Saravanan666/pypi-org huggingface dataset:
Package: ciscoris
ciscorisUses Realtime Information Service (RIS) to capture registration status of Cisco IP Phones on CUCMhttps://developer.cisco.com/docs/sxml/#risport70-api-referenceInstall with pip or clone repopipinstallciscorisimport ris, logcollection or other classesfromciscorisimportrisspecify your CUCM detailscucm=os.getenv('cucm','10.10.10.10')version=os.getenv('version','11.5')risuser=os.getenv('risuser','risadmin')rispass=os.getenv('rispass','p@ssw0rd')instanciate your RIS objectris=ris(username=risuser,password=rispass,cucm=cucm,cucm_version=version)input an array of phonesphones=['SEPF8A5C59E0F1C','SEP1CDEA78380DE','SEP01CD4EF58980']input an array of "process nodes" or nodes which run Callmanager servicesubs=['sub1','sub2','sub3']you can use the relatedciscoaxllibrary grab process nodes via API.defgetSubs():nodes=axl.listProcessNodes()ifnodes['success']:returnnodes['response']subs=getSubs()group phones into 1000 and check registrations per grouplimit=lambdaphones,n=1000:[phones[i:i+n]foriinrange(0,len(phones),n)]groups=limit(phones)forgroupingroups:registered=ris.checkRegistration(group,subs)user=registered['LoginUserId']regtime=time.strftime('%Y-%m-%d%H:%M:%S',time.localtime(registered['TimeStamp']))foriteminregistered['IPAddress']:ip=item[1][0]['IP']foriteminregistered['LinesStatus']:primeline=item[1][0]['DirectoryNumber']name=registered['Name']print('name: '+name)print('user: '+user)print('primary dn: '+primeline)print('ip address: '+ip)print('registration time: '+regtime)
Package: cisco-support
Cisco Support APIs for PythonPython implementation of theCisco Support APIImplemented APIsAutomated Software DistributionBugCaseEoXProduct InformationSerial Number to InformationService Order Return (RMA)Software SuggestionInstallationpipinstallcisco_supportUsageAutomated Software DistributionTO BE IMPLEMENTEDBugfromcisco_supportimportBugbug=Bug(client_id='abc',client_secret='def')Casefromcisco_supportimportCasecase=Case(client_id='abc',client_secret='def')EoXfromcisco_supportimportEoXeox=EoX(client_id='abc',client_secret='def')Product Informationfromcisco_supportimportProductInformationproduct_information=ProductInformation(client_id='abc',client_secret='def')Serial Number to Informationfromcisco_supportimportSerialNumberInformationserial_number_information=SerialNumberInformation(client_id='abc',client_secret='def')Service Order Return (RMA)fromcisco_supportimportServiceOrderReturnservice_order_return=ServiceOrderReturn(client_id='abc',client_secret='def')Software Suggestionfromcisco_supportimportSoftwareSuggestionsoftware_suggestion=SoftwareSuggestion(client_id='abc',client_secret='def')
Package: ciscosupportsdk
Python API wrapper for the Cisco Support APIs.Theciscosupportsdksupports all of the Cisco Support API
interactions via a native Python library.  This makes working with
these APIs a morenaturalexperience and eases the burden of writing
your own boilerplate code to deal with API semantics, like authentication
and pagination.For detailed information and onboarding information, see thesupport apidocumentation on DevNet.Quick Usagefromciscosupportsdk.apiimportCiscoSupportAPIapi=CiscoSupportAPI(CS_API_KEY,CS_API_SECRET)# find if a serial number is covered and when it's warranty expiresforiteminapi.serial_information.get_coverage_status(['FXS2130Q286']):print(f'{item.is_covered}{item.warranty_end_date}')FeaturesRepresents all of the Cisco Support API interactions in native pythonAuthentication and connection managementAll APIs organized hierarchically as attributes and methods under the main API objectReturned data objects are all native python objectsPagination is automatic and transparentAPI documentation will appear in your IDE to ease developmentInstallationInstalling and upgrading theciscosupportsdkis easy withpippip install ciscosupportsdk#ortoupgradeuse...pip install ciscosupportsdk --upgradeIf you want to setup a development environment, usepoetryinstead:#Installpoetryusingpipxpython -m pip install pipx
python -m pipx ensurepath
pipx install poetry#Clonerepositorygit clone https://github.com/supermanny81/ciscosupportsdk.git
cd ciscosupportsdk/#Installdependenciespoetry installExamplesLooking for some sample usage?  Check out theexamplesfolder!
