Saravanan666/pypi-org huggingface dataset:
Package: pycounts_yimengxia
pycounts_yimengxiaCalculate word counts in a text file!Installation$pipinstallpycounts_yimengxiaUsagepycounts_yimengxiacan be used to count words in a text file and plot results
as follows:frompycounts_yimengxia.pycounts_yimengxiaimportcount_wordsfrompycounts_yimengxia.plottingimportplot_wordsimportmatplotlib.pyplotaspltfile_path="test.txt"# path to your filecounts=count_words(file_path)fig=plot_words(counts,n=10)plt.show()ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepycounts_yimengxiawas created by Yimeng Xia. It is licensed under the terms of the MIT license.Creditspycounts_yimengxiawas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pycounts-zherenx
pycounts_zherenxCalculate word counts in a text file!Installation$pipinstallpycounts_zherenxUsagepycounts_zherenxcan be used to count words in a text file and plot results
as follows:frompycounts_zherenx.pycounts_zherenximportcount_wordsfrompycounts_zherenx.plottingimportplot_wordsimportmatplotlib.pyplotaspltfile_path="test.txt"# path to your filecounts=count_words(file_path)fig=plot_words(counts,n=10)plt.show()ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepycounts_zherenxwas created by Zheren Xu. It is licensed under the terms of the MIT license.Creditspycounts_zherenxwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pycounts_zhy99
pycounts_zhy99A package for counting words in a file.Installation$pipinstallpycounts_zhy99Usagepycounts_zhy99can be used to count words in a text file and plot results
as follows:frompycounts_zhy99.pycounts_zhy99importcount_wordsfrompycounts_zhy99.plottingimportplot_wordsimportmatplotlib.pyplotaspltfile_path="test.txt"# path to your filecounts=count_words(file_path)fig=plot_words(counts,n=10)plt.show()ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepycounts_zhy99was created by Hongyang Zhang. It is licensed under the terms of the MIT license.Creditspycounts_zhy99was created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pycounts_zsz
pycounts_zszCalculate word counts in a text file!Installation$pipinstallpycounts_zszUsagepycounts_zszcan be used to count words in a text file and plot results
as follows:frompycounts_zsz.pycounts_zszimportcount_wordsfrompycounts_zsz.plottingimportplot_wordsimportmatplotlib.pyplotaspltfile_path="test.txt"# path to your filecounts=count_words(file_path)fig=plot_words(counts,n=10)plt.show()ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepycounts_zszwas created by shizhezh. It is licensed under the terms of the MIT license.Creditspycounts_zszwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pycounts_zty
pycounts_ztyCalculate word counts in a text file!Installation$pipinstallpycountsUsagepycountscan be used to count words in a text file and plot results
as follows:frompycounts.pycountsimportcount_wordsfrompycounts.plottingimportplot_wordsimportmatplotlib.pyplotaspltfile_path="test.txt"# path to your filecounts=count_words(file_path)fig=plot_words(counts,n=10)plt.show()ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepycounts_ztywas created by Rachel Li. It is licensed under the terms of the MIT license.Creditspycounts_ztywas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pycounts-zwj
pycounts_zwjCalculate word counts in a text file!Installation$pipinstallpycounts_zwjUsageTODOContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepycounts_zwjwas created by Wenjia Zhu. It is licensed under the terms of the MIT license.Creditspycounts_zwjwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pycount-thayehas1
pycounts_thayehas1Calculate word counts in a text file!Installation$pipinstallpycounts_thayehas1Usagepycounts_thayehas1can be used to count words in a text file and plot results
as follows:frompycounts_thayehas1.pycounts_thayehas1importcount_wordsfrompycounts_thayehas1.plottingimportplot_wordsimportmatplotlib.pyplotaspltfile_path="test.txt"# path to your filecounts=count_words(file_path)fig=plot_words(counts,n=10)plt.show()ContributingInterested in contributing? Check out the contributing guidelines.
Please note that this project is released with a Code of Conduct.
By contributing to this project, you agree to abide by its terms.Licensepycounts_thayehas1was created by Taiwo Owoseni. It is licensed under the terms
of the MIT license.Creditspycounts_thayehas1was created withcookiecutterand
thepy-pkgs-cookiecuttertemplate.
Package: pycountwords
pycountsCalculate word counts in a text file!Installation$pipinstallpycountsUsagepycountscan be used to count words in a text file and plot results
as follows:frompycounts.pycountsimportcount_wordsfrompycounts.plottingimportplot_wordsimportmatplotlib.pyplotaspltfile_path="test.txt"# path to your filecounts=count_words(file_path)fig=plot_words(counts,n=10)plt.show()ContributingInterested in contributing? Check out the contributing guidelines.
