Saravanan666/pypi-org huggingface dataset:
Package: pyCIAP
pyCIAPThis a very simple package to solve the Combinatorial Integral Approximation Problem (CIAP)
including dwell-time constraints by a dwell-time sum-up rounding algorithm, see1for the theoretical results.InstallClone this repo and then runpython3 setup.py installinside the repo directory.Example:frompyCIAPimportDSUR,solveCIAPMDTimportnumpyasnp# Relaxed control fulfilling SOS1-constraintb_rel=np.array([[0.47131227,0.78736104,0.97325193,0.53496864,0.73187786,0.07838749,0.48948843,0.64580892],[0.52868773,0.21263896,0.02674807,0.46503136,0.26812214,0.92161251,0.51051157,0.35419108]])# time griddt=1.0time=np.arange(0,b_rel.shape[1],dt)# Computes a binary control fulfilling the minimum dwell times# The dwell times are always in number of time steps, i.e. multiples of dtb_bin=DSUR(b_rel,1.0,time,min_up_time=3,min_down_time=3)givesarray([[1,1,1,0,0,0,1,1],[0,0,0,1,1,1,0,0]])In order to compare the DSUR solution to the global optimum, one can
solve the CIAP by Gurobi and use the solution as MIP start:runtime,eps_opt,eps_dsur=solveCIAPMDT(b_rel,dt,3,3,start_sol=b_bin)Hereeps_optandeps_dsurdenote the objective values of the corresponding
CIAP, i.e. theintegrality gap.
Package: pyCICY
pyCICY - v0.5A python CICY toolkit, which allows the computation of line bundle cohomologies over Complete Intersection Calabi Yau manifolds. It further contains functions for determining various topological quantities, such as Chern classes, triple intersection and Hodge numbers.Installation is straighforwad with pippip install pyCICYor get the latest versionpip install --upgrade git+https://github.com/robin-schneider/CICY.gitQuickstartWe import the CICY object from the modulefrompyCICYimportCICYNext we define a CICY, for example the tetraquadric:M=CICY([[1,2],[1,2],[1,2],[1,2]])Now we are able to do some calculations, e.g.M.line_co([1,2,-4,1])determines the hodge numbers of the line bundle L = O(1,2,-4,1).Since the rank computation takes the most time we includedSpasM - github. Therank_hybridexecutable of SpaSM has to be in your $PATH.T=CICY([[1,2,0,0,0],[1,0,2,0,0],[1,0,0,2,0],[1,0,0,0,2],[3,1,1,1,1]])and do some computations:T.line_co([3,-4,2,3,5],SpaSM=True)DocumentationDocumentation can be found on readthedocspyCICY.LiteratureThe module has been developed in the context of the following paper:@article{Larfors:2019sie,
    author = "Larfors, Magdalena and Schneider, Robin",
    title = "{Line bundle cohomologies on CICYs with Picard number two}",
    eprint = "1906.00392",
    archivePrefix = "arXiv",
    primaryClass = "hep-th",
    reportNumber = "UUITP-18/19",
    doi = "10.1002/prop.201900083",
    journal = "Fortsch. Phys.",
    volume = "67",
    number = "12",
    pages = "1900083",
    year = "2019"}Further literature can be found here:@book{Hubsch:1992nu,
	author         = "Hubsch, Tristan",
	title          = "{Calabi-Yau manifolds: A Bestiary for physicists}",
	publisher      = "World Scientific",
	address        = "Singapore",
	year           = "1994",
	ISBN           = "9789810219277, 981021927X",
	SLACcitation   = "%%CITATION = INSPIRE-338506;%%"}@phdthesis{Anderson:2008ex,
	author         = "Anderson, Lara Briana",
	title          = "{Heterotic and M-theory Compactifications for String
	Phenomenology}",
	school         = "Oxford U.",
	url            = "https://inspirehep.net/record/793857/files/arXiv:0808.3621.pdf",
	year           = "2008",
	eprint         = "0808.3621",
	archivePrefix  = "arXiv",
	primaryClass   = "hep-th",
	SLACcitation   = "%%CITATION = ARXIV:0808.3621;%%"}The SpaSM library can be found here:github@manual{spasm,
title ={{SpaSM}: a Sparse direct Solver Modulo$p$},
author ={The SpaSM group},
edition ={v1.2},
year ={2017},
note ={\url{http://github.com/cbouilla/spasm}}}Useful softwarepyCICY works nicely withSage. Other useful packages for dealing with Calabi Yau manifolds in toric varieties arecohomCalgandPALP.
Package: py-cid
CID (Content IDentifier)What is CID ?CIDis a format for referencing content in distributed information systems,
likeIPFS.
