Saravanan666/pypi-org huggingface dataset:
Package: readless
A python module for conversation and text summarization and much more
exciting features.Featuresprovided by this module:Text Segmentationusing:TextTilingwithBlock ScoreTextTilingwithVocabulary introductionConversational summarizationusing:Cluster RankText summarizationusing :TextRankRandomInstallationMake sure you havePython2.7/3.3+ andpip(Windows,Linux)
installed. Run simply (preferred way):$[sudo]pipinstallreadlessOr for the latest version in development:$[sudo]pipinstallgit+git://github.com/adichat/read-less.gitReadLess APIYou can use readless like a library in your project.For quickly summarizing a conversation using ClusterRank algorithm:# -*- coding: utf8 -*-fromreadless.Summarizationimportclusterranksummarizer=clusterrank.ClusterRank()pathToFile="C:/conversation.in"summary=summarizer.summarizeFile(pathToFile)For segmenting a text using TextTiling algorithm:# -*- coding: utf8 -*-fromreadless.Segmentationimporttexttilingsegmentation=texttiling.TextTiling()pathToFile="C:/conversation.in"segmentedText=segmentation.segmentFile(pathToFile)For a detailed list of other API functionalities, see**ReadLess
Documentation**.ContributionsAll contributions are welcomed. This module is in development and there
are several scopes of improvement. Tests are to be implemented along
with other Summarization algorithms with support for web page
summarization. For upcoming features, seeFuture developments.LICENSE
Package: read-lif
read_lifLoad 3D confocal images fromliffiles asnumpyarrays.The code was originally written by Mathieu Leocmach in packagecolloids.InstallThe most convenient way would be:pip install read_lifYou can also Include the fileread_lifin your project directoryHow to Use Itimportread_lifreader=read_lif.Reader('lif_file.lif')series=reader.getSeries()chosen=series[0]# choose first image in the lif file# get a numpy array corresponding to the 1st time point & 1st channel# the shape is (z, y, x)image=chosen.getFrame(T=0,channel=0)
Package: readligo
ReadLIGOThis module provides tools for reading LIGO data files.
Data along with supporting documentation can be downloaded from theGWOSC web site.! NoticeThis module has been deprecated and we recommend usingGWPyinstead.We keep this module public for archival reasons only. No further development is planned.InstallationTo install download the repo and install with pipgitclonehttps://git.ligo.org/gwosc/readligo.git;cdreadligo
pipinstall.DocumentationSome possible use cases are shown below.Example 0To load all data from a single file:strain,time,dq=rl.loaddata("ligo_data/H-H1_LOSC_4_V1-842653696-4096.hdf5","H1")Some GWF files require parameters to name the strain, DQ, and hardware injection channel:strain,time,dq=rl.loaddata("H-H1_LOSC_16_V1-1127415808-4096.gwf","H1",strain_chan="H1:GWOSC-16KHZ_R1_STRAIN",dq_chan="H1:GWOSC-16KHZ_R1_DQMASK",inj_chan="H1:GWOSC-16KHZ_R1_INJMASK")Example 1This default configuration assumes that the needed LIGO data files are available in the current working directory or a subdirectory.
LIGO data between the input GPS times are loaded into STRAIN.
META is a dictionary of gps start, gps stop, and the sample time.
DQ is a dictionary of data quality flags.segList=getsegs(842657792,842658792,'H1')for(start,stop)insegList:strain,meta,dq=getstrain(start,stop,'H1')# -- Analysis code here...Example 2In Example 2,H1_segs.txtis a segment list downloaded from the
GWOSC web site using theTimeline application.  This may be used in the same
manner assegListin example 1.segList=SegmentList("H1_segs.txt")Example 3In this example, the first command searches the indicated directory and
sub-directories for LIGO data files.
