Saravanan666/pypi-org huggingface dataset:
Package: recharge
This library makes interacting with the Recharge API dead simple.InstallationpipinstallrechargeUsagefromrechargeimportRechargeAPIapi=RechargeAPI(access_token='XXXXX')response=api.Order.list({'status':'QUEUED','limit':'250'})fororderinresponse['orders']:print(order['id'])For more details on the content of the reponses, visit theofficial recharge API docs.Resources Availableapi.Address
api.Charge
api.Checkout
api.Customer
api.Order
api.SubscriptionMethods Availableapi.*.create
api.*.update
api.*.get
api.*.list

api.Address.apply_discount
api.Checkout.charge
api.Order.change_date
api.Order.delete
api.Subscription.cancel
api.Subscription.set_next_charge_date
Package: recharge-api
This library makes interacting with the Recharge API dead simple.Installationpipinstallrecharge-apiUsagefromrecharge-apiimportRechargeAPIapi=RechargeAPI(access_token='XXXXX')response=api.Order.list({'status':'QUEUED','limit':'250'})fororderinresponse['orders']:print(order['id'])For more details on the content of the reponses, visit theofficial recharge API docs.Resources Availableapi.Address
api.Charge
api.Checkout
api.Customer
api.Order
api.SubscriptionMethods Availableapi.*.create
api.*.update
api.*.get
api.*.list

api.Address.apply_discount
api.Checkout.charge
api.Order.change_date
api.Order.delete
api.Subscription.cancel
api.Subscription.set_next_charge_dateLicenseMIT. SeeLICENSEfor more details.
Package: rechat-eval
rechat-evalUtilities that help with:Data extractionAnnotation, review and evaluationVisualizationThese tools are very specific toRechat, and may
not generalize to other situations.InstallThe python library is located on this private repo on GitHubparlance-labs/rechat-evalpipinstallgit+https://github.com/parlance-labs/rechat-eval.gitDocsClone this repo and runcd _docs && python -m http.serverYou will see the site athttp://localhost:8000/. We aren’t hosting the
site on GitHub Pages because this site is private.Usage
Package: recheck
Re(quirements)CheckUsageUsage:recheck -r /path/to/requirements/fileYou may also provide an ignore file.  The default is$CWD/.recheckignore.  You can pass a different file by providing a-iflag:recheck -r /path/to/requirements/file -i /path/to/ignore/fileThe ignore file should list dependencies (one per line) you wish to ignore from the check.InstallationRun:pip install recheckLicenceMITAuthorsrecheckwas written byKevin J.Qiu.
Package: recho
Reddit EchoReposts Reddit posts from a target user to a specific slack channelHelper class to make working with Selenium recho waits easier and
more accessible(Optional) Create a virtual environmentIts useful to create a virtual environment for installing and running recho$sudopipinstallvirtualenv$cd~$virtualenv.venvrecho$source.venvrecho/bin/activateRegister Your AppRegister your app with Reddit, and jot down your Client ID and Secrethttps://ssl.reddit.com/prefs/appsClick “create another app” button at the bottomClick “script” radio buttonFill in the remaining boxes, the actual values don’t matterClick create, and record Client ID and SecretInstallationInstall from PyPI using pip:$pipinstall--updaterechoAdd the configuration file$touch~/.recho.iniWrite the following into that file, adding your Slack token and channel[praw]client_id:<RedditClientID>client_secret:<RedditClientSecret>[slack]# Follow instructions at https://my.slack.com/services/new/bottoken:<Yourslacktoken>channel:<yourchannelname>Note that the channel name is without the hash.generalinstead of#generalRunning RechoRecho is designed for use with cron. Simply add an entry similar to the one below:$sudovi/etc/crontabIf you use a virtual environment:*****usersource~/.venvrecho/bin/activate&&rechoacidtwistOtherwise you can simply call recho directly*****userrechoacidtwist
Package: rechtspraak-citations-extractor
Rechtspraak citationsThis library contains a function that aqcuires citation data for Rechtspraak cases using the LIDO.VersionPython 3.9ContributorsPiotr LewandowskishashankmcgijsvdHow to install?pip install rechtspraak_citations_extractorWhat are the functions?Rechtspraak Citations Extractorget_citationsGets all the data about case law citing/being cited and the legislations cited from the cases 
    in passed on DataFrame of case metadata. Requires a valid DataFrame object with a column titled 'ecli'. Returns the same Dataframe object,
     with 3 additional columns containing JSON strings of citation information.What are the parameters?get_citations(dataframe = None, username = '', password = '', threads = 2)Parameters:dataframe: Pandas DataFrame object, requiredA Dataframe object, which must have a column titled 'ecli'. 
        The code extracts citations for each separate ECLI in the column. 
        A Dataframe with Rechtspraak data can be aqcuired via the rechtspraak extractor - https://pypi.org/project/rechtspraak-extractorDefault: Noneusername: string, required, default ''The username that together with the password can be used to log into LIDO.password: string, required, default ''The password that together with the username can be used to log into LIDO.threads: int, optional, default 1Option for multi-threading of LiDO requests - not recommended to go above 2, as LiDO breaks connections when overwhelmed.Examplesimport rechtspraak_extractor as rex
import rechtspraak_citations_extractor as rex_citations
-----------------------------------------------------------------------------------------------------------------------

