Saravanan666/pypi-org huggingface dataset:
Package: pcp
Performance Co-Pilot (PCP) provides a framework and services to support
system-level performance monitoring and management. It presents a unifying
abstraction for all of the performance data in a system, and many tools
for interrogating, retrieving and processing that data.PCP is a feature-rich, mature, extensible, cross-platform toolkit
supporting both live and retrospective analysis. The distributed PCP
architecture makes it especially useful for those seeking centralized
monitoring of distributed processing.For more information and details on how to contribute to the PCP project
visitpcp.io.
Package: pcpartpicker
pcpartpickerThis is an unofficial Python 3.7+ API for the website pcpartpicker.com.
It is written using asynchronous requests for efficient data retrieval.
This package is currently in a stable beta.Installation:Package retrieval and installation can be easily accomplished through pip.pipinstallpcpartpickerExamples:In order to use the API, simply import API from the pcpartpicker package.frompcpartpickerimportAPIYou can then instantiate the API class and use it to make requests.api=API()cpu_data=api.retrieve("cpu")all_data=api.retrieve_all()api.retrieve()andapi.retrieve_all()methods both return aPartDatainstance, which contains a timestamp and ato_json()method.A list of supported parts can be obtained in the following manner:api=API()print(api.supported_parts)>>>{'wireless-network-card','case-fan','cpu','cpu-cooler','headphones','motherboard','monitor','internal-hard-drive','external-hard-drive','ups','fan-controller','case','keyboard','mouse','wired-network-card','sound-card','video-card','speakers','optical-drive','power-supply','thermal-paste','memory'}There are also a number of methods that can be used in order to customize the API behavior.
For example, you can change the region, determine the number of concurrent, asynchronous connections
that can be made, and can also set whether or not the API can use multiple threads.Retrieving supported API regions:api=API()print(api.supported_regions)>>>{'be','us','it','uk','ie','nz','de','ca','au','fr','se','es','in'}Retrieving currently selected region (default is US):api=API()print(api.region)>>>usCreating an API object with a different default region:api=API("de")print(api.region)>>>deChanging the default region:api=API()api.set_region("de")print(api.region)>>>de
Package: pcprimefinder
This is a library to find if a number is prime.
It takes O(n^1/2) time complexity as compared to O(n) in common methodChange Log0.0.1 (23/01/2023)First Release0.0.2 (24/01/2023)Second Releasechanged package structure0.0.3 (24/01/2023)Added rule functions from notebook0.1.0 (25/01/2023)Demo rules added to run on notebooks
Package: pcprox-reader
pcProx ReaderLibrary for reading cards via usb RFIDeas pc prox readersFree software: MIT licenseDocumentation:https://pcprox-reader.readthedocs.io.FeaturesThis application allows a pcProx Reader to read the code from an
HID card.Permissions issues on most Linux systems may be resolved by running:sudo python -m pcprox_reader.udev_ruleTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2019-06-25)First release on PyPI.
Package: pcpy
pcpyA Python package for pcset operations, relation measures, and queries.Reference:Forte, Allen.The Harmonic Organization of The Rite of Spring. New Haven: Yale University Press, 1978.———.The Structure of Atonal Music. New Haven and London: Yale University Press, 1973.Morris, Robert D.Class Notes for Atonal Music Theory. Lebanon, NH: Frog Peak Music, 1991.Roig-Francoli, Miguel A.Understanding Post-Tonal Music. Boston: McGraw-Hill, 2008.Straus, Joseph N.Introduction to Post-Tonal Theory. 3rd ed. Upper Saddle River: Pearson Education, 2005.Kobayashi, Yota. “Forms for String Quartet and Computer.” DMA diss., University of British Columbia, 2018.https://dx.doi.org/10.14288/1.0372893.
Package: pcraft
pCraftpCraft is a PCAP Crafter, which creates a PCAP from a YAML scenario.When generating data for testing, it is rather hard to do forthe following reasons:Lack of consistency between clients and serversMake sure no personal data leaksConsistency across different services.Keeping timing rightetc.This program helps solving this problem, one simply creates a script in YAML and the program outputs a PCAP.Creating a Hello World scriptCreate a file called "hello.yaml", we want to add the following content:start: Generate_a_new_domain

