Saravanan666/pypi-org huggingface dataset:
Package: plyvel-win32
Why does this fork exist?The sole reason for this fork existing is to provide win32 python wheels for
ease of installation.In other words, I am compiling the C++ leveldb -> x86 and x86-64 binaries + doing
the cython build and wheel creation so that you don’t have to. I have no intention
whatsoever of doing any development work on plyvel beyond this - please continue to use
the main repository for all other purposes.To install:>py-3.7-32-mpipinstallplyvel-win32>py-3.7-mpipinstallplyvel-win32>py-3.8-32-mpipinstallplyvel-win32>py-3.8-mpipinstallplyvel-win32Then use like you normally use plyvel:importplyveldb=plyvel.DB('/tmp/testdb/',create_if_missing=True)PlyvelPlyvelis a fast and feature-rich Python interface toLevelDB.Plyvel has a rich feature set, high performance, and a friendly Pythonic API.
See the documentation and project page for more information:DocumentationProject pagePyPI pageNote that using a released version is recommended over a checkout from version
control. See the installation docs for more information.
Package: plzpy
PLZ Rest APIA simple rest API that exposes data related to zip codes and buildings in Berlin.This project is the Python implementation ofPLZThe source dataset is published byEsriand is availablehere.MotivationsBuilt as an exerciseRest APIPLZ provides the following endpoints:/statusreturns the status of the service/zip/buildingsreturns the number of buildings aggregated by zip code/zip/buildings/historyreturns the number of buildings aggregated by zip code and year/zip/buildings/:codereturns the number of buildings for a specific zip code/zip/buildings/:code/historyreturns the number of buildings aggregated by zip code and year for a specific zip codeUsageThere are 2 ways to run the PLZ api service: using Docker(recommended) or viamanual setup.For best results with Docker please use the image from the go project as describedheresince the image is orders of magnitude smaller.Manual setupThose are the steps to run the project manually:Install the librarypip install plzpyDownload the dataset linked above:curl-Lhttps://opendata.arcgis.com/datasets/273bf4ae7f6a460fbf3000d73f7b2f76_0.csv?outSR=%7B%22latestWkid%22%3A3857%2C%22wkid%22%3A102100%7D-o/tmp/src.csvMassage the dataset to produce an optimized json to be served via the Rest APIplzpymassage--in/tmp/src.csv--outrest.jsonRun the Rest API serviceplzpyserve--datarest.jsonDevelopmentThe project relies onpoetry.
Package: plzz-cli
> This is an ongoing projects. Please stay tuned for the first release!
>
>
<div align=center>
<h1 align=center> PLZZ </h1><img align=center src=”logo.jpg” alt=”logo”><p align=center> A python CLI to automate daily tasks of both common and advanced users :) </p></div># List of commands`plzz –develop`: Only for development purpose. Not intended to ship during publishing.`plzz –about`: About the app.`plzz –list-commands`: List all the supported operations.`plzz –update`: Check for if any update of the app is available.`plzz –find-commands`: Search for a operations.`plzz [OPERATION]`: Run a operation from the supported list. Ex.plzz create-random-text-files# Supported operations## FILE OPERATIONScreate-random-text-files: Creates a specified number of random text files with random text under a given directory.create-lorem-ipsum-file: Creates a Lorem Ipsum file with a specified number of lines.generate-toc: Generate Table of contents from a given markdown file or all the markdown files under a directory.format-sentences: Format each sentences correctly in a english text a file or all files under a directory.find-urls: Find all the links from a text file or all the text files under a directory.count-offensive-words: Count offensive words from a file or a directory.censor-offensive-words: Censor offensive words from a file or all files under a directory.check-hash: Encrypt a file (MD5) or all the files under a directory and print the key(s).count-word: Count number of words in a file or under all the files under a given directory.## FOLDER ORGANIZATIONSadd-missing-extensions: Add missing extension to a file or all the files under a directory.delete-duplicates: Generates the MD5 hash of all the files in a given directory and deletes one of the files if two hashes match.rename-files: Rename a file/all files under directory by replacing specified character with new one.delete-empty-files: Delete all empty text files from src_dir.replace-words: Replace all the words in a given file or all the files under a directory with a new word.## UTILITIESdownload-todays-wallpaper: Download today’s wallpaper from bing, and save them.generate-password: Generate a password of a given strength (low,medium,strong) or any specific length.create-qr-code: Create qr code and save it as a image.## DEVELOPMENT TASKSupload-to-gist: Upload a file or all files under a directory to Github Gist.add-license: Create a license file of desired type.<p align=center><a href=”https://www.buymeacoffee.com/deep5050” target=”_blank”><img src=”https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png” alt=”Buy Me A Coffee” style=”height: 40px !important;width: 117px !important;” ></a></p>
