Saravanan666/pypi-org huggingface dataset:
Package: repaper
repaperConvert photo of a form to web based froms or editable pdf forms.Free software: MIT licenseDocumentation:https://re-paper.readthedocs.io.InstallationStable releaseTo install repaper, run this command in your terminal:$pipinstallrepaperThis is the preferred method to install repaper, as it will always install the most recent stable release.UsageTo use repaper in a project:from repaper import repaperTo generate a google form from the a form image:from repaper import repaper

re_paper = repaper('../samples/test.jpg')

form_id = re_paper.make_google_from('../secrets/credentials.json')

print(f'''Form created with form id: {form_id["formId"]} and is accessible at: \n https://docs.google.com/forms/d/{form_id['formId']}/viewform \n
edit and publish the form to make it accessible to others''')Command line usage to generate google form from image:repaper google-form --img_path ./samples/test.jpg --oauth_json ./secrets/credentials.jsonDevelopment LeadBhanu Pallakonda <pvbhanuteja@gmail.com>Gaurav Sood <gsood07@gmail.com>ContributorsNone yet. Why not be the first?FeaturesTODOCreditsPortions of this research were conducted with the advanced computing resources provided byTexas A&M High Performance Research Computing.This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2022-11-13)First release on PyPI.0.1.2 (2022-11-15)Setup update
Package: reparo
reparoReparo is a python sci-kit learn inspired package for Missing Value Imputation. It contains a some feature transformers to eliminate Missing Values (NaNs) from your data for Machine Learning Algorithms.This version of reparo has the next methods of missing value imputation:Cold-Deck Imputation (CDI).Hot-Deck Imputation (HotDeckImputation).Fuzzy-Rough Nearest Neighbor for Imputation (FRNNI).K-Nearest Neighbors Imputation (KNNI).Single Center Imputation from Multiple Chained Equation (SICE).Predictive Mean Matching (PMM).Multivariate Imputation by Chained Equation (MICE).All these methods work like normal sklearn transformers. They have fit, transform and fit_transform functions implemented.Additionally every reparo transformer has an apply function which allows to apply an transformation on a pandas Data Frame.How to use reparoTo use a transformer from reparo you should just import the transformer from reparo in the following framework:fromreparoimportMICEclass names are written above in parantheses.Next create a object of this algorithm (I will use k-Nearest Neighbors Imputation as an example).method=KNNI()Firstly you should fit the transformer, passing to it a feature matrix (X) and the target array (y). y argument is not really used (as it causes data leackage)method.fit(X,y)After you fit the model, you can use it for transforming new data, using the transform function. To transform function you should pass only the feature matrix (X).X_transformed=method.transform(X)Also you can fit and transform the data at the same time using the fit_transform function.X_transformed=method.fit_transform(X)Also you can apply a transformation directly on a pandas DataFrame, choosing the columns that you want to change.new_df=method.apply(df,'target',['col1','col2'])With <3 from Sigmoid.
We are open for feedback. Please send your impression tovladimir.stojoc@gmail.com
Package: reparsec
reparsecSmall parsec-like parser combinators library with semi-automatic error recovery.Installationpip install reparsecUsageTutorialDocumentationExampleWithreparsec, simple arithmetic expression parser and evaluator could be written like this:fromtypingimportCallablefromreparsecimportDelayfromreparsec.scannerlessimportliteral,parse,regexpfromreparsec.sequenceimporteofdefop_action(op:str)->Callable[[int,int],int]:return{"+":lambdaa,b:a+b,"-":lambdaa,b:a-b,"*":lambdaa,b:a*b,}[op]spaces=regexp(r"\s*")number=regexp(r"\d+").fmap(int)<<spacesmul_op=regexp(r"[*]").fmap(op_action)<<spacesadd_op=regexp(r"[-+]").fmap(op_action)<<spacesl_paren=literal("(")<<spacesr_paren=literal(")")<<spacesexpr=Delay[str,int]()expr.define((number|expr.between(l_paren,r_paren)).chainl1(mul_op).chainl1(add_op))parser=expr<<eof()This parser can:evaluate an expression:>>>parser.parse("1 + 2 * (3 + 4)").unwrap()15report first syntax error:>>>parser.parse("1 + 2 * * (3 + 4 5)").unwrap()Traceback(mostrecentcalllast):...reparsec.types.ParseError:at8:expected'('attempt to recover and report multiple syntax errors:>>>parser.parse("1 + 2 * * (3 + 4 5)",recover=True).unwrap()Traceback(mostrecentcalllast):...reparsec.types.ParseError:at8:expected'('(skipped2tokens),at17:expected')'(skipped1token)automatically repair input and return some result:>>>parser.parse("1 + 2 * * (3 + 4 5)",recover=True).unwrap(recover=True)15track line and column numbers:>>>parse(parser,"""1 +... 2 * * (... 3 + 4 5)""",recover=True).unwrap()Traceback(mostrecentcalllast):...reparsec.types.ParseError:at2:5:expected'('(skipped2tokens),at3:7:expected')'(skipped1token)More examples:JSON parserScannerless JSON parser
Package: reparted
IntroductionReparted is my attempt at learning python ctypes module to create bindings for c api’s so use it
at your own risk. I was a bit confused on the way parted and pyparted interface works, my aim was
to create a simple interface. It does not have the full set of features parted has to offer, only
enough to create and delete partitions and set the labels. It has been tested using python 2.7 and
libparted 3.0. Feel free to check the code and point out enhancements.
