Saravanan666/pypi-org huggingface dataset:
Package: pypager
A $PAGER in pure Pythonpip install pypagerPypager can be used as a stand-alone application, or as a library.What is a pager?A pager is a terminal program that can be used to view the content of a file,
or the output stream from another application.For instance, when we runman vim, the actual content is displayed in a
pager, according to the$PAGERenvironment variable.Important for a pager is that the input can be streamed. For instance when we
executefind / | pypager; we don’t want to wait for the whole file system
to be traversed, before displaying anything. Data is only read from the input
pipe, when it needs to be displayed.Popular pager applications aremore,lessandmost.FeaturesHighlighting of text [0].Searching.Many key bindings fromlessare implemented.[0] (It understands the output of man pages, ANSI escape codes and further, it
can use Pygments to highlight about any file.)Usage# Install it.pipinstallpypager# Tell the environment to use this pager. Put the following line in
# ~/.bashrc if you like.exportPAGER=pypager# Following commands, and many others should pick up the pager.manvimgitdiff# View a file, using this pager.pypagersome_source_code.pyAs a libraryfrompypager.sourceimportGeneratorSourcefrompypager.pagerimportPagerdefgenerate_a_lot_of_content():"""
    This is a function that generates content on the fly.
    It's called when the pager needs to display more content.

    This should yield prompt_toolkit `(style_string, text)` tuples.
    """counter=0whileTrue:yield[("",'line:%i\n'%counter)]counter+=1if__name__=='__main__':p=Pager()p.add_source(GeneratorSource(generate_a_lot_of_content())p.run()
Package: pypagination
USAGETo import:from pypagination import paginateCall the paginate function:paginate(150):{ 
    totalItems: 150,
    currentPage: 1,
    pageSize: 10,
    totalPages: 15,
    startPage: 1,
    endPage: 10,
    startIndex: 0,
    endIndex: 9,
    pages: [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ] 
}paginate(150, 7):
totalItems: 150, currentPage: 7, pageSize: 15{ 
    totalItems: 150,
    currentPage: 7,
    pageSize: 10,
    totalPages: 15,
    startPage: 2,
    endPage: 11,
    startIndex: 60,
    endIndex: 69,
    pages: [ 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 ] 
}paginate(150, 7, 15, 5)
totalItems: 150, currentPage: 7, pageSize: 15, maxPages: 5{ 
    totalItems: 150,
    currentPage: 7,
    pageSize: 15,
    totalPages: 10,
    startPage: 5,
    endPage: 9,
    startIndex: 90,
    endIndex: 104,
    pages: [ 5, 6, 7, 8, 9 ] 
}BRIEFThe paginate function accepts the following parameters:totalItems (required)- the total number of items to be pagedcurrentPage (optional)- the current active page, defaults to the first pagepageSize (optional)- the number of items per page, defaults to 10maxPages (optional)- the maximum number of page navigation links to display, defaults to 10The output of the paginate function is an object containing all the information needed to display the current page of items in the view and the page navigation links.
Package: pypago
DescriptionInter-comparison of model and gridded observations of the ocean is a challenge when they use different grids.
Interpolation from one grid to another brings eventual errors that may affect significantly large scale budgets of tracers (heat, salt, freshwater).The PyPAGO suite of programs offers the possibility to analyze gridded ocean data along physical sections with minimum interpolation.
For example, this allows to monitor the circulation across an observed array in various model outputs, whatever their spatial resolution or type of discretization (B- or C- grids).