# To get the rechtspraak data in a dataframe:
df = rex.get_rechtspraak(max_ecli=100, sd='2022-08-01', save_file='y')  # Gets 100 ECLIs from 1st August 2022
df = get_rechtspraak_metadata(save_file='n',dataframe=df)
# To get the citations:
df_with_citaitons = rex_citations.get_citations(df,'username','password')LicensePreviously under theMIT License, as of 28/10/2022 this work is licensed under aApache License, Version 2.0.Apache License, Version 2.0

Copyright (c) 2022 Maastricht Law & Tech Lab

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.
Package: rechunker
RechunkerRechunkeris a Python package which enables efficient and scalable manipulation of the chunk structure of chunked array formats such asZarrandTileDB.Rechunkertakes an input array (or group of arrays) stored in a persistent storage device (such as a filesystem or a cloud storage bucket) and writes out an array (or group of arrays) with the same data, but different chunking scheme, to a new location.Rechunker is designed to be used within a parallel execution framework such asDask.Seethe documentationfor more.
Package: recinam
‘Nucleic Acid Memory Reciprocal Converter’ converts any file to a DNA sequence and vice versa.>>> This package is developed to convert any type of file into DNA sequence and reversely back to the first file.
As nucleic acids are more stable when they have a reach ‘G+C’ content, this code attempts to set G and C as the most frequent nucleotides in the DNA output. Hence, a key is generated to address the origin of each nucleotide and this key file is requisite for the “sequence_to_file (name, Format)” function.It contains two separate functions.>>> First one “file_to_sequence (name, Format)” gets two arguments. The name of your file and the format. For example (‘music’,’.mp3’) and it generates two files, one is the DNA sequence (.nuc) and the other is the key (key.nky).>>> The second function “sequence_to_file (name, Format)”  brings back the initial file. It gets two arguments, the name of the DNA file (.nuc) and the output format (for example ‘.mp3’).Thanks for reading.
Package: recipe
Legos for SQLRecipe is an MIT licensed cross-database querying library, written
in Python. It allows you to reuse SQL fragments to answer data questions
consistently. Extension classes allow you to support data anonymization,
automatic generation of where clauses, user permissioning to data, subselects,
and response formatting.Installationpip install recipeDocumentationhttps://recipe.readthedocs.io/DevelopmentTo run the all tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append tox
Package: recipebook
recipebookI'm writing a cookbook to learn Python, Postgresql, and other potential tools.PrerequisitesInstallpoetryfor managing virtual environment (similar tovenvorpipenv):```
curl -sSL https://raw.githubusercontent.com/sdispater/poetry/master/get-poetry.py | python3
```Read more aboutpoetry:https://python-poetry.org/Optional: I've installedpyenvto manage versions of Python on my system. Read more aboutpyenv:https://github.com/pyenv/pyenvBuildpoetry install
poetry run examplePackagepoetry buildDeploypoetry publish
Package: recipebox_pkg
recipebox_pkgA Python package designed for fetching information about recipes.Installation$pipinstallrecipebox_pkgFeaturesExplore Recipe Details:Access comprehensive information about recipes through user queries.Nutrition Insights:Retrieve detailed nutritional information tailored to specific dietary constraints.Ingredient Details:Discover essential details about ingredients required for a recipe.Visualize the Dish:View images showcasing the appearance of the prepared dish.Usage# Import the necessary function from recipebox_pkgfromrecipebox_pkgimport(fetch_recipe,id_search,ing_search,nutr_search)# Replace the empty string with actual API keyapi_key='your_actual_api_key'# Use the fetch_recipe.search_recipes function to search for recipes 
recipes = fetch_recipe.search_recipes(api_key, 'pizza')

# Convert the retrieved recipes into a Pandas DataFrame
recipes_retrieved = fetch_recipe.convert_recipes(api_key, recipes)# Define a list of ingredients you want to search for recipes
ingredients_list = ['beef', 'potato']

recipe_ingr = ing_search.ingredient_search_recipe(api_key, ingredients_list, number=5)

ingr_image = ing_search.display_images_ingredients(recipe_ingr)# Define nutritional constraints using a dictionary
nutr_constraints = {'minProtein':'20', 'maxFat':'50' }

nutr_recipe = nutr_search.nutrient_search_recipe(api_key, nutr_constraints)

nutr_image = nutr_search.display_images_nutrient(nutr_recipe)example_recipe_id = 123456