Generate_a_new_domain:
  _plugin: GenerateNewDomain
  _next: DNSConnection

DNSConnection:
  _plugin: DNSConnection
  _next: loop-1

loop-1:
  count: 3
  newip: 1 # We get a new IP address for each loop
  _sleep: {"before-start":3,"interval":0.2,"once-finished":0.3}
  _next: done
  _start: DNSConnection # Where our loop startsNow execute the pcraft program:pcrafter hello.yaml hello.pcapLet's read the result pcap using tshark:$ tshark -r hello.pcap 
    1   0.000000 192.168.67.150 → 10.218.175.58 DNS 81 Standard query 0x0000 A masaryk-treasurer.com
    2   0.000552 10.218.175.58 → 192.168.67.150 DNS 118 Standard query response 0x0000 A masaryk-treasurer.com A 199.34.228.66
    3   0.001115 192.168.53.38 → 10.44.21.216 DNS 81 Standard query 0x0000 A masaryk-treasurer.com
    4   0.001529 10.44.21.216 → 192.168.53.38 DNS 118 Standard query response 0x0000 A masaryk-treasurer.com A 199.34.228.66
    5   0.002126 192.168.160.175 → 10.79.78.60  DNS 81 Standard query 0x0000 A masaryk-treasurer.com
    6   0.002531  10.79.78.60 → 192.168.160.175 DNS 118 Standard query response 0x0000 A masaryk-treasurer.com A 199.34.228.66
    7   0.003038 192.168.33.44 → 10.46.101.67 DNS 81 Standard query 0x0000 A masaryk-treasurer.com
    8   0.003439 10.46.101.67 → 192.168.33.44 DNS 118 Standard query response 0x0000 A masaryk-treasurer.com A 199.34.228.66
    9   0.003947 192.168.140.220 → 10.117.63.91 DNS 81 Standard query 0x0000 A masaryk-treasurer.com
   10   0.004350 10.117.63.91 → 192.168.140.220 DNS 118 Standard query response 0x0000 A masaryk-treasurer.com A 199.34.228.66Writing a ScenarioPlease look at the documentation on this topic to understand more about the engine: "Writing a Scenario".Available PluginsThe Plugins documentation is generated from themselves:Plugins Documentation
Package: pcrawler
# pcrawler爬虫程序
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/mumupy/pcrawler/blob/master/LICENSE)
[![Build Status](https://travis-ci.org/mumupy/pcrawler.svg?branch=master)](https://travis-ci.org/mumupy/pcrawler)
[![codecov](https://codecov.io/gh/mumupy/pcrawler/branch/master/graph/badge.svg)](https://codecov.io/gh/mumupy/pcrawler)
[![pypi](https://img.shields.io/pypi/v/pcrawler.svg)](https://pypi.python.org/pypi/pcrawler)
[![Documentation Status](https://readthedocs.org/projects/pcrawler/badge/?version=latest)](https://pcrawler.readthedocs.io/en/latest/?badge=latest)*pcrawler是一款python版本的爬虫程序，通过该爬虫程序可以非常快速方便的编写一个自己的爬虫程序。pcrawler主要
包含downloader、schedular、processor、storage四大组件组成。而且可以非常方便快捷的拓展各个组件。*## 特性：
- 简单的API，可快速上手
- 模块化的结构，可轻松扩展
- 提供多线程和分布式支持## 架构
pcrawler主要包含downloader、schedular、processor、storage四大组件组成。
- processor 爬虫页面处理器，对页面进行分析。目前集成图片下载处理器、多媒体视频下载处理器、新浪新闻处理器。
- schedular URL管理组件，对待抓取的URL队列进行管理，对已抓取的URL进行去重。目前url队列管理支持文件缓存管理和集合管理。url去重支持文件缓存、集合、bloomFilter布隆过滤器等。
- downloader 下载组件，默认使用urllib2下载。
- storage 存储组件，支持多样文件格式(csv、json、avro、video)## 相关阅读
[webmagic爬虫](http://webmagic.io/)
[Bloom Filter](http://blog.csdn.net/jiaomeng/article/details/1495500)## 联系方式以上观点纯属个人看法，如有不同，欢迎指正。
email:<babymm@aliyun.com>
github:[https://github.com/babymm](https://github.com/babymm)
Package: pcre2
PCRE2.py: Python bindings for the PCRE2 regular expression libraryThis project contains Python bindings forPCRE2.
PCRE2 is the revised API for the Perl-compatible regular expressions (PCRE) library created by Philip Hazel.
For original source code, see theofficial PCRE2 repository.InstallationFrom PyPI:pip install pcre2If a wheel is not available for your platform, the module will be built from source.
Building requires:cmakeC compiler toolchain, such asgccandmakelibtoolPython headersUsageRegular expressions are compiled withpcre2.compile()which accepts both unicode strings and bytes-like objects.
This returns aPatternobject.
Expressions can be compiled with a number of options (combined with the bitwise-or operator) and can be JIT compiled,>>>importpcre2>>>expr=r'(?<head>\w+)\s+(?<tail>\w+)'>>>patn=pcre2.compile(expr,options=pcre2.I,jit=True)>>># Patterns can also be JIT compiled after initialization.>>>patn.jit_compile()Inspection ofPatternobjects is done as follows,>>>patn.jit_size980>>>patn.name_dict(){1:'head',2:'tail'}>>>patn.options524296>>># Deeper inspection into options is available.>>>pcre2.CompileOption.decompose(patn.options)[<CompileOption.CASELESS:0x8>,<CompileOption.UTF:0x80000>]Once compiled,Patternobjects can be used to match against strings.