When defining sections that enclose a specific volume, large scale budgets of tracers can be reconstructed and inter-compared among all kinds of gridded ocean data.DocumentationFull documentation is available inhttp://pypago.nicolasbarrier.fr/
Package: pypagseguro
API Pagseguro============Installation============If you have _setuptools_ you can use$ easy_install -U pypagseguroOtherwise, you can download the source from [GitHub][git] and run$ python setup.py install[git]: https://github.com/avelino/pypagseguro "pyPagSeguro"Examples========Some simple examples of what pyPagSeguro code looks like:# -*- coding: utf-8 -*-from pagseguropy import *carrinho = Pagseguro(email_cobranca='pagseguro@visie.com.br',tipo='CP')carrinho.item(id=1, descr='Um produto de exemplo', quant=5, valor=10)carrinho.item(id=2, descr='Outro produto de exemplo', quant=2, valor=100)print carrinho.mostra()
Package: pypai
PyPAIThis is a python tool for Open Platform for AI.Installationpip install pypaiDemoCreate and runsubmit.pyinyour project folderto generate the configuration:frompypaiimportPAI# Create a PAI clusterpai=PAI(username='xxx',passwd='xxx')# Generate the configurationpai.generate_config()Openpai_configuration.jsonand modify it，The path of code dir MUST follows '/$PAI_DEFAULT_FS_URI/.../$PAI_USER_NAME~$PAI_JOB_NAME'. The default path is $PAI_DEFAULT_FS_URI/Users/$PAI_USER_NAME/$PAI_USER_NAME~$PAI_JOB_NAME.Change and runsubmit.pyto submit your job:frompypaiimportPAI# Create a PAI clusterpai=PAI(username='xxx',passwd='xxx')# Submit jobpai.submit()All the code in your project folder will be uploaded and your job will be submitted to the PAI.APIclass PAI:
    @paremeters:
    username: (str) PAI username
    passwd: (str) PAI password
    url: (str) PAI master node IP
    worker: (int) thread number for uploading code

function generate_config:
    @paremeters:
    jobName='test'
    image='192.168.193.253:5000/pytorch'
    dataDir=''
    outputDir=''
    codeDir='$PAI_DEFAULT_FS_URI/Users/$PAI_USER_NAME/$PAI_USER_NAME~$PAI_JOB_NAME'
    gpuType=''

function submit:
    @paremeters:
    config_path='./pai_configuration.json'
    dir_path='./'            code path
    dest_dir='/Users/'       code root path in the hdfs
Package: pypair
PyPairPyPair is a statistical library to compute pairwise association between any two variables. In general, statistical variable types are viewed ascategoricalorcontinuous. Categorical variables have no inherit order to their values, while continuous variables do. This API hasover 130 association measuresimplemented for any combination of categorical and/or continuous variables.To install.pipinstallpypairAdditional links.DocumentationPyPiGitterHere's a short and sweet snippet for using the API against a dataframe that stores strictly binary data. The PandasDataFrame.corr()method no longer processes non-numeric fields!frompypair.associationimportbinary_binaryfrompypair.utilimportcorrjaccard=lambdaa,b:binary_binary(a,b,measure='jaccard')tanimoto=lambdaa,b:binary_binary(a,b,measure='tanimoto_i')df=get_a_pandas_binary_dataframe()jaccard_corr=corr(df,jaccard)tanimoto_corr=corr(df,tanimoto)print(jaccard_corr)print('-'*15)print(tanimoto_corr)Another way to get started with PyPair is to use theconveniencemethods whose names indicate the variable pair types.frompypair.associationimportbinary_binary,categorical_categorical,\binary_continuous,concordance,categorical_continuous,continuous_continuous,confusion,agreement# assume a and b are the appropriate iterables of values for 2 variablesjaccard=binary_binary(a,b,measure='jaccard')acc=confusion(a,b,measure='acc')phi=categorical_categorical(a,b,measure='phi')kappa=agreement(a,b,measure='cohen_k')biserial=binary_continuous(a,b,measure='biserial')tau=concordance(a,b,measure='kendall_tau')eta=categorical_continuous(a,b,measure='eta')pearson=continuous_continuous(a,b,measure='pearson')Software CopyrightCopyright 2020 One-Off Coder

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.Book CopyrightCopyright 2020 One-Off CoderThis work is licensed under aCreative Commons Attribution 4.0 International LicensebyOne-Off Coder.Art CopyrightCopyright 2020 Daytchia VangCitation@misc{oneoffcoder_pypair_2020,
title={PyPair, A Statistical API for Bivariate Association Measures},
url={https://github.com/oneoffcoder/py-pair},
author={Jee Vang},
year={2020},
month={Nov}}Sponsor, LovePatreonGitHub
Package: pypairs
PyPairs - A python scRNA-Seq classifierThis is a python-reimplementation of the Pairs algorithm as described by A. Scialdone et. al. (2015).
Original Paper available under:https://doi.org/10.1016/j.ymeth.2015.06.021A supervised maschine learning algorithm aiming to classify single cells based on their transcriptomic signal.
