Saravanan666/pypi-org huggingface dataset:
Package: pyquerystring
Copyright 2011-2016 Adam VenturellaLicensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless 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.
Description: Python’s default urlparse.parse_qs() does not understand the concept of data structures. While this works for simple querystrings, anything more complex returns a less than desirable result.This library will intelligently parse complex querystrings that python’s library is unable to handle such as the following:mylist[]=item0&mylist[]=item1mylist[0]=item0&mylist[1]=item1mylist[0][0]=subitem0&mylist[0][1]=subitem1mylist.element=item0mylist.element[0]=item0&mylist.element[1]=item0Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Package: pyquery-xpath
pyquery_xpath一个继承于pyquery的python库起因它没有重写任何 pyquery 的方法，我非常喜欢这个库，认为它在操作 html 方面的各种方法非常简洁但我习惯于使用 xpath 选择器，pyquery 仅支持 css 选择器和部分伪类选择器在选择包含某些文本的节点时，总是会选择符合条件的最外层节点看了 pyquery 部分代码，发现它基于 lxml.etree 模块实现了 html 路径选择，也就是说它原生支持 xpath 选择器，但却没有实现相应的方法，让我很奇怪（也可能很少有像我这样喜欢混搭的人）于是我为它添加了一个 xpath 方法，仅此而已使用方式>>> h = '<a class="foo1"><span class="foo2"><span class="foo3">Hello</span></span></a>'
>>> d = PyQuery(h)
>>> d('a').xpath('.//span[@class="foo2"]')
[<span.foo2>]
>>> d.xpath('//span[@class="foo2"]')('.foo3')
[<span.foo3>]
>>> d.xpath('.//span[@class="foo2"]')('.foo1')
[]
Package: pyquestaal
PyQUESTAALThis is a calculator class that has been written to interface calculations done usingQUESTAALwith highthroughput calculators likeASE.Note: The module can be used as a stand alone python controller for questaal jobs as well.Featuresmake symmetry line files supported by QUESTAAL on the fly with a given structureplot bands directly(requires plotquestaal.py)relaxations includedcan read forces from output filesControl number of processorsInstallationCopy the files lmf.py to the working directoryImport them and use !Make sure "lmf" is recognizable in the path and also modify the type of mpi call. default "mpirun"ExamplesSimple example usage shown insimple_examples.ipynbComprehensive example shown intutorial_example.ipynbTo use it with ASE, one can do something likefromlmfimportlmf#load the lmf calculatorimportnumpyasnpfromase.ioimportreadfromase.unitsimportkJfromase.eosimportEquationOfStatefromaseimportAtomsfromase.io.trajectoryimportTrajectorydeftest():a=4.0# approximate lattice constantb=a/2ag=Atoms('Ag',cell=[(0,b,b),(b,0,b),(b,b,0)],pbc=1,calculator=lmf())# Use QUESTAAL's LMF as calculatorcell=ag.get_cell()traj=Trajectory('Ag.traj','w')forxinnp.linspace(0.95,1.05,5):ag.set_cell(cell*x,scale_atoms=True)ag.get_potential_energy()traj.write(ag)configs=read('Ag.traj@0:5')# read 5 configurations# Extract volumes and energies:volumes=[ag.get_volume()foraginconfigs]energies=[ag.get_potential_energy()foraginconfigs]eos=EquationOfState(volumes,energies)v0,e0,B=eos.fit()print(B/kJ*1.0e24,'GPa')eos.plot('Ag-eos.png')test()CitationIf you find this work useful, please cite using@misc{https://doi.org/10.5281/zenodo.4292415,
  doi = {10.5281/ZENODO.4292415},
  url = {https://zenodo.org/record/4292415},
  author = {Radha, Santosh Kumar},
  title = {pyQuestaal: An python interface or Questaal quantum codes.},
  publisher = {Zenodo},
  year = {2020},
  copyright = {Open Access}
}To Docontrol over all variablesInterface with pyamtgenAdd the developed lattice relaxation module which uses Genetic AlgorithmMake more standaloneMore complex parser for questaal output (look for questaal-reader repo)
Package: pyquest-cffi
