Saravanan666/pypi-org huggingface dataset:
Package: pycv
PyCV is a package of C++ and Python modules implementing various algorithms
that are useful in computer vision, and augments the capabilities of OpenCV.
In particular, PyCV provides implementations for:Fast training and selection of Haar-like features for a weak classifier[Pham2007b].  This is currently the world’s fastest method for training a face
detector. It runs in just a few hours, while most existing methods run in
days or weeks.Asymmetric Online Boosting[Pham2007a]: a variant of AdaBoost that learns
incrementally using an asymmetric goal as the learning criterion.Additionally, PyCV contains many useful modules for computer vision and
machine learning, specially boosting techniques, Haar-like features, and face
detection.The package is primarily developed by Minh-Tri Pham, as part of his PhD
research on face detection. This research is being carried out in the Centre
for Multimedia & Network Technology (CeMNet), School of Computer Engineering,
Nanyang Technological University, Singapore.Copyright 2007 Nanyang Technological University, Singapore.Founding Contributors:Minh-Tri Pham <mtpham@ntu.edu.sg> – Primary authorViet-Dung D. Hoang <hoan0008@ntu.edu.sg> – Contributing authorTat-Jen Cham <astjcham@ntu.edu.sg> – Supervising facultyReferences[Pham2007a]Minh-Tri Pham and Tat-Jen Cham. Online Learning Asymmetric
Boosted Classifiers for Object Detection. In Proc. IEEE Computer Society
Conference on Computer Vision and Pattern Recognition (CVPR’07),
Minneapolis, MN, 2007.[Pham2007b]Minh-Tri Pham and Tat-Jen Cham. Fast Training and Selection of
Haar features using Statistics in Boosting-based Face Detection. In Proc.
11th IEEE International Conference on Computer Vision (ICCV’07), Rio de
Janeiro, Brazil, 2007.
Package: pycvcqv
pycvcqvCoefficient of Variation (CV) and Coefficient of Quartile Variation (CQV) with Confidence Intervals (CI)Python port ofcvcqvIntroductionpycvcqvprovides some easy-to-use functions to calculate the
Coefficient of  Variation (cv) and Coefficient of Quartile Variation (cqv)
with confidence intervals provided with all available methods.InstallpipinstallpycvcqvUsageimportpandasaspdfrompycvcqvimportcoefficient_of_variation,cqvcoefficient_of_variation(data=[0.2,0.5,1.1,1.4,1.8,2.3,2.5,2.7,3.5,4.4,4.6,5.4,5.4],multiplier=100,)# 64.6467cqv(data=[0.2,0.5,1.1,1.4,1.8,2.3,2.5,2.7,3.5,4.4,4.6,5.4,5.4],multiplier=100,)# 51.7241data=pd.DataFrame({"col-1":pd.Series([0.2,0.5,1.1,1.4,1.8,2.3,2.5,2.7,3.5]),"col-2":pd.Series([5.4,5.4,5.7,5.8,5.9,6.0,6.6,7.1,7.9]),})coefficient_of_variation(data=data,num_threads=3)#   columns      cv# 0   col-1  0.6076# 1   col-2  0.1359cqv(data=data,num_threads=-1)#   columns      cqv# 0   col-1  0.3889# 1   col-2  0.0732For contributors:Testing:exportPATH="$HOME/.poetry/bin:$PATH"makeinstall
makepre-commit-install
maketest&&makecoverage&&makecheck-codestyle&&makemypy&&makecheck-safety&&makeextrabadgesUpload code to GitHub:gitpull
pre-commitrun--all-files
gitadd.