This list of data files is then used to construct a segment list and load
the requested data.filelist=FileList(directory="/home/ligodata")segList=getsegs(842657792,842658792,"H1",filelist=filelist)forstart,stopinsegList:strain,meta,dq=getstrain(start,stop,"H1",filelist=filelist)# -- Analysis code hereSegment ListsSegment lists may be downloaded from the GWOSC web site
using the Timeline Query Form or constructed directly
from the data files.Read in a segment list downloaded from theTimeline applicationon theGWOSC web sitewithSegmentList.fromreadligoimportSegmentListseglist=SegmentList("H1_segs.txt")Or Construct a segment list directly from the LIGO data files withgetsegs.fromreadligoimportgetsegsseglist=getsegs(842657792,842658792,'H1',flag='DATA',filelist=None)
Package: readlike
A Python module that providesGNU Readline-like line editing functions (the
default Emacs-style ones). If you just want to use Readline, use thereadlinepackage in the standard library–but this package allows access to those
capabilties in settings outside of a standard CLI.Currently, all stateless Readline commands are implemented. This means that
yanking and history are not supported.This module is especially well-suited to interfacing withUrwiddue to a
shared syntax for describing key inputs.InstallationInstall or upgrade to the latest version fromPyPI:[sudo] pip install -U readlikeQuick exampleTranspose words:>>> import readlike
>>> readlike.edit('perilous siege', 9, 'meta t')
('siege perilous', 14)CommandsImplemented commands and their correspondings keys are as follows:backward-char            ctrl b, left
backward-delete-char     ctrl h, backspace
backward-kill-word       ctrl meta h, meta backspace
backward-word            meta b, meta left
beginning-of-line        ctrl a, home
capitalize-word          meta c
delete-char              ctrl d, delete
delete-horizontal-space  meta \
downcase-word            meta l
end-of-line              ctrl e, end
forward-char             ctrl f, right
forward-word             meta f, meta right
kill-line                ctrl k
kill-word                meta d, meta delete
transpose-chars          ctrl t
transpose-words          meta t
unix-line-discard        ctrl u
unix-word-rubout         ctrl w
upcase-word              meta uFor more information about each command, see readline(3) or see the doc
strings inreadlike.py.Projects using Readlikehangups
Package: readline0
Read lines of data with an arbitrary delimiter, like a null, newline or even an x.It passes pylint, passes pycodestyle, passes pydocstyle, is thoroughly unit tested, and runs on CPython 2.7, CPython 3.x,
Pypy 7.3.1, and Pypy3 7.3.1.It gains a lot of speed by eschewing single-character reads.Usage looks like:importreadline0file_=open('/etc/shells','r')forlineinreadline0.readline0(file_=file_,separator=b'\n'):...print(line)...b'# /etc/shells: valid login shells'b'/bin/sh'b'/bin/dash'b'/bin/bash'b'/bin/rbash'Of course separator need not be a newline; it defaults to a null byte.
Alsofile_defaults to sys.stdin.
And there’s a blocksize argument as well, which defaults to 64K.
Package: readlog
readlogA python code to read thermo info from the log file of LAMMPS outputInstallationgitclonehttps://github.com/eastsheng/readlog.gitcdreadlog
pipinstall.# orpipinstallreadlogRequirementsnumpypandasmatplotlibUsagerunplot_themo.pyindemofolder:pythonplot_thermo.pyout:Fixed2023-10-11: v1.2.2a great modification2023-09-16: v1.2.1FixedUnicodeDecodeError: 'utf-8' codec can't decodeproblem.2023-06-20: v1.2.0Fixed a read error in the complete message frame under incomplete message;addprint_readlogfunction;addReadRunTimefunction.
Package: readma
Readma? What's Readma?Readma is a binary stream reading library I made for fun that I decided I would extend on and releaseWell, what does it do?Well I'm glad you asked!Readma is a little library I started to help with parsing binary files.That's it?Well yeah, what did you expect?