PyQuEST-cffi READMEPyQuEST-cffi is a python interface toQuESTbased oncffideveloped by HQS Quantum Simulations. QuEST is an open source toolkit for the simulation of quantum circuits (quantum computers).PyQuEST-cffi provides an interactive python to QuEST interface based on cffi, mapping QuEST functions to python and executing them during runtime.For more information see the detailed codedocumentationNotePlease note, PyQuEST-cffi is not an official QuEST project.In the developing branches of QuEST the QuEST project has implemented actypes-based python interfaceQuestPyfor unit testing.Do not assume that any bugs occuring using PyQuEST-cffi are QuEST bugs unless the same bug occurs when compiling/using a QuEST c-program with the official release version ofQuEST.InstallationWe do provide a PyPi source packages. The recommended way to install PyQuEST-cffi ispipinstallpyquest_cffiIf you want to install PyQuEST-cffi in development mode we recommend# PyQuEST-cffi add QuEST as a git submodulegitclone--recurse-submoduleshttps://github.com/HQSquantumsimulations/PyQuEST-cffi.git
pipinstall-ePyQuEST-cffi/
Package: pyquestions
pyquestionIt's a very simple and easy to use module which calls a function named getQuestion and returns a python problem with hint to solve it.Example:import pyquestionprint(pyquestion.getQuestion())Output:Write a program which will find all such numbers which are divisible by 7 but are not a multiple of 5,between 2000 and 3200 (both included).The numbers obtained should be printed in a comma-separated sequence on a single line.Hints:Consider use range(#begin, #end) method
Package: pyqueued
Python client for HTTP message queue Queued:https://github.com/scttnlsn/queued.Usage>>> import pyqueuedGet a client.>>> client = pyqueued.Client(host='localhost', port=5353)Enqueue a message:>>> loc = client.enqueue("q", "my message")
>>> loc
'http://localhost:5353/q/155'Get the head of the queue. Without any timeout, the item is marked as completed when dequeued.>>> msg, loc = client.dequeue("q")
>>> msg
'my message'THe queue is empty now, so another dequeue will fail:>>> msg, loc = client.dequeue("q")
...
RuntimeError: dequeue failed: <Response [404]>Enqueue another message:>>> loc = client.enqueue("q", "another message")But dequeue with timeout (given in seconds). If the message is not completed withintimeout,
it will be enqueued again.>>> client.dequeue("q", timeout=2)
('another message', 'http://localhost:5353/q/160')The has message timed out and has been enqueued again. So we can actually dequeue it once more. But now we
mark it completed in time.>>> client.dequeue("q", timeout=20)
('my message with timeout', 'http://localhost:5353/q/160')>>> client.complete("q", "160")Alternatively, item can be completed by URL. To the last line have been written also as:>>> client.complete_by_url('http://localhost:5353/q/160')Stats about the queue:>>> client.stats("q")
{'depth': 1, 'dequeued': 3, 'enqueued': 3, 'timeouts': 1}
Package: pyqueues
pyqueuesA library for Priority-Queues containing Indexed-Priority-Queue and Simple Priority-Queue.--Installation:clone the this reporitory using,https://github.com/abecus/Queue.gitor, install using pip,pip install pyqueuesWorks with Python 3.x and PyPy.OverviewBoth, the Indexed priority queue and the queue has been implemented as a min binary heap to use it as a max heap or to uea it with custome key pass the values as a tuple in the heaps eg. (key, value). The time complexities are,peek highest priority element: O(1)pop highest priority element: O(log n)push new element: O(log n)additionally for Indexed Priority Queue,lookup of any item by key: O(1)remove element by key: O(log n)update element by key: O(log n)Usagefrom pyqueues.indexedPriorityQueue import IndexedPriorityQueue
	from pyqueues.heap import heapify, heapPop, heapPushto heapify a list (does not changes the original list, but heapifies internally),arr = [10, 20, 15, 12, 40, 25, 18, 40]
  pq = IndexedPriorityQueue(arr)
  pq.heapify()to push items into the priority queue,pq.push(2)
  pq.push(-1)to update a item using key (we an saperatly keep track of the key of the values using a dict by mapping values to the arrSize arrtibute of the priority queue)pq.update(pq.arrSize-1, 100)    # updates -1 to 100