It leveragescontent addressing,cryptographic hashing, andself-describing formats.It is the core identifier used byIPFSandIPLD.CID is a self-describing content-addressed identifier.It uses cryptographic hashes to achieve content addressing.It uses severalmultiformatsto achieve flexible self-description,
namelymultihashfor hashes,multicodecfor data content
types, andmultibaseto encode the CID itself into strings.Sample Usage>>>fromcidimportmake_cid>>>make_cid('QmaozNR7DZHQK1ZcU9p7QdrshMvXqWK6gpu5rmrkPdT3L4')CIDv0(version=0,codec=dag-pb,multihash=b"\x12\xb9M'\xb9\x93M>\x08\xa5.R\xd7\xda}\xab\xfa\xc4\x84..")>>>cid=make_cid('QmaozNR7DZHQK1ZcU9p7QdrshMvXqWK6gpu5rmrkPdT3L4')>>>print(cid.version,cid.codec,cid.multihash)>>>print(cid.encode())QmaozNR7DZHQK1ZcU9p7QdrshMvXqWK6gpu5rmrkPdT3L4>>>str(cid)'QmaozNR7DZHQK1ZcU9p7QdrshMvXqWK6gpu5rmrkPdT3L4'InstallationStable releaseTo install CID, run this command in your terminal:$pipinstallpy-cidThis is the preferred method to install CID, as it will always install the most recent stable release.If you don’t havepipinstalled, thisPython installation guidecan guide
you through the process.From sourcesThe sources for CID can be downloaded from theGithub repo.You can either clone the public repository:$gitclonegit://github.com/ipld/py-cidOr download thetarball:$curl-OLhttps://github.com/ipld/py-cid/tarball/masterOnce you have a copy of the source, you can install it with:$pythonsetup.pyinstallOther infoFree software: MIT licenseDocumentation:https://py-cid.readthedocs.io.Python versions: 3.5, 3.6History0.2.1 (2018-10-20)Fix edge cases with multibase and multihash decodingAdded hypothesis tests while verifying CIDs0.1.5 (2018-10-12)Handle the case where an incorrect base58 encoded value is provided tomake_cid0.1.0 (2017-09-05)First release on PyPI.
Package: pycidr
ip_calculatorA cli utility to get detailed IP informationIP Address Information for: 172.14.15.16/21ClassBCIDR block/21IP Address172.14.15.16Network Mask255.255.248.0Network ID172.14.8.0Broadcast Address172.14.15.255Total Addresses2048Usable hosts2046Binary IP10101100.00001110.00001111.00010000Binary Network Mask11111111.11111111.11111000.00000000
Package: pyciede2000
AboutPython implementation of CIEDE2000 color difference calculation based on this paper:The CIEDE2000 Color-Difference Formula: Implementation Notes, Supplementary Test Data, and Mathematical Observations.More info:http://www2.ece.rochester.edu/~gsharma/ciede2000/Use this BibTeX to cite:@article{Sharma2005TheObservations,title={{The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations}},year={2005},journal={Color Research {\&} Application},author={Sharma, Gaurav and Wu, Wencheng and Dalal, Edul N},number={1},month={2},pages={21--30},volume={30},publisher={Wiley Subscription Services, Inc., A Wiley Company},url={http://dx.doi.org/10.1002/col.20070},doi={10.1002/col.20070},issn={1520-6378},keywords={CIE, CIE94, CIEDE2000, CIELAB, CMC, color-difference metrics}}Installpip install pyciede2000Usagefrompyciede2000importciede2000res=ciede2000((50.0000,2.6772,-79.7751),(50.0000,0.0000,-82.7485))print(res)ciede2000accepts two color values as tuples inLabrepresentation. Also supports optional keyword parameters for para-metric weighting factork_L,k_Candk_H.Output formatciede2000()returns a dict with all significant fields in CIEDE2000 calculation.res={"a_1_dash":a_1_dash,"a_2_dash":a_2_dash,"C_1_dash":C_1_dash,"C_2_dash":C_2_dash,"h_1_dash":h_1_dash,"h_2_dash":h_2_dash,"h_bar_dash":h_bar_dash,"G":G,"T":T,"S_L":S_L,"S_H":S_H,"S_C":S_C,"R_T":R_T,"delta_E_00":delta_E_00}You might be only interested in the final delta value,delta_E_00.print(res['delta_E_00'])
Package: pyciff
PyCIFFThis package provides a python interface toPISA's Common Index File Format Import/Export toolset, which is written in Rust.UsageConverting CIFF to PISA:pyciff.ciff_to_pisa(input_file, output, generate_lexicons)input_fileis the input CIFF file.outputis thebasenameof the output PISA canonical files.generate_lexiconsis a Boolean flag; if True, the.termlexand.doclexfiles will be created.Example (using the toy CIFF file stored in this repo):$> cd tests