Package: pm
Simple project manager in Python. This application helps you keeping track of
the status of your projects in their Source Code Management (SCM) system.For now, pm only supports Git.Normally, it should be compatible with Python 2.7 and Python 3.x. Post an issue
if you find something that is not compatible one of these versions and I’ll do
my best to improve that.InstallationYou can usepipto install the latestpmrelease from PyPI:pip install pmAlternatively, you can download the latest development sources and
install the package manually by running:python setup.py installUsageHelp can be obtained by runningpm --helpto obtain information about
the general usage orpm <subcommand> --helpto obtain help about a
specific subcommand.usage: pm [-h] [--version] {status,ls,fetch,update} ...

optional arguments:
  -h, --help            show this help message and exit
  --version             show program's version number and exit

subcommands:
  Valid subcommands

  {status,ls,fetch,update}
                        Subcommands
    status              check status
    ls                  List projects
    fetch               Fetch all projects
    update              Update all projectsLicenseThis project is distributed under the MIT License. ReadLICENSEfor details.
Package: pm2case
postman2caseConvert postman data to yaml testcases for HttpRunner.usageTo seepostman2caseversion:$pythonmain.py-V0.0.1To see available options, run$pythonmain.py-h
usage:main.py[-h][-V][--log-levelLOG_LEVEL][postman_testset_file][output_testset_file]ConvertpostmantestcasestoJSONtestcasesforHttpRunner.

positionalarguments:postman_testset_fileSpecifypostmantestsetfile.output_testset_fileOptional.SpecifyconvertedJSONtestsetfile.

optionalarguments:-h,--helpshowthishelpmessageandexit-V,--versionshowversion--log-levelLOG_LEVELSpecifylogginglevel,defaultisINFO.examplesIn most cases, you can runpostman2caselike this:$python3main.pytest/test.jsonoutput.json
INFO:root:GenerateJSONtestsetsuccessfully:output.jsonAs you see, the first parameter is postman source file path, and the second is converted JSON file path.The output testset file type is detemined by the suffix of your specified file.If you only specify postman source file path, the output testset is in JSON format by default and located in the same folder with source file.$python3main.pytest/test.json
INFO:root:GenerateJSONtestsetsuccessfully:test/test.output.jsongenerated testsetgenerated JSON testsetoutput.jsonshows like this:[{"test":{"name":"/api/v1/Account/Login","request":{"method":"POST","url":"https://httprunner.top/api/v1/Account/Login","headers":{"Content-Type":"application/json"},"json":{"UserName":"test001","Pwd":"123","VerCode":""}},"validate":[]}}]
Package: pm2hw
pm2hwA flasher for all Pokemon mini Flash Cards (that I can actually test).This is a work in progress, PokeUSB will come soon.InstallationIt would be best to install this viapipxrather than plain pip; but of course, both are possible.WindowsThe system has been tested on Windows 10 with Python 3.9Download and install theFTD2XX driversfor Windows (Desktop).Install pipx if it's not installed:py -m pip install pipx --userNote you will very likely need to add the folder to your PATH variable (it will warn you post-install).Install pm2hw:pipx install pm2hwLinux/MacOS XThe system has not been tested on these OSes, but it should work.Download and install theFTD2XX driversfor Linux or Mac OS X as appropriate.Install pipx if it's not installed:python3 -m pip install pipx --userInstall pm2hw:pipx install pm2hwUsageCLI:pm2hw --helpOpen GUI:pm2hw-guiNavigate to Help -> How to UseComparisonAll tests run on Python 3.10.5. Write times do not include verification (add the read time for that).PokeCard 512 v2UtilityReadWritePokeFlash (Win10)1.344s10.109spm2hw (Win10)1.481s14.771sDitto miniUtilityRead 512 KiBRead 2 MiBWrite 512 KiBWrite 2 MiBDitto Flash (Win10)7.610s16.497spm2hw (Win10)7.370s29.209s18.706s20.331s
Package: pm4py
# pm4py
pm4py is a python library that supports (state-of-the-art) process mining algorithms in python.