  pq.update(pq.arrSize-2, -1)     # updates 2 to -1"similarly use pq.decreaseKey() and pq.increaseKey() methods (works in half of, the time required for update method), when we know that we are increseing or decresing the values while updating."to remove a values from priority queue,pq.remove(pq.arrSize-1)    # removes 100to pop highest priority element,pq.pop()        # pops -1LicenseMIT LicenseCopyright (c) 2020 abecusPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: pyquibbler-labextension
Quibbler's Jupyterlab extensionIntegrate Quibbler's Undo/Redo and Save/Load capabilities within JupyterLab.For a complete guide to using Quibbler within JupyterLab, seehere.Undo / RedoThe extension addsUndo/Redobuttons to the JupyterLab toolbar.Here is and example of how these buttons behave
(with theimage thresholding demo):Save / LoadAssignments to quibs can be saved into the JupyterLab's notebook,
allowing restoring prior values both within the session and when
restarting the notebook as a new session. To enable saving quib assignments into the notebook
check the “Save/Load inside Notebook” option in the JupyterLabQuibblermenu.Once enabled, quib assignments can easily be saved/loaded, either
globally for the entire notebook by choosingSave/Loadfrom the JupyterLab'sQuibblermenu, or
individually by clicking the Save/Load buttons at the bottom of the Quib
Editor of the relevant quib, as shown here:RequirementsJupyterLab >= 3.0InstallTo install the extension, execute:pipinstallpyquibbler_labextensionUninstallTo remove the extension, execute:pipuninstallpyquibbler_labextensionContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the pyquibbler_labextension directory# Install package in development modepipinstall-e.# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Rebuild extension Typescript source after making changesjlpmbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseDevelopment uninstallpipuninstallpyquibbler_labextensionIn development mode, you will also need to remove the symlink created byjupyter labextension developcommand. To find its location, you can runjupyter labextension listto figure out where thelabextensionsfolder is located. Then you can remove the symlink namedpyquibbler-labextensionwithin that folder.Packaging the extensionSeeRELEASE
Package: pyquickbench
PyquickbenchPyquickbench is an open source, easy to use benchmarking tool written in pure Python. Checkout theexample galleryto get an idea of what pyquickbench is capable.Tutorial:https://gabrielfougeron.github.io/pyquickbench/tutorial.htmlDocumentation:https://gabrielfougeron.github.io/pyquickbench/Source code:https://github.com/gabrielfougeron/pyquickbenchBug reports:https://github.com/gabrielfougeron/pyquickbench/issuesChangelog:https://github.com/gabrielfougeron/pyquickbench/releases/Main featuresTimings / repeatability / output benchmarksError handlingBenchmark results cachingMultithreaded / multiprocessed benchmarksBenchmark timeoutMultidimensional benchmarksTransformed data plotting (relative values, convergence order, ...)Intelligent plotsSensible defaultsInstallationPyquickbench is available on thePython Package Index. To install using pip, simply type:pip install pyquickbenchPyquickbench is available onconda-forge. To install using conda, simply type:conda install pyquickbench -c conda-forgeTo install the current development version of pyquickbench from thegithub repository, you can type:pip install git+ssh://git@github.com/gabrielfougeron/pyquickbench.gitTestsTo run tests locally on your machine, first checkout this reposity and install dependencies using pip:git clone git@github.com:gabrielfougeron/pyquickbench.git
cd pyquickbench
pip install .[tests]Then, run tests usingpytest:pytestLicenseThis software is published under theBSD 2-Clause License.Other open source alternativesYou might likeperfplot, one of the inspirations for this work.
