python.exiftoolis a perl library for reading and writing various image metadata, including command-line tools.Books:Robin Mills. "Image Metadata and Exiv2 Architecture". 2021
Package: pyexml
PyExMLpyexlabExtension usingtorchfor Machine LearningAuthor: Blake WilsonOverviewRunning machine learning experiments can be a huge hassle. Optimizing hyper parameters, saving off specific data throughout epochs, and modifying models without breaking code are just a few of the headaches I come across on a daily basis.pyexmlsimplifies the design process for machine learning experimentation by building on top of thepyexlabpackage.
Package: pyExoplaneteu
A pure-Python package to download data from theExtrasolar Planets EncyclopaediaThis small package downloads all the data from theexoplanet.euonline catalogue of exoplanets
and builds a (custom) dictionary with each column.
It is a pure-Python package with no extra dependencies (see below).How to useInstall it from pip (pyExoplaneteuhas no extra depencies)pip install pyExoplaneteuand it’s ready to use from PythonimportpyexoplaneteupyExoplaneteuhas one simple function,get_data(),
which downloads the data from the online archive and returns it in a dictionary.>>>data=pyexoplaneteu.get_data()Downloading exoplanet.eu data
Saved exoplanet.eu data to $HOME/.pyexoplaneteu/exoplanetEU.csv
Data in `exoplanetEU.csv` is recent.
There are 98 columns with 3793 entries each in `exoplanetEU.csv`where$HOMEwill  be your home directory.
The second time you callget_data()it will check if the data was downloaded recently,
and only conditionally download it again.>>>data=pyexoplaneteu.get_data()Data in `exoplanetEU.csv` is recent.
There are 98 columns with 3793 entries each in `exoplanetEU.csv`Now,datais (basically) a Python dictionary with the each column as keys.
But it has a couple extra methods and properties. For example>>>data.size3793returns the number of values in each column. Thecolumns()method>>>data.columns()['name','planet_status','mass','mass_error_min','mass_error_max','mass_sini','mass_sini_error_min','mass_sini_error_max','radius','radius_error_min','radius_error_max','orbital_period',...will print the available columns.The columns can be accessed as in a normal dictionary, withdata['name']# the name of the planetdata['mass']# the mass of the planetdata['star_radius']# the radius of the host starAlso, to drop the NaN values in a column (for some columns there will be quite a few)
we can usedata['mass_nonan']np.isnan(data['mass']).any()# Truenp.isnan(data['mass_nonan']).any()# Falsewhich allows us to more easily do histograms of the values.Finnally, the.to_numpy(inplace=True)method converts all the columns to numpy arrays,
either in place or not (this is the only function inpyExoplaneteuthat requires numpy).LicenseCopyright 2018 João Faria.pyExoplaneteuis free software made available under the MIT License. For
details see theLICENSEfile.
Package: pyexpander
AboutPyexpander is a powerful macro processing language based on python.  Instead of
simple macro replacement it offers evaluation of arbitrary python expressions
and execution of python code. Pyexpander is Turing Complete.AuthorGoetz Pfeiffer <Goetz.Pfeiffer@helmholtz-berlin.de>DocumentationDocumentation is available online here:pyexpander documentation.Documentation is also included in the software distribution in HTML and RST
(reStructuredText) format.InstallationYou can install pyexpander withpip(python package manager), asdebianorrpmpackage or fromsource.All is described here:pyexpander install.Licensepyexpander is licensed under GNU GPL v.3. Here is the license text:pyexpander license.
Package: pyexpandobjects
# ExpandObjects: Python EditionPython Implementation of the EnergyPlus ExpandObjects Utility# Build Status [![Build Status](https://travis-ci.org/Myoldmopar/py-expandobjects.svg?branch=master)](https://travis-ci.org/Myoldmopar/py-expandobjects)Builds of each commit and pull request are built by Travis.# Test Coverage [![Coverage Status](https://coveralls.io/repos/github/Myoldmopar/py-expandobjects/badge.svg?branch=master)](https://coveralls.io/github/Myoldmopar/py-expandobjects?branch=master)Unit test are run by Travis on each build with a constant target of 100%.# Documentation [![Documentation Status](http://readthedocs.org/projects/pyexpandobjects/badge/?version=latest)](http://pyexpandobjects.readthedocs.io/en/latest/?badge=latest)Documentation of this library is built by ReadTheDocs.