It is open source (licensed under GPL) and intended to be used in both academia and industry projects.
pm4py is a product of the Fraunhofer Institute for Applied Information Technology.## Documentation / API
The full documentation of pm4py can be found athttps://pm4py.fit.fraunhofer.de## First Example
A very simple example, to whet your appetite:import pm4pyif __name__ == “__main__”:log = pm4py.read_xes(‘<path-to-xes-log-file.xes>’)
net, initial_marking, final_marking = pm4py.discover_petri_net_inductive(log)
pm4py.view_petri_net(net, initial_marking, final_marking, format=”svg”)## Installation
pm4py can be installed on Python 3.9.x / 3.10.x / 3.11.x / 3.12.x by invoking:pip install -U pm4pypm4py is also running on older Python environments with different requirements sets, including:
- Python 3.8 (3.8.10): third_party/old_python_deps/requirements_py38.txt## Requirements
pm4py depends on some other Python packages, with different levels of importance:
*Essential requirements: numpy, pandas, deprecation, networkx
*Normal requirements(installed by default with the pm4py package, important for mainstream usage): graphviz, intervaltree, lxml, matplotlib, pydotplus, pytz, scipy, stringdist, tqdm
*Optional requirements(not installed by default): scikit-learn, pyemd, pyvis, jsonschema, polars, openai, pywin32, python-dateutil, requests, workalendar, pygetwindow, pynput## Release Notes
To track the incremental updates, please refer to theCHANGELOGfile.## Third Party Dependencies
As scientific library in the Python ecosystem, we rely on external libraries to offer our features.
In the/third_partyfolder, we list all the licenses of our direct dependencies.
Please check the/third_party/LICENSES_TRANSITIVEfile to get a full list of all transitive dependencies and the corresponding license.## Citing pm4py
If you are using pm4py in your scientific work, please cite pm4py as follows:Alessandro Berti, Sebastiaan van Zelst, Daniel Schuster. (2023).PM4Py: A process mining library for Python. Software Impacts, 17, 100556. [DOI](https://doi.org/10.1016/j.simpa.2023.100556) | [Article Link](https://www.sciencedirect.com/science/article/pii/S2665963823000933)BiBTeX:@article{pm4py,
title = {PM4Py: A process mining library for Python},
journal = {Software Impacts},
volume = {17},
pages = {100556},
year = {2023},
issn = {2665-9638},
doi = {https://doi.org/10.1016/j.simpa.2023.100556},
url = {https://www.sciencedirect.com/science/article/pii/S2665963823000933},
author = {Alessandro Berti and Sebastiaan van Zelst and Daniel Schuster},
}
Package: pm4pydistr
# pm4py-distr
Support for distributed logs and computations in PM4Py.See the currently supported API in api.txtTo execute locally an example (one master running on 5001 and two slaves running on 5002 and 5003)
just run “python main.py”The example contains the partitioned version of the logs “receipt” and “roadtraffic”.## Example of usage of the distributed services (default keyphrase is “hello”):ALLOCATION OF THE PARTITIONS BETWEEN THE SLAVEShttp://localhost:5001/doLogAssignment?keyphrase=helloCALCULATION OF THE DFGhttp://localhost:5001/calculateDfg?keyphrase=hello&process=receipt## Configuration of the keyphraseThe keyphrase that is shared between the slaves and the master is contained in the pm4pydistr.configuration file.## Custom executions of master/slaveIf instead of running the default example, you want to execute the master/slaves in custom configuration,