For any questions my email isrq.sysadmin@gmail.com, have fun!DownloadsYou can download the package from PyPi:http://pypi.python.org/pypi/reparted/or checkout reparted on github:http://github.com/xzased/repartedInstallationYou can get reparted using pip to install it from PyPI:pip install -U repartedNoteYou must have libparted installed and available from your LD_LIBRARY_PATHDocumentationYou can view the documentation and quickstart guide here:http://xzased.github.com/reparted1.2 Release NotesChanges from 1.1There are no syntax changes in this version (and hopefully never will), so code working on
previous versions should work just fine, however, there are some minor structure changes that
improve readability and fixed weird behavior. The Partition class has been moved to its own
modulepartition.py, this will not affect you if you are importing like:from reparted import *Other than that, there are only the following bugfixes and cool additions:Bug FixesFailed to add primary partition after extended partition was created in msdos disks.Reparted would segfault if attempting to add logical partitions on non-msdos disks.Partition types were not being checked against disk types and extended partitions.AdditionsBasic operation support for size class.Device, Disk and Partition instances provide a size method.Disk class now provides usable_free_space and total_free_space methods.Logical partitions are added automatically to extended partitions(you can still provide the start and/or end sector if you want to).*1.1 Release NotesBug FixesNo error was raised when calling Device with an invalid path.Calculations in to method from Size class were wrong.Reparted would segfault when initializing a fresh disk and call certain disk methods.AdditionsCustom exceptions.Nice documentation.
Package: repast4py
Repast for Python (Repast4Py)Build StatusMasterDevelopRepast4PyRepast for Python (Repast4Py) is the newest member of theRepast Suiteof
free and open source agent-based modeling and simulation software.
It builds onRepast HPC, and provides the ability to build large, distributed agent-based models (ABMs) that span multiple processing cores.
Distributed ABMs enable the development of complex systems models that capture the
scale and relevant details of many problems of societal importance. Where Repast HPC is
implemented in C++ and is more HPC expert focused, Repast4Py is a Python package and is
designed to provide an easier on-ramp for researchers from diverse scientific communities to apply large-scale distributed ABM methods.
Repast4Py is released under the BSD-3 open source license, and leveragesNumba,NumPy, andPyTorchpackages, and the Python C API
to create a scalable modeling system that can exploit the largest HPC resources and emerging computing architectures. See our paper on Repast4Py for additional information about the design and implementation.Collier, N. T., Ozik, J., & Tatara, E. R. (2020). Experiences in Developing a Distributed Agent-based Modeling Toolkit with Python. 2020 IEEE/ACM 9th Workshop on Python for High-Performance and Scientific Computing (PyHPC), 1–12.https://doi.org/10.1109/PyHPC51966.2020.00006RequirementsRepast4Py requires Python 3.7+Repast4Py can run on Linux, macOS and Windows provided there is a working MPI implementation
installed and mpi4py is supported. Repast4Py is developed and tested on Linux. We recommend
that Windows users use the Windows Subsystem for Linux (WSL). Installation instructions for
WSL can be foundhere.Under Linux, MPI can be installed using your OS's package manager. For example,
under Ubuntu 20.04 (and thus WSL), the mpich MPI implementation can be installed with:$sudoaptinstallmpichInstallation instructions for MPI on macOS can be foundhere.A typical campus cluster, or HPC resource will have MPI and mpi4py installed.
Check the resource's documentation on available software for more details.InstallationRepast4Py can be downloaded and installed from PyPI using pip.