gitcommit-m":tada: Initial commit"gitpush-uoriginmainCreditsThis project was generated withpython-package-templateLicense
Package: py-cvedb
cvedbA local CVE db repositoryClone thecvelistV5github repoloop through all CVEsCVE instance will be created based on CVE json fileIf the CVE json file contains metrics entry, create Metrics for the CVEOtherwise, if--create-metricsargument is given, fetch metrics from NVD and create Metrics for the CVEstore in local database (python pickle)InstallationUse pip command to install:pipinstallpy-cvedbUsageCommand LineUsecvedb --cloneto clone thecvelistV5 repoand init the local dataThis action will first check ifcvelistV5 repois cloned.If not cloned yet, clone the repo firstThen, loop through all CVE JSON file and create CVE instanceThe local database will be dumped to a compressed pickle file located in$HOME/.config/cvedb/cvedb.pickleUsecvedb --updateto check if there contains update fromcvelistV5 repoIf contains detectedFirstly, get all updated fileRe-create CVE instance and do update or insert to local databaseThecvelistV5 repotake several minutes to clone, actual time taken is affected by Internet connectionSearchUsecvedb -sorcvedb --searchto search from databaseusing-yor--yearto get CVEs in a specific yearAdding-por--patternto filter out CVE records. Give a string start will-for negative match.If giveninjection -databasewill get all records containsinjectionbut notdatabase.using-ior--idto get CVE with a specific CVE idUse it in python project>>>fromcvedbimportcvedb>>>>>>cvedb=cvedb.init_db()>>>type(cvedb)# <class 'cvedb.cvedb.CVEdb'>
Package: pycvesearch
Important Note: The API search endpoint has been removed from the public instance due to massive abusive behavior. You can use this API against a local version of CVE Search.PyCVESearchis an easy to use wrapper around cve-search. Some of the calls will work againsthttps://cve.circl.lubut for most of them, you need your own CVE Search instance. For the ones available on the public instance, seehttps://github.com/cve-search/PyCVESearch/blob/main/tests/tests.py.This library is based on the work ofMartin SimonandKai Renken.Installation:From source use$ pip install pycvesearchDocumentation:GET /api/browse/GET /api/browse/vendor>>>frompycvesearchimportCVESearch>>>cve=CVESearch()>>>cve.browse(<vendor>)GET /api/search/vendor/product>>>cve.search('microsoft/office')GET /api/cveid/cveid>>>cve.id('CVE-2014-0160')GET /api/last>>>cve.last()GET /api/dbInfo>>>cve.dbinfo()GET /api/cpe2.2/cpe>>>cve.cpe22('cpe:/a:microsoft:office:2011::mac')GET /api/cpe2.3/cpe>>>cve.cpe23('cpe:2.3:a:microsoft:office:2011:-:mac')GET /api/cvefor/cpe>>>cve.cvefor('cpe:/a:microsoft:office:2011::mac')License:Apache v2.0 License
    Copyright 2015-2016 Martin Simon
    Copyright 2015-2016 Kai Renken
    Copyright 2016 Raphaël Vinot

     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.
Package: pycvm
Aboutcvmis a Python library whose job is to extract data from publicly-held companies
provided by CVM, thus allowing its use in automated systems. The library was designed
to be part of a software for analysis of public companies, although it may be used on
its own for other purposes.What is the CVM?CVM is the acronym for "Comissão de Valores Mobiliários" ("Securities and Exchange Commission"),
which is the government agency that defines the rules for publicly-held companies.