Package: py-experimenter
PyExperimenterPyExperimenteris a tool to facilitate the setup, documentation, execution, and subsequent evaluation of results from an empirical study of algorithms and in particular is designed to reduce the involved manual effort significantly.
It is intended to be used by researchers in the field of artificial intelligence, but is not limited to those.The empirical analysis of algorithms is often accompanied by the execution of algorithms for different inputs and variants of the algorithms (specified via parameters) and the measurement of non-functional properties.
Since the individual evaluations are usually independent, the evaluation can be performed in a distributed manner on an HPC system.
However, setting up, documenting, and evaluating the results of such a study is often file-based.
Usually, this requires extensive manual work to create configuration files for the inputs or to read and aggregate measured results from a report file.
In addition, monitoring and restarting individual executions is tedious and time-consuming.These challenges are addressed byPyExperimenterby means of a single well defined configuration file and a central database for managing massively parallel evaluations, as well as collecting and aggregating their results.
Thereby,PyExperimenteralleviates the aforementioned overhead and allows experiment executions to be defined and monitored with ease.For more details check out thePyExperimenterdocumentation:InstallationExamplesCite PyExperimenterIf you usePyExperimenterin a scientific publication, we would appreciate a citation in one of the following ways.Citation StringTornede et al., (2023). PyExperimenter: Easily distribute experiments and track results. Journal of Open Source Software, 8(84), 5149,https://doi.org/10.21105/joss.05149BibTex@article{Tornede2023, 
    title = {{PyExperimenter}: Easily distribute experiments and track results}, 
    author = {Tanja Tornede and Alexander Tornede and Lukas Fehring and Lukas Gehring and Helena Graf and Jonas Hanselle and Felix Mohr and Marcel Wever}, 
    journal = {Journal of Open Source Software},
    publisher = {The Open Journal},  
    year = {2023}, 
    volume = {8}, 
    number = {84}, 
    pages = {5149}, 
    doi = {10.21105/joss.05149}, 
    url = {https://doi.org/10.21105/joss.05149}
}
Package: pyexpert
# PyExpert 0.0.1This is a small embeddable Prolog interpreter in Python3, designed primarily forimplementing explainable expert systems.Usage:```python# Importsfrom weak.prolog import prolog_driver,prolog_default_env,prolog_next_solution,prolog_core_library# Initialise environmentenv = prolog_default_env()# Execute queryret,vars = prolog_driver(env, '? append(A, B, [x,y]).')print(vars)# Inspect all the remaining solutionswhile prolog_next_solution(env):print(vars)```# Weak setsThe main feature of this implementation is a `weak set` - a value that unifieswith any other weak set, resulting in a new set containing elements of bothsets. This is useful for implementing certain kinds of type systems and forhigher level hacks, such as tracing a Prolog execution (e.g., for ahuman-readable narration of an expert system decision), implementingconstraints, etc.For example:```prolog? weak(a,W1), weak(b,W1), weak(c,W2), W1=W2.```results in `W1=W2=[a,b,c]`See `weak/narrate.py` for an example of an instrumentation of a Prolog code forproducing execution traces, or a "narration", which can then be used togenerate, for example, a plain English narration of the expert system thoughtprocess.See `tests/demo.py` for an example of constructing an explainable expert system.
Package: pyexphys
PyExPhysPyExPhys is a Python library of exercise physiology and healthcare equations for transforming basic health data into insights at scale.  PyExPhys is a collection of bodybuilding competition formulas, aerobic performance and weightlifting performance models, and body composition equations.InstallingInstall the library usingpip:pip install pyexphysTestsTo test the calculations of PyExPhys, run thedistutilstest:python setup.py testSupportPlease raise potential bugs onGithub.
Package: pyExploitDb
pyExploitDb (https://govanguard.com)
==[![Build Status](https://travis-ci.com/GoVanguard/pyExploitDb.svg?branch=master)](https://travis-ci.com/GoVanguard/pyExploitDb)
[![Known Vulnerabilities](https://snyk.io/test/github/GoVanguard/pyExploitDb/badge.svg?targetFile=requirements.txt)](https://snyk.io/test/github/GoVanguard/pyExploitDb?targetFile=requirements.txt)
[![Maintainability](https://api.codeclimate.com/v1/badges/c718eabcdd4b815698db/maintainability)](https://codeclimate.com/github/GoVanguard/pyExploitDb/maintainability)## Authors:
Shane William Scott## About pyExploitDb
An optimized Python3 library to fetch the most recent exploit-database, create searchable indexes for CVE->EDBID and EDBID -> CVE, and provide methods to perform searches.
