Saravanan666/pypi-org huggingface dataset:
Package: demo-generacion-libreria
Demo construccion libreriaEn esta demo se va a explicar como generar una libreria instalable con el comandopip install.
Asi como comosubiriamoslalibreriagenerada a PyPI para que sea instalable desde el repositorio online.Esquema de la libreria:/saludos_y_despedidas_espanol
    __init__.py

    /despedidas
        __init__.py
        despedidas.py

    /saludos
        __init__.py
        saludos.py
        /preguntas_cortesia
            __init__.py
            cortesias.py
Package: demography
demographyThis package implements a simple mechanism for quickly loading demographic data based on post codes. This is currently only implemented for the UK. It is based on data made available by the UK's Office for National Statistics (ONS).The data was taken fromGeoportal.If you want to jump to seeing how this package can play withpandas,see below.The package comes with built-in caching, makes extensive use of hash maps (i.e. dictionaries), and should generally be pretty fast!As well as providing mappings toOAC11groups (demographic codes), you can also map to lower-level groups within these codes too. See below for examples.Hopefully it'll save you having to repeatedly find, load and transform ONS census data!Getting startedYou can installdemographywith:pipinstalldemographyThere's only really one main function in this package, and it works like this:importdemographydemography.get("SW1A 0AA",using="groups")You'll get something like:['Cosmopolitans', 'Aspiring and affluent', 'Highly-qualified quaternary workers']These are Classification for Output Areas (OAC)groups-- demographic groupings provided by ONS for specific regions. If a specific OAC group cannot be found from the full postcode, it will default to using the prefix value (i.e. area-level demographics). If this too does not return a value, it will return the value provided by thedefaultparameter.You can also get the group codes:demography.get("SW1A 0AA",using="oac")And you'd get:2D2If you want to access the mappings between OAC codes and the groups together, you can use:demography.groups("uk")To give:{'1A1': ['Rural residents', 'Farming communities', 'Rural workers and families'], '1A2': ['Rural residents', 'Farming communities', 'Established farming communities'] ...Finally, it can be useful to have these groups encoded with:demography.get("SW1A 0AA",using="encoded_groups")To give:[30, 55, 59]To retrieve the encodings for this, you can use:demography.encoded_groups("uk")ValidationAs an additional benefit, you can enable validation for postcodes with:demography.get("SW1A 0AA",using="encoded_groups",validate=True)Playing with pandasYou can usedemographyto encodepandas.DataFramecolumns pretty easily too:importpandasaspdimportdemographyasdmdf=pd.read_csv("my-dataset.csv")# get the encoded 'super group', 'group', 'sub group' set.data_gen=(dm.get(code,using="encoded_groups")forcodeindf["postcode"])# build a dataframedm_df=pd.DataFrame(data=data_gen,columns=["super_group","group","sub_group"])# horizontally concatenate the groups dataframe to your original frame.df=pd.concat([df,dm_df],axis=1)Or alternatively, if you only needoac11codes, you can use:df["demographic"]=df["postcode"].apply(lambda_:dm.get(_))Note that you'll need to use the name of your column forpostcode!
Package: demo-helpingai
demo-helpingaiHelpingAI most advance AI chatbotGetting Started:python -m pip install -U demo-helpingaiJoin myDiscord serverfor live chat, support, or if you have any issues with this package.Support this repository:🎉Join my Discord Server:Chat with me and others.Join here:Async:fromdemo_helpingaiimportChatBotbot=ChatBot()bot.query_chat()bot.close()
Package: demoji-noprint
Changelog0.3.0Feature: addfindall_list()andreplace_with_desc()functions. (See 7cea333.)Modernize setup config to usesetup.cfg. (See 8f141e7.)0.2.1Tox: formally add Python 3.8 tests.0.2.0Windows: use thecoloramapackage to support printing ANSI escape sequences on Windows;
this introduces colorama as a dependency.  (See cd343c1.)Setup: Fix a bug insetup.pythat would require dependencies to be installedprior toinstallation ofdemojiin order to find the__version__.
