Saravanan666/pypi-org huggingface dataset:
Package: fenrir-api
# Introduction  The Fenrir Cloud API allows you to interact with Fenrir Cloud  and manage Applications, Deployments, and other resources  using conventional HTTP requests.    ## Authentication  The Fenrir Cloud API uses API keys for the authentication.  You can create new API keys in your Fenrir Cloud dashboard.  Your bearer API key must be set in the \&quot;Authorization\&quot; header, for example:  &#x60;&#x60;&#x60;bash curl https://api.fenrircloud.com/1.0/api/applications \    -H \&quot;Accept: application/json\&quot; \    -H \&quot;Authorization: Bearer FENRIR_API_KEY\&quot; &#x60;&#x60;&#x60;  ## Responses  When a request is successful, a response body will typically contain a JSON object.  For DELETE requests, a response with successful HTTP 204 NO_CONTENT status and a simple status will be returned.  For other request, a JSON object will contain a requested object. If list of objects is requested, an array of them will be returned instead.   ### Example Response (Single Object)  &#x60;&#x60;&#x60;json {   \&quot;application\&quot;: {     \&quot;name\&quot;: \&quot;my-app\&quot;,     ...   } } &#x60;&#x60;&#x60;  ### Example Response (Multiple Objects)  &#x60;&#x60;&#x60;json {   \&quot;applications\&quot;:      [         {           \&quot;name\&quot;: \&quot;my-app\&quot;,           ...         },         {           \&quot;name\&quot;: \&quot;another-app\&quot;,           ...         }     ] } &#x60;&#x60;&#x60;  ## Error Handling  Depending on the issue, a *4XX* status code will be returned.  A body will contain a JSON object with the details of the message.  Inside a JSON object, an error message will be included.   For 400 Bad Request errors caused by validation issues, additional &#x60;errors&#x60; key will be set. That key will contain a list of   ### Example Error Response  &#x60;&#x60;&#x60;json {   \&quot;message\&quot;: \&quot;Invalid Request\&quot;,   \&quot;errors\&quot;: [     {       \&quot;field\&quot;: \&quot;configuration.name\&quot;,       \&quot;error\&quot;: \&quot;must not contain special characters\&quot;]     },     ...   ] } &#x60;&#x60;&#x60;
Package: fenrir-screenreader
# FenrirA modern, modular, flexible and fast console screenreader.It should run on any operating system. If you want to help, or write drivers to make it work on other systems, just let me know.This software is licensed under the LGPL v3.# OS Requirements- Linux (ptyDriver, vcsaDriver, evdevDriver)- macOS (ptyDriver)- BSD (ptyDriver)- Windows (ptyDriver)# Core Requirements- python3 >= 3.3- screen, input, speech, sound or braille drivers dependencies see "Features, Drivers, Extras".# Features, Drivers, Extras, Dependencies# Input Drivers:1. "evdevDriver" input driver for linux evdev- python-evdev >=0.6.3 (This is commonly referred to as python3-evdev by your distribution)- python-pyudev- loaded uinput kernel module- ReadWrite permission- /dev/input- /dev/uinput2. "ptyDriver" terminal emulation input driver- python-pyte# Screen Drivers:1. "vcsaDriver" screen driver for linux VCSA devices- python-dbus- Read permission to the following files and services:- /sys/devices/virtual/tty/tty0/active- /dev/tty[1-64]- /dev/vcsa[1-64]- read logind DBUS2. "ptyDriver" terminal emulation driver- python-pyte# Speech Drivers:1. "genericDriver" (default) speech driver for sound as subprocess:- espeak or espeak-ng2. "espeakDriver" speech driver for Espeak or Espeak-NG:- python-espeak3. "speechdDriver" speech driver for Speech-dispatcher:- Speech-dispatcher- python-speechd4. "emacspeakDriver" speech driver for emacspeak- emacspeak# Braille Drivers:1. "BrlttyDriver" braille driver (WIP):- brltty (configured and running)- python-brlapi# Sound Drivers:1. "genericDriver" (default) sound driver for sound as subprocess:- Sox2. "gstreamerDriver" sound driver for gstreamer- gstreamer >=1.0- GLib# Extras:1. spellchecker- python-pyenchant- aspell-YourLanguageCode (example aspell-en for us English)2. Unix daemon (also needed for Systemd):- python-daemonize3. Modify system volume:- pyalsaaudio (needs libasound2's headers).