Saravanan666/pypi-org huggingface dataset:
Package: perg
Regex Sampler---Simple commandline utility to generate samples uniformly over the space of strings matching a provided regular expression. Useful for spoofing input to programs!## Example:We can generate a stream of fake JSON data representing people and their emails!```$	./perg.py '{ "name":"(\w+) (\w+)", "email": "\1_\2@\w+.(edu|com|org)"}'{ "name":"R TWER", "email": "R_TWER@PVRcyR)com"}{ "name":"mwGwTOWKRXs GIGY", "email": "mwGwTOWKRXs_GIGY@FvERutwS]org"}{ "name":"igUMTrViMt oTkFPAySfn", "email": "igUMTrViMt_oTkFPAySfn@kQekedu"}{ "name":"MtvMHGBi R", "email": "MtvMHGBi_R@UCPbGDjJai&com"}{ "name":"fbMyddFkTRP QeH", "email": "fbMyddFkTRP_QeH@ekmjacom"}{ "name":"vO devQkFbORdi", "email": "vO_devQkFbORdi@LaAPfnmMcnTZlYorg"}{ "name":"khT BoWvCONzyeOYoNgasncZnU", "email": "khT_BoWvCONzyeOYoNgasncZnU@kV-com"}{ "name":"TmEU TvjeB", "email": "TmEU_TvjeB@pMMnvdcom"}{ "name":"rzjoN jkpSd", "email": "rzjoN_jkpSd@qTLvRUedu"}{ "name":"pgzQ fz", "email": "pgzQ_fz@Shtedu"}```
Package: pergenie
perGENIEis a Web/CUI application forpersonal genome interpretation. This repository contains
the core utils of perGENIE, such asDisease Risk Report.Quick Start (For non-developers)Without installation, just download this repository and run:$python./pergenie[command][options]Usage ExamplesTo runDisease Risk Report:$python./pergenieriskreport-Iexample/vcf_whole_genome.vcf\-Fvcf_whole_genome\-PAsianFor developpersHow to InstallIf you are familier withpip:$pipinstallpergenieOr clone this repository, then, install by setup script:$pythonsetup.pyinstallHow to run test$pythonsetup.pytestLicenseCopyright (c) 2012,2013,2014,2015 perGENIE Team <knmkr3gma[at]gmail.com>perGENIE is licensed under the GNU AGPLv3.0.CHANGELOG0.1.0
- Initial release0.1.1
- Update readme0.1.2
- Change license to AGPLv30.1.3
- Rewrite README.md to .rst
Package: pergola
CircleCI statusA python library for the conversion of behavioral data into genome
browser compatible formats. Once behavioral data is formatted in genomic
formats it is easy to use genomic software tools for its analysis. For
instance you can query your data using BEDTools or visualize your
records using a genome browser (see snapshot below corresponding to a
rendering of mice feeding behavior on theIGVgenome
browser).For more information, instructions for installation and tutorials please
visit:Pergola documentationYou can also use our web server still under development:Pergola web serverMouse feeding behavior-IGV snapshot
Package: peri
A software which implements the generalized framework of extracting parameters
(e.g. locations and properties of objects in an image) by full reconstruction
of experimental images. The general framework is built on combining components
(e.g. illumination field, background, particles, point-spread function) into a
model which is then optimized given data.InstallationVery straightforward, simply use distutils’ setup.py:python setup.py installTestingTesting is done through nose, and can be performed with:nosetestsDocumentationCurrently, the documentation is hosted athttps://peri-source.github.io/peri-docs/
Package: periancli
MyApp Does Amazing Things!Installation$ pip install -r requirements.txt

$ python setup.py installDevelopmentThis project includes a number of helpers in theMakefileto streamline common development tasks.Environment SetupThe following demonstrates setting up and working with a development environment:### create a virtualenv for development

$ make virtualenv

$ source env/bin/activate


### run pcli cli application

$ pcli --help


### run pytest / coverage

$ make testReleasing to PyPiBefore releasing to PyPi, you must configure your login credentials:~/.pypirc:[pypi]
username = YOUR_USERNAME
password = YOUR_PASSWORDThen use the included helper function via theMakefile:$ make dist

$ make dist-uploadDeploymentsDockerIncluded is a basicDockerfilefor building and distributingMy Application,
and can be built with the includedmakehelper:$ make docker