$> python -c "import pyciff; pyciff.ciff_to_pisa('toy-complete-20200309.ciff', 'my-pisa-files', False)"

----- CIFF HEADER -----
Version: 1
No. Postings Lists: 9
Total Postings Lists: 9
No. Documents: 3
Total Documents: 3
Total Terms in Collection 16
Average Document Length: 5.333333333333333
Description: Export of toy 3-document collection from Anserini's io.anserini.integration.TrecEndToEndTest test case
-----------------------
Processing postings
  [00:00:00] [========================================] / (0s)
Processing document lengths
  [00:00:00] [========================================] / (0s)

$> ls my-pisa-files.*
my-pisa-files.docs  my-pisa-files.documents  my-pisa-files.freqs  my-pisa-files.sizes  my-pisa-files.termsConverting PISA to CIFF:pyciff.pisa_to_ciff(collection_input, terms_input, titles_input, output, description)collection_inputis thebasenameof the (canonical PISA) collection.terms_inputis a newline delimited file containing a single term per line (the first line is the 0-th postings list).titles_inputis a newline delimited file containing a single document identifier per line (the first line is the 0-th document identifier).outputis the name of the CIFF file to output.descriptionis stored inside the CIFF blob, and can be used to describe the collection/parsing/etc.Example using the example files created previously:# Still working in `tests` directory

$> python3 -c "import pyciff; pyciff.pisa_to_ciff('my-pisa-files', 'my-pisa-files.terms', 'my-pisa-files.documents', 'my-new.ciff', 'My example description')"

Collecting posting lists statistics
  [00:00:00] [========================================] / (0s)
Computing average document length
  [00:00:00] [========================================] / (0s)
Writing postings
  [00:00:00] [========================================] / (0s)