Package: ciscotmg
ciscotmgCisco TMG Matrix Python SDK (as a CLI tool)This is a Private API that is converted in to Python objects and printed in to your terminalUsageSearchciscotmg search QSFP-100G-ERLookupciscotmg lookup QDD-400G-ZR-Sciscotmg lookup -n C9500X-28C8DAuthors & MaintainersUsers responsible for the creation and maintenance of this project:Robert Csaporcsapo@cisco.comLicenseThis project is licensed to you under the terms of theCisco Sample
Code License.
Package: cisco-zeus
Python client for CiscoZeus.io. It allows a user to send and receive data to and from Zeus.Free software: Apache LicenseDocumentation:https://cisco-zeus.readthedocs.org.FeaturesSend logs and metrics to ZeusQuery both logs and metricsHistory0.2.1 (2015-06-06)Fixed some bugs. Ready for the Hackathon.0.2.0 (2015-06-04)Added support for the new API, which includes metric deletion.0.1.0 (2015-04-30)First release on PyPI.
Package: cis-DjangoSignUp
Description:The main motive is to upload our own package on PyPI. so for doing testing, I have
uploaded it on this platform.installation:Just run a command on the terminalpip install cis_DjangoSignUp.In settings.py,Add in the installed app‘cis_DjangoSignUp’,Add in context processor‘cis_DjangoSignUp.context_processors.AJAX_POST’,
‘cis_DjangoSignUp.context_processors.reg_form’Also, set email backend to activate accountEMAIL_BACKEND = ‘django.core.mail.backends.smtp.EmailBackend’
EMAIL_HOST = ‘smtp.gmail.com’
EMAIL_USE_TLS = True
EMAIL_PORT =
EMAIL_HOST_USER = ‘’
EMAIL_HOST_PASSWORD = ‘’
SUCCESS_SIGNUP_URL = ‘’
AJAX_POST = TrueIn main urls.py :path(‘’, include(‘cis_DjangoSignUp.url’)),After then add it in the template where you want :{% include ‘cis_DjangoSignUp/register.html’ %}
Package: ci-sdr
Convolutive Transfer Function Invariant SDRThis repository contains an implementation for theConvolutive transfer function Invariant Signal-to-Distortion Ratioobjective for PyTorch as described in the publicationConvolutive Transfer Function Invariant SDR training criteria for Multi-Channel Reverberant Speech Separation(link arXiv).Here, a small example, how you can use this CI-SDR objective in your own source code:importtorchimportci_sdrreference:torch.tensor=...# reference.shape: [speakers, samples]estimation:torch.tensor=...# estimation shape: [speakers, samples]sdr=ci_sdr.pt.ci_sdr_loss(estimation,reference)# sdr shape: [speakers]The idea of this objective function is based in the theory fromE. Vincent, R. Gribonval and C. Févotte, Performance measurement in blind audio source separation, IEEE Trans. Audio, Speech and Language Processing, known asBSSEval.