(See d5f429c.)Python 2 + Windows support: useio.open(..., encoding='utf-8')consistently insetup.py.
(See 1efec5d.)Distribution: use a universal wheel in PyPI release. (See 8636a32.)0.1.5Performance improvement: usere.escape()rather than failing to compile a small subset of codes.Remove an unused constant in__init__.py.
Package: demojipy
DiscordEmojiPy - DiscordEmoji API Wrapper for PythonDocumentationEnglishInstallationpip install demojipySearch:fromDEmojiPythonimportDEmojiDEmoji.attr()Available attributes:AttributeParametersReturnDescriptionsearch_by_id()emojiid: intdictFetch DiscordEmoji's Emoji by idsearch_by_name()name: strdictFetch DiscordEmoji's Emoji by namesearch_by_author()author: strlist[dict]Fetch DiscordEmoji's Emojis submitted by an usersearch_emojis()search: str, startswith: boollist[dict]Fetch emojis you want to search, specifying whether search will be by the beginning of the word (default) or not (by specifying False in the startswith parameter)stats()NonedictFetch DiscordEmoji's statspacks()Nonelist[dict]Fetch DiscordEmoji's emoji packsExamples:fromDEmojiPythonimportDEmoji# CodeDEmoji.search_by_id(1)# Response{'id':1,'title':'zombie','slug':'zombie','image':'https://discordemoji.com/assets/emoji/zombie.png',...}# CodeDEmoji.search_by_name('zombie')# must be case insensitive# Response:{'id':1,'title':'zombie','slug':'zombie','image':'https://discordemoji.com/assets/emoji/zombie.png',...}# CodeDEmoji.search_by_author('Kohai')# must be case insensitive# Response[{'title':'emoji','submitted_by':'Kohai'},{'title':'emojiTwo','submitted_by':'Kohai'}...]# CodeDEmoji.search_emojis('PR_',startswith=True)# Response[{'id':3830,'title':'PR_bug',...},...]# If not found, returns None# CodeDEmoji.stats()# Response:{"emoji":int,"users":int,"faves":int,"pending_approvals":int}# CodeDEmoji.packs()#Response:[{"id":2,"name":"Anime Pack  #1",...},...]More attributes are coming soon...If there is any grammar error call me at Discord: Alguem#1599ChangeLogv2.0.1Fix cache bugv2.0.0Add site urls in dictsChange aiohttp to requests again(because very bugs)Added parameter "startswith" in "search_emojis"(specifies whether search will be by the beginning of the word or not)Added Packs attributeAdded cache system, to avoid making too many requests for api.v2.0.0aChange requests to aiohttp(testing)Added Packs attribute(Testing)Future UpdatesAdd categories
Package: demo-lt.v0.1
douyin_image [![Version][version-badge]][version-link] ![MIT License][license-badge]Add douyin effect to imagedouyin_image是一个给图片添加抖音效果的库示例原图转换后的代码图片使用方式usage: douyin_image [-h] [--image IMAGEFILE] [--out OUTIMAGE]

optional arguments:
  -h, --help         show this help message and exit
  --image IMAGEFILE  path of image to add effect
  --out OUTIMAGE     path of output image安装$ pip install douyin_imageLicenseMIT
Package: demommath
demmomathA simple Python package for basic mathematical operations.Installationpipinstalldemommath

Tocallthefunctionsbyspecifyingtheirdirectory(Thesefunctionsareimportedinthe__init__.pyfilesoftherespectivedirectories):## Usage for adding numbers>>>fromdemommathimportaddsub
>>>addsub.add(2,8)10## Usage for subtracting numbers>>>fromdemommathimportaddsub
>>>addsub.subtract(3,5)-2## Usage for multiplying numbers>>>fromdemommathimportmultidiv
>>>multidiv.multiply(4,9)36## Usage for dividing numbers>>>fromdemommathimportmultidiv
>>>multidiv.divide(5,4)1.25## Usage for identifying odd and even numbers>>>fromdemommathimportodd_even
>>>odd_even.is_odd_or_even(6)'Even'##  Usage for finding LCM of 3 numbers>>>fromdemommathimportcalculations
>>>calculations.lcm(5,7,8)280##  Usage for finding mean of a list of numbers>>>fromdemommathimportcalculations
>>>calculations.find_mean([4,6,7,3,5])5.0## Usage for identifying prime numbers>>>fromdemommathimportprime_num