In addition to regulating such companies, CVM also makes their data available for
public access.CVM DocumentsTheCVM's Data Portalprovides the following types
of documents from publicly-held companies:Registration Form ("Formulário Cadastral" or "FCA")Standardized Financial Statements ("Demonstrações Financeiras Padronizadas" or "DFP")Quarterly Information ("Informações Trimestrais" or "ITR")Reference Form ("Formulário de Referência" or "FRE")Eventual and Periodical Reports ("Informes Periódicos e Eventuais" or "IPE")Registration Information ("Informação Cadastral" or "CAD")Currently, this library supports the documents FCA, FRE (partial), DFP, and ITR.Usageimportcvmwithcvm.FCAFile('path/to/fca.zip')asfile:forfcainfile:print(fca.company_name,'sent an FCA document on',fca.receipt_date)withcvm.DFPITRFile('path/to/dfp_or_itr.zip')asfile:fordfpitrinfile:print(dfpitr.company_name,'sent a',dfpitr.type.name,'document on',dfpitr.receipt_date)Note that this library has not been thoroughly tested and its API is still unstable.More elaborated examples are in the directorysamples:>python-msamples.dfp.print_accounts'path/to/dfp_or_itr.zip'>python-msamples.dfp.print_balances'path/to/dfp_or_itr.zip'
Package: pycvodes
pycvodesprovides aPythonbinding to theOrdinary Differential Equationintegration routines fromcvodesin theSUNDIALS suite.pycvodesallows a user to numerically integrate
(systems of) differential equations. Note that routines for sensitivity analysis is not yet exposed in this binding (which makes
the functionality essentially the same as cvode).The following multistep methods are available:bdf: Backward differentiation formula (of order 1 to 5)adams: implicit Adams method (order 1 to 12)Note that bdf (as an implicit stepper) requires a user supplied
callback for calculating the jacobian.You may also want to know that you can usepycvodesfrompyodesyswhich can e.g. derive the Jacobian analytically (using SymPy). Pyodesys also provides
plotting functions, C++ code-generation and more.DocumentationAutogenerated API documentation for latest stable release is found here:https://bjodah.github.io/pycvodes/latest(and the development version for the current master branch are found here:http://hera.physchem.kth.se/~pycvodes/branches/master/html).InstallationSimplest way to install is to use theconda package manager:$ conda install -c conda-forge pycvodes pytest
$ python -m pytest --pyargs pycvodestests should pass.Manual installationBinary distribution is available here:https://anaconda.org/bjodah/pycvodesSource distribution is available here:https://pypi.python.org/pypi/pycvodesWhen installing from source you can choose what lapack lib to link against by setting
the environment variablePYCVODES_LAPACK, your choice can later be accessed from python:>>>frompycvodesimportconfig>>>config['LAPACK']# doctest: +SKIP'lapack,blas'If you usepipto installpycvodes, note that prior to installing pycvodes, you will need
to install sundials (pycvodes>=0.12.0 requires sundials>=5.1.0, pycvodes<0.12 requires sundials<5)
and its development headers, with cvodes & lapack enabledExamplesThe classic van der Pol oscillator (seeexamples/van_der_pol.py)>>>importnumpyasnp>>>frompycvodesimportintegrate_predefined# also: integrate_adaptive>>>mu=1.0>>>deff(t,y,dydt):...dydt[0]=y[1]...dydt[1]=-y[0]+mu*y[1]*(1-y[0]**2)...>>>defj(t,y,Jmat,dfdt=None,fy=None):...Jmat[0,0]=0...Jmat[0,1]=1...Jmat[1,0]=-1-mu*2*y[1]*y[0]...Jmat[1,1]=mu*(1-y[0]**2)...ifdfdtisnotNone:...dfdt[:]=0...>>>y0=[1,0];dt0=1e-8;t0=0.0;atol=1e-8;rtol=1e-8>>>tout=np.linspace(0,10.0,200)>>>yout,info=integrate_predefined(f,j,y0,tout,atol,rtol,dt0,...method='bdf')>>>importmatplotlib.pyplotasplt>>>series=plt.plot(tout,yout)>>>plt.show()# doctest: +SKIPFor more examples seeexamples/, and rendered jupyter notebooks here:http://hera.physchem.kth.se/~pycvodes/branches/master/examplesLicenseThe source code is Open Source and is released under the simplified 2-clause BSD license. SeeLICENSEfor further details.Contributors are welcome to suggest improvements athttps://github.com/bjodah/pycvodesAuthorBjörn I. Dahlgren, contact:gmail address: bjodahSee fileAUTHORSin root for a list of all authors.
Package: pycvs
pycvsA python client for CVS repositories.Yeah, I know that CVS is a hundred years old, but sometimes you are stick to work with it. This utility is your best buddy to help you out! :)AdvantagesNo password promptingBeautiful outputRecursive additionDependenciesIt runs only on Python 3 and depends on some libraries (available at PyPI):pexpect>=4.1.0colorama>=0.3.7InstallationInstall from PyPI:pip3 install pycvsSupported commandsThis contains the current supported commands:Checkout a brand new repository or update an existing one:% pycvs checkout <repo>
Checking out repository repo

385 files checked out
70 directories checked out

% pycvs update <repo>Get current status of a repository:% cd my_repo
% pycvs status
On branch HEAD
Untracked files:
 (use cvs add <file>... to add them for commit)

  	bla

Changes staged for commit:
 (use cvs commit... to check them in)

	./my_script.pyAdd new files to repository. It works recursively:% cd my_repo
% pycvs add foo/
Directory foo added
	staging foo/bla to commit
	staging foo/ble to commitDiff the modified files from the server:% pycvs diff [parameters]
(open a less windows with the differences in the unified syntax and colors)Log the file history from the server:% pycvs log [parameters]
(open a less windown with file's revisions, tags...)