Matching return aMatchobject, which has several functions to view results,>>>subj='foo bar buzz bazz'>>>match=patn.match(subj)>>>match.substring()'foo bar'>>>match.start(),match.end()(8,17)Substitution is also supported, both fromPatternandMatchobjects,>>>repl='$2 $1'>>>patn.substitute(repl,subj)'bar foo buzz bazz'>>>patn.substitute(repl,subj,options=pcre2.G)# Global substitutions are also supported.'bar foo bazz buzz'>>>match.expand(repl)'bar foo buzz bazz'Additionally,Patternobjects support scanning over subjects for all non-overlapping matches,>>>formatchinpatn.scan(subj):...print(match.substring('head'))...foobuzzPerformancePCRE2 provides a fast regular expression library, particularly with JIT compilation enabled.
Below are theregex-reduxbenchmark results included in this repository,ScriptNumber of runsTotal timeReal timeUser timeSystem timebaseline.py103.0200.3020.0200.086vanilla.py1051.3805.13811.4080.529hand_optimized.py1013.1901.3192.8460.344pcre2_module.py1013.6701.3672.2690.532Script descriptions are as follows,ScriptDescriptionbaseline.pyReads input file and outputs stored expected outputvanilla.pyPure Python versionhand_optimized.pyManually written Pythonctypesbindings for shared PCRE2 C librarypcre2_module.pyImplementation using Python bindings written hereTests were performed on an M2 Macbook Air.
Note that to run benchmarks locally,Git LFSmust be installed to download the input dataset.
Additionally, a Python virtual environment must be created, and the package built
withmake initandmake buildrespectively.
For more information on this benchmark, seeThe Computer Language Benchmarks Game.
See source code of benchmark scripts for details and original sources.
Package: pcrglobwb-utils
OverviewHandy functions to work with PCR-GLOBWB input and output.Free software: GNU General Public License v3Documentation:https://pcrglobwb-utils.readthedocs.io.FeaturesMost mature:evaluation of timeseries simulated by PCR-GLOBWB with observations from GRDC.multiple GRDC-stations and properties can be provided via a yml-file.using command line functions and wide range of user-defined options.command line functions to validate model output against GRACE and GLEAM data for multiple polygons.Other:aggregating and averaging over time scales.water balance assessments of PCR-GLOBWB runs.statistical analyses.ensemble analysis.CreditsContributions from Jannis M. Hoch (j.m.hoch@uu.nl).The package structure was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.3 (2020-05-07)Analysing the water balance components of a PCR-GLOBWB runCalculating statistics of ensemble output and plotting it0.1.2 (2020-04-23)Additional functionality.Added functions for temporal aggregation (daily to monthly, daily to yearly)Statistics of simulated discharge (mean, max, min etc) can be computed0.1.1 (2020-04-20)Minor updates.Moved towards object based programmingReading from ‘normal’ csv-files supported now0.1.0 (2020-03-24)First stable release with minimal functionality.Extracting timeseries from netCDF-files for certain lon/latReading of GRDC station files and extracting meta-dataAggregating daily values to monthly averagesValidating timeseries of observed and simulated values for common time periodProvision of example data and jupyter notebook(Shell)scripts for validating and benchmarking timeseries
Package: pCrunch
IO and Post Processing Interface for OpenFAST Results.Authors:Jake Nunemaker, Nikhar AbbasInstallationpCrunch is installable through pip viapip install pCrunchor conda,conda install pCrunch.Development SetupTo set up pCrunch for development, follow these steps:Download the latest version ofMinicondafor the appropriate OS. Follow the remainingstepsfor the appropriate OS version.From the terminal, install pip by running:conda install-canaconda pipNext, create a new environment for the project with the following.conda create -n pcrunch-devTo activate/deactivate the environment, use the following commands.conda activate pcrunch-dev