>>>prime_num.is_prime(5)True## Usage for adding arrays>>>fromdemommathimportsumarray
>>>sumarray.add_num([5,6,7],[4,3,2])array([9,9,9])Tocallthedefaultfunctions(Thesefunctionsareimportedinthe__init__.pyfileinthemaindirectory):## Usage for adding numbers>>>importdemommathasdm
>>>dm.add(5,6)11## Usage for subtracting numbers>>>importdemommathasdm
>>>dm.subtract(5,6)-1##  Usage for finding LCM of 3 numbers>>>importdemommathasdm
>>>dm.lcm(5,7,8)280##  Usage for finding mean of a list of numbers>>>importdemommathasdm
>>>dm.find_mean([4,6,7,3,5])5.0

Tocallthefunctionsdirectly(Thesefunctionsaredefinedinthe__all__listinthe__init__.pyfileofthemaindirectory):## Usage for adding numbers>>>fromdemommathimport*
>>>add(3,6)9##  Usage for finding LCM of 3 numbers>>>fromdemommathimport*
>>>lcm(5,7,8)280##  Usage for finding mean of a list of numbers>>>fromdemommathimport*
>>>find_mean([4,6,7,3,5])5.0
Package: demon
DEMON - Overlapping Community Discovery.Community discovery in complex networks is an interesting problem with a number of applications, especially in the knowledge extraction task in social and information networks. However, many large networks often lack a particular community organization at a global level. In these cases, traditional graph partitioning algorithms fail to let the latent knowledge embedded in modular structure emerge, because they impose a top-down global view of a network. We propose here a simple local-first approach to community discovery, able to unveil the modular organization of real complex networks. This is achieved by democratically letting each node vote for the communities it sees surrounding it in its limited view of the global system, i.e. its ego neighborhood, using a label propagation algorithm; finally, the local communities are merged into a global collection.Note:Demon has been integrated withinCDliba python package dedicated to community detection algorithms, check it out!CitationIf you use our algorithm please cite the following works:Coscia, Michele; Rossetti, Giulio; Giannotti, Fosca; Pedreschi, Dino"Uncovering Hierarchical and Overlapping Communities with a Local-First Approach"ACM Transactions on Knowledge Discovery from Data (TKDD), 9 (1), 2014.Coscia, Michele; Rossetti, Giulio; Giannotti, Fosca; Pedreschi, Dino"DEMON: a Local-First Discovery Method for Overlapping Communities"SIGKDD international conference on knowledge discovery and data mining, pp. 615-623, IEEE ACM, 2012, ISBN: 978-1-4503-1462-6.InstallationIn order to install the package just download (or clone) the current project and copy the demon folder in the root of your application.Alternatively use pip:pipinstalldemonor condacondainstall-cgiuliorossettidemonDemon is written in python and requires the following package to run:networkxtqdmImplementation detailsExecutionThe algorithm can be used as standalone program as well as integrated in python scripts.Standalonepythondemonfilenameepsilon-cmin_com_sizewhere:filename: edgelist filenameepsilon: merging threshold in [0,1]min_community_size: minimum size for communities (default 3 - optional)Demon results will be saved on a text file.Input file specsEdgelist format: tab separated edgelist (nodes represented with integer ids).Row example:node_id0    node_id1As python libraryDemon can be executed specifying as input:an edgelist fileimportdemonasddm=d.Demon(network_filename="filename.tsc",epsilon=0.25,min_community_size=3,file_output="communities.txt")dm.execute()anetworkxGraph objectimportnetworkxasnximportdemonasdg=nx.karate_club_graph()dm=d.Demon(graph=g,epsilon=0.25,min_community_size=3)coms=dm.execute()The parameterfile_output, if specified, allows to write on file the algorithm results.