Package: pycvss
Easily manipulate and compute scores according to the Common Vulnerability Scoring SystemCurrent statusThis library was developped following the specifications athttp://www.first.org/cvss/cvss-guideand is currently in a stable state.PyCvss is available in the cheeseshop, you can start using it withpipinstallpycvssFeaturesCompute base, temporal and environmental scoresConvert from and to short vectors (“AV:N/AC:L/Au:N/C:C/I:C/A:C”)100% test coveragePure pythonUsagec=Cvss()# Build from enums:c.set(AV.network)c.set(E.functional)c.set(CDP.low)# Or from a vector:c=Cvss.from_vector("AV:N/CDP:L/E:F")# Get scores.c.to_vector())# "AV:N/CDP:L/E:F"c.base_score# 7.8c.temporal_score# 6.4c.environmental_score# 9.2Or from a real CVE(2002_0392)c=Cvss.from_vector("AV:N/AC:L/Au:N/C:N/I:N/A:C")# tempc.set(E.functional)c.set(RL.official_fix)c.set(RC.confirmed)# envc.set(CDP.high)c.set(TD.high)c.set(CR.medium)c.set(IR.medium)c.set(AR.high)print(c)A:C/AC:L/AR:H/AV:N/Au:N/C:N/CDP:H/CR:M/E:F/I:N/IR:M/RC:C/RL:OF/TD:Hbasescore7.8accessvector1.0accesscomplexity0.71authentication0.704confidentialityimpact0.0integrityimpact0.0availabilityimpact0.66temporalscore6.4exploitability0.95remediationlevel0.87reportconfidence1.0environmentalscore9.2collateraldamagepotential0.5targetdistribution1.0confidentialityrequirement1.0integrityrequirement1.0availabilityrequirement1.51
Package: pycvtools
pycvtoolsFunctionality of the pydlmodelsTake image snaps from videoUsageTo take snap from video/ camera and save it as .jpgTo crop person from an imagepip install pycvtoolsTo runfrom pycvtools import *Functionsvd2img for Video to imagecam2img for camera to omageperson_crop for detection of person from the imageNoteFind detailed functionality onpycvtools.phaf.inPlease drop your suggestions onpydev@phaf.inMore InformationVisitpycvtools.phaf.in
Package: pycw
pycwPython Morse Code GeneratorGenerate Morse Code (CW) audio files in Python.Usageoptional arguments:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Input text file (defaults to stdin)
  -t TEXT, --text TEXT  Input text. Overrides --input.
  -s SPEED, --speed SPEED
                        Speed, in words per minute (default: 12)
  -n TONE, --tone TONE  Tone frequency, in Hz (default: 800)
  -v VOLUME, --volume VOLUME
                        Volume (default: 1.0)
  -r SAMPLE_RATE, --sample_rate SAMPLE_RATE
                        Sample rate (default: 44100)
  -o OUTPUT, --output OUTPUT
                        Name of the output fileOrimport pycwand then use functions in your code, for example:import pycw

pycw.output_wave("Intro.wav", "CQ CQ CQ DE BG5AWO BG5AWO BG5AWO PSE K", 20)Then you can get a output file calledIntro.wavin your working directory.