$> ls my-new.ciff
my-new.ciffDeploymentTo upload to Pypi:dockerrun--rm-v(pwd):/iokonstin2/maturinpublish-rhttps://test.pypi.org/legacy/-uUSER-pPASSWORDTo upload to Test Pypi:dockerrun--rm-v(pwd):/iokonstin2/maturinpublish-uUSER-pPASSWORD
Package: pycify
pycifyConvert your entire Python project from.pyfiles to.pycfiles.InstallationpipinstallpycifyUsage$pythoncli.pyHello CLI!$pycify.Replacing ./utils/foo.py with ./utils/__pycache__/foo.cpython-311.pycReplacing ./cli.py with ./__pycache__/cli.cpython-311.pyc$tree..├── cli.pyc└── utils└── foo.pyc2 directories, 2 files$pythoncli.pycHello CLI!Local Development / TestingCreate and activate a virtual environmentRunpip install -r requirements-dev.txtto do an editable installRunpytestto run testsType CheckingRunmypy .Create and upload a package to PyPIMake sure to bump the version insetup.cfg.Then run the following commands:rm-rfbuilddist
pythonsetup.pysdistbdist_wheelThen upload it to PyPI usingtwine:twineuploaddist/*
Package: pycimg
READMEpycimgis a python extension for theCImglibrary.The package contains a single class CImg that provides access to the
image processing methods of theCImglibrary.Pixel data of CImg objects can be accessed as anumpyarray.Vice versa new CImg objects can be created from pixel data in anumpyarray
or an image file. Supported file formats arepng,jpeg,tiff, bmp, and cimg.frompycimgimportCImgimportnumpyasnp# Load image from fileimg=CImg('test/test.png')img.display()# Access pixel data as numpy arrayarr=img.asarray()# Set pixels in upper left 100 x 100 px rectanglearr[:,:,0:99,0:99]=0# Pixel data is shared with the image instanceimg.display()# Create image from numpy arrayimg=CImg(np.random.randn(100,100))FeaturesAccess pixel data as anumpyarray.Builtin support for reading/writingpng,jpeg, andtiffimage formats.InstallationInstall pycimg by running:pipinstallpycimgDocumentationSeereadthedocs.LicenseThe project is licensed under the GPL3 license.
Package: pycine
pycineReading Vision Research .cine files with pythonInstallationRelease VersionWith pipIf you have Python 3 installed you can just usepip:pip3 install -U pycineDevelopment versionpip install git+https://github.com/ottomatic-io/pycine.gitExample usageChanging the playback and timecode frameratespfs_meta set --playback-fps 60/1.001 --timecode_fps 60/1.001 A001C001_190302_16001.cineYou can also set metadata for multiple clips at once:pfs_meta set --playback-fps 24/1.001 --timecode_fps 24/1.001 *.cineHelpEvery command has its own help output. Just append--help:$ pfs_meta --help
Usage: pfs_meta [OPTIONS] COMMAND [ARGS]...

  This tool allows .cine file metadata manipulation. Use COMMAND --help for
  more info.

Options:
  --help  Show this message and exit.

Commands:
  copy  Copy metadata from a source clip
  set   Set metadata
  show  Show metadata$ pfs_meta set --help
Usage: pfs_meta set [OPTIONS] [DESTINATIONS]...

  Set metadata

Options:
  --temp FLOAT          Set color temperature.
  --cc FLOAT            Set color correction.
  --record-fps INTEGER  Set record FPS.
  --playback-fps TEXT   Set playback FPS. Use 60 or 60/1.001 but not 59.94
  --timecode-fps TEXT   Set timecode FPS. Use 60 or 60/1.001 but not 59.94
  --tone TEXT           Set tone curve in the form of "[LABEL] x1 y1 x2 y2".
                        You can set up to 32 xy points.
  --help                Show this message and exit.$ pfs_raw --help
Usage: pfs_raw [OPTIONS] CINE_FILE [OUT_PATH]

Options:
  --file-format [.png|.jpg|.tif]
  --start-frame INTEGER
  --count INTEGER
  --version                       Show the version and exit.
  --help                          Show this message and exit.Jupyter notebookCheck out an example on how to use the library from a jupyter notebook:notebooks/Display frames.ipynb
Package: pycinema
Cinema python toolsThepycinemapython module (https://github.com/cinemascience/pycinema) is a set of tools for reading, writing, manipulating and viewing Cinema databases. The toolkit includes a filter-based python core, command line tools, viewers and a visual app building application (Cinema:Theater).Documentation for this module is available athttp://pycinema.readthedocs.ioYou can find out more about Cinema athttp://cinemascience.org.Installing and running the pycinema modulepip install --upgrade pip
pip install pycinema
Package: pycinga
Pycinga is a simple Python library meant to make writingIcingaplugins much easier. Icinga
plugins havequite a few guidelinesto adhere to, and Pycinga provides helpers to make this
easy.InstallTo install, simply usepiporeasy_install:pip install pycingaDocumentationDocumentation for the latest version can always be found athttp://pycinga.readthedocs.io/en/latest.FeaturesThe core features supported by Pycinga:Parsing command line arguments such that the standard expected
arguments (such as-H,-w,-c) are accepted.Returning proper POSIX exit code based on status.Parsing Icinga range formats (such as “@10:20”, “~:50”, “10”, etc.)Outputting status and message.Outputting performance data.ExampleWhat all these features result in is a concise, simple, and
guidelines-compliant Python-based Icinga plugin:from pycinga import Plugin

class UserCheck(Plugin):
    """
    Icinga plugin to check how many users are logged into this
    machine.
    """

    def check(self):
        # Get the number of logged in users, for now we hardcode
        users = 27