Package: pyquickcopy
pyQuickCopyPython implementation ofQuickCopy.Hierarchypyquickcopy
'---- QuickCopy()
    |---- copy()
    |---- paste()
    |---- clear()
    '---- loop()Examplepythonimportpyquickcopyaccumulate_list=[]# currently not working with clipboard with '\n' characterdeflistener(clipboard):# tbd# copy a special text to trigger clear accumulate_listif"::clear"==clipboard:accumulate_list.clear()qc.clear()qc.copy(clipboard)return# prevent loop after joining accumulate_listif"\n"inclipboard:returnaccumulate_list.append(clipboard)qc.copy("\n".join(accumulate_list))print(accumulate_list)print()qc=pyquickcopy.QuickCopy(listener=listener,# how frequent the listener is calledlisten_rate=1/10,debug=False)qc.loop()
Package: pyquickenv
A command line tool to start Python virtual environments faster and easier.Installation:sudo pip install pyquickenvNext, add the following to your .bashrc:pyenv() {eval $(pyquickenv "$@")}Add An Environment:pyenv add proj1 /home/user/git/proj1_path*** Last argument is your project home directory and is optional ***Activate Environment:pyenv proj1The command "pyenv proj1" executes:1. source /home/user/pyenv/proj1/bin/activate2. cd /home/user/git/proj1_pathOnce in a virtual env you can type:pyenvThis executes:cd /home/user/git/proj1_pathTo add projects manually that are not added via "pyenv add" edit the file:/home/user/.pyenv.jsonSample JSON file, note "cd" is optional:{"proj1": {"env": "/home/user/ENVs/project1", "cd": "/home/user/git/project1"},"proj2": {"env": "/home/user/ENVs/project2", "cd": "/home/user/git/project2"}}List Environments:pyenv listRemove an Environment:pyenv rm proj1
Package: pyquickhelper
pyquickhelper: automation of many thingspyquickhelperis used to automate the release of the documentation such as automatingJenkins,
converting notebooks into many formats, extendingSphinxwith custom
extensions… It assumes the project is organized on the same template
as this one.Functionalitiessimple forms in notebookshelp generation including notebook conversionfolder synchronizationlogginghelp running unit testssimple server to server sphinx documentationfile compression, zip, gzip, 7zhelpers for ipython notebooks (upgrade, offline run)parser to quickly add a magic command in a notebookSphinx directives to integrate a blogpost in the documentationmechanism to add forms in notebooksDesignThis project contains the following folders:a source folder:srca unit test folder:_unittests, go to this folder and runrun_unittests.pya folder:_doc, it will contain the documentation, a subfolder_doc/sphinxdox/source/blogcontains blog post
to communicate on the modulea filesetup.pyto build and to install the module, if the source were retrieve from GitHub,
the script can also be called with the following extra options (python setup.py <option>):
* clean_space: remove extra spaces in the code
* build_sphinx: builds the documentation
* unittests: run the unit tests, compute the code coveragea scriptbuild_script.batwhich produces many script on Windows to easily run the setup,
generate the documentation, run the unit tests.ExamplesConvert a notebook into slides:from pyquickhelper.helpgen import nb2slides
nb2slides("nb.ipynb", "convert.slides.html")Merge two notebooks:from pyquickhelper.ipythonhelper import read_nb
nb1 = read_nb("<file1>", kernel=False)
nb2 = read_nb("<file2>", kernel=False)
nb1.merge_notebook(nb2)
nb1.to_json(outfile)Run a notebook:from pyquickhelper.ipythonhelper import run_notebook
run_notebook("source.ipynb", working_dir="temp",
            outfilename="modified.ipynb",
            additional_path = [ "c:/temp/mymodule/src" ] )Run a command line program:from pyquickhelper.loghelper import run_cmd
out,err = run_cmd("python setup.py install", wait=True)A sphinx extension to generate python documentation from a script:.. runpython::
    :showcode:

    import sys
    print("sys.version_info=", str(sys.version_info))LinksGitHub/pyquickhelperdocumentationBlog
Package: pyquickjoin
Utility to quickly join two unsorted filesFree software: BSD licenseFeaturesTODOHistory2.0.0 (2019-10-30)Clarified file behavior and column orderingreverted column ordering1.0.0 (2018-06-14)on-disk db working with bsddbreordered output columns0.1.0 (2015-01-11)Starting out with in-memory db.