The original author provided MATLAB source code (link) and the packagemir_eval(link) contains a python port. Some peoble refer to these implementations asBSSEval v3(link).The PyTorch code in this package is tested to yield the sameSDRvalues asmir_evalwith the default parameters.NOTE:If you want to useBSSEval v3 SDRas metric, I recomment to usemir_eval.separation.bss_eval_sourcesand use as reference the clean/unreverberated source signals. The implementation in this repository has minor difference that makes it problematic to compare SDR values accorss different publications (e.g. here the permutation is calculated on the SDR, whilemir_evalcomputes it based on theSIR.).InstallationInstall it directly with Pip, if you just want to use it:pipinstallci-sdror to get the recent version:pipinstallgit+https://github.com/fgnt/ci_sdr.gitIf you want to install it withalldependencies (test and doctest dependencies), run:pipinstallgit+https://github.com/fgnt/ci_sdr.git#egg=ci_sdr[all]When you want to change the code, clone this repository and install it aseditable:gitclonehttps://github.com/fgnt/ci_sdr.gitcdci_sdr
pipinstall--editable.# pip install --editable .[all]CitationTo cite this implementation, you can cite the following paper (link):@article{boeddeker2020convolutive,
  title   = {Convolutive Transfer Function Invariant {SDR} training criteria for Multi-Channel Reverberant Speech Separation},
  author  = {Boeddeker, Christoph and Zhang, Wangyou and Nakatani, Tomohiro and Kinoshita, Keisuke and Ochiai, Tsubasa and Delcroix, Marc and Kamo, Naoyuki and Qian, Yanmin and Haeb-Umbach, Reinhold},
  journal = {arXiv preprint arXiv:2011.15003},
  year    = {2020}
}
Package: ciseau
Ciseau------Word and sentence tokenization in Python.[![PyPI version](https://badge.fury.io/py/ciseau.svg)](https://badge.fury.io/py/ciseau)[![Build Status](https://travis-ci.org/JonathanRaiman/ciseau.svg?branch=master)](https://travis-ci.org/JonathanRaiman/ciseau)![Jonathan Raiman, author](https://img.shields.io/badge/Author-Jonathan%20Raiman%20-blue.svg)[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE.md)Usage-----Use this package to split up strings according to sentence and word boundaries.For instance, to simply break up strings into tokens:```tokenize("Joey was a great sailor.")#=> ["Joey ", "was ", "a ", "great ", "sailor ", "."]```To also detect sentence boundaries:```sent_tokenize("Cat sat mat. Cat's named Cool.", keep_whitespace=True)#=> [["Cat ", "sat ", "mat", ". "], ["Cat ", "'s ", "named ", "Cool", "."]]````sent_tokenize` can keep the whitespace as-is with the flags `keep_whitespace=True` and `normalize_ascii=False`.Installation------------```pip3 install ciseau```Testing-------Run `nose2`.If you find this project useful for your work or research, here's how you can cite it:```latex@misc{RaimanCiseau2017,author = {Raiman, Jonathan},title = {Ciseau},year = {2017},publisher = {GitHub},journal = {GitHub repository},howpublished = {\url{https://github.com/jonathanraiman/ciseau}},commit = {fe88b9d7f131b88bcdd2ff361df60b6d1cc64c04}}```
Package: cish
I used to write small bash scripts that created the virtualenv and
executed thepython setup.pyandnosetestscommands using
one of several Python versions I keep installed on my build machines.
But bash scripts aren’t supported on Windows, so I want to write
this script in Python instead.cishis a set of utility functions to write bash-like python
scripts that deal with several installed python interpreters.Let’s get going!importcishcish.rm("build")cish.default.pip("install","nose")cish.default.python("setup.py","build")cish.default.nosetests()This will delete thebuilddirectory if it exists with all content,
installnose, and build and test the package.defaultis an ‘environment’ which consists of a python interpreter,
library path, and utilities such aspip.defaultis the environent
of the interpreter executing the script itself.We can also use a different interpreter:importcishenv=cish.from_interpreter("path/to/python")env.python("setup.py","build")env.nosetests()The installation location of the python interpreters is often
dependent on the test machine. We can place a simple JSON file
in one of several locations, for example in/etc/cish.json,
to specifiy their location:{"2.6.9":"/opt/python2.6.9/bin/python","2.7.8":"/opt/python2.7.8/bin/python"}We can then choose the interpeter in our script using, say,
an environment variable set by jenkins:importcish,osenv=cish.from_config()[os.environ["PYTHON_VERSION"]]env.python("setup.py","build")virtualenvis very easy too:importcishvenv=cish.default.virtualenv("optional/location")venv.pip("install","package_to_install_inside_virtualenv")Bug Reports and other contributionsThis project is hosted herecish github page.AlternativesYou might want to look atsha cool library to
run executables without dealing withsubprocessdirectly. It has a far wider
scope thancishbut lacks the abstraction we offer for different python installations
and OS specific file extensions and installation locations.