$ docker run -it pcli --help
Package: pericaat
Interface Extension:Overview:The Interface Extension program was developed to identify pharmacologically relevant residues at the periphery of a protein’s interface from a known three-dimensional structure. First, the set of normal interface and extended interface residues are defined. The normal interface residues are then excluded from the extended interface. Lastly, the potential residues are filtered by their ability to reach the normal interface threshold upon in-silica mutation. The extended interface positions present themselves as important positions in a variety of applications, as mutations at these positions have potential to affect the protein binding without damaging the interface.Installation and Dependencies:Requires python 3.6 or later. Tested on python 3.9.Requires Anocanda to install Modeller easily. (https://www.anaconda.com/)install:pipinstallpericaatDownload Modeller:https://salilab.org/modeller/download_installation.htmlfor Conda enviroment:condaconfig--addchannelssalilabcondainstallmodellerDownload SCRWL4 (optional):http://dunbrack.fccc.edu/lab/scwrlDownload qhull (optional):http://www.qhull.org/Usage:run periCaat:pericaatCommand Line Arguments:-pdb: RCSB PDB id, if not provided you will be prompted to select one. If it is is in the input/ folder it will be used. Otherwise it will be downloaded from the RCSB.-qc: Query chain to find extended positions on.-ic: partner chain.-sr: solvent radius for extension (default 4.4).-mi: Interaction cutoff for extension (default 1).-m:Amino Acids used for extension (default TRP,ARG).-r:Output file name.-c:Number of cores to use in parallel (default 4).Add these flags to use certain features.-p: Run Interface Extention in parallel.--scwrl: Use scrwl4 to remodel sidechain (default no sidechain remodeling) (-s also works).-qh: Use qhull (default pyhull).-nomod: (FOR TESTING ONLY) Dont use modeller and instead just change the names of the residue in the pdb.Notes:Intercaat may not understand pdbs with insertion codes so pdb-tools fixinsert function is run to reformat the pdb. (https://github.com/haddocking/pdb-tools).for extended mutants argument(-m) please use upper case three letter amino acid name separated by a comma without spaces.if qhull is not downloaded then pyhull will be used (wrapper for qhull). For more info on pyhull seehttps://github.com/materialsvirtuallab/pyhull. To use qhull downloaded it (http://www.qhull.org/), update the contents of intercaat_config.ini in 'scripts/intercaatmaster' folder  and use the -qh flag in the command line.if Scrwl4 isnt working make sure it is properly alliased in your shell config (.bashrc or .zshrc).Written by Evan EdelsteinPlease report any questions or complaints tosteven.grudman@einsteinmed.org
Package: peridot-periscope
Periscope (1.0)Usage:Peri.dotvar periscope = include('periscope')

var pscope_add() -> Null {
    return(periscope.skip(
        'Out of date'
    ))
}

var pscope_sub() -> Null {
    assert(10 - 5 == 5)

    return(Null)
}

var pscope_mul() -> Null {
    assert(10 - 1 == 10, 'Hmm. Somethings not right')

    return(Null)
}Bash# Test filesperiscopeperitests/*# More helpperiscope-h
Package: perin-parser
(Unofficial) PERIN: Permutation-invariant Semantic ParsingUnofficial package for the PERIN parser:https://github.com/ufal/perinIntended for easy installation and faster batching.Installationpipinstallperin_parserLicenseCopyright 2020 Institute of Formal and Applied Linguistics, Faculty of
Mathematics and Physics, Charles University, Czech Republic.

This Source Code Form is subject to the terms of the Mozilla Public
License, v. 2.0. If a copy of the MPL was not distributed with this
file, You can obtain one at http://mozilla.org/MPL/2.0/.
Package: periodical-requests-recorder
periodical_requests_recorderUsageperiodical_recorder example.yamlyaml data format example.gmail_address:example@gmail.comgmail_oauth:"~/yagmail_secret.json"tasks:-name:"some_data"url:"https://example.com/somedata.csv"record_dir:"~/hist_data/"output_file_format:"{name}/{name}_%Y-%m-%d.csv"cron_expr:"0******"encoding:"ms932"-name:"some_data_2"url:"https://www.google.com/"record_dir:"~/hist_data/"output_file_format:"{name}/{name}_%Y-%m-%d.txt"cron_expr:"@reboot"target_elements:-element:"#gws-output-pages-elements-homepage_additional_languages__als"index:3Request result will be stored in therecord_dirwith youroutput_file_format.If you set upyagmail, error messages will be sent to your address.cron_exprformat is the same asCrython.InstallationYou can install this with pip.RequirementsCompatibilityLicenceAuthorsperiodical_requests_recorder was written byfx-kirin.
Package: periodic-element-properties
This library has 3 functionsget_element_details_based_on_atomic_numberget_elements_belonging_to_a_particular_groupget_elements_belonging_to_a_particular_period---------------- get_element_details_based_on_atomic_number -----------------from periodic_element_properties import Functions