Some large module I've been writing my entire life that will change the world with its amazing binary reading ability?Cool BadgesUsageNote, requires Python 3.8 or higher (For now at least)InstallationpipinstallreadmaSample codefromreadmaimportReadma# Let's say this file contains in order:# - An integer# - An unsigned integer# - A float# - A string prefixed by its length with a byte# - An unknown amount of data you just really need readr=Readma("some_file.bin")# note: defaults to Little Endianinteger=r.read(4)# size in bytesunsigned_integer=r.uread(4)a_float=r.float()length=r.read(1)string=r.bytes(length)important_data=r.readall()Example of ways to do the same actionfromreadmaimportReadma,ReadmaTypesr=Readma(b"AAAABBBBCCCCDDDD")A=r.read(4)# Reads a 32 bit (4 byte) integerB=r.read("int")# this also reads a 32 bit intC=r.read(ReadmaTypes.int)# someone might prefer this idkD=r.bytes(4)# its a bytestring, do whatever with itYou can also move around the buffer using seek, skip, and tellfromreadmaimportReadmar=Readma(b"AAAABBCCCCXXXXXXXXDDDD")A=r.read(4)r.seek(6)# seek past BC=r.read(4)r.skip(8)# skip past the next 8 bytesD=r.read(4)Oh and you can check the size of the buffer toofromreadmaimportReadmar=Readma(b"AAAABBBBCCCCDDDD")assertr.size()==16# observe the script not haltingDocumentationtbaLicenseCopyright (c) 2021whamer100This project isMITlicensed.hey is this project name just one big ligma jokemaybe
Package: readmat
readmatreadmat is a Python package with helpful functions for loading .mat MATLAB files into Python. Most data types are supported.Installation:pip install readmatPrerequisites:python 3python modules:scipynumpyFunctions:load(filename, isNumber=False, isCharArray=False, isStruct=False, isFunction=False, isArray=False, isMatrix=False, isBool=False, isInf=False, isNaN=False, isFunctionHandle=False)Example:matdata1 = readmat.load('matfile1.mat', isCharArray=True)Usage depends on data type. For structs, an example usage ismatdata1.this.is.a.test. For all other data types,matdata1.Input: .mat fileOutput: depends on data typemat2obj(filename)Example:matdata2 = readmat.mat2obj('matfile2.mat')Example Usage:matdata2.this.is.a.testInput: .mat fileOutput: objectmat2dict(filename)Example:matdata3 = readmat.mat2dict('matfile3.mat')Example Usage:matdata3['this']['is']['a']['test']Input: .mat fileOutput: dictionaryoptions(matobj)Example:readmat.options(matdata1)Example:readmat.options(matdata2)Input: objectOutput: list of optionsHow structs are loaded:The load function loads your MATLAB structure as an object in Python. What does this mean? Basically, the method of exploring the depths of your struct in Python is similar to what you'd do in python. Pretty neat examples below:MATLABPythonDWI.dat(1,1,1)myMat.DWI.dat[0][0][0]DWI.hdr.private.hdr.test.hellomyMat.DWI.hdr.private.hdr.test.hellolesion_jhu.meanmyMat.lesion_jhu.meandata.grades(101)myMat.data.grades[100]Known limitations:The following MATLAB data types are not supported:string arrays (for example: "example" [notice the pair of double quotes])datetimecategoricaltabletimetableTips for overcoming each limitation:(MATLAB commands listed below)convert string arrays to char arrays, command:char(stringarray)convert datetime to either a char array or a struct, command:char(vardatetime)orstruct(vardatetime)convert categorical to double, command:double(varcategorical)convert table to cell array, command:arrayfun(@convertStringsToChars,arrayfun(@string,[vartable.Properties.VariableNames;table2cell(vartable)]),'UniformOutput',false)convert timetable to cell array, command:horzcat(vertcat('Time',cellstr(char(vartimetable.Properties.RowTimes))), arrayfun(@convertStringsToChars,arrayfun(@string,[vartimetable.Properties.VariableNames;table2cell(vartimetable)]),'UniformOutput',false))Sources cited:Although I did write part of readmat's code , without the amazing stackoverflow answers from the following stackoverflow users, this project would not have be possible:users cs01 and jpapon:https://stackoverflow.com/a/29126361user andyvanee:https://stackoverflow.com/a/6573827LicenseThis software includes aMIT license.