conda deactivate pcrunch-devClone the repository:git clonehttps://github.com/NREL/pCrunch.gitNavigate to the top level of the repository
(<path-to-pCrunch>/pCrunch/) and install pCrunch as an editable package
with following commands.pip install -e '.[dev]'(Preferred) Install the pre-commit hooks to autoformat code, ensuring
consistent code style across the repository.pre-commit installExamplesFor an up to date example of the core functionalities, seeexample.ipynb. More
examples coming soon.
Package: pcrunner
Pcrunner (Passive Checks Runner is a daemon and service that periodically runsNagios/Icingachecks paralell. The results are posted via HTTPS to aNSCAwebserver.FeaturesRuns as a daemon on Linux.Runs as a service on win32.Command line interface for single test runs and/or cron use.Parallel execution of check commands.Posts check results external commands.Termniation of check commands if maximum time exceeds.Configuration in YAML.Command definition in YAML or text format.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.
Package: pcrypt
# python-crypt [![Build Status](https://travis-ci.org/thusoy/python-crypt.svg?branch=master)](https://travis-ci.org/thusoy/python-crypt)Pure-python implementation of the crypt(3) SHA2 functions.Useful for creating crypt-compatible hashes from non-*nixes (like Windowsand OS X), like when creating password hashes to initialize a *nix serverwith.## Install$ pip install pcrypt## UsageAPI is identical to the [built-in crypt](https://docs.python.org/3.5/library/crypt.html) module on *nix:>>> import pcrypt, getpass>>> print(pcrypt.crypt(getpass.getpass()))$6$tyjS23QPnY6k37iD$7oM9nObOVQUQ<...>/x7VKbuiyqgT81If you want to override the number of rounds used for hashing, you can specify the parameter `rounds` to crypt:>>> print(pcrypt.crypt(getpass.getpass(), rounds=50000))$6$rounds=50000$FEkeiFqoGiU6Bd3v$6jn8ZZ<...>uXKvs7XAbp.The default number of rounds is 5000, same as for crypt(3).To use SHA256 instead of the default SHA512:>>> print(pcrypt.crypt(getpass.getpass(), pcrypt.METHOD_SHA256))$5$Zcxyug8MUozUjGIQ$yqvzOQR<...>pnLMvpOhhmrOWfn5If the second argument is given it must be either an existing salt string matching theformat `$<algo>$(rounds=<rounds>$)?<salt>($<hash>)?`, or one of `pcrypt.METHOD_SHA256`or `pcrypt.METHOD_SHA512`.Without specifying salt manually the module will generate a new salt and usethe strongest hash function available.As a little extra nugget, there's also a handy CLI to quickly generate a hash:$ pcrypt -husage: pcrypt [-h] [-r ROUNDS] [-a {sha256,sha512}] [-s]Compute a password hash for SHA256/SHA512 in crypt(3)-compatible format.Password will be prompted for.optional arguments:-h, --help            show this help message and exit-r ROUNDS, --rounds ROUNDSHow many rounds of hashing to perform. More rounds areslower, making it harder to reverse a hash throughbrute force. Default: 5000-a {sha256,sha512}, --algo {sha256,sha512}Which algorithm to use. Default: sha512-s, --single-prompt   Don't ask to repeat the password**NB**: You'd probably guess from this being a pure-python implementation of a compute-heavy operation, but I just have to say this explicitly: Do not use this for performance-critical applications! Performance is roughly five orders of magnitude slower than the plain C version.Change log==========[1.0.5] - 2018-01-12--------------------### Fixed- Only print trailing newline in cli when writing to a tty.[1.0.4] - 2016-02-08--------------------### Added- Passwords can now be piped in to the pcrypt CLI.[1.0.3] - 2015-12-19--------------------Practically first release.[1.0.5]: https://github.com/thusoy/python-crypt/compare/v1.0.4...v1.0.5[1.0.4]: https://github.com/thusoy/python-crypt/compare/v1.0.3...v1.0.4
Package: pcs-api
Personal Cloud Storages API abstracts providers and gives
a uniform API to access several personal cloud storages. As of today,
the following providers are supported:Dropbox,hubiC,Google Drive,CloudMe.API provides the following methods:list/create/delete folderupload/download/delete blob (a blob is a regular file)inquire about user and about used/available storage quota.The API is available in many languages (Java, android and Python 2.7).Some samples programs showing how to use pcs_api are availables in the repositorysamplesdirectory.Refer tohttps://github.com/netheosgithub/pcs_apifor more documentation.