f = Functions()

element_info = f.get_element_details_based_on_atomic_number(3)

print(element_info)---------------- get_elements_belonging_to_a_particular_group -----------------from periodic_element_properties import Functions

f = Functions()

group_info = f.get_elements_belonging_to_a_particular_group(18)

print(group_info)---------------- get_elements_belonging_to_a_particular_period -----------------from periodic_element_properties import Functions

f = Functions()

period_info = f.get_elements_belonging_to_a_particular_period(1)

print(period_info)
Package: periodicity
PeriodicityUseful tools for periodicity analysis in time series data.Documentation: https://periodicity.readthedocs.ioCurrently includes:Auto-Correlation Function (and other general timeseries utilities!)Spectral methods:Lomb-Scargle periodogramBayesian Lomb-Scargle with linear Trend (soon™)Time-frequency methods:Wavelet TransformHilbert-Huang TransformComposite SpectrumPhase-folding methods:String LengthPhase Dispersion MinimizationAnalysis of Variance (soon™)Decomposition methods:Empirical Mode DecompositionLocal Mean DecompositionVariational Mode Decomposition (soon™)Gaussian Processes:georgeimplementationcelerite2implementationcelerite2.theanoimplementationInstallationThe latest version is available to download via PyPI:pip install periodicity.Alternatively, you can build the current development version from source by cloning this repo (git clone https://github.com/dioph/periodicity.git) and runningpip install ./periodicity.DevelopmentIf you're interested in contributing to periodicity, installpipenvand you can setup everything you need withpipenv install --dev.To automatically test the project (and also check formatting, coverage, etc.), simply runtoxwithin the project's directory.
Package: periodicity-detection
Periodicity DetectionDetect the dominant period in univariate, equidistant time series data.Toolbox for detecting the dominant period in univariate, equidistant time series data.
The toolbox contains the following methods:AutocorrelationAutoPeriodFast Fourier Transform (FFT)find_lengthPython-adaption of the R packageforecast'sfindfrequencyfunctionNumber of Peaks-method📖 Periodicity Detection's documentation is hosted athttps://periodicity-detection.readthedocs.io.InstallationYou can install Periodicity Detection as a package or from source.Prerequisitespython >= 3.7, <= 3.11pip >= 20Installation usingpip(recommended)pipinstallperiodicity-detectionInstallation from sourcegitclonegit@github.com:CodeLionX/periodicity-detection.gitcdperiodicity-detection
pipinstall.UsagePeriodicity Detection can be used as a Python library or as a command line tool.
Please refer to thepackage documentationfor more information.APIimportnumpyasnpimportperiodicity_detectionaspyd# Create sample datadata=np.sin(np.linspace(0,40*np.pi,1000))+np.random.default_rng(42).random(1000)# Calculate period size using a specific methodperiod_size=pyd.findfrequency(data,detrend=True)assertperiod_size==50# Calculate period size using the default methodperiod_size=pyd.estimate_periodicity(data)assertperiod_size==50Plot of the example dataset:CLI$>periodicity--help
usage:periodicity[-h][--version][--use-initial-nUSE_INITIAL_N][--channelCHANNEL]dataset_path{find-length,number-peaks,autocorrelation,fft,autoperiod,findfrequency}...

Detectthedominantperiodinunivariate,equidistanttimeseriesdata.

positionalarguments:dataset_pathPathtothedatasetforwhichthedominantperiodsizeshouldbeestimated.{find-length,number-peaks,autocorrelation,fft,autoperiod,findfrequency}find-lengthDetermineperiodsizebasedonACFasintheTSB-UADrepository.number-peaksCalculatesthenumberofpeaksofatleastsupportninthetimeseriesandthetimeserieslengthdividedbythenumberofpeaksdefinestheperiodsize.autocorrelationDetermineperiodsizebasedonACF.fftDetermineperiodsizebasedonFFT.autoperiodAUTOPERIODmethodcalculatestheperiodsizeinatwo-stepprocess.First,itextractscandidateperiodsfromtheperiodogram.Then,itusesthecircularautocorrelationtovalidatethecandidateperiods.findfrequencyDetermineperiodsizeusingthemethodfindfrequencyfromtheRforecastpackage.Re-implementation!