Initially created to predict cell cycle phase from scRNA-Seq data, this algorithm can be used for various applications.Build to be fully compatible withScanpy. For more details see thefull documentation.Getting StartedNote: Version 3 still under development.InstallationThis package is hosted at PyPi (https://pypi.org/project/pypairs/) and can be installed on any system running
Python3 via pip with:pip install pypairsAlternatively, pypairs can be installed usingConda(most easily obtained via theMiniconda Python distribution:conda install -c bioconda pypairsMinimal ExampleAssuming you have two scRNA count files (csv, columns = samples, rows = genes) and one annotation file (csv, no header,
two rows: “gene, class”) a minimal example would look like thisfrompypairsimportpairs,datasets# Load samples from the oscope scRNA-Seq dataset with known cell cycletraining_data=datasets.leng15(mode='sorted')# Run sandbag() to identify marker pairsmarker_pairs=pairs.sandbag(training_data,fraction=0.6)# Load samples from the oscope scRNA-Seq dataset without known cell cycletesting_data=datasets.leng15(mode='unsorted')# Run cyclone() score and predict cell cycle classesresult=pairs.cyclone(testing_data,marker_pairs)# Further downstream analysisprint(result)Core DependenciesNumpyNumbaPandasAnnDataAuthorsAntonio Scialdone-original algorithmRon Fechtner-implementation and extension in PythonLicenseThis project is licensed under the BSD 3-Clause License - see theLICENSEfile for details
Package: pypairtree
# pypairtree [![Build Status](https://travis-ci.org/unt-libraries/pypairtree.svg?branch=master)](https://travis-ci.org/unt-libraries/pypairtree)pypairtree is a Python implementation of Pairtree for storing objects
in a filesystem hierarchy that maps object identifiers to two character
directory paths (http://tools.ietf.org/html/draft-kunze-pairtree-01).## LicenseSee LICENSE.txt.## Acknowledgementspypairtree was developed at the UNT Libraries and has been worked on
by a number of developers over the years including[Kurt Nordstrom](https://github.com/kurtnordstrom)Brandon Fredericks[Mark Phillips](https://github.com/vphill)[Lauren Ko](https://github.com/ldko)[Joey Liechty](https://github.com/yeahdef)[Gio Gottardi](https://github.com/somexpert)If you have questions about the project feel free to contact Mark Phillips
atmark.phillips@unt.edu.## InstallationInstall with:`sh $ python setup.py install `## TestsUnit tests are provided. To run them via Tox, ensure you are in the
pypairtree directory with the tox.ini file and execute:`sh $ tox `
Package: pypal-api
PyPal-APIWhat is it?PyPal-API is a python package that includes helper functions that ease development of API's for the most popular API's (google ,shopify , etc) and tools such as FastAPI and Flask.
There aren't a lot of content at the moment but given time, it will hopfully grow into a huge project helping countless number of people!date_to_string: very simple function that with an input of a datetime object, it will return the date as a string!new_date: Input a number (positive or negative) to tell this function the amount of days before or after the current day, default returned value is a stringGetting StartedTo get started using this package, install from test pypi here:https://test.pypi.org/project/pypal-api/If you're really lazy you can use this PiP command to install it:$pipinstall-ihttps://test.pypi.org/simple/pypal-apidate_to_stringSimple function that you input a datetime and it will return it in the nice simple string format YYY-MM-DDcode to use:frompipal_apiimportdate_to_stringimportdatetimedate=datetime.datetime(2021,12,2)date_to_string(date)new_dateInput anumber(positive or negative) and it'll return (default:string. other options includedatetimeorstring/integerlist) the specifiedreturn_type.
The defaultfrom_dateusesdatetime.date.today()but can use astringdate (YYYY-MM-DD) or adatetimeand it will act accordingly.frompipal_apiimportnew_datenew_date(2)
Package: pypale
pypale(Py)thon (Pa)ssword(le)ss Tokens.pipinstallpypaleUsagefrompypaleimportPypaletoken_ttl_minutes=14*24*60# 2 weekstoken_issue_ttl_seconds=2*60*60# 2 hoursbase_url="mydomain.com"secret_key="loadthisfromyoursecretsmanager"pypale=Pypale(base_url=base_url,secret_key=secret_key,token_ttl_minutes=token_ttl_minutes,token_issue_ttl_seconds=token_issue_ttl_seconds)email="jane.doe@example.com"token=pypale.generate_token(email)assertpypale.valid_token(token,email)An example with SendGrid# send an email with a magic login link to "jane.doe@example.com"importsendgridfromsendgrid.helpers.mailimportContent,Email,Mail,Toemail="jane.doe@example.com"token=pypale.generate_token(email)link=f"https://mydomain.com/link_login/?code={token}"sg=sendgrid.SendGridAPIClient(api_key=your_sendgrid_api_key)from_email=Email("bob@mydomain.co")to_email=To(email)subject="Hello!"content=Content("text/html",f"Click this <a href={link}>link</a> to log in.")mail=Mail(from_email,to_email,subject,content)response=self.sg.client.mail.send.post(request_body=mail.get())print(response)# in your link_login route, mentioned in the link var above,# make sure to call pypale.validate_token with the token and# properly handle valid and invalid tokens.# for example ...deflink_login(code:str):ifnotpypale.valid_token(code):raiseException("Invalid login.")access_token=base64.b64decode(code).decode("utf8")return{"access_token":base64.b64decode(code).decode("utf8"),"token_type":"bearer"}Contributions & SuggestionsPull requestsandissuesare very welcome!