# installation- Archlinux: PKGBUILD in AUR- PIP: sudo pip install fenrir-screenreader- Manual:- install "espeak" and "sox" with your package manager- sudo pip install -r requirements.txt- run install.sh and uninstall.sh as root- you also can just run it from Git without installing:You can just run the following as root:if you are in Fenrir Git rootfolder:cd src/fenrir/sudo ./fenrirSettings "settings.conf" is located in the "config" directory or after installation in /etc/fenrir/settings.Take care to use drivers from the config matching your installed drivers.By default it uses:- sound driver: genericDriver (via sox, could configured in settings.conf)- speech driver: genericDriver (via espeak or espeak-ng, could configured in settings.conf)- braille driver: brlttyDriver (WIP)- input driver: evdevDriver# DocumentationYou can see all information on the Wiki:https://wiki.linux-a11y.org/doku.php?id=fenrir_user_manual
Package: fentoimage
fen-to-imageGenerate a chess board image given a FEN, à la Lichess style.Installationfentoimage is available onPyPI.pipinstallfentoimageExample Usageimportchessfromfentoimage.boardimportBoardImagefen="rnbqk1nr/pppp1ppp/8/4p3/1bP5/2N5/PP1PPPPP/R1BQKBNR w KQkq - 2 3"renderer=BoardImage(fen)image=renderer.render(highlighted_squares=(chess.F8,chess.B4))image.show()Example Output
Package: f-enum
fastenumBased onpython/cpython#17669andpython/cpython#16483Patch for stdlibenumthat makes itfast.How fast?~10x fastername/valueaccess~6x faster access to enum members~2x faster values positive check~3x faster values negative check~3x faster iteration~100x faster newFlagsandIntFlagscreation for Python 3.8 and belowWow this is fast! How do I use it?First, install it from PyPi using pippipinstallf-enumor using poetrypoetryaddf-enumThen enable the patch just by callingfastenum.enable()once at the start of your programm:importfastenumfastenum.enable()You don't need to re-apply patch across different modules: once it's enabled, it'll work everywhere.What's changed?fastenum is designed to give effortless boost for all enums from stdlib. That means that none of optimizations should break existing code, thus requiring no changes other than installing and activating the library.Here are summary of internal changes:OptimizedEnum.__new__RemoveEnumMeta.__getattr__StoreEnum.nameand.valuein members__dict__for faster accessReplaceEnum._member_names_with._unique_member_map_for faster lookups and iteration (old arg still remains)Replace_EmumMeta._member_namesand._last_valueswith.membersmapping (old args still remain)Add support for direct setting and getting class attrs onDynamicClassAttributewithout need to use slow__getattr__Various minor improvements
Package: fenwick
fenwickA Python library that implements Fenwick trees, based on the algorithm in
(Fenwick 1994).FeaturesUpdate a frequency in O(log n).Retrieve a single frequency in O(log n).Initialize existing frequencies in O(n).Retrieve all frequencies in O(n).Requirementsfenwicksupports Python 2.7 and Python 3.x.Linux, Mac, and Windows are supported.Installationfenwickis available on PyPI, the Python Package Index.$ pip install fenwickDocumentationSeedocumentation.md.Example UsageSeeexample.py.TestsTests are intests/.# Run tests
$ python -m unittest discover tests -vLicenseThe code in this repository has anMIT License.SeeLICENSE.ReferencesFenwick, Peter M. 1994. “A New Data Structure for Cumulative Frequency Tables.”
Software: Practice and Experience 24 (3): 327–36.