Package: readmdict
readmdictRead mdx/mdd files (repacking of readmdict from mdict-analysis)This is a repacking ofreadmdict.pyinhttps://github.com/csarron/mdict-analysis. All credit goes to the original author(s).Prerequisitepython-lzoIfpython-lzois not present, you' ll see "LZO compression support is not available" when runningreadmdict.pipinstallpython-lzo# or poetry add python-lzoIn Windows without a functioning C++ environment, you won't be able to installpython-lzoviapip. Head tohttps://www.lfd.uci.edu/~gohlke/pythonlibs/#python-lzo. Download and installpython-lzowhl for your python version.Installationpipinstallreadmdict# or poetry add readmdictUsageCommand lineBrowse a mdx or mdd file and print its meta informationreadmdictorpython-mreadmdictPrint meta info of a filefile.mdxreadmdictfile.mdxorpython-mreadmdictfile.mdxPrint a short summaryreadmdict-horpython-mreadmdict-hIn Python codefromreadmdictimportMDX,MDDfilename="some.mdx"headwords=[*MDX(filename).header]print(headwords[:10])# fisrt 10 in bytes formatforhdwinheadwords[:10]:print(hdw.decode())# fisrt 10 in string formatitems=[*MDX(filename).items()]forkey,valinitems[:10]:print(key.decode(),val.decode())# first 10 entries# read an mdd filefilename="some.mdd"items=MDD(filename).items()idx=0forfilename,contentinitems:idx+=1ifidx>10:breakprint(filename.decode(),content.decode())# first 10 entries
Package: readme
WarningThe readme library was renamed to readme_renderer to work around an
installation issue that could prevent it from being installed on
some systems. Use thereadme_rendererlibrary instead.Readme is a library that will safely render arbitrary README files into HTML.
It is designed to be used inWarehouseto render thelong_descriptionfor packages.Check Description LocallyTo check your long description’s locally simply install the readme library
using:$pipinstallreadme$pythonsetup.pycheck-r-s
Package: readme42
Installation$[sudo]pipinstallreadme42$[sudo]npmi-greadme42Exampleshttps://readme42.com/templates/username/template{% if examples %}
### Examples
{{ examples }}
{% endif %}

{% if links %}
### Links
{{ links }}
{% endif %}cli$exportREADME42_TOKEN="XXX"# https://readme42.com/token/$exportREADME42_TEMPLATE="username/template"$readme42.>README42.mdpython api:url='https://api.readme42.com/templates'headers={'Authorization':'Token README42_TOKEN'}data=dict(examples=open('examples.md').read(),links=open('links.md').read())r=requests.post(url,headers=headers,data=data)open('README.md','w').write(r.text)Linksreadme42.comreadme42.com
Package: read-me-cli
Command line tool that displays github README.md content for github repositories in the terminal!UsageTo run it, in the terminal, run the following Command::$ readme_cli <github repository link>InstallationTo install::$ pip install readme_cliRequirementsCompatibilityPython 3>LicenceMITAuthorsKisekka Davidreadme_cliwas written byKisekka David.