Since Repast4Py includes native MPI C++ code that needs to be compiled,
the C compilerCCenvironment variable must be set
to thempicxx(ormpic++) compiler wrapper provided by your MPI installation.env CC=mpicxx pip install repast4pyNOTE: If you see an error message about a missingpython.hheader file when
installing Repast4Py under Ubuntu (or other Linuxes), you will need to install
a python dev package using your OS's package manager. For example, assuming
Python 3.8,sudo apt install python3.8-devwill work for Ubuntu.DocumentationUser's GuideAPI DocsExample ModelsContact and SupportGitHub IssuesGitHub RepositoryIn addition to filing issues on GitHub, support is also available viaStack Overflow.
Please use therepast4pytag to ensure that we are notified of your question.
Software announcements will be made on therepast-interestmailing list.Jonathan Ozik is the Repast project lead. Please contact him through
theArgonne Staff Directoryif you
have project-related questions.
Package: repathlib
repathlibrepathlibis a package that combinesrepathlibandre, enabling you to
search, match, etc., onPathobjects, and to search directories withPath.reiterdir:fromrepathlibimportPathdocs=Path('docs')docs.search('d[a-z]+')<re.Match object; span=(0, 4), match='docs'>list(docs.reiterdir('\.rst'))[PosixPath('docs/api.rst'), PosixPath('docs/index.rst')]Complete documentation is onreadthedocs.
Package: re-patterns
re_patternspython regular expressions for humansDescriptionThis module helps you build complex regular expressions.UsageExample:>>> from re_patterns import Rstr

>>> regex = Rstr("Isaac").not_followed_by("Newton").named("non_newtonians")
>>> regex
'(?P<non-newtonians>Isaac(?!Newton))'
>>> match = regex.search("Isaac Lobkowicz, Isaac Newton")
>>> match.span()
(0, 5)
>>> match.group("non_newtonians")
'Isaac'For further uses please look at the methods of theRstrclass in__init__.py.
Package: repcal
RepcalA small application that converts date and time to the systems used by the French First Republic.The calendar from 1793 to 1805 and decimal time for about a year between 1794 and 1795. More information can be found onWikipedia.It uses the Romme method of calculating leap years, as in keeping the ones used by the French Republic and using the Gregorian rules for the years after the calendar was abolished.CLI ToolInstallation usingpipx:$ pipx install repcalWhen called without any parameters it will print the current local time and date:$ repcal
7:76:5 - Septidi 7 nivôse an CCXXXIIConversions-i DATE, --input DATEThis parameter accepts a specific date and/or time in ISO format and will print it's republican counterpart.$ repcal -i '1969-07-20 20:17:40'
8:45:60 - Primidi 1 thermidor an CLXXVIIUTC Offset-u OFFSET, --utc-offset OFFSETThis parameter is used to get the current date and time for a given number of standard minutes from UTC. For example, the current time in New York (EST, UTC-05:00):$ repcal -u -300Paris Mean Time-p, --paris-meanFor the full republican experience, it can also use Paris Mean Time (6.49 decimal minutes ahead of UTC).Output Formatting-f [FORMAT], --format [FORMAT]The default output format can be overridden with a string containing placeholders for specific datetime values.$ repcal -i '1969-07-20' -f '{%d} {%+B}'
1 ThermidorUsing-f, --formatwithout a provided format string will print acheat sheetof available placeholders.The format can also be set using the environment variablesREPCAL_DATE_FORMATandREPCAL_TIME_FORMAT:$ REPCAL_DATE_FORMAT='{%d} {%+B}' repcal -i '1969-07-20'Python PackageThe script can also installed withpipand used as a package in other Python projects:fromrepcalimportRepublicanDate,DecimalTimefromdatetimeimportdatetimen=datetime.fromisoformat('1969-07-20 20:17:40')rd=RepublicanDate.from_gregorian(n.date())dt=DecimalTime.from_standard_time(n.time())# The objects have standard string representations,...print(rd)# Primidi 1 thermidor an CLXXVIIprint(dt)# 8:45:60# ...access to specific properties...print(rd.get_year_roman())# CLXXVIIprint(dt.decimal)# 0,8456# ...and formatting.print(rd.get_formatter().format('{%d} {%+B}'))# 1 Thermidor
Package: repcalchn
Repcalchn本项目提供公历日期与时间向法国共和历转换的功能，支持汉语（简体中文）和法语。A script that converts date and time to the French Republican systems used by the French Republic, supports Simplified Chinese and French.This repo borrows heavily fromdekadans/repcal.A script that converts date and time to the systems used by the French Republic, the calendar from 1793 to 1805 and decimal time for about a year between 1794 and 1795.