Conversely, the communities will be returned to the main program as a list of node ids tuple, e.g.,[(0,1,2),(3,4),(5,6,7)]
Package: demon-connect
🌟 Demon Connect - WhatsApp API 🌟Overview•Features•Usage•Installation•Contributing•LicenseOverview 👹Welcome toDemon Connect - WhatsApp API, your powerful tool for unleashing the potential of WhatsApp in your applications. This API allows you to integrate WhatsApp messaging into your projects with ease.Unleash the demon within as you explore the capabilities of this WhatsApp API. Transform your digital experience with the magic ofDemon Connect.Features ✨📲WhatsApp Integration: Seamlessly integrate WhatsApp messaging into your applications.📩Message Sending: Send text messages, images, and videos programmatically.🚀Group Messaging: Engage with WhatsApp group chats via the API.🪄Customization: Customize and extend the API to suit your project's needs.Usage 📱InstallDemon Connect - WhatsApp APIin your Python project.Initialize the API and connect to WhatsApp Web.Send messages and media programmatically to your WhatsApp contacts.Explore advanced features and customization options.Installation 🧙‍♂️Install Demon Connect via pip:pipinstalldemon-connectInclude Demon Connect in your Python project:fromdemon.whatsapp_apiimportDemon# Initialize the APIwhatsapp_api=Demon()# Log in to WhatsApp Webwhatsapp_demon.login()# Send a messagemessage="heyy"contact="Grp"whatsapp_demon.send_message(contact,message)whatsapp_demon.delete_message(contact,message)# Send an image (provide the path to the image file)image_path=r"C:\Users\raman\Downloads\aatman.jpg"contact="Grp"whatsapp_demon.send_image(contact,image_path)# Send a video (provide the path to the video file)video_path="path/to/your/video.mp4"whatsapp_demon.send_video(contact,video_path)# tag all in groupgroup_name="Grp"whatsapp_demon.tag_all(group_name)@whatsapp_demon.eventdefon_message(chat):print(f"New message from{chat.name}:{chat.message}")@whatsapp_demon.eventdefon_ready():print("Demon is ready!")chat=whatsapp_demon.open("Anupam Maurya")chat.send("HI")Contributing 🌟Contributions are welcome! Feel free to open issues and pull requests to enhance the API's power.ContributorsLicense 📜This project is licensed under theWhatsApp API License. See theLICENSEfile for details.Unlock the potential of WhatsApp in your applications withDemon Connect - WhatsApp API!
Package: demono
demonoSimple and small Unix daemon library.License: MIT.FeaturesVery simpleInstallationFrom source:git clone git@gitlab.com:mezozoysky/demono.gitcd demonopython3 setup.py installRequirementsPython 3Note: Click 6.x required for running sample daemons only.LimitationsUnix onlyGetting HelpEmail me: <s.demyanovich@protonmail.com>Postissues to GitLab <http://gitlab.com/mezozoysky/demono/issues>
Package: demonoid-api
# demonoid-api[![Latest Version](https://pypip.in/version/demonoid-api/badge.svg)](https://pypi.python.org/pypi/demonoid-api/)
[![Documentation Status](https://readthedocs.org/projects/demonoid-api/badge/?version=latest)](https://readthedocs.org/projects/demonoid-api/?badge=latest)A [WIP] www.demonoid.pw REST API client.