Package: pcsFilter
pcsFilterTool for filtering outPythonCodeSmells by
formatting the code and checking the code style after.pcsFilteris a wrapper around the following tools:blueisortflake8radon("cc" command)pcsFilter runs mentioned tools in a given order. The following functionality
is applied on top:flake8number of issues with details andradon ccscore are saved upon
the first run to./.pcsFilterfolder. The./.pcsFilterfolder path is
default and can be overriden via the output path option
(-oor--output-path).WhenpcsFilteris executed again the new results are compared with the
previous ones.If new results are worse then:a short message will be printedif "strict" (-sor--strict) option is used then:pcsFilterwill exit with status = 1New scores and their details will be saved to a default or given output path.UsageShellInstallationpipinstallpcsFilterBase commandpcsFilter<pathtoprojectorfile>StrictFail with status = 1, when new scores are worse. Has no effect during the
first run.pcsFilter-s<pathtoprojectorfile>
pcsFilter--strict<pathtoprojectorfile>Override output pathDefault output path is./.pcsFilter. It can be overriden the following way:pcsFilter-o<newoutputpath><pathtoprojectorfile>
pcsFilter--output-path<newoutputpath><pathtoprojectorfile>Help messagepcsFilter--helpDockerInstallationdockerpullalexdbondarev/pcsfilter:latestBase commanddockerrun--rm-v$(PWD):/project-italexdbondarev/pcsfilter:latest<pathtoprojectorfile>StrictFail with status = 1, when new scores are worse. Has no effect during the
first run.dockerrun--rm-v$(PWD):/project-italexdbondarev/pcsfilter:latest-s<pathtoprojectorfile>
dockerrun--rm-v$(PWD):/project-italexdbondarev/pcsfilter:latest--strict<pathtoprojectorfile>Override output pathDefault output path is./.pcsFilter. It can be overriden the following way:dockerrun--rm-v$(PWD):/project-italexdbondarev/pcsfilter:latest-o<newoutputpath><pathtoprojectorfile>
dockerrun--rm-v$(PWD):/project-italexdbondarev/pcsfilter:latest--output-path<newoutputpath><pathtoprojectorfile>Help messagedockerrun--rm-v$(PWD):/project-italexdbondarev/pcsfilter:latest--helpContributingAny contribution is always welcome!Please followthis code of conduct.This docexplains contribution details.
Package: pcsg
pcsg - a constructive solid geometry library for PythonConstructive geometry is a technique used for modeling shapes and solids.
Thepcsglibrary can be used to create 3D printable solid objects, images and animations utilizing external programs likeOpenScadandPOV-Ray.
Introducing a common description format eleminates the need for learning different scripting languages and rewriting your code.NOTE: The current implementation of pcsg is a prototype. It’s assumed that the API will change in future releases.Getting startedRead thedocumentation.Install fromPyPI.Checkout thesources.
Package: pcs-scraper
pcs_scraperv0.1.0A python package to query, organize and prepare pandas dataframes from procyclingstats.com data to facilitate further analysisProject DescriptionThis project was undertaken as a side project while working as a data/race analyst with professional cycling teams. While commonplace for many other major sports, I couldn't find any available packages that provided access to professional cycling datasets. There were, however, already fantastic websites devoted to cataloguing this data and presenting it for free. The most user-friendly website I found was procyclingstats.com (PCS) but they didn't have a publicly available api, so I decided to make this package to interact with their posted data programmatically.pcs_scraperlets users interact with PCS through three fundamental and distinct classes:RidersTeamsRacesIn the next versions of this project I would like to link the statistical data from PCS with rider Strava data.InstallationVia pip:pip install pcs-scraperVia conda:Coming soonVia source code:Fork/clone this repo and create a conda environment to develop in using:# create environment using existing environment file
conda env create -f environment.yml