Package: cis-interface
The CiS framework provides support for combining scientific models
written in different programming languages. To combine two models,
modelers add simple communications interfaces to the model code and
provide simple declarative specification files that identify the models
that should be run and the inputs and outputs those models expect.The system uses the specification files to configure the communications
channels and expose them to the models. The complexity of the particular
communications system is managed by the framework, which performs
communication setup, binds the communications to simple interfaces
within the models, and manages execution of the models. The complexities
of model registration and discovery, as well as the complexities of
setup and management of the communications system are handled
under-the-hood by the framework under direction of the model
specification, freeing the domain scientist from implementing
communications protocols or translating models to the same programming
language.Please refer to the packagedocumentationfor
additional information about the package and directions for installing
it.WarningThis will be the last release of the Crops in Silico
framework under the namecis_interface. Moving forward,
the package will be refered to asyggdrasil. The new
Github repository foryggdrasilcan be foundhereand the new documentation can be foundhere.
Future versions of theyggdrasilpackage be installed from
PyPI viapip installyggdrasil-framework. We apologize for
any inconvenince this change causes, but feel the new name
better reflects the spirit of the project.
Package: ciso
# ciso[![Tests](https://github.com/ioos/ciso/actions/workflows/tests.yml/badge.svg)](https://github.com/ioos/ciso/actions/workflows/tests.yml)
[![Wheels](https://github.com/ioos/ciso/actions/workflows/cibuildwheel.yml/badge.svg)](https://github.com/ioos/ciso/actions/workflows/cibuildwheel.yml)Fast cythonized code for iso-slices of ocean models properties.
Package: cisort
C/С++ Includes SortThis is a tool that allows you to quickly and
conveniently sort all libraries included in the project in
alphabetical order.ExamplesText before:#include<iostream>#include<vector>#include<stdio.h>#include<algorithm>#include"mylib.h"#include"b_lib.h"#include"a_first_lib.h"#include<external/lib/main.hpp>#include<external/lib/abuse.hpp>#include<external/lib/func.hpp>intmain(){std::cout<<"Hello, World!"<<std::endl;}Text after:#include<algorithm>#include<iostream>#include<stdio.h>#include<vector>#include"a_first_lib.h"#include"b_lib.h"#include"mylib.h"#include<external/lib/abuse.hpp>#include<external/lib/func.hpp>#include<external/lib/main.hpp>intmain(){std::cout<<"Hello, World!"<<std::endl;}Installation:pipinstallcisortUsage:cisort [flags] [path]Flags:-r--recursive- recursive searching C/C++ files-ls- show info about sorted files-h--help- to get help-c--comments- add comments to sorted blocks\n'ContactsVK,Telegram,Discord
Package: cit
序言github上有很多好项目,但是国内用户连github却非常的慢.每次都要用插件或者其他工具来解决.
这次自己做一个小工具,输入github原地址后,就可以自动替换为代理地址,方便大家更快速的下载.
速度太慢可以看下gitee仓库地址github仓库安装pipinstallcit# 代理安装路径pipinstall-ihttps://mirrors.cloud.tencent.com/pypi/simplecit主要功能与用法主要功能change 将目标地址转换为加速后的地址clone 常见的git加速,最快10M/s,有时候慢一点sub git子模块加速,等同于git submodule addget 就是单纯的下载功能示例用法clone功能:等效于git clone <url>citclone<url># 示例citclonehttps://github.com/solider245/cit.git如上图所示,输入一个数字,选择一个链接即可开始下载.默认使用0.sub功能:  等效于git submodule add <url>citsub<url># 案例citsubhttps://github.com/solider245/cit.git逻辑和git clone一样,这里就不放图了.get功能:  等效于wget下载
get功能会根据你的输入,智能判定下载raw文件或者release文件
使用示例:citget<url># 案例citgethttps://github.com/cheat/cheat/archive/4.2.0.zip下载raw文件下载安装包.如上图所示,因为是使用https下载,所以速度快点惊人,如果下载速度太慢可以选择别的地址.我目前测试下来,基本都能用.其他功能[x ] 常用软件下载,类似python,go等下载[x ] 常用系统加速,类似ubuntu或者centos等加速[] 其他常用功能欢迎询问或者给我邮箱发邮件.