Package: demo-orifice-calc
Demo Orifice CalculationA simple python package containing a single-function module which calculates the orifice diameter required to acheive a given flowrate in a pipe. The calculation itself is straightforward and serves as an example of how Python libraries could be used to manage verified and tested calculations rather than using uncontrolled and untrusted spreadsheets.InstallationYou can install this demo orifice calculation module from PyPI:pip install demo-orifice-calcHow to useThe module can be imported into any python 3.x environment such asJupyter. Or, using the Python interpreter:>>> from demo_orifice_calc import orifice_calc
>>> help(orifice_calc)As a working example if we want to find the orifice diameter required to give a 1.0 m headloss in a 300 mm diameter pipe at 100 L/s :>>> orifice_calc(0.1, 0.3, 1.0)
0.1892662941723228TrustA test suite can be created to gain confidence in the validity of the results of calculation functions like this. This demo library includes one such test which can be checked by looking for the "build | passing" icon near the top of the page on GitHub. The tests can be run manually by downloading the source repo and running:pytest
Package: demo-package
demo_packagePython Boilerplate contains all the boilerplate you need to create a Python package.Free software: MIT licenseDocumentation:https://demo-package.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-07-24)First release on PyPI.
Package: demo-package-041320pt
demo package 041320ptDemo package for classFree software: GNU General Public License v3Documentation:https://demo-package-041320pt.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-02-19)First release on PyPI.
Package: demo-pip-math
Your first Pip package in PythonThis repository is the companion post to my blog"Your first Pip package in Python"Usagefromdemo_pip_math.mathimportadd,subtract,multiplydeftest_add():assertadd(3,2)==5deftest_subtract():assertsubtract(3,2)==1deftest_multiply():assertmultiply(3,2)==6
Package: demoProfile
A package to generate profile picture from a given string and gives you the option to choose the background color of the image. It is a simple package that can be used in any python project. Eg: django, flask, etc.InstallationpipinstalldemoProfileUsagefromdemoProfileimportgenerateimg=generate("sheikh umaid")img.save("profile.png")To use a custom background colorfromdemoProfileimportgenerateimg=generate("sheikh umaid",'pink')img.save("profile.png")
Package: demo-project-ding
Python Poetry TutorialGetting StartedRun the following to install and launch the demo app usingPoetry:$gitclonehttps://github.com/hackersandslackers/python-poetry-tutorial.git
$cdpython-poetry-tutorial
$poetryshell
$poetryinstall
$poetryrunHackers and Slackerstutorials are free of charge. If you found this tutorial helpful, asmall donationwould be greatly appreciated to keep us in business. All proceeds go towards coffee, and all coffee goes towards more content.
Package: demopy
Une démo de packagingFIXME: provide a two paragraphs summary of this packageFull documentation and APIFIXME: Provide the URL of the documentation (@ readthedocs.org ?)Developer notesPlease use a virtualenv to maintain this package, but I should not need to say that.Grab the source from the SCM repository:$ python setup.py develop
$ easy_install demopy[test,devel]Run the tests:$ nosetestsBuild the Sphinx documentation:$ python setup.py build_sphinx
$ firefox build/sphinx/html/index.htmlLinksFIXME: Provide real linksProject home pagehttp://www.mystuff.com/projectSource codehttp://www.mystuff.com/sourceIssues trackerhttp://www.mystuff.com/issuesContributorsdemopyis a software provided by Mafa.Gilles lenfantChanges log1.0.0Package creation withbobtemplates.gillux[glenfant]
Package: demo-py