Package: pyquicksql
Python Quick SQLA light-weight (out-of-the box) tool for pushing SQL (MySQL and SQLite) queries, markup-language for structured txt files and running data loggers in python.pip install pyquicksql==1.1.1SQL QueriesDesigned as a purely light-weight and object-oriented aproach to sending MySQL queries to a database server from python. Current modules offer partialy oo aproaches, resulting in over-complicated syntax for simple sql queries. The goal is that this module will offer ease-of-use in comparison to other modules while providing faster development time.Supported DatabasesMySQL(v.7.0)FunctionalityConstructorsserver = Server('0.0.0.0.0', 800, username, password)
database = Database('users', 'credentials', True)
connector = Connect(server, database)Lookupresult = connector.lookup(unknown_column, known_colum, known_element)Pushresult = connector.push(columns, elements)Swapresult = connector.swap(unknown_data, known_data)Removeresult = connector.remove(column, element)LoggerThe logger offers developers who wish to log all sql traffic localy within their project OR for those who do not wish to overcomplicate their projects with SQL queries and use standard txt files. The goal is to offer a basic but efficient markup language which mimics relational tables found within MySQL for faster lookup times for values. This is (yet another) out-of-the-box module the package promises, to speed up development time by offering individuals who do not know how to make their own relational markup language.FunctionalityConstructorl = Logger(directory) <- directory must be an active file pathRetreive Logsbackup = l.getLogs()Logl.log(Server, Database, Message)Indexvalue = l.index(0)Lookupvalue = l.lookup(column, element, starting)Data MarkupThe 'Data Markup' is a markup-language designed with Rust and interface with python to offer the speed that it cannot. The language offers relational column-element formating for standard txt files for faster data lookup and retreival.Syntax<Server<>Database>?Time?!Message!Parsevalue = l.parse(line, Request)Request TypesColumn.SERVERColumn.DATABASEColumn.TIMESTAMPColumn.MESSAGECreditspyquickdbGabriel CordovadoFunctionality of all classes are not limited to this README, I encourage your to view the source
Package: pyquickstart
pyquickstartCreate Python projects easily using well-defined templates.FeaturesIntuitive Python project creationWell-defined project structure using source directory layoutPre-configured code linting with PEP8 in mindImproved code quality leveraging static code analysisEnabled unit and integration testing supporting test-driven developmentProduction-ready continuous integration and deployment toolchainStandard templateWe use this template for our own projects following modern best practices:Formatting code with brunette (a better configurable black fork)Sort and style import with isortLinting with flake8Testing automation with pytest and tox for current Python releasesMeasuring code coverage using coverageContinuous integration on GitlabPackaging as wheelDeployment on PyPI using twineTechnical requirementsBelow is the list of currently supported Python releases:#Python13.723.833.943.10Code and contributionThe code is open source and released under theMIT License (MIT). It is available onGitlaband follows the guidelines aboutSemantic Versioningfor transparency within the release cycle and backward compatibility whenever possible.All contributions are welcome, whether bug reports, reviews, documentation or feature requests.If you're a developer and have time and ideas for code contributions, fork the repo and prepare a merge request:# Prepare your environment the first timepython3.10-mvenv~/virtualenvs/pyquickstart-py310source~/virtualenvs/pyquickstart-py38/bin/activate
pipinstall-e.[development]# Running the tests while developmentpytest# Individual Python release tests and code quality checkstox-epy310
tox-ebrunette
tox-ecoverage
tox-eflake8
tox-eisort
tox-emypy# Ensure code quality running the entire test suite,# this requires all supported Python releases to be installedtoxInstallationInstallpyquickstartusingpip:pipinstallpyquickstartUsageCreate a new Python project from the standard template in your current working directory by runningpyquickstart:pyquickstartThen answer a few simple questions, default values in square brackets:project[shinyprojectname]:author[JohnDoe]:author_email[john@example.com]:repository_url[https://gitlab.com/johndoe/shinyprojectname]:year[2022]:
Package: pyquiet
QUIET-paser环境配置ANTLR-Python Runtime首先， 需要检查Python下的antlr运行环境，quiet-parser使用的版本为antlr4-python3-runtime=4.13.0$ pip show antlr4-python3-runtime

Name: antlr4-python3-runtime
Version: 4.13.0
Summary: ANTLR 4.13.0 runtime for Python 3
Home-page: 
Author: Terence Parr, Sam Harwell
Author-email: Eric Vergnaud <eric.vergnaud@wanadoo.fr>
License: BSD
Location: /home/liudingdong/anaconda3/envs/quingo/lib/python3.8/site-packages
Requires: 
Required-by: pyquiet若已安装其它版本的antlr4-python3-runtime，会在使用pip安装quiet-parser之后卸载并安装4.13.0的antlr4-python3-runtime。Parser&Lexer 生成新版本已经将生成后的文件上传，故无需进行额外的操作测试pip install -e .
pytest