Package: readme-cli
README CLISimple README.md generator.InstallationTo install type the following in the terminal:pipinstallreadme-cliUsageCommand to generate LICENSE.md file looks like:readmeOr you can specify a variant of the generated README.md:readme<readme-variant>Where<readme-variant>is one of:small- title, installation, usagemedium- title, installation, usage, license, contributinglarge- lots of stuffLicenseMITContributingSeeCONTRIBUTING.md
Package: readmedocs-fetcher-haystack
🎾 ReadmeDocsFetcher Node for HaystackThis custom component for Haystack is designed to fetch documentation pages from the ReadMe documentation you have access to. It uses aMarkdownConverterto convert all of your documentation pages to a list of HaystackDocuments. You can use this node as a standalone node or within an indexing pipeline.Instllationpipinstallreadmedocs-fetcher-haystackUsage in HaystackTo initialize aReadmeDocsFetcheryou have to provide anapi_keyparamter. This is your ReadMe Docs API Key.There are also 4 optional parameters to initialize theReadmeDocsFetcherslugs: To fetch a list of specific pages from your documentation. E.g. if you have want to fetch 'https://docs.haystack.deepset.ai/docs/installation' the slug would beinstallation. If not set, all of the available pages will be fetched.base_url: Optionally provide this to add the full url of a documentation page to themetaof the created document. For examplebase_url='https://docs.haystack.deepset.ai'"version: If not set, the latest stable version of tour docs will be fethed.markdown_converter: When documents are fetched from ReadMe, temporary.mdfiles are created and we use aMakrdownConverterto create a list of haystackDocuments. If not provided at initialization, the aMarkdownConverterwith the default parameters is used.Standaloneimportosfromdotenvimportload_dotenvfromhaystack.nodesimportMarkdownConverterfromreadmedocs_fetcher_haystackimportReadmeDocsFetcherload_dotenv()README_API_KEY=os.getenv('README_API_KEY')converter=MarkdownConverter(remove_code_snippets=False)readme_fetcher=ReadmeDocsFetcher(api_key=README_API_KEY,markdown_converter=converter,base_url="https://docs.haystack.deepset.ai")readme_fetcher.fetch_docs()To fetch a single doc from a specific version:readme_fetcher.fetch_docs(slugs=["nodes_overview"],version="v1.18")In a Pipelineimportosfromdotenvimportload_dotenvfromhaystackimportPipelinefromhaystack.nodesimportMarkdownConverter,PreProcessorfromhaystack.document_storesimportInMemoryDocumentStorefromreadmedocs_fetcher_haystackimportReadmeDocsFetcherload_dotenv()README_API_KEY=os.getenv('README_API_KEY')converter=MarkdownConverter(remove_code_snippets=False)readme_fetcher=ReadmeDocsFetcher(api_key=README_API_KEY,markdown_converter=converter,base_url="https://docs.haystack.deepset.ai")preprocessor=PreProcessor()doc_store=InMemoryDocumentStore()pipe=Pipeline()pipe.add_node(component=readme_fetcher,name="ReadmeFetcher",inputs=["File"])pipe.add_node(component=preprocessor,name="Preprocessor",inputs=["ReadmeFetcher"])pipe.add_node(component=doc_store,name="DocumentStore",inputs=["Preprocessor"])pipe.run()To fetch a single documentation page:pipe.run(params={"ReadmeFetcher":{"slugs":["nodes_overview"]}})
Package: readme-docstring
Installation$[sudo]pipinstallreadme-docstringExamplesexample withreadme-generatorclassReadme(readme_generator.Readme):order=[...,"classes","functions",...]defclasses(self):classes=self.getclasses()returnreadme_docstring.Classes(classes)deffunctions(self):functions=self.getfunctions()returnreadme_docstring.Functions(functions)custom tableclassExecutableModules(readme_docstring.Table):columns=["usage","`__doc__`"]def__init__(self,modules):self.objects=modulesdefgetleftcell(self,obj):default="python -m%s"%obj.__name__.replace(".__main__","")return"`%s`"%getattr(obj,"USAGE",default)readme42.com
Package: readmemaker
readmemakerA Python utility library to help make a README file from document files.Exampleshttps://github.com/thombashi/pathvalidate/blob/master/docs/make_readme.pyOutput:https://github.com/thombashi/pathvalidate/blob/master/README.rsthttps://github.com/thombashi/pytablewriter/blob/master/docs/make_readme.pyOutput:https://github.com/thombashi/pytablewriter/blob/master/README.rsthttps://github.com/thombashi/SimpleSQLite/blob/master/docs/make_readme.pyOutput:https://github.com/thombashi/SimpleSQLite/blob/master/README.rstInstallationpip install readmemakerDependenciesPython 3.6+path