Package: fe-openedx-alerts
fe-openedx-alertsA command line tool that send alerts if any Open edX service failasticsearch service is activePython versionPython: 3.9.16Poetry Configuration# https://pypi.org/poetryconfigpypi-token.pypi$PYPI_TOKEN# https://test.pypi.org/poetryconfigrepositories.testpypihttps://test.pypi.org/legacy/
poetryconfigpypi-token.testpypiPYPI_TEST_TOKENOpen edX Instancegitclonehttps://github.com/pyenv/pyenv.git~/.pyenvexportPATH=/home/ubuntu/.pyenv/bin:$PATHpyenvinstall3.9.16
pyenvglobal3.9.16

/home/ubuntu/.pyenv/versions/3.9.16/bin/pip3installfe-openedx-alerts==0.0.5-U# How to execute the script/home/ubuntu/.pyenv/versions/3.9.16/bin/python/home/ubuntu/.pyenv/versions/3.9.16/lib/python3.9/site-packages/fe_openedx_alerts/es_status.pyCronjobmkdir/home/ubuntu/logs/

crontab-e
Package: fepdf
Generacion en PDF de facturas electrónicas. Módulo inspirado depyfepdfdeMariano Reigart.pyfepdf es uno de los modulos del excelente proyecto PyAFIPWS. Si aun no lo  conoces deberias mirarlo, antes de utilizar esta utilidad. Si bien el proyecto entero funciona muy bien, hemos encontrado algunas defeciencias.ObjetivosBuscamos realizar las siguientes mejoras comparadas con el modulo original de reingart.Funcionamiento exclusivo en Python 3.x (Sin soporte a Python 2.x)Cumplimiento de las recomendaciones de PEP8Facilidad de instalcion utilizando pipMejora en la documentación.Impresion en tamaño de papel A5Simplificacion de codigo dejango solo las etiquetas necesarias para emitir facturas dentro del mercado interno.InstalaciónInstalable desde PyPI con el siguiente comnado$ pip install fepdfGuia de UsoHemos mantenido la misma interfaz del proyecto original, pero utilizando nombresundescore, por lo que, por ej. el metodoCrearFacturaahora escrear_factura.En elfepdf.pyhay una pequeña guia que le servirá para utilizar este modulo correctamente
Package: feplot
A visualization tool for FElupeFEplot is based on the popular visualization librarypyvistawhich is a comprehensive library for creating static, animated, and interactive visualizations in Python. The main aim of this package is to visualizeFEluperesults.SetupTo run this project, you can easily install it locally using pip:pip install feplotAll is ready now, let's move on!How to UseStarting with a quick example:importfelupeasfemfromfeplotimportPlottermesh=fem.Cube(n=6)region=fem.RegionHexahedron(mesh)field=fem.FieldContainer([fem.Field(region,dim=3)])boundaries,loadcase=fem.dof.uniaxial(field,clamped=True)umat=fem.OgdenRoxburgh(material=fem.NeoHooke(mu=1),r=3,m=1,beta=0)solid=fem.SolidBodyNearlyIncompressible(umat,field,bulk=5000)move=fem.math.linsteps([0,1,0,1,2,1],num=5)step=fem.Step(items=[solid],ramp={boundaries["move"]:move},boundaries=boundaries)job=fem.CharacteristicCurve(steps=[step],boundary=boundaries["move"])job.evaluate(filename="result.xdmf")p=Plotter()p.read_xdmf("result.xdmf")https://github.com/ZAARAOUI999/feplot/assets/115699524/19ac3be1-b829-44bd-82bc-20d0461452a8LicenseFEplot - A visualization tool for FElupe (C) 2023 Mohamed ZAARAOUI, Tunisia.This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.You should have received a copy of the GNU General Public License along with this program. If not, seehttps://www.gnu.org/licenses/.
Package: fepr-py-rpa
2021-02-02Python_RPAモジュール追加==================== Emojis ====================🎉  :初めてのコミット（Initial Commit）🔖  :バージョンタグ（Version Tag）✨  :新機能（New Feature）🐛  :バグ修正（Bugfix）♻️  :リファクタリング(Refactoring)📚  :ドキュメント（Documentation）🎨  :デザインUI/UX(Accessibility)🐎  :パフォーマンス（Performance）🚀  :パフォーマンス改善🔧  :ツール（Tooling）🚨  :テスト（Tests）💩  :非推奨追加（Deprecation）🗑️  :削除（Removal）🚧  :WIP(Work In Progress)
Package: fepydas
A python3 tool for data analysis and fitting.Install fromhttps://pypi.org/project/fepydas/with "pip install fepydas".