follow the process:REMOVE THE EXAMPLE FILESRemove the “master.db” database and the “master” folderCREATE A “master” FOLDER CONTAINING THE PARTITIONED DATASETS THAT YOU WANT TO USESee the PARTITIONING.txt file for instructions on how to partition a log file into a partitioned dataset!LAUNCH THE MASTERLaunch the master with the command: python launch.py –type master –conf master –port 5001
(replace possibly the port, it is by default listening on 0.0.0.0)LAUNCH THE SLAVESLaunch a slave (that are master-aware) with the command:python launch.py –type slave –conf slave1 –port 5002 –master-host 127.0.0.1 –master-port 5001
(replace possibly the port used by the slave, and the host/port that points to the master).## Demo on a custom serverIt may work, or it may not work :)Distributed DFG calculation:http://212.237.8.106:5001/calculateDfg?keyphrase=hello&process=roadtraffichttp://212.237.8.106:5001/calculateDfg?keyphrase=hello&process=bpic2018http://212.237.8.106:5001/calculateDfg?keyphrase=hello&process=bpic2019Retrieval of the start activities of the log:http://212.237.8.106:5001/getStartActivities?keyphrase=hello&process=roadtraffichttp://212.237.8.106:5001/getStartActivities?keyphrase=hello&process=bpic2018http://212.237.8.106:5001/getStartActivities?keyphrase=hello&process=bpic2019Retrieval of the end activities of the log:http://212.237.8.106:5001/getEndActivities?keyphrase=hello&process=roadtraffichttp://212.237.8.106:5001/getEndActivities?keyphrase=hello&process=bpic2018http://212.237.8.106:5001/getEndActivities?keyphrase=hello&process=bpic2019
Package: pm4pyminimal
# pm4py
pm4py is a python library that supports (state-of-the-art) process mining algorithms in python.
It is open source (licensed under GPL) and intended to be used in both academia and industry projects.
pm4py is a product of the Fraunhofer Institute for Applied Information Technology.## Documentation / API
The full documentation of pm4py can be found athttps://pm4py.fit.fraunhofer.de## First Example
A very simple example, to whet your appetite:import pm4pyif __name__ == “__main__”:log = pm4py.read_xes(‘<path-to-xes-log-file.xes>’)
net, initial_marking, final_marking = pm4py.discover_petri_net_inductive(log)
pm4py.view_petri_net(net, initial_marking, final_marking, format=”svg”)## Installation
pm4py can be installed on Python 3.9.x / 3.10.x / 3.11.x / 3.12.x by invoking:pip install -U pm4pypm4py is also running on older Python environments with different requirements sets, including:
- Python 3.8 (3.8.10): third_party/old_python_deps/requirements_py38.txt## Requirements
pm4py depends on some other Python packages, with different levels of importance:
*Essential requirements: numpy, pandas, deprecation, networkx
*Normal requirements(installed by default with the pm4py package, important for mainstream usage): graphviz, intervaltree, lxml, matplotlib, pydotplus, pytz, scipy, stringdist, tqdm
*Optional requirements(not installed by default): scikit-learn, pyemd, pyvis, jsonschema, polars, openai, pywin32, python-dateutil, requests, workalendar, pygetwindow, pynput## Release Notes
To track the incremental updates, please refer to theCHANGELOGfile.## Third Party Dependencies
As scientific library in the Python ecosystem, we rely on external libraries to offer our features.
In the/third_partyfolder, we list all the licenses of our direct dependencies.