Please note that this project is released with a Code of Conduct.
By contributing to this project, you agree to abide by its terms.Licensepycountswas created by Tomas Beuzen. It is licensed under the terms
of the MIT license.Creditspycountswas created withcookiecutterand
thepy-pkgs-cookiecuttertemplate.
Package: pycount-xilinx
pycount_xilinxCount words in a text file.Installation$pipinstallpycount_xilinxUsagepycount_xilinxcan be used to count words in a text file and plot results
as follows:frompycount_xilinx.pycountsimportcount_wordsfrompycount_xilinx.pycountsimportplot_wordsimportmatplotlib.pyplotasplot_wordsfile_path="test.txt"# path to your filecounts=count_words(file_path)fig=plot_words(counts,n=10)plt.show()ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepycount_xilinxwas created by Xilinx. It is licensed under the terms of the MIT license.Creditspycount_xilinxwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pycourseexam
PyCourseDOCUMENTANCIÓN EN ELABORACIÓNModulo de python que permite procesar información de determinas instancias de evaluación (previamente configuradas) y calcular si un alumno aprobó el curso o no.Los cursos (fundamentalmente los unversitarios) pueden tener diferentes instancias de evaluación, cada una con sus requerimientos para aprobarlas.Supongamos un curso que tiene 2 parciales, cada uno con su recuperatorio, pero el primer parcial se aprueba con 4, su recuperatorio con 4, pero el segundo parcial se aprueba con 6 y su recuperatorio con 7.Configurando un sencillodictionaryde python con esta información y con los campos donde se almacenan los resultados de cada instancia, el módulo calcula si el alumno aprobó o no el curso, y en caso de haber aprobado, calcula el promedio con las notas de los examenes (parcial o recuperatorio) aprobados.RequerimientosPython 3.8pandas=>1.3.3Modo de usoInstalaciónpip install pycourseImportimport pycourseConfiguración deldictionaryde examenes y notas mínimasdict = {
        primer_instancia:{
                           'primer_parcial' : 4,
                           'primer_recuperatorio' : 4
                           },
        segunda_instancia:{
                           'segundo_parcial' : 4,
                           'segundo_recuperatorio' : 4
                           },
        tercer_instancia: {
                           'solo_un_examen' : 7
        }
                           
}El uso es relativamente sencillo. Sólo tener en cuenta que los nombres dentro de lasninstancias corresponden a los nombres de las columnas donde se encuentran las notas de los alumnos de ese examen.Luego, se llama a la función:approve (nombre_del_df, dict)Change Log0.0.1 (30/11/2021)First release
Package: pycourseprogress
Course Progress APIA one-liner description of your project goes here.This project is intended to grab data from course progress domains (*.courseprogress.co.uk).Tested with a swim school course on southnorfolk.courseprogress.co.uk.Install# Install toolpip3installpycourseprogress# Install locallyjustinstallDevelopment# Get a comprehensive list of development toolsjust--list
Package: pycover
A simple and elegant client that allows you to make group voice calls quickly and easily.Examples•Documentation•PyPi•Channel•ChatPyCoverThis project allows making Telegram group call using MtProto and WebRTC, this is possible thanks to the power of NodeJS's WebRTC library and@evgeny-nadymovWhat are the supported clients?The supported clients for now are Fipper and Telethon, but we accept other clients too, you can open a pull request with the editsHow to install?Here's how to install the PyCover lib, the commands are given below:# With Gitpipinstallgit+https://github.com/pytgcalls/pytgcalls-U# With PyPi (Recommended)pipinstallpy-tgcalls-UConversion command (Video)From file to raw videoffmpeg-i{INPUT_FILE}-frawvideo-pix_fmtyuv420p-vfscale=640:-1{OUTPUT_FILE}From H264/VP8/VP9 to Audio and Videoffmpeg-i{INPUT_FILE}-fs16le-ac1-ar{BITRATE}{OUTPUT_AUDIO_FILE}-frawvideo-r{FRAMERATE}-pix_fmtyuv420p-vfscale={SCALING}:-1{OUTPUT_VIDEO_FILE}From YouTube video/live-stream to Audio and Videoffmpeg-i"$(youtube-dl-x-g"{YOUTUBE_LINK}")"-fs16le-ac1-ar{BITRATE}{OUTPUT_AUDIO_FILE}-frawvideo-r{FRAMERATE}-pix_fmtyuv420p-vfscale={SCALING}:-1{OUTPUT_VIDEO_FILE}From YouTube Live stream to VideoImportant!The max resolution allowed by Telegram is of 720p at 30 fps