Package: citable
CitableCitableis a Python package for downloading datasets fromZenodoby using their DOIs.fromcitableimportCitabledataset=Citable('DOI')r=dataset.download()Installing Citable and supported versionsCitable is available on PyPI:$python-mpipinstallcitableCitable supports Python 3.6+.Supported FeaturesCitable is a handy tool for downloading and using data from Zenodo.Downloading data from ZenodoUnzipping the downloaded data if necessaryReturning suitable data as apandasDataFrame or displayingMarkdowndescriptions if you like toUsageFirst the Citable class must be imported into Python:fromcitableimportCitableAfter doing so you must initiate a Citable object. You pass a DOI from Zenodo formatted as a string into the initiating method and give the returned object a name:dataset=Citable('DOI')The Citable class has only one function. This is thedownload()function.r=dataset.download(showMarkdown=True,pandas=True)You can pass along two arguments with this function, both of which are boolean:showMarkdownandpandas. By default both are set toTrue, meaning that any markdown description contained in the downloaded data is shown viaIPythonand the package assumes you are usingpandas DataFrames.InputshowMarkdown: if you don't want the markdown displayed, insert the argumentshowMarkdown = Falseinto the download functionpandas: if you don't want to return a list containing pandas DataFrames but rather want to do your own thing and just want to know where the downloaded data was stored, insert the argumentpandas = Falseinto thedownload()function.OutputThe output of the download function depends whether the input variable pandas is True or False:pandas == True: The download function returns a list of pandas DataFrames and strings ready for you to usepandas == False: The download function returns a dictionary of the file names of the downloaded data and where they have been stored, so that you can copy & paste the path of the data you want to work with into your favourite data handler
Package: citation-extractor
# (Canonical) Citation Extractor## Status[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.35470.svg)](https://doi.org/10.5281/zenodo.35470)
[![Build Status](https://travis-ci.org/mromanello/CitationExtractor.svg?branch=master)](https://travis-ci.org/mromanello/CitationExtractor)
[![codecov](https://codecov.io/gh/mromanello/CitationExtractor/branch/master/graph/badge.svg)](https://codecov.io/gh/mromanello/CitationExtractor)## InstallationThis software supports Python version 2.7, and it was tested only on POSIX–compliant operating systems (Linux, Mac OS X, FreeBSD, etc.).To install theCitationExtractorfirst run:$ pip installhttp://www.antlr3.org/download/Python/antlr_python_runtime-3.1.3.tar.gz#egg=antlr_python_runtime-3.1.3$ pip installhttps://github.com/mromanello/treetagger-python/archive/master.zip#egg=treetagger-1.0.1followed by:$ pip install citation-extractorNB:the installation of all other dependencies is handled bysetup.pybut for some reason
(that I’m still trying to figure out) it does not pick up these two.## DocumentationI’m working on it ;-)For the time being, you can find a concrete example of how to use the library in [this notebook](https://gist.github.com/mromanello/3d29add74a33da6629509742fe738ca1).