Package: pycwatch
pycwatchThepycwatchlibrary provides access to theCryptowatch APIand implements all resources of the REST API.InstallationEither install from pypi or clone this repository and install locally.pip install pycwatchQuick StartSee thecryptowat.ch docsfor available endpoints.frompycwatchimportCryptoWatchClient# create api clientclient=CryptoWatchClient()# get list of available assetsassets=client.list_assets()# get some price infoexchange,pair="binance","btceur"price=client.get_market_price(exchange,pair)If you have an account atcryptowat.ch, you can either set your key as an environment variable or in the code.exportCRYPTO_WATCH_KEY="my-awesome-key"orfrompycwatchimportCryptoWatchClientapi_key="my-awesome-key"client=CryptoWatchClient(api_key)Note that anonymous users are limited to 10 Cryptowatch Credits worth of API calls per 24-hour period.
Seehttps://docs.cryptowat.ch/rest-api/rate-limit#api-request-pricing-structurefor more information.
Package: pycwatch-cli
pycwatch-cliThepycwatch-cliis a command line application that makes the power of CryptoWatch
available to you on the command line.CLI InstallationThe easiest way to install is withpipx.pipxinstallpycwatch-cliThis will make the commandpycwavailable.CLI Quick StartRunpycw --helpto get usage info.❯ pycw --help
                                                                                                            
 Usage: pycw [OPTIONS] COMMAND [ARGS]...                                                                    
                                                                                                            
 PyCwatch CLI.                                                                                              
                                                                                                           
╭─ Commands ───────────────────────────────────────────────────────────────╮
│ assets                           Get or list assets.                     │
│ exchanges                        Get or list exchanges.                  │
│ info                             Get API info.                           │
│ markets                          Get or list markets.                    │
│ pairs                            Get or list pairs.                      │
╰──────────────────────────────────────────────────────────────────────────╯All the endpoints implemented bypycwatch-libare available via thepycwcommand.
For example:# list available assetspycwassetslist# get some price infopycwmarketspricebinancebtceur
Package: pycwatch-lib
pycwatchThepycwatchlibrary provides access to theCryptowatch APIand implements all resources of the REST API.InstallationEither install from pypi or clone this repository and install locally.pip install pycwatchQuick StartSee thecryptowat.ch docsfor available endpoints.frompycwatchimportCryptoWatchClient# create api clientclient=CryptoWatchClient()# get list of available assetsassets=client.list_assets()# get some price infoexchange,pair="binance","btceur"price=client.get_market_price(exchange,pair)If you have an account atcryptowat.ch, you can either set your key as an environment variable or in the code.exportCRYPTO_WATCH_KEY="my-awesome-key"orfrompycwatchimportCryptoWatchClientapi_key="my-awesome-key"client=CryptoWatchClient(api_key)Note that anonymous users are limited to 10 Cryptowatch Credits worth of API calls per 24-hour period.
Seehttps://docs.cryptowat.ch/rest-api/rate-limit#api-request-pricing-structurefor more information.
Package: pycw-fn
pycw_fn- efficient piecewise functions in PythonThis package is a Python wrapper around thepcw_fnRust crate built using maturin. It supports arbitrary piecewise functions on the real line.ExampleThis example constructs a few piecewise functions, does some basic arithmetic with them and finally plots them:importnumpyasnpimportmatplotlib.pyplotaspltfromnumpy.polynomialimportPolynomialfrompycw_fnimportPcwFng_0=PcwFn.from_funcs_and_jumps([Polynomial([1,5,-10],window=np.array([-1.,1.]),domain=np.array([-1.,1.])),Polynomial([0,10,-20,10],window=np.array([-1.,1.]),domain=np.array([-1.,1.])),],[0.5,],)g_1=PcwFn.from_funcs_and_jumps([Polynomial([0.4*a**2,-4*a,10],window=np.array([-1.,1.]),domain=np.array([-1.,1.]))forainrange(6)],[0.1,0.3,0.5,0.7,0.9,],)b_2=Polynomial([1/10,-4,40])g_2=PcwFn.from_funcs_and_jumps([b_2(Polynomial([-0.1*a,1]))forainrange(10)],np.linspace(0.1,1,num=9,endpoint=False),)g=g_0+5*g_2ts=np.linspace(0,1,num=1000)ys=g(ts)plt.plot(ts,ys)plt.show()