More information can be found onWikipedia,Wikipedia ChineseIt uses the Romme method of calculating leap years, as in keeping the ones used by the French Republic and using the Gregorian rules for the years after the calendar was abolished.In comparison withdekadans/repcal, this repo offers flag and APIs that supports Chinese.Installation$ pip install repcalchnUsageThe current local time is used by default.$ repcalchn
5:60:56, 法国共和历 231年 菓月 18 鼠李日 星期八Or, for the full Republican experience, it can default to Paris Mean Time (6.49 decimal minutes ahead of GMT).$ repcalchn --paris-mean
2:33:91, 法国共和历 231年 菓月 18 鼠李日 星期八If you want see it in French, just add--fr$ repcalchn --fr
5:62:1, octidi 18 fructidor an CCXXXIIt also accepts date, time and format as arguments.$ repcalchn '1969-07-20 20:17:40'
8:45:60, 法国共和历 177年 牧月 1 紫花苜蓿日 星期一

$ repcalchn '1969-07-20'
法国共和历 177年 牧月 1 紫花苜蓿日 星期一

$ repcalchn '20:17:40'
8:45:60

$ repcalchn '1969-07-20' --format '{%d} {%B}'
1 thermidor

$ repcalchn '1969-07-20' --format '{%y}年 {%b} {%d}'
177年 牧月 1As a Python packagefromrepcalchnimportRepublicanDate,DecimalTimefromdatetimeimportdatetimen=datetime.now()rd=RepublicanDate.from_gregorian(n.date())rd.set_chinese_formatting()dt=DecimalTime.from_standard_time(n.time())print(rd)# 法国共和历 231年 菓月 18 鼠李日 星期八print(dt)# 5:66:4RepublicanDate APIValueInstance methodFormat placeholderExampleNoteYear (arabic)get_year_arabic()%y219Year (roman)get_year_roman()%YCCXXIXMonthget_month()%BvendémiaireMethod returnsNoneand placeholder returns''ifis_sansculottides()isTrue.Month (Chinese)get_month_chn()%b获月Method returnsNoneand placeholder returns''ifis_sansculottides()isTrue.Week (décade)get_week_number()%W3Day in monthget_day()%d28Day in weekget_weekday()%AoctidiMethod and placeholder returns french sansculottides name ifis_sansculottides()isTrue.Day in week (Chinese)get_weekday_chn()%a星期八Method and placeholder returns Unique Day name ifis_sansculottides()isTrue.Unique Day name (Chinese)get_unique_chn()%x紫花苜蓿日Every date in French Republican Calendar has an unique name.Full Unique Day name (Chinese)get_full_unique_chn()%X牧月 紫花苜蓿日Month and unique day name in chinese. No month ifis_sansculottides()isTrue.Is complementaryis_sansculottides()--falseCheck if it is a sansculottides day, which is not included in any month.DecimalTime APIValuePropertyFormat placeholderExampleHourhour%H8Minuteminute%M1Secondsecond%S65
Package: repchar
This is a simple command line script that creates a list of all
characters contained in a given document.Download, Installationrepchar is available on PyPI <https://pypi.python.org/pypi/repchar/>.Install withpip install repchar.Usagerepchar [-h] -o OUTFILENAME [-v] [-c] INFILENAMEpositional arguments:INFILENAME            Filenameoptional arguments:-h,--helpshow this help message and exit-oOUTFILENAME,--outfileOUTFILENAME,--outOUTFILENAMEFilename for report-v,--verboseSet log level to INFO.--versionshow program’s version number and exit-c,--comb,--combiningCreate special report for combining charactersTheReporterclassYou can also use theCharReporterclass in your own code:>>>fromrepcharimportCharReporter>>>s=u"ABCD">>>r=CharReporter()>>>r.feed(s)>>>print(r.report())chr hex     count   unicode
A   0041    1       LATIN CAPITAL LETTER A
B   0042    1       LATIN CAPITAL LETTER B
C   0043    1       LATIN CAPITAL LETTER C
D   0044    1       LATIN CAPITAL LETTER DThe count of each letter is stored inCharReporter.chars:>>>r.chars{u'A': 1, u'C': 1, u'B': 1, u'D': 1}Special information about combining characters can be collected inCharReporter.combdirif you say so at instantiation:>>>fromrepcharimportCharReporter>>>r2=CharReporter(combining=True)>>>s=u"Caffe\u0300">>>r2.feed(s)>>>print(r2.report().encode("UTF-8"))chr hex     count   unicode
C   0043    1       LATIN CAPITAL LETTER C
a   0061    1       LATIN SMALL LETTER A
e   0065    1       LATIN SMALL LETTER E
f   0066    2       LATIN SMALL LETTER F
 ̀  0300    1       COMBINING GRAVE ACCENT
                        1 with: LATIN SMALL LETTER E>>>r2.combdir{u'\u0300': {u'e': 1}}
Package: rep-cli
Rep is a tiny tool for freelancers and contractors to track time and calculate invoices. It's written primarily based on my experience and process so it definitely won't work for all of you out there. However, some of you might still find it useful.At the moment, Rep can:Track timeTake notesCalculate invoicesApproachRep uses logs to track time and group notes. It's a very simple approach that I used to use with pen and paper.For example, this is a single log:Nov 4 2020 14:00 - Start work
Nov 4 2020 18:00 - Note: Let's go, wohoooooo!