Package: pypam3
pypam3 - Project Assignment MethodPypam3 is a small tool to assign students(workers) to projects(jobs)
based on their rank of preference(cost) to each of the projects(jobs).moduleCurrently, there is only one module namedassignin this packageassignTwo functions,assign_project()andgenerate_sample(), realize
the facility.assign_project(csv_name, capacity, **kwargs)This function is for assigning. To use this function, you need to
put a .csv file on the same directory whose rows represent
students and columns represents projects. The numbers represent the rank of preference that students evaluate. No title should be included.
for example:5, 4, 2, 1, 3
4, 3, 2, 1, 5
3, 2, 1, 5, 4To convert an Excel file to .csv file, you can easily use Microsoft Excel and press File-Save File as-.csvThe name of the csv file is the first argument.The second argument is the number of students that a project can take at most.This function also take several optional key-word arguments:output: This argument has two options,"file"or"stdout". The "file" value will ask the program tooutput the result by creating a new fileresult.xlsx, the Sheet1 of the Excel file show the project that each student is assigned to, and the Sheet2 shows which students are assigned to each project.
The "stdout" option is the default option. It will directly output the result to the terminal.deviation: If set to True(default), the program will also output the standard deviation to the terminal. If set to False, it will not be calculated.time: If set to True(default), the program will also print the runtime of the function to the terminal. Otherwise, no.Example of using:frompypam3.assignimportassign_projectassign_project("data.csv",5,output="file")generate_sample(csv_name, student_num, project_num)This function can randomly generate samples, and it's mainly for testing purpose.Example of using:frompypam3.assignimportgenerate_samplegenerate_sample("data.csv",80,20)This will create a csv file named "data.csv" at the current directory with 80 rows and 20 columns.UsingFirst install python3 fromhttps://www.python.org. Note that the package should be added to PATH.
To download this package, type in the terminal:
linux/mac:pip3installpypam3
pip3installopenpyxl
pip3installmunkreswindows:pipinstallpypam3
pipinstallopenpyxl
pipinstallmunkresAnd add these lines at the beginning of your python script:frompypam3.assignimportgenerate_sample,assign_projectfrommunkresimportMunkresimportopenpyxlThen you can use this package as stated above.
Package: pypama
How to installpip install pypamaPresentationThis package provides a pattern matching for list of objects. Just as Regex provides regular expression for
strings, this package provides regular expression for other type of lists.An example is worth a thousand words: assume you have a list>>> example_list = ['a', 'a', 1, '', None, 'b', 'c',  'e']For some reason, you know that there is an int and a None, and you
want to extract that number and the 2 strings following the None>>> from pypama import build_pattern, is_int, is_none
>>> g = build_pattern((~is_int).star(False), '(', is_int, ')', '.*', is_none, '(',ANY,ANY, ')')
>>> g.match(example_list).groups()
[[1], ['b', 'c']]~is_intwill matching anything that’s not an integer.star(False): equivalent to*?in regular expressions: repeat as many as necessaryparenthesis are for capturing groups.*is short forANY.star()(match anything, repeatedly)Therefore the pattern above reads as follow: match anything that’s not an int, repeatedly,
until you find an int that you capture in group 1. Then match anything until you
find a None. That must be followed by two elements that you capture in group 2.This is therefore very similar to therepackage, but applied to a list and with
matching that goes beyond strings.Usagebuild_pattern(*args,**functions)where args is a list of strings orPatternobjects, and functions maps function names to executable.The args can be a string or a list of strings containing:<string>: will match the string inside <>callable unction: X will match if function(X) returns TrueX?: will be ignored or match XX*: will match if X matches repeatedly (greedy)X*?: will match if X matches repeatedly (non greedy)(X): will capture the X in a group(P<name>X): will capture X in a group named “name”X|Y: will match if X or Y matches\n: will match the nth group previously matched<r:X>: will match if the word matches regexp X<re:X>: same as<r:X><c:function>or<call:function>: will match if function(X) matches. If function does not exist in the namespace of pypama, add the definition in the function call egbuild_pattern('<c:foo>',foo=lambda x:x<2)will match [1].will match any item$will match if at the end of the listX{n}will match X exactly n times. n can be a list of integerX!: will match if the item doesn’t match X (X must match exactly 1 element)Both are equally valid and evaluate to the same result;build_pattern('<hello>','<world>','.*')build_pattern('<hello><world>.*')
Package: pypanda
PyPanda is a Python implementation of the PANDA algorithm using the Python Numpy library, which is optimized for matrix operations. Using matrix operations the Python implementation is significantly faster than the C implementation of PANDA. PyPanda is also capable of predicting single sample networks using the Lioness algorithm and returning indegrees and outdegrees for further analysis with GSEA for example. As PyPanda was build using the Numpy it is optimized for multicore processing using BLAS and LAPACK functions which significantly decreases run times compared to the C-code.