Package: citationhelper
citationhelperThis is a utility that generates a list of all packages imported into python scripts (*.py) in a given list of directories.  It is intended to be used to help keep track of community software used in research projects so that the packages can be properly cited in publications.  The utility works by first walking the named directories and identifying *.py files, then searching these files for import statements.Installationcitationhelper can be installed via pippip install citationhelperAlternatively, citationhelper can be installed from githubpip install git+https://github.com/EarthCubeInGeo/citationhelper.gitAfter installing, set the environment variable CITEHELP_REFFILE if you want to use a custom JSON library of full citations.  The utility will work without this, but it can only generate a list of package names with no citation information.export CITEHELP_REFFILE=filenameUsageRun citationhelper with thecitehelpcommand followed by a list of the directories to search for import statements and print a report to the screen.citehelp project_directoryWARNING: This tool was developed to assist researchers in keeping track of software packages, but it is HIGHLY recommended users review the list of packages produced.
Package: citation-langserver
citation-langservercitation-langserver is a language server for working with citations stored in BibTeX or BibLaTeX files.citation-langserver supports code completion, hover, jump to definition, and find references. It supports absolute file paths for bibliographies, relative file paths, as well as glob-based file paths. It is compatible with all clients that support theLanguage Server ProtocolInstallationRunpip3 install citation-langserverto install.UsageConfigurecitation-langserveras you would any other LSP in your text editor of choice.For instance, usingCoCin Vim, you might add the following to yourcoc-settings.jsonfile:"languageserver":{"citation":{"command":"/usr/local/bin/citation-langserver","filetypes":["markdown"],"settings":{"citation":{"bibliographies":["~/library.bib","./*.bib"]}}}}ConfigurationThe settingcitation.bibliographiesneeds to be sent by the client to the server and contain an array of file paths. The file paths can include:Absolute pathsRelative pathsGlobs (absolute or relative)
Package: citation-parser
Canonical references (e.g. “Hom.Il.1,124-125”) use punctuation symbols in a consistent way, meaning that we can define a formal grammar to process them.When encountering the reference “Hom.Il.1,124-125”, the human reader will parse it as follows:the text preceding the numbers contains information about work and author being citedthe hyphen is used to specify a range of text passages, e.g. lines 124 to 125;the semicolon separates a reference from another within the sanme citation (is common to chain together references to mutiple of the same work or of different works);the comma separates the hierarchical levels of the work being cited. In the example above 1,124-5 stands for from Book 1, Line 124 to Book 1, Line 125when the citation scope is a range, the identical hierarchical level are collapsed: 1.124 - 1.125 can be written as both 1.124-125 or 1.124 s. without any loss of information for the human reader.The CitationParser is composed by a lexer, a parser and a tree parser written in ANTLR and compiled into Python code. The parsed reference is then serialized into JSON.An example:>>> cp = CitationParser()
>>> cp.parse("Hom. Il. 1,124-125")
[{'work': u'Hom. Il.', 'scp': {'start': ['1', '124'], 'end': ['1', '125']}
Package: citation-sorter
CitationSorterCitationSorteris a Python package for sorting and organizing citations in LaTeX documents. It is designed to help you neatly arrange in-text citations within LaTeX files based on the author and publication year.InstallationYou can installCitationSorterusing pip:pipinstallcitation-sorterUsageCitationSortercan be used both as a library and as a command-line tool.As a LibraryYou can useCitationSorteras a library in your Python scripts. Here's an example of how to use it:fromcitation_sorterimportCitationSorter# Create an instance of the CitationSorter classsorter=CitationSorter()# Process LaTeX files in the input folder and save the modified versions in the output foldersorter.process_folder(input_folder='input_folder_path',output_folder='output_folder_path')As a Command-Line ToolYou can also useCitationSorterfrom the command line. After installing it, you can run it as follows:citation_sorterinput_folderoutput_folderReplaceinput_folderwith the path to the folder containing your LaTeX files andoutput_folderwith the path where you want the modified files to be saved.LaTeX File FormatCitationSorterworks with LaTeX files containing citation commands starting with \cite. It sorts the citations within these commands based on the author's name and publication year.Example LaTeX citation command:\cite{smith2023book, jones2022paper, brown2021article}\cite[p.1]{smith2023book, jones2022paper, brown2021article}\citet{smith2023book, jones2022paper, brown2021article}\citep{smith2023book, jones2022paper, brown2021article}LicenseThis project is licensed under the GPL-3.0 license. See the LICENSE file for details.