# add pcs_scraper to path for environment
cd .../anaconda3/envs/pcs_env/lib/python3.9/site-packages
nano packages.pth 
# then in nano type **full path** to main pcs_scraper directory (ie. .../Users/name/Desktop/pcs_scraper)
# press control+O to save file, press control+X to exit nanoUsageBasic# for specific rider

# import 
import pcs_scraper as pcs

# request rider object for tadej pogacar
pogacar = pcs.Rider(name = 'tadej-pogacar')

# get pogacar's entire race history 
pogacar_race_hx = pogacar.get_race_history()# for specific race

# import
import pcs_scraper as pcs

# request race object for tour de france
tdf = pcs.Race(name = 'tour-de-france', year = 2021)

	# if unsure about spelling of race name according to PCS you can search using:
	# race_options = pcs.race_options_by_year(2021)
	# can refine output using race circuit or classification when requesting
	# race_options = pcs.race_options_by_year(2021, classification = '2.UWT', circuit = 'UCI World Tour')

# request the GC results
tdf_final_gc = tdf.get_results()# for specific team

# import
import pcs_scraper as pcs

# request team object for Ineos 
ineos = pcs.Team(name = 'ineos-grenadiers', year = 2021)

	# if unsure about spelling of team name according to PCS you can search using:
	# team_options_2021 = pcs.teams_by_year(year = 2021, gender = 'M')

# get the riders from the team
ineos_2021_riders = ineos.get_riders()Practical ExamplesComing soonDocumentationComing soon