Package: readme-md
Install$[sudo]pipinstallreadme-mdFeatures<section-name>.mdsectionsattrs/properties/methods sections- subclassreadme_md.Readmeauto headers- if section 1st line is not empty and not#headersectionsorder-Readme.orderororder.txtpython project (setup.cfgrequired) sections -install,classes,functions,cliClassesreadme_md.Readme- README.md generatorReadmeattrs__doc__header_lvlheader default lvl (4)headersdict with sections headers (optional)orderlist of sections ordersectionsdict with sections (loaded from .md files)Readmemethods__doc__get_header(name)return a string with section headerget_section(name)return a string with README sectionget_sections()return all sections in a list of (name, string) pairs sorted byorderload(path)load sections and orderrender()render to a stringsave(path='README.md')save to fileFunctionsfunction__doc__readme_md.broken_links(string, timeout=5)return a list with broken markdown linksreadme_md.links(string)return a list with markdown linksreadme_md.tables.attrs(cls)return a string with class attributes tablereadme_md.tables.cls(cls)return a string with class name, description and attrs+methods+properties tablesreadme_md.tables.methods(cls)return a string with class methods tablereadme_md.tables.properties(cls)return a string with class properties tablereadme_md.tables.usage(modules)return a string with cli modules usage table.python -m moduleor moduleUSAGEvariable (if defined).if __name__ == "__main__"line requiredCLIusage__doc__python -m readme_md.broken_links path [timeout]print README.md broken linkspython -m readme_md.create [path ...]generate README.mdpython -m readme_md.links pathprint README.md linksExamples# .README/examples.md, .README/features.md, .README/order.txt$python-mreadme_md.create.README>README.md
$python-mreadme_md.broken_linksREADME.md# find broken linksclassReadme_npm(readme_md.Readme):order=["description","features","install",...]disabled=["generator"]@propertydefinstall(self):return"`$ [sudo] npm i -g%s`"%json.loads(path)["name"]Readme(".README").save("README.md")# load sections and create README.mdreadme-md- README.md generator
Package: readme-metrics
ReadMe MetricsTrack usage of your API and troubleshoot issues faster.WithReadMe's Metrics APIyour team can get deep insights into your API's usage. If you're a developer, it takes a few small steps to send your API logs toReadMe. Here's an overview of how the integration works:You add the ReadMe middleware to yourDjango,Flask, orWSGIapplication.The middleware sends to ReadMe the response object that your application generates each time a user makes a request to your API. The entire response is sent, unless you allow or deny keys.ReadMe populates Metrics with this information, such as which endpoint is being called, response code, and error messages. It also identifies the customer who called your API, using whichever keys in the middleware you call out as containing relevant customer info.pipinstall"readme-metrics[Django]"# Django applicationspipinstall"readme-metrics[Flask]"# Flask applicationspipinstallreadme-metrics# WSGIDjango IntegrationsFlask IntegrationsWSGI Integrations🚧 Any Issues?Integrations can be tricky!Contact supportif you have any questions/issues.
Package: readme-page
# Readme PageA script to create a readme [GitHub Page](https://help.github.com/articles/creating-project-pages-manually) for your project. See an [example](http://fernandojunior.github.io/readme-page).This project uses [BeautifulSoup](http://www.crummy.com/software/BeautifulSoup/), [mkdocs](http://mkdocs.github.io/mkdocs-bootstrap/) and [six](https://pythonhosted.org/six/).## Installation & UsageRunpip install readme-pageto install the script.Runreadme-pageto create your repository GitHub Page.Checkout the repository page athttp://<your_github_username>.github.io/<repository_name>## ContributingSee [CONTRIBUTING](https://github.com/fernandojunior/readme-page/CONTRIBUTING.md).## License[![CC0](https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png)](https://creativecommons.org/licenses/by-nc-sa/4.0/)The MIT License.Copyright (c) 2016 [Fernando Felix do Nascimento Junior](https://github.com/fernandojunior/).