        # Build a response and exit. This `response_for_value` automatically
        # creates a response with the proper status given the value and the
        # warning/critical ranges passed in via the command line.
        response = self.response_for_value(users, "%d users" % users)
        response.set_perf_data("users", users)
        response.set_perf_data("another metric", 27, "MB")
        return response

if __name__ == '__main__':
    # Build the plugin instance and run it. This will also parse
    # command line arguments by default.
    UserCheck().check().exit()While the above example subclassesPlugin, you’re of course welcome
to simply callPlugin`s methods directly and build a ``Response`yourself.
Package: pyciosa
Utilidades Para Cualquier Proyecto NuevoModulesPeriodoA "Periodo" is another date representation as a string from the year and the month in format  YYYYMM for example: 202001,
is the representation of january of 2020.Functionsis_validexplodesplitget_periodointerpolateget_previous_quarter_periodoget_periodo_labelget_periodo_range_labelvalidate_dateget_period_full_labelget_date_for_sql_filter_from_periodo
Package: pycipher
Common classical ciphers implemented in Python.
Documentation is available athttp://pycipher.readthedocs.io/en/master/.Installpip install git+git://github.com/jameslyons/pycipherExample usage>>> from pycipher import ADFGVX
>>> adfgvx = ADFGVX(key='PH0QG64MEA1YL2NOFDXKR3CVS5ZW7BJ9UTI8', keyword='GERMAN')
>>> adfgvx.encipher("Hello world!")
'FVFDAGXAFFFFGFAGADFG'
>>> adfgvx.decipher(_)
'HELLOWORLD'FeedbackThe code is hosted on GitHub:https://github.com/jameslyons/pycipherIf you find any bugs make an issue or create a pull request.To run the test suite:python setup.py test
Package: pyciphering
PycipheringAn awesome package to text cipheringInstallationYou can install pyciphering withpipas follows:pip install pycipheringUsageimportpycipheringPrinting encoded and decoded text is incredibly easy:print(pyciphering.atbash.encode("Hello world!")print(pyciphering.atbash.decode("ZYX")CiphersList of all ciphersatbashcaesarviegenerebifidtrifidpolybius
Package: pyciphers
Cipher-Python-PackageSummary of the Python PackageThis package encrypts your text using Hill Cipher Technique.
Hill ciphers are an application of linear algebra to cryptology (the science of
making and breaking codes and ciphers).Algorithm:Let the order of the encryption key be N (as it is a square matrix).
Your text is divided into batches of length N and converted to numerical vectors
by a simple mapping starting with A=0 and so on.The key is then multiplied with the newly created batch vector to obtain the
encoded vector. After each multiplication modular 36 calculations are performed
on the vectors so as to bring the numbers between 0 and 36 and then mapped with
their corresponding alphanumerics.While decrypting, the decrypting key is found which is the inverse of the
encrypting key modular 36. The same process is repeated for decrypting to get
the original message back.Implementation:from pycipher import HillCipherobj = HillCipher("beaf")print(hc.encrypt("Love Python"))print(hc.decrypt("PITTOO"))References:https://apprendre-en-ligne.net/crypto/hill/Hillciph.pdf
Package: pycipherwallet
A Python library to access the cipherwallet API.SetupYou can install this package by using the pip tool and installing:$ pip install cipherwalletOr:$ easy_install cipherwalletSetting up a cipherwallet AccountSign up for a free cipherwallet account athttps://cipherwallet.comUsing the cipherwallet APIDocumentation for the python bindings can be found at:https://cipherwallet.com/docsWe also provide SDKs for other languages (php, node.js, and hopefully more to come).
Package: pycirce
pycirceSome primitive combinators for structurally decoding Pythondataclass's,namedtuple's, or other types.Usagepycirce.decode_listThedecode_listcombinator accepts a decoder as its first argument and returns a decoder:>>>decode_intlist=decode_list(int)>>>decode_intlist(["1","2","3"])[1,2,3]pycirce.decode_objectThedecode_objectcombinator accepts a constructor as its first argument,