demo-pyCollecting tools I use to demo in one place.TodoAdd some real test cases for the puml ...Need to add examples of how to use them ...Can maybe make a blog post on this ...Tinker with platuml themes ...https://the-lum.github.io/puml-themes-gallery/#cerulean-outlineAdd more chartsAdd an interactive time barPersonal RemindersTo publish to pypi w/o an alpha version, push a commit withPublish To PYPIin its commit message.Referenceshttps://kapernikov.com/ipywidgets-with-matplotlib/https://stackoverflow.com/questions/20288711/post-install-script-with-python-setuptoolshttps://stackoverflow.com/questions/50842160/how-to-display-matplotlib-plots-in-a-jupyter-tab-widgethttps://matplotlib.org/gallery/api/barchart.htmlhttps://pandas.pydata.org/pandas-docs/stable/user_guide/style.htmlhttps://blog.emacsos.com/bootstrap-a-python-project.htmlhttps://plantuml.com/sitemap
Package: demort
demortevaluates demultiplexed fastq files by computing various metrics.DEPENDENCIESYou need to installpython 3.7and depencies. Check version by typing on:python3 --versionpython3 depencies :joblibbiopythonmatplotlibUSAGEdemortcheck fastq files into specified folder(s) then count number of reads for each fastq files for each folder and finally return a summarycsvtable and apdfboxplot picture.(process a list of folder as a strings)demort.py -d folder/folder1,folder/folder2,folder/folder3 \
 -t 8 \
 -p results.pdf \
 -o results.csv(process a list of folder into a file)demort.py -d example/folder_to_process.txt \
 -t 8 \
 -p results.pdf \
 -o results.csvCOMMAND-LINE ARGUMENTScomplete flag argumentshort flagDefault valueSummary--inputFolder-dNAa string of folderpath separated by coma,OR a file containing a list--threads-t1Number of available cores--output_pdf-pNApath of the file where to write apdfboxplot picture--output_csv-oNApath of the file where to write acsvtableINPUTfolder/
├── folder1
│   ├── fqfileA.fq.gz
│   ├── fqfileB.fq.gz
│   └── fqfileC.fq.gz
├── folder2
│   ├── fqfileD.fq.gz
│   └── fqfileE.fq.gz
└── folder3
    ├── fqfileF.fq.gz
    ├── fqfileG.fq.gz
    └── fqfileH.fq.gzOUTPUTSsummarycsvtable [foldername, filename, number of reads]pdfboxplot pictureSYSTEM REQUIREMENTSLinux (64-bit and 32-bit with slightly limited functionality) and macOS (OS X) are supported.
Package: demosaicnet
# Deep Joint Demosaicking and Denoising
SiGGRAPH Asia 2016Michaël Gharbigharbi@mit.eduGaurav Chaurasia Sylvain Paris Frédo DurandA minimal pytorch implementation of “Deep Joint Demosaicking and Denoising” [Gharbi2016]# InstallationFrom this repo:`shell python setup.py install `Using pip:`shell pip install demosaicnet `Then run the demo script with:`shell python scripts/demosaicnet_demo.py output `To train a dummy model on the demo dataset provided, run:`shell python scripts/train.py--datademosaicnet/data/dummy_dataset--checkpoint_dirckpt `To build and update the whee:`shell pip install wheel twine make distribution make upload_distribution `# FAQHow is noise handled? Where is the pretrained model?The noise-aware model is not implementation, see the earlier Caffe implementation for that <https://github.com/mgharbi/demosaicnet_caffe>How do I train this?The scriptscripts/train.pyis a good start to setup your training job, but I haven’t tested it yet, I recommend rolling your own.
Package: demo-same-package-one
OVERVIEWa experiment for verifying if two pypi packages can have the same {namespace} or notSTRUCTUREPACKAGESone : demo_same_package/one.pytwo : demo_same_package/two.pyTHIS PACKAGEoneEXPECTATIONPACKAGE INSTALLATIONpipinstalldemo-same-package-one
pipinstalldemo-same-package-twoEXPECTED RESULTSthe source code would bedemo_same_package/onetwo
Package: demo-same-package-two
OVERVIEWa experiment for verifying if two pypi packages can have the same {namespace} or notSTRUCTUREPACKAGESone : demo_same_package/one.pytwo : demo_same_package/two.pyTHIS PACKAGEtwoEXPECTATIONPACKAGE INSTALLATIONpipinstalldemo-same-package-one
pipinstalldemo-same-package-twoEXPECTED RESULTSthe source code would bedemo_same_package/onetwo