Nov 5 2020 00:30 - Stop workRep stores these logs inside a hidden.repdirectory in your project folder. The database is a human-friendly JSON file that can be manually edited when needed.UsageThere are six commands you need to know to use Rep:CommandActionrep initInitialize Rep in the current directory.rep startOpen a new log and start measuring time.rep stopClose the current log and stop measuring time.rep noteAdd a note to the last log.rep tablePrint logs in a table (doesn't show notes).rep printPrint logs and notes.rep invoicePrint the invoice amount for unbilled logs.rep billMark logs as billed.LicenseRep is licensed under the MIT license.
Package: repcomp
repcomprepcomp(short for representation comparison) is a package for comparing trained embedding models. You can use it to compare Deep Neural Networks, Matrix Factorization models, Graph Embeddings, Word Embeddings, etc.repcompsupports the following embedding comparison approaches:Nearest Neighbors: Fetch the nearest neighbor set of each entity according to embedding distances, and compare model A's neighbor sets to model B's neighbor sets.Canonical Correlation: Treat embedding components as observations of random variables and compute the canonical correlations between model A and model B.Unit Match: Form a unit-to-unit matching between model A's embedding components and model B's embedding components and measure the correlations of the matched units.A simple example comparing random embeddings:fromrepcomp.comparisonimportCCAComparisonimportnumpyasnp# Generate random embedding matricesnum_samples=100num_components=10embedding_1=np.random.random((num_samples,num_components))embedding_2=embedding_1+0.5*np.random.random((num_samples,num_components))# Run the comparisoncomparator=CCAComparison()sim=comparator.run_comparison(embedding_1,embedding_2)print("The canonical correlation similarity is{}".format(sim["similarity"]))A more involved example comparing word embeddings:importgensim.downloaderasapiimportnumpyasnpfromrepcomp.comparisonimportNeighborsComparison# Load word vectors from gensimglove_wiki_50=api.load("glove-wiki-gigaword-50")glove_twitter_50=api.load("glove-twitter-50")# Build the embedding matrices over the shared vocabulariesshared_vocab=set(glove_wiki_50.vocab.keys()).intersection(set(glove_twitter_50.vocab.keys()))glove_wiki_50_vectors=np.vstack([glove_wiki_50.get_vector(word)forwordinshared_vocab])glove_twitter_50_vectors=np.vstack([glove_twitter_50.get_vector(word)forwordinshared_vocab])# Run the comparisoncomparator=NeighborsComparison()print("The neighbors similarity between glove-wiki-gigaword-50 and glove-twitter-50 is{}".format(comparator.run_comparison(glove_wiki_50_vectors,glove_twitter_50_vectors)["similarity"]))
Package: repDNA
repDNArepDNA is a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects.This repDNA package is open source software made available under GPL license. Please see the LICENSE file for further details.Important linksHome-page:http://bioinformatics.hitsz.edu.cn/repDNA/Official source code repo:https://github.com/liufule12/repDNADownload releases:http://bioinformatics.hitsz.edu.cn/repDNA/downloadSupplementary (manual and example):http://bioinformatics.hitsz.edu.cn/repDNA/supplementaryIssue tracker:https://github.com/liufule12/repDNA/issuesCitation:http://bioinformatics.hitsz.edu.cn/repDNA/citationPython RequirementsThe repDNA was tested to work under Python 2.7, 3.3 and 3.4 on Windows, Mac and Linux.InstallationIf the user had installedpip(A tool for installing and managing Python packages), just type:pip install repDNAOtherwise, download and unzip the repDNA package, go to the directory, and type:python setup.py installorsudo python setup.py install