optionalarguments:-h,--helpshowthishelpmessageandexit--versionShowversionnumber.--use-initial-nUSE_INITIAL_NOnlyusetheninitialpointsofthedatasettocalculatetheestimatedperiodsize.--channelCHANNELIfthedatasetismultivariate,usethechannelonthisintegerposition.Thefirstdimensionisalwaysassumedtobetheindexandskippedover!
Package: periodicitytest
Quick and dirty introduction to usageFor an extensive description and explanation, see [arXiv:1506.01287](http://arxiv.org/abs/1506.01287).Very briefly, this test decides whether a given time series can be interpolated by a periodic function with the same number of local extrema as the time series, where only local extrema with a prominence higher than a given error allowance σ are taken into account. The method also returns the period length. It is not intended for experimental but for simulated data.The method has two parameters that can be chosen straightforwardly:Themaximum allowed period length τ<sub>max</sub>: Choose this parameter reasonably low to limit the runtime and to avoid period lengths that are close to the length of the time series. Unless you know what you are doing, τ<sub>max</sub> should at least be half the length of the time series.Theerror allowance σ:Choose this parameter to correspond to the maximum expected absolute numerical error of your simulation, e.g., the maximum absolute integration error of an adaptive integrator.Instructions for buildingThe following describes how to use this source depending on how you want to use it:A. As a Python moduleBuild and install the module by running (for example)`sh python3 setup.py install--user`This generates a Python module calledperiodicitytest, which contains one function calledperiodicitytest. It can be loaded, e.g., as follows:`python from periodicitytest import periodicitytest `For further documentation, seeperiodicitytest’s docstring.B. As a standalone programBuild the program by running`sh python3 setup_C.py `or`sh python3 setup_C.py test `if you want to run the tests.This generates an executable calledperiodicitytestin the folderbin. It takes the maximum period length τ<sub>max</sub> and the error allowance σ as an argument. The time series is read from STDIN.Take a look atstandalone.cif you want to modify input and output.C. As a C libraryThe central function is contained and documented insearch.h. For input and output it requires simple datatypes defined inbasics_standalone.handinterval.h. It needs to compiled with-DSTANDALONE. Several costly assertions can be avoided by compiling with-DNDEBUG.
Package: periodic-simpletime
PeriodicSimpleTimeThis package helps to manage periodic events.Calculate next periodic datetimefrom periodic_simpletime import *