Here also listed the scaling format360p = 640480p = 854720p = 1280If you have any problem with green screen or un-synchronized video, it can be one of these problems:Invalid FFMPEG commandThe video quality specified to convert is higher than the original video oneInvalid PyCover video parametersIf you're using fifo, the Fifo max buffer size is too low and this cause the lag problem.Conversion commandsFrom file to raw formatffmpeg-i{INPUT_FILE}-fs16le-ac1-ar{BITRATE}{OUTPUT_FILE}From stream link to raw formatffmpeg-y-i{STREAM_LINK}-fs16le-ac1-ar{BITRATE}{OUTPUT_FILE}From YouTube video/live-stream to raw formatffmpeg-i"$(youtube-dl-x-g"{YOUTUBE_LINK}")"-fs16le-ac1-ar{BITRATE}{OUTPUT_FILE}CreditsBig thanks to@evgeny-nadymovfor allowing us to use their code fromtelegram-react, and thanks
toalemidevfor helping to rebuild this libraryThis library is based ontgcallsjsdeveloped@AndrewLaneXand pyservercall by@Laky-64
Package: py-cover-letters
Py Cover LettersProject to create, manage and email cover letters.This app will only run in linux and Mac OS. I'm not sure it will run in Windows.Documentation:https://luiscberrocal.github.io/py-cover-lettersGitHub:https://github.com/luiscberrocal/py-cover-lettersPyPI:https://pypi.org/project/py-cover-letters/Free software: MITFeaturesTODOCreditsThis package was created withCookiecutterand thewaynerv/cookiecutter-pypackageproject template.
Package: pycoverm
pyCoverMThis package is still in experimental stages and aims to be a simple Python interface toCoverM's fast coverage estimation functions. Currently, pyCoverM provides two functions:is_bam_sorted, which checks whether a BAM file is sorted by coordinate, andget_coverages_from_bam, that computes average contig coverages from sorted BAM files.Installationpip install pycovermUsage/// is_bam_sorted(bam_file)/// --////// Checks whether a BAM file is sorted by coordinate.////// Parameters/// ----------/// bam_file : str///     Path to a BAM file.////// Returns/// -------/// bool///     Returns `True` if the BAM file is sorted by coordinate and `False`///     otherwise./// get_coverages_from_bam(bam_list, contig_end_exclusion=75, min_identity=0.97,/// trim_lower=0.0, trim_upper=0.0, contig_list=None, threads=1)/// --////// Computes contig mean coverages from sorted BAM files. All BAM files must be/// mapped to the same reference./// Trimmed means will be computed if `trim_min` and/or `trim_max` are set to/// values greater than 0.////// Parameters/// ----------/// bam_list : list///     Paths to input BAM files./// contig_end_exclusion : int, optional///     Exclude bases at the ends of reference sequences from calculation.///     Default is 75./// min_identity : float, optional///     Exclude reads by overall identity to the reference sequences.///     Default is 0.97./// trim_lower : float, optional///     Fraction to trim from the lower tail of the coverage distribution.///     Default is 0.0./// trim_upper : float, optional///     Fraction to trim from the upper tail of the coverage distribution.///     Default is 0.0./// contig_set : set, optional///     If provided, only the coverages of the contigs within `contig_set` will///     returned.///     Default is None (return the coverages of all contigs)./// threads : int, optional///     Number of threads to use for coverage computation. Default is 1.////// Returns/// -------/// tuple///     A tuple whose fist element is a list of the contig names and the second///     one is a numpy matrix of contig coverages in the input BAM files.
Package: pycovfefe
Info:Simple module to convert content to “covfefe” qualityVersion:0.1a0Author:Peter Sanchez (http://www.petersanchez.com)CreditNow any Python developer can take their content and improve it to “covfefe” quality with ease.End tweets with styleIt’s a frameworkNod to Kyle Kelley for his JS library -https://github.com/rgbkrk/covfefeInstallationPIP:pip install pycovfefeBasic Manual Install:$ python setup.py build
$ sudo python setup.py installUsageUsage – Python>>> from confefe import convert
>>> convert('Despite the constant negative press')
u'Despite the constant negative press covfefe'Usage – CLI$ covfefe Despite the constant negative press
Despite the constant negative press covfefeTestingTo test the library run$ python tests.pyCopyright & WarrantyAll documentation, libraries, and sample code are
Copyright 2017 Peter Sanchez <petersanchez@gmail.com>. The library
and sample code are made available to you under the terms of the BSD license
which is contained in the included file, BSD-LICENSE.