Package: pyc-wheel
pyc_wheelCompile all py files in a wheel to pyc files.Overviewpyc_wheelis a strict fork of Grant Patten’spycwheelpackage
with a fixes allowing to work with Python3 or higher and with a code
reformatting and some improvements.PyPI record.Documentation.UsageProcessing the wheel in place:$python-mpyc_wheelyour_wheel-1.0.0-py3-none-any.whl# Output: your_wheel-1.0.0-py3-none-any.whlor with backup:$python-mpyc_wheel--with_backupyour_wheel-1.0.0-py3-none-any.whl# Output: your_wheel-1.0.0-py3-none-any.whl
#         your_wheel-1.0.0-py3-none-any.whl.bakor with quiet:$python-mpyc_wheel--quietyour_wheel-1.0.0-py3-none-any.whl# Output: your_wheel-1.0.0-py3-none-any.whlInstallationPrerequisites:Python 3.6 or higherhttps://www.python.org/3.7 is a primary test environment.pip and setuptoolshttps://pypi.org/project/pip/https://pypi.org/project/setuptools/To install run:python -m pip install --upgrade pyc_wheelDevelopmentPrerequisites:Development is strictly based ontox. To install it run:python -m pip install --upgrade toxVisitdevelopment page.Installation from sources:clone the sources:git clonehttps://github.com/karpierz/pyc_wheel.gitpyc_wheeland run:python -m pip install ./pyc_wheelor on development mode:python -m pip install --editable ./pyc_wheelLicenseCopyright (c) 2016 Grant PattenCopyright (c) 2019-2021 Adam KarpierzLicensed under the MIT Licensehttps://opensource.org/licenses/MITPlease refer to the accompanying LICENSE file.AuthorsGrant Patten <grant@gpatten.com>Adam Karpierz <adam@karpierz.net>Changelog1.2.7 (2021-10-14)Setup update.1.2.6 (2021-07-20)Setup general update and improvement.1.2.4 (2020-10-18)Drop support for Python 3.5.Fixed docs setup.1.1.0 (2020-09-22)Add support for Python 3.9.Fixed improper permission setting to read distribution.Setup general update and cleanup.1.0.3 (2020-01-16)Added ReadTheDocs config file.Setup update.1.0.2 (2019-12-03)Added the ability to exclude files from compilation.Added the ability to use wildcards.1.0.1rc3 (2019-11-30)A little fix for README.rst1.0.1rc2 (2019-11-30)Creating a fork of Grant Patten’spycwheelpackage with a fixes,changes and improvements allowing to work with Python3 or higher.Changes of the originalpycwheel:1.0.0 (Sep 25, 2016)Initial commit.
Package: py-cwru
IntroductionThepy-cwruis a bearing fault diagnosis dataset and all pythonic, which can be applied toDeep Learning,Transfer LearningandSemi-Supervised Learning(domain adaptation), etc.. Original data comes from the official bearing vibration data of Western Reserve University [1]. The data is based on the original vibration data without repeated segmentation (the sampling window lengthis equal to hop length) and is provided in numpy.Array format.Although the original '*. mat' file can be downloaded automatically at the first call ofpy-cwru, we still recommend you, for possible time consumption and transmission interruption, manually download the dataset file through the link below:Download Link：https://pan.xunlei.com/s/VNNBE0GiGHD5r5_l4BsYOTP-A1?pwd=3syk#Extraction code：3sykYou may need to reorganize file path if you download from the official file:Cwru
	12DriveEndFault
		1797
			12DriveEndFault
				1797	
					0.007-Ball.mat
					..........
			NormalBaseline
				1797
					.........
	12FanEndFault
		......
	48DriveEndFaultOur code refers to [Litchiware/cwru (github.com)] and modifies a bit of impractical code.[1]https://engineering.case.edu/bearingdatacenter/download-data-file.Exampleimportpy_cwrucwru=py_cwru.CWRU(exp='12DriveEndFault',rpm='1797',length=1024,root=r'.')train_x,train_y=cwru.x,cwru.yprint(train_x.shape,train_y.shape)print(type(train_x))--------(2013,1024)(2013,)<class'numpy.ndarray'>