View repository athttps://git.tu-berlin.de/nippert/fepydasFind usage examples athttps://git.tu-berlin.de/nippert/fepydas/-/tree/master/examplesRequirements:
Python3
numpy
scipy
matplotlib
lmfit
scikit-learn
pyamg
Package: ferenda
Ferenda is a python library and framework for transforming
unstructured document collections into structured Linked Data. It
helps with downloading documents, parsing them to add explicit
semantic structure and RDF-based metadata, finding relationships
between documents, and publishing the results, including through a
REST-based HTTP API.Quick startThis example uses ferenda’s project framework to download the 50
latest RFCs and W3C standards, parse documents into structured,
RDF-enabled XHTML documents, loads all RDF metadata into a triplestore
and generates a web site of static HTML5 files that are usable
offline:pip install ferenda
ferenda-setup myproject
cd myproject
./ferenda-build.py ferenda.sources.tech.RFC enable
./ferenda-build.py ferenda.sources.tech.W3Standards enable
./ferenda-build.py all all --downloadmax=50 --staticsite --fulltextindex=False
open data/index.htmlThe same functionality can also be accessed through a python API, if
you want to use ferenda as part of a larger system. It’s also possible
to just use the parts of ferenda that you need (eg. only the
downloading and parsing features).More informationSeehttp://ferenda.readthedocs.org/for in-depth documentation.Copyright and licenseMost of the code written by Staffan Malmgren, licensed under the main
2-clause BSD license.Some bundled code and other creative works are written by other
authors, included in accordance with their respective licenses:rdflib-sqliteby Graham
Higgins, BSDpatchby Anatoly
Techtonik, MITGrit XSLT stylesheetsandRDL service UIby Niklas Lindstrom, BSDhttpheaderby Deron
Meranda, LGPLsmc.mwby Marcus Brinkmann, BSDnormalize.css, MITresponsive template, PDjquery, MITmodernizr, MITrespond.js, MIT/GPLGentleface wireframe toolbar icons, CC-BY-NC
Package: fermentools
dtu.prosysAbout this project 🚀This project intends to be a didactic tool to teach spectroscopy and chemometrics in the context of fermentation technology. During my studies, I often felt that many courses were theory-based only due to the limited access to real-world data. For this reason, I have decided to distribute the data I generated during my studies hoping to improve the learning experience of future students.This module contains:Training data (spectra of different samples and the glucose concentration).Fermentation spectra (spectra measured inreal-timeevery minute).Fermentation HPLC data (measured off-line every hour).Common preprocessing operations used in chemometrics.Workflow to train partial least squares (PLS) models.Plotting functions for time-series and spectral data.These functions can be used as a starting point for the, but more advanced users are encouradged to explore other packages to play with this data (e.g.,scikit-learn, orscipy).About the data 📈This project provides two datasets (a training and a validation set). Both data sets were recorded at the Technical University of Denmark, at the PROSYS research center (department of Chemical and Biochemical engineering) during 2019. More information about the dataset can be found in the following articleTransforming data to information: A parallel hybrid model for real-time state estimation in lignocellulosic ethanol fermentationThe training setThe training set contains the spectra of 20 semi-synthetic samples and their reference glucose concentration measured with high performance liquid chromatography (HPLC). The spectra were measured using attenuated total refractance mid infrared (ATR-MIR) spectroscopy.Validation setThe validation contains spectra measured every minute during a lignocellulose to ethanol fermentation. These spectra were collected inreal-timeusing the same ATR-MIR instrument, connected to a flow-cell. Moreover, the extracellular concentrations of glucose, xylose, ethanol, furfural and acetic acid were also measured every hour using HPLC.Installation 💻DependenciesThis project is build targetting Python >= 3.7 to ensure compatibility with Google Colab.User installationpippip install -U dtuprosysQuick start 🏁A complete example of can be found in theexample.ipynb. The raw data can be conviniently accessed using as the following commands:from dtuprosys.datasets import load_train_data, load_fermentation_datato access the training datatrain_spectra, train_hplc = load_train_data()to access the validation data:fermentation_spectra, fermentation_hplc = load_fermentation_data()
Package: fermi-contours
Fermi ContoursReferenceCode adapted fromPerez-Piskunow, Pablo M, Bovenzi, Nicandro, Akhmerov, Anton R, & Breitkreiz, Maxim. (2021).
Code and data associated with the paper
"Chiral Anomaly Trapped in Weyl Metals: Nonequilibrium Valley Polarization at
Zero Magnetic Field"
(1.0.1). Zenodo.https://doi.org/10.5281/zenodo.4704325and extended to take into account periodic boundaries and other edge-cases.RequirementsPython >=3.9InstallationYou can installFermi ContoursviapipfromPyPI:$pipinstallfermi-contoursUsagePlease see theCommand-line Referencefor details.ContributingContributions are very welcome.
To learn more, see theContributor Guide.LicenseDistributed under the terms of theMIT license,Fermi Contoursis free and open source software.IssuesIf you encounter any problems,
pleasefile an issuealong with a detailed description.CreditsThis project was generated from@cjolowicz'sHypermodern Python Cookiecuttertemplate.