Package: pycovid-19
Pycovid-19COVID-19 Python plots and mapsThis small package allows for downloading and plotting
covid-19 confirmed cases, recovered and deaths from data
gathered by theJohn Hopkins University.
It allows for country evolutions to be compared between
them, as well as for prevalence to be calculated.Basic usageJupyter notebookLaunch Binder to get access to the online interactive Jupyternotebook.
Once you are in the online Jupyter Lab, you just has to open thecovid-notebooknotebook, and adapt the different functions to your own needs (countries,
case type, type of visualization, etc.).Local installationTo install the package locally, the following line should do the trick:$ pip install pycovid-19See alsoLouis Gostiaux'spackage
Package: pycovid19lstm
COVID19 Cases Forcast Time Series By using LSTMaboutA small package of Python to access and track the number of cases of confirmed and deaths and  recovered people
from the Coronavirus for any countryInstallationpip install covid19-cases
or in colab google cloud
!pip install covid19-casesUsagefrom covid19_cases import corona19
country_name='any_country' #name of country# to get confirmed count for country in real time
confirmed_count=corona19.confirmed_people(country_name)
#to get deaths count for country in real time 
deaths_count=corona19.deaths_people(country_name)
#to get recoverd count in real time 
recoverd_count=corona19.recoverd_people(country_name)CheckingTo verify the retrieved data within this library
go to worldmeters web site for checking for any coutryhttps://www.worldometers.info/coronavirus
Package: pycovid-india
india_covidIndian COVID-19 Vaccine and Cases Status
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people who fall sick with COVID-19 will experience mild to moderate symptoms and recover without special treatment.import packagePython3.6.9(default,Jan262021,15:33:00)[GCC8.4.0]onlinuxType"help","copyright","credits"or"license"formoreinformation.>>>importpycovid_india>>>inCovid=pycovid_india.CovidInfo()>>>>>>Get State idthisidstate code. return value dict format.>>>>>>inCovid.get_state_idoutput:{"0":"Andaman and Nicobar","1":"Andhra Pradesh","2":"Arunachal Pradesh","3":"Assam","4":"Bihar","5":"Chandigarh","6":"Chhattisgarh","7":"Dadra and Nagar Haveli and Daman and Diu","8":"Delhi","9":"Goa","10":"Gujarat","11":"Haryana","12":"Himachal Pradesh","13":"Jammu and Kashmir","14":"Jharkhand","15":"Karnataka","16":"Kerala","17":"Ladakh","18":"Lakshadweep","19":"Maharashtra","20":"Manipur","21":"Meghalaya","22":"Mizoram","23":"Madhya Pradesh","24":"Nagaland","25":"Odisha","26":"Puducherry","27":"Punjab","28":"Rajasthan","29":"Sikkim","30":"Tamil Nadu","31":"Telengana","32":"Tripura","33":"Uttar Pradesh","34":"Uttarakhand","35":"West Bengal"}india covid vaccine last update infomation>>>>>>inCovid.get_covid_vaccine_last_update()output:{"day":"2021-05-29","india_dose1":167617477,"india_dose2":44449137,"india_total_doses":212066614,"india_last_dose1":164779253,"india_last_dose2":44123192,"india_last_total_doses":208902445}get state covid cases infomation and covid acivityinput id is state code16>>>inCovid.get_state_covid_info(16)output:{"Name of State / UT":"Kerala","state_code":"32","abbreviation_code":"KL","state_helpline":"0471-2552056","covid_portal_url":"http://dhs.kerala.gov.in/public-health-2019-n-corona-virus/","covid_facilities":"http://arogyakeralam.gov.in/2020/03/25/guidelines/","state_donation_url":"https://donation.cmdrf.kerala.gov.in/","Total Confirmed cases":"2494385","Active":"233425","Cured/Discharged/Migrated":"2252505","Death":"8455","whatsapp_chatbot_url":"https://wa.me/919072220183?text=Hi","fb_chatbot_url":"","epass_url":"https://covid19jagratha.kerala.nic.in/home/addDomestic","last_confirmed_covid_cases":"2470872","last_cured_discharged":"2224405","last_death":"8257","last_active_covid_cases":"238210","diff_confirmed_covid_cases":"23513","diff_cured_discharged":"28100","diff_death":"198","diff_active_covid_cases":"-4785"}get state covid vaccine activitythis id state code30>>>inCovid.get_state_covid_vaccine_info(30)output{"st_name":"Tamil Nadu","state_id":"31","covid_state_name":"Tamil Nadu","covid_state_id":"33","dose1":"6782968","dose2":"2013165","total_doses":"8796133","last_dose1":"6523932","last_dose2":"1995551","last_total_doses":"8519483"}
Package: pycows