as well as a kwarg of parameter names to decoders for that particular name.>>>@dataclass...classPerson:...name:str...age:int...>>>decode_person=decode_object(Person)()>>>decode_person({"name":"John Smith","age":"45"})Person(name='John Smith',age=45)If members don't require downstream decoders, the second argument list kwargs can be
empty:>>>@dataclass...classPerson:...name:str...age:str...>>>decode_person=decode_object(Person)()>>>decode_person({"name":"John Smith","age":"45"})Person(name='John Smith',age="45")
Package: pycircleci
pycircleciPython client forCircleCI API.Based on the discontinuedcircleci.pyproject.FeaturesSupportsAPI v1.1andAPI v2Supports bothcircleci.comand self-hostedEnterprise CircleCIInstallation$ pip install pycircleciUsageCreate a personalAPI token.Set up the expected env vars:CIRCLE_TOKEN           # CircleCI API access token
CIRCLE_API_URL         # CircleCI API base url. Defaults to https://circleci.com/apifrompycircleci.apiimportApi,CIRCLE_TOKEN,CIRCLE_API_URLcircle_client=Api(token=CIRCLE_TOKEN,url=CIRCLE_API_URL)# get current user infocircle_client.get_user_info()# get list of projectsresults=circle_client.get_projects()# pretty print results as jsoncircle_client.ppj(results)# pretty print the details of the last request/responsecircle_client.ppr()Interactive development consolemake consoleThis starts a pre-configured python interactive console which gives you access to aclientobject - an instance of theApiclass to play around. From the console
typeman()to see the help screen.ContributingFork itInstall dev dependencies (pip install -r requirements-dev.txt)Create your feature branch (git checkout -b my-new-feature)Make sureflake8and thepytesttest suite successfully run locallyCommit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create new Pull Request
Package: pycircleci-async
pycircleciAsynchronous Python client forCircleCI API.Ported frompycircleci, a fork of the discontinuedcircleci.pyproject.FeaturesSupportsAPI v1.1andAPI v2Supports bothcircleci.comand self-hostedEnterprise CircleCIInstallation$ pip install pycircleci-asyncUsageCreate a personalAPI token.Set up the expected env vars:CIRCLE_TOKEN           # CircleCI API access token
CIRCLE_API_URL         # CircleCI API base url. Defaults to https://circleci.com/apiimportasynciofrompycircleci_asyncimportCircleCIClientasyncdefmain():asyncwithCircleCIClient(token='<access-token-uuid>')ascircle_client:# get current user infoawaitcircle_client.get_user_info()# get list of projectsresults=awaitcircle_client.get_projects()asyncio.run(main())ContributingFork itInstall poetry (pip install poetry)Install dependencies (poetry install)Create your feature branch (git checkout -b my-new-feature)Make sureflake8and thepytesttest suite successfully run locallyCommit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create new Pull Request
Package: pycircos
# Python Modules for Circos Plot[![Build Status](https://travis-ci.com/KimBioInfoStudio/PyCircos.svg?branch=develop)](https://travis-ci.com/KimBioInfoStudio/PyCircos)
![codecov](https://codecov.io/gh/KimBioInfoStudio/PyCircos/branch/develop/graph/badge.svg)## 1. Pre Installation> As official, Pyhton2 will end life form 2020-1-1, So we develop a new version support Python3.5+, We deeply recommand all users using the python version 3.5+, Thx!### Python 3.5+ packages(automatically installed)numpypandasmatplotlib## 2. Installation
### intall dev branchinstall from source code` git clonehttps://github.com/KimBioInfoStudio/PyCircos.gitcd PyCircos pip install-rrequirements.txt python3 setup.py install[--user]`or install form source code with using ‘make’` git clonehttps://github.com/KimBioInfoStudio/PyCircos.gitcd PyCircos make install `install release branch` pip install pycircos `## 3. Examples
### command` cd ./test/ python3 test.py open ./demo.png `### results![](./test/demo.png)