Package: fermilib
FermiLib is an open source effort for analyzing quantum simulation algorithms.The current version (v0.1a2) is an alpha release which features data structures and tools for obtaining and manipulating representations of fermionic Hamiltonians. FermiLib is designed as a library on top ofProjectQand leverages ProjectQ to compile, emulate and simulate quantum circuits. There are alsopluginsavailable for FermiLib.Getting startedTo start using FermiLib, simply follow the installation instructions in theintro. There, you will also findcode examples. Also, make sure to check out theProjectQ
websiteand the detailedcode documentation. Moreover, take a look at the available plugins for FermiLib.PluginsIn order to generate molecular hamiltonians in Gaussian basis sets and perform other complicated electronic structure calculations, one can install plugins. We currently support Psi4 (pluginhere, recommended) and PySCF (pluginhere).How to contributeTo contribute code please adhere to the following very simple rules:Make sure your new code comes with extensive tests!Make sure you adhere to our style guide. Until we release a code style
guide, just have a look at our code for clues. We mostly follow pep8 and use the pep8 linter to check for it.Put global constants and configuration parameters into src/fermilib/config.py, and
addfrom config import *in the file that uses the constants/parameters.Documentation can be foundhere.AuthorsThe first release of FermiLib (v0.1a0) was developed byRyan Babbush,Jarrod McClean,Damian S. Steiger,Ian D. Kivlichan,Thomas
Häner,Vojtech Havlicek,Matthew Neeley, andWei Sun.Questions?If you have any other questions, please contactfermilib@projectq.ch.LicenseFermiLib is released under the Apache 2 license.
Package: fermilibpluginpsi4
This repository contains a plugin which allowsFermiLib(licensed under Apache 2) to interface with the open-source quantum chemistry packagePsi4(licensed under GNU Lesser General Public License version 3).InstallationTo install this plugin, clone this git repo and then change directory to the top level folder. Then, runpython-mpipinstall-e.Alternatively, one can install using pip with the commandpython-mpipinstallfermilibpluginpsi4LicenseCopyright (C) 2017 FermiLib DevelopersThis plugin is released under the GNU Lesser General Public License (LGPL), Version 3 or any later version.
Package: fermioniq
This package is the interface to the Fermioniq quantum circuit emulator.
The client can be used to send jobs, monitor their status and receive results.Website:fermioniq.comDocumentation:docs.fermioniq.comPrerequisitesBefore installing the package, ensure you have met the following requirements:You have a working installation of Python (3.10)You have installed thepippackage managerInstallationYou can install the client with the following command:pip install fermioniqSetup:Sending jobs to the emulator requires a user-specificaccess_token_idandaccess_token_secret.
They are tied to your Fermioniq user account.You can either define them as environment variables- export FERMIONIQ_ACCESS_TOKEN_ID=""
- export FERMIONIQ_ACCESS_TOKEN_SECRET=""Alternatively, you can also provide them as input arguments to thefermioniq.Clientconstructor.
Package: fermium
fermiumShort blurb about what your product does.One to two paragraph statement about your product and what it does.InstallationOS X & Linux:pip3installfermiumWindows:pipinstallfermiumUsage exampleA few motivating and useful examples of how your product can be used. Spice this up with code blocks and potentially more screenshots.For more examples and usage, please refer to theWiki.Development setupDescribe how to install all development dependencies and how to run an automated test-suite of some kind. Potentially do this for multiple platforms.pipinstall--editablefermiumDocumentationRead the DocsMetaStephen R A King :stephen.ra.king@gmail.comDistributed under the MIT License. SeeLICENSEfor more information.https://github.com/Stephen-RA-King/fermium
Package: fern-api
Fern Python LibraryThe Fern Python Library provides convenient access to the Fern API from applications written in Python.Installationpipinstall--upgradefern-apiUsagefromfern.clientimportFernclient=Fern(token="YOUR_TOKEN",)Async Clientfromfern.clientimportAsyncFernclient=AsyncFern(token="YOUR_TOKEN",)Beta StatusThis SDK is in beta, and there may be breaking changes between versions without a major
version update. Therefore, we recommend pinning the package version to a specific version.
This way, you can install the same version each time without breaking changes.ContributingWhile we value open-source contributions to this SDK, this library is generated programmatically.
Additions made directly to this library would have to be moved over to our generation code,
otherwise they would be overwritten upon the next generated release. Feel free to open a PR as
a proof of concept, but know that we will not be able to merge it as-is. We suggest opening
an issue first to discuss with us!On the other hand, contributions to the README are always very welcome!