Thecowspython package is an implementation of the cosmic filament finder COsmic Web Skeleton (COWS). The cosmic filament finder works on Hessian-based cosmic web idetifier (such as the V-web) and returns a catalogue of filament spines.It works by identifying the medial axis, or skeleton, of cosmic web filaments and then separating this skeleton into individual filaments. For more information of the specifics of the method, seehere.Requirementsnumpy>=1.19.3Quick installationTo install thecowspython package using PyPI:pip install pycowsTo install the package from source:python setup.py installFor more inforamtion on installation, seeINSTALL.rst.DocumentationThe full documentation can be accessed atreadthedocsor generated as a set of local files by running:sphinx-build ./docs ./docs/_buildCitingWhen using COWS in a publication, please cite the following paper:arXiv:2201.04624: “COWS: A filament finder for Hessian cosmic web identifiers”
Package: pycowsay
pycowsayA talking cow!RunUsepipxto run without permanently installingpipx run pycowsay mooo>> pipx run pycowsay mooooo

  ------
< mooooo >
  ------
   \   ^__^
    \  (oo)\_______
       (__)\       )\/\
           ||----w |
           ||     ||InstallUsepipxto install to isolated environmentpipx install pycowsayorpip install pycowsay>> pycowsay mooooo

  ------
< mooooo >
  ------
   \   ^__^
    \  (oo)\_______
       (__)\       )\/\
           ||----w |
           ||     ||
Package: pycowsay-rich
pycowsay-richA talking cow! Arichversion ofpycowsay.RunUsepipxto run without permanently installing.pipxrunpycowsay-richmoooInstallUsepipxto install to isolated enviroment.pipxinstallpycowsay-richUsepipto install to python enviroment.pipinstallpycowsay-rich
Package: pycox
pycoxis a python package for survival analysis and time-to-event prediction withPyTorch.
It is built on thetorchtuplespackage for trainingPyTorchmodels.Read the documentation at:https://github.com/havakv/pycoxThe package containssurvival models: (Logistic-Hazard, DeepHit, DeepSurv, Cox-Time, MTLR, etc.)evaluation criteria (concordance, Brier score, Binomial log-likelihood, etc.)event-time datasets (SUPPORT, METABRIC, KKBox, etc)simulation studiesillustrative examples
Package: pycoxmunk
PyCoxMunkA python library for simulating satellite-viewed sea surface reflectances.The pycoxmunk library computes the sea surface reflectance, using theCox-Munk method, as expected to be seen from space based on the satellite and
weather conditions at the sea surface.The main purpose of this library is to enable an easy method for computing sea surface reflectance that is applicable
to a wide variety of low-earth and geostationary orbit satellites and sensors. The library is closely linked to thesatpy librarythat loads, calibrates and produces projection information for many
satellites. Under the hood, pycoxmunk usesdaskandxarrayto store and process data. Results are made available via the samesatpyscene used to provide the input satellite images.As well as computing the sea surface reflectance, pycoxmunk can also compute the four BRDF terms, which can be useful in
radiative transfer, cloud and aerosol properties retrieval codes, and other uses such as cloud or sea ice detection.Installationpycoxmunk can be installed from PyPI with pip:pipinstallpycoxmunkIt is also available fromconda-forgefor conda installations:condainstall-cconda-forgepycoxmunkTestspycoxmunk comes with a set of scripts for testing the functionality of the library. These are located in the./Tests/subdirectory and can be run usingpytest:cd Tests
pytest .This will run all tests. You can also run just a single test script with, for example,pytest test_CMCalcs.py.
You may first need to install pytest via:conda install pytest.Once testing is complete, a summary will be displayed. This should indicate that all tests have passed, as well as
potentially listing some warnings depending on your environment and the current status ofpycoxmunk's dependencies.CreditsThis code was written by Simon Proud and is based on a fortran implementation of the Cox-Munk algorithm written by
Greg McGarragh as part of theORAC algorithm.Feedback and ContributionFeedback, suggestions, bug reports or any other type of contribution is welcome.If you encounter any problems with this code or the documentation then please file anissue.
It may help in debugging any problems to enable satpy's debug mode:fromsatpyimportdebug_ondebug_on()This will print additional log and diagnostic information.Suggestions for new features are welcome, but may not always be possible for me to code due to limited time. You can
also submit your ownpull requeststhat add features of fix bugs.
This is the recommended way to change the library code, rather than emailing me your updates.
By submitting a pull request please ensure that your code changes and additions are documented and, where appropriate,
covered by tests.