Please check the/third_party/LICENSES_TRANSITIVEfile to get a full list of all transitive dependencies and the corresponding license.## Citing pm4py
If you are using pm4py in your scientific work, please cite pm4py as follows:Alessandro Berti, Sebastiaan van Zelst, Daniel Schuster. (2023).PM4Py: A process mining library for Python. Software Impacts, 17, 100556. [DOI](https://doi.org/10.1016/j.simpa.2023.100556) | [Article Link](https://www.sciencedirect.com/science/article/pii/S2665963823000933)BiBTeX:@article{pm4py,
title = {PM4Py: A process mining library for Python},
journal = {Software Impacts},
volume = {17},
pages = {100556},
year = {2023},
issn = {2665-9638},
doi = {https://doi.org/10.1016/j.simpa.2023.100556},
url = {https://www.sciencedirect.com/science/article/pii/S2665963823000933},
author = {Alessandro Berti and Sebastiaan van Zelst and Daniel Schuster},
}
Package: pm4py-model-repair
This repository contains an implementation of a process model repair algorithm. It can be used to repair a process model to fit an event log.The fileprocess_model_repair_algorith.pycontains the implementation for repairing a Petri net to fit an event log. It repairs the Petri net in place.Usage:` event_log =pm4py.read_xes('example.xes')net, im, fm =pm4py.convert_to_petri_net(pm4py.read_bpmn('example.bpmn'))pm4py.view_petri_net(net, im, fm) net_repaired, im_repaired, fm_repaired = repair_process_model(net, im, fm, event_log) pm4py.view_petri_net(net_repaired, im_repaired, fm_repaired) `The fileprocess_model_repair_with_change_set.pycontains the implementation for repairing a BPMN model to fit an event log and obtain a change set. It is the the function used in the integration into the PAIS Customate.Usage:` repair_process_model(bpmn, event_log, activity_mappings) `Activity Mappings map between ids in the BPMN models and the activity ids in the event log.The fileapp.pycontains the flask server implementation for the integration into the PAIS Customate.
Package: pm4py-wrapper
pm4py-wrapperCLI wrapper for pm4py.InstallationInstall usingpip:pipinstallpm4py-wrapperKnown Issues for macOS with M1cvxopt@1.3.0: umfpack.h is missingDiscussion is athttps://github.com/cvxopt/cvxopt/issues/78.Solution:Installsuite-sparseSpecifyCPPFLAGSandLDFLAGSRunpip install cvxoptMore details athttp://cvxopt.org/install/index.html$brewinfosuite-sparse
$exportCPPFLAGS="-I/opt/homebrew/include/"$exportLDFLAGS="-L/opt/homebrew/lib"$pipinstallcvxoptscipy@1.6.1Discussion is athttps://github.com/scipy/scipy/issues/13409Solution: use a newer version starting from 1.7.0UsageUsage: pm4py_wrapper [OPTIONS] COMMAND [ARGS]...

Options:
  -i, --input_log PATH   Path to the input event log.  [required]
  -o, --output_dir PATH  Path to the output directory.
  --help                 Show this message and exit.

Commands:
  csv-to-xes
  xes-to-csvExamples:$pm4py_wrapper-itests/assets/input/Production.xes-otests/assets/outputxes-to-csv
$pm4py_wrapper-itests/assets/input/Production.csv-otests/assets/outputcsv-to-xesLinksA helpfulansweron StackOverflow on how to do CI/CD with Poetry.
Package: pma
PiXL Maths App FarmThis project requires at least Python 3.8.
The tool is designed to work withPiXL's Maths App.