# for this example, current utc time is 2023-01-01 11:56:02
period = PeriodicSimpleTime(minute=5)
next_end_dt = get_next_periodic_dt(period)
> 2023-01-01 12:00:00 (utc)
Package: periodic-table-dataclasses
A Python library of periodic data statically generated fromPeriodicTableJSON.json(https://github.com/NMRbox/Periodic-Table-JSON) on 2023 Jan 28.AnElementdataclass andPeriodicTablecontainer class is generated from the JSON data.Currently only the single valued str, float, and int are supported. The JSON fieldsshells,ionization_energies,imageare omitted.Installationpip install periodic_table_dataclassesUsagefrom periodic_table import PeriodicTable
pt = PeriodicTable()
h = pt.search_name('hydrogen')
s = pt.search_number(16)
fe = pt.search_symbol('Fe')
for element in pt.elements:
    print(element)DiscussionUnnecessaryThis module is not necessary to use PeriodicTableJSON.json in Python.with open('PeriodicTableJSON.json') as f:
        data = json.load(f)
elements = data['elements']will bring all data into Pyton as nested data structure.ConvenientThe module was implemented for the convenience of named class fields. A static definition allows type
checking and code completion when working in Python integrated development environments (IDE).Additional featureThePeriodicTable.search_namefeatures supports the British spellingsaluminiumandsulphur.
Package: periodiq
Simple Scheduler for Dramatiq Task Queuedramatiqtask queue is great but lake a scheduler. This
project fills the gap.FeaturesCron-like scheduling.Single process.Fast and simple implementation.Easy on ressources using SIGALRM.No dependency except dramatiq ones.CLI consistent with dramatiq.Skip outdated message.Installationperiodiq is licensed under LGPL 3.0+.$pipinstallperiodiqDeclare periodic tasks like this:# filename: app.pyimportdramatiqfromperiodiqimportPeriodiqMiddleWare,cronbroker.add_middleware(PeriodiqMiddleWare(skip_delay=30))@dramatiq.actor(periodic=cron('0 * * * *))defhourly():# Do something each hour…...Then, run scheduler with:$periodiq-vapp[INFO] Starting Periodiq, a simple scheduler for Dramatiq.[INFO] Registered periodic actors:[INFO][INFO]     m h dom mon dow          module:actor@queue[INFO]     ------------------------ ------------------[INFO]     0 * * * *                app:hourly@default[INFO]...SupportIf you need help or found a bug, mindopening a GitLab
issueon the project. French
and English spoken.
Package: period-iterator
Period IteratorPeriod Iterator is a library easing you to iterate through given period.Usagefromperiod_iterator.period_iteratorimportperiod_iteratorperiod=period_iterator('2020-02-01,2020-02-03','Asia/Bangkok')whileTrue:print(period.cursor.begin())# Begin of dayprint(period.cursor.end())# End of dayprint(period.cursor.date())# Dateifnotperiod.next():break# Expected Output## 2020-02-01T00:00:00+07:00# 2020-02-01T23:59:59+07:00# 2020-02-01# 2020-02-02T00:00:00+07:00# 2020-02-02T23:59:59+07:00# 2020-02-02# 2020-02-03T00:00:00+07:00# 2020-02-03T23:59:59+07:00# 2020-02-03LicenseMIT
Package: periodogram
PeriodogramSimple and tested periodogram normalizations for astronomical time-seriesInstallationpipinstallperiodogramUsageThere are three types of normalizations available. The amplitude spectrum is normalized such that a sine wave of amplitude 1 will have a peak amplitude of 1. The power spectrum will have 1^2, and the power spectral density will have 1^2 * TobsfromperiodogramimportPeriodogramp=Periodogram.calculate(x,y,normalization='amplitude')p.plot()Lower-level functions for directly calculating different normalizations are also availablefromperiodogramimportamplitude_spectrum,psd,power_spectrumfrequency,amplitude=amplitude_spectrum(x,y)
Package: periodparser
periodparserpython parser for human-readable period datesУстановкаpip install periodparserОписаниеБиблиотека для парсинга дат и времени в естественной речи на русском языке.Примерimportperiodparserasppresult=pp.extract('Техобслуживание пройдет с вечера следующей среды до пол 9 утра')print(result.dates[0])# [Type=DateTimeTokenType.PERIOD, From=2023-06-28T17:00:00, To=2023-06-29T08:30:00, Span=None, HasTime=True, StartIndex=24, EndIndex=62]
Package: periscope-daemon
periscoped==========A daemon to download subtitles based on the great [periscope](https://github.com/patrickdessalle/periscope).Installation-------------You will need periscope,  pyinotify, sqlite.Installation via pip```shpip  install periscope-daemon```Installation from the sources```shpython setup.py buildsudo python setup.py install```Availables commands-------------------First, you'll need to import your library```shperiscope-daemon --import ~/media/videos```Then, in a first console :Start watching a folder for new video files```shperiscope-daemon --watch ~/media/videos```And in a second :Start downloading subtitles```shperiscope-daemon --run```Purge the library```shperiscope-daemon --purge```Configuration-------------The main config file is located in ~/.config/periscope-daemon/daemon.confThis file will override the default distributed configuration.Availables configuration keys :```[DEFAULT]# Laguages.lang = fr,en# How often the daemon should run, in minutesrun_each = 1# When a subtitle is not found, the time to wait before re-processing the file will be multiplyed by this valueretry_factor = 3```
Package: periscope-firehose
# The Periscope Firehose!Provides a class, `PeriscopeFirehose`, that allows you to listen for new Periscope broadcasts published on Twitter simply by overriding the method `on_broadcast`.### Installation`$ pip install periscope-firehose`### Usage```pythonfrom periscope_firehose import PeriscopeFirehoseclass MyFirehose(PeriscopeFirehose):def on_broadcast(self, broadcast):print "New Periscope Broadcast published!"print "- id:", broadcast.idprint "- twitter handle:", broadcast.twitter_screen_nameprint "- status:", broadcast.statusfirehose = MyFirehose(TWITTER_CONSUMER_KEY, TWITTER_CONSUMER_SECRET, TWITTER_OAUTH_TOKEN, TWITTER_OAUTH_SECRET)firehose.listen()```Get your Twitter consumer key, consumer secret, oauth token, and oauth secret from the [Twitter Application Management page](https://apps.twitter.com/).
Package: perisim
A peristaltic table simulation.This package simulates a square grid of peristaltic cells beneath a flexible surface. Each cell is modelled as a gaussian disturbance in the flexible surface. Each cell can actuate to increase or decrease its amplitude. Objects on the surface then roll down the gradients of the surface.The simulation can randomly vary its parameters in order to allow for controller optimization using the radical envelope-of-noise hypothesis [Evolutionary Robotics and the Radical Envelope-of-Noise Hypothesis, Nick Jakobi, 1997].