Package: pypandora
Python client and module for PandoraInstallationpipinstallpypandoraUsageCommand lineYou can use thepandoracommand to submit a file:$poetryrunpandora-h
usage:pandora[-h][--urlURL][--redis_up|-fFILE][--task_idTASK_ID][--seedSEED][--all_workers][--worker_nameWORKER_NAME][--details]Submitafile.

options:-h,--helpshowthishelpmessageandexit--urlURLURLoftheinstance(defaultstohttps://pandora.circl.lu/).--redis_upCheckifredisisup.-fFILE,--fileFILEPathtothefiletosubmit.

getStatus:--task_idTASK_IDTheidofthetaskyou'd like to get the status of--seed SEED           The seed of the task you'dliketogetthestatusof--all_workersTrueifyouwantthestatusofeveryworkers--worker_nameWORKER_NAMEThenameoftheworkeryouwanttogetthereportof--detailsTrueifyouwantthedetailsoftheworkersLibrarySeeAPI Reference
Package: py-pane
panepaneis a modern Python library for dataclasses and data conversion, aiming
for speed and expressiveness.panedraws heavy inspiration fromPydantic(among others), but its goals
are quite different. For example,panehas first-class conversion to and from
all JSON datatypes, not just mappings (and no 'root' hacks necessary).
In this sensepaneis a library for general data conversion & validation,
while Pydantic is a dataclass-first library. In addition,paneis stricter
than Pydantic in several cases. For instance,panewill not attempt to coerce3.14or"3"to an integer.paneis designed to be used to create complex declarative configuration languages
in formats like JSON, TOML, and YAML. This requires full support for complex, nested
types liket.Union[int, t.Tuple[int, str], list[int]]. It also requires
useful error messages:>>>pane.convert('fail',t.Union[int,t.Tuple[int,str],list[int]])Traceback(mostrecentcalllast):File"<stdin>",line1,in<module>File"pane/convert.py",line489,inconvertreturnfrom_data(data,ty)^^^^^^^^^^^^^^^^^^^File"pane/convert.py",line484,infrom_datareturnconverter.convert(val)^^^^^^^^^^^^^^^^^^^^^^File"pane/convert.py",line128,inconvertraiseConvertError(node)pane.convert.ConvertError:Expectedoneof:-anint-tupleoflength2-sequenceInsteadgot`fail`oftype`str`Featurespaneis a work in progress. The following is a roadmap of features:FeatureStateBasic type conversionsDoneNumeric array types (numpy)DoneSum & product type supportDoneTagged unionsPartial'Flattened' fieldsPlannedBasic dataclassesDoneDataclass helpersPartialGeneric & inherited dataclassesDoneParameter aliases & renamingDoneArbitrary validation logicDoneSchema import/exportNot planned
Package: pypanelx
PyPanelX ProjectThe goal for this project it's to write a full python panel cli with tools for what it's call "Data Hoarding" or backups if you think in another ways(?)Tools?Yes, tools or addons that you can write thanks to modular construction of PyPanelList of tools:iltools:Using the powerfullInstaloader Python Modulei write this for a better archiving of a instagram media.meditor:[Option 4] (Currently working only in windows): this is a monaco-editor and electron executable, whith save option(Ctrl or CMD + S)(send a POST Req to a flask server)serviceWorker:[Option 4]: will be a flask based server for handle DB, Files and other kind of things.Usage:Frompypi:pip install pypanelxBuild and install by yourself:git clone https://github.com/jamesphoenixcode/pypanelxl.git
cd pypanelx
pip install setuptool wheel
python setup.py sdist bdist_wheelInstallin yoursystem:pip install ./dist/pypanelx-1.0.3-py3-none-any.whlThen:instaloader -l userNameUsedToDownload
pypanelxFiles will be downloaded inside"pypanelMedia, pypanelFiles"in the directory where pypanel has been executed.thanks to coffee and weed i write the most base code in one sunday (03/26/2023)