It was created by reverse engineering the flash file and took a huge amount of time so any
support is appreciated.SetupInstallPythonRunpip install -U pmain your terminal/command prompt. This is the same command to updateThere are also docker images onGitHubandDocker Hub.CLI Usagepma farm --helppython -m pma farm --helppython -m pma farm --goal 100 SCHOOL_ID USERNAME PASSWORDpython -m pma farm --yes SCHOOL_ID USERNAME PASSWORDpython -m pma farm --goal 100 --yes SCHOOL_ID USERNAME PASSWORDpython -m pma farm SCHOOL_ID USERNAME PASSWORDNote: You can use eitherpmaorpython -m pma
Package: pmacct-to-elasticsearch
pmacct-to-elasticsearchpmacct-to-elasticsearchis a python script designed to read output frompmacctdaemons, to process it and to store it intoElasticSearch. It works with bothmemoryandprintplugins and, optionally, it can performmanipulations on data(such as to add fields on the basis of other values).pmacct daemonscollect IP accounting data and process them with their plugins;data are stored intoin-memory-tables(memoryplugins),JSON or CSV files(printplugins);crontab jobs(memoryplugins) ortrigger scripts(printplugins) are invoked to execute pmacct-to-elasticsearch;pmacct’s output records are finally processed bypmacct-to-elasticsearch, which reads them from stdin (memoryplugins) or directly from file.Optionally, somedata transformationscan be configured, to allow pmacct-to-elasticsearch toadd or remove fieldsto/from the output documents that are sent to ElasticSearch for indexing. These additional fields may be useful to enhance graphs and reports legibility, or to add a further level of aggregation or filtering.InstallationInstall the program using pip:pipinstallpmacct-to-elasticsearchThen clone the repository and run the ./install script to setup your system:cd/usr/local/src/gitclonehttps://github.com/pierky/pmacct-to-elasticsearch.gitcdpmacct-to-elasticsearch/./installConfigurationPlease refer to theCONFIGURATION.mdfile. TheTRANSFORMATIONS.mdfile contains details about data transformations configuration.A simple tutorial on pmacct integration with ElasticSearch/Kibana using pmacct-to-elasticsearch can be found athttp://blog.pierky.com/integration-of-pmacct-with-elasticsearch-and-kibana.Future workAdd support of more pmacct output formats (Apache Avro, …).AuthorPier Carlo Chiodi -https://pierky.com/Blog:https://blog.pierky.com/Twitter:@pierkyChangelog0.3.2Code linting and fixing import and pip3 errors.Thanks to@palisadoes (Peter Harrison) <https://github.com/palisadoes>for these fixes.0.3.1Fix: ES 6.2 compatibility.Issue #9 <https://github.com/pierky/pmacct-to-elasticsearch/issues/9>.0.3.0New:CSVoutput support.TheInputFormatoption in the plugin configuration file can be used to instruct pmacct-to-elasticsearch to parse CSV output from pmacct.New:Multithreadingsupport.TheReaderThreadsoption in the plugin configuration file sets the number of threads used to process pmacct’s output.New: More command line arguments.The command line arguments under theConfiguration optionsgroup can be used to override settings done on the plugin configuration file.Fix issue with index creation on ElasticSearch 5.x.Thanks to Kristoffer Olsson and Daniel Lindberg for reporting this and for their extensive support.Improved template for index creation.Fix an issue with transformations.0.2.0New feature: HTTP Authentication support for ES API.0.1.0First release.
Package: pmac-motorhome
pmac_motorhome is a python3 tool to generator homing PLCs from a python
scriptPyPIpip install pmac_motorhomeSource codehttps://github.com/dls-controls/pmac_motorhomeDocumentationhttps://dls-controls.github.io/pmac_motorhomeThis is where you should put some images or code snippets that illustrate
some relevant examples. If it is a library then you might put some
introductory code here:frompmac_motorhome.helloimportHelloClasshello=HelloClass("me")print(hello.format_greeting())Or if it is a commandline tool then you might put some example commands here:pmac_motorhome person --times=2Seehttps://dls-controls.github.io/pmac_motorhomefor more detailed documentation.
Package: pmacparser
PMACParser is a library that parses PMAC programs.
It includes an emulator for forward kinematic programs,
which parses the program and then, using an input dictionary of
variables, runs the program, returning a dictionary of populated
variables based on the operations of the kinematic program.DocumentationTo use:from pmacparser.pmac_parser import PMACParsercode_lines = [“Q1=(P(4800+1)*P1+P(4900+1))”, “Q5=(P(4800+2)*P2+P(4900+2))”]input_vars = {“P1”: 51, “P2”: 345.3, “P4801”: 45.4, “P4802”: 162.4, “P4901”: 4, “P4902”: 5}parser = PMACParser(code_lines)output_vars = parser.parse(input_vars)