Last DB Refresh: 02/24/2023## Upcoming features
> CPE database, indexes and mappings## Installation
pip install pyExploitDb
> Note: This assumes pip is for your python3 environment. Use pip3 if pip is for your python2 environment.## Example Usage`python from pyExploitDb import PyExploitDb pEdb = PyExploitDb() pEdb.debug = False pEdb.openFile() results =pEdb.searchCve("CVE-2018-14592")print(results) `## Example debug/verbose output
CVE-2018-1459
Found
Exploit DB Id: 45447
File: ./exploit-database/exploits/php/webapps/45447.txt
Date: 2018-09-24
Author: Haboob Team
Platform: webapps
Type: php
Port: 80
{‘edbid’: ‘45447’, ‘exploit’: ‘./exploit-database/exploits/php/webapps/45447.txt’, ‘date’: ‘2018-09-24’, ‘author’: ‘Haboob Team’, ‘platform’: ‘webapps’, ‘type’: ‘php’, ‘port’: ‘80’}## Credits
Originally based on fork of cve_searchsploit by Andrea Fioraldi.
Package: pyExplore
python-package-boilerplateBoilerplate for a Python PackagePackageBasic structure of package is├── README.md
├── packagename
│   ├── __init__.py
│   ├── packagename.py
│   └── version.py
├── pytest.ini
├── requirements.txt
├── setup.py
└── tests
    ├── __init__.py
    ├── helpers
    │   ├── __init__.py
    │   └── my_helper.py
    ├── tests_helper.py
    └── unit
        ├── __init__.py
        ├── test_example.py
        └── test_version.pyRequirementsPackage requirements are handled using pip. To install them dopip install -r requirements.txtTestsTesting is set up usingpytestand coverage is handled
with the pytest-cov plugin.Run your tests withpy.testin the root directory.Coverage is ran by default and is set in thepytest.inifile.
To see an html output of coverage openhtmlcov/index.htmlafter running the tests.Travis CIThere is a.travis.ymlfile that is set up to run your tests for python 2.7
and python 3.2, should you choose to use it.
Package: pyexplorer
pyexplorerAn utility to enable fast exploring of a python package.UsageTo start usingpyexplorerjust type the command followed by the name of the
package, module or attributepyexplorer <package>.<module>.<attribute>You can start exploring a package by typing its name. This will shows you a
list of its modules and subpackages.pyexplorer <package>InstallationYou can install the latest released version ofpyexplorerusingpip.pip install pyexplorerAlternativaly you can install it from the source code.gitclonegit@github.com:dexpota/pyexplorer.gitcdpyexplorer
pipinstall-e.
Package: pyexpool
PyExPool is a concurrent execution pool with custom resource constraints (memory, timeouts, affinity, CPU cores and caching) and load balancing of the external applications on NUMA architecture.  All main functionality is implemented as a single-file module to be easily included into your project and customized as a part of your distribution (like inPyCaBeMto execute multiple apps in parallel on the dedicated CPU cores and avoiding their swapping from the main memory), also it can be installed as a library. An optional minimalistic Web interface is provided in the separate module to inspect the load balancer and execution pool. Typically, PyExPool is used as an application framework for benchmarking, load testing or other heavy-loaded multi-process execution activities on constrained computational resources. PyExPool is convenient for the fine-grained resource control (including apps execution on the specific number of the optionally dedicated logical CPUs) and for the failover execution.hwloc / lstoposhould be additionally installed if customized CPU affinity masking and cache control are required, seeRequirementssection.See details on thePyExPool pageand star the project if you like it! For any further assistance you can drop me a email or writeme on Linkedin.BibTeX:@misc{pyexpool,author={Artem Lutov and Philippe Cudré-Mauroux},title={PyExPool-v.3: A Lightweight Execution Pool with Constraint-aware Load-Balancer.},year={2018},url={https://github.com/eXascaleInfolab/PyExPool}}