recipe = id_search.Recipe_id(pick_id, api_key)

# Retrieve information about the ingredients used in the recipe
ingredient_info = recipe.search_ingredient_id()

# Retrieve nutritional information for the recipe
nutr_info = recipe.search_nutrient_id()

# Retrieve information about the equipment required for the recipe
equipment_info = recipe.search_equipment_id()

# Retrieve raw instruction data for the recipe
raw_instruction = recipe.search_instruction_id()

# Convert the raw instruction data into a more usable format
instruction_info = recipe.convert_instruction(raw_instruction)# List of recipe IDs for which you want to search for taste information
example_id_list = [123456, 987654]

# Retrieve taste information for the specified recipe IDs
taste = recipe.search_taste_id(id_list)DependenciesThis package requires the following Python libraries:PandasRequestsTo install these libraries, run:pipinstallpandasrequestsContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licenserecipebox_pkgwas created by Yuchen An. It is licensed under the terms of the MIT license.Creditsrecipebox_pkgwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.LinksDocumentationRecipe-Food-Nutrition API DocumentationTestPyPI
Package: recipe-caching
Recipe_Caching is an MIT licensed caching extension for the recipe querying
library, written in Python. It caches SQL query results keyed by the SQL query.
By providing a custom oven and a recipe extension. Using it requires defining
adogpile.cachecache region, using the caching oven, and telling the recipe
to use the caching extension.Installationpip install recipe_cachingDocumentationhttps://recipe_caching.readthedocs.io/DevelopmentTo run the all tests run:py.test
Package: recipeGetter
# Recipe Collector
This library will try to scrape recipe websites and get the information of the recipe. This work on a majority of websites. Give an url to the scraper and get back an instance of theRecipe()class with all the information about the recipe (if it was found).## Usage
### Install the library` pip install recipeGetter `### Scrape the recipe`python recipe = RecipeScraper(url) infos = recipe.scrape() # Informations available for the recipe infos.name # The name of the recipe infos.author # The name of the author of the recipe infos.description # Description of the recipe infos.yeild # Number of yeild that the recipe give infos.category # The category of the recipe infos.ingredients # Ingredients used in the recipe infos.instructions # Instructions used in the recipe infos.prep_time # Preping time of the recipe infos.cook_time # Cooking time of the recipe infos.image # A link to an image of the recipe `Some informations may not be present if the scraper was not succesful to find it or if the information was not present on the website.## How it works
### Trivial case
A majority of popular recipe websites put data about the recipe in a<script type=”application/ld+json”>tag. They put it there because Google will improve the searching result if a website use this technique. The data is very easily pared and returned as aRecipeTrivial()instance.### Complex case
When a website is not putting it’s data in ascripttag, the library will search the arbitrary html for the informations. Not all the data is accessible with this technique and only the ingredients, instructions, name of the recipe, description and author will be searched.## License
[License](https://github.com/xavierhamel/recipeGetter/blob/main/LICENSE)
Package: recipemd
RecipeMDAstandard formatfor recipes asMarkdownfiles
and apython reference implementation. The reference
implementation can be used as aCLI programand as apython library.More info on our website:recipemd.orgLicenseThis program is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as
published by the Free Software Foundation, either version 3 of the
License, or any later version.This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.You should have received a copy of the GNU Lesser General Public License
along with this program. If not, seehttps://www.gnu.org/licenses/.
Package: recipe-md
Download a recipe to MarkdownSetupInstall Poetry:curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | pythonClone this repository:git clone https://gitlab.com/muchomuchacho/recipe-to-md.gitcd recipe-to-mdInstall thedownrecCLI tool:poetry installDetailsThe logic behind the way this works is somehow aligned to my personal workflow but it should be quite easy to adapt to others.It scrapes a recipe, converts it to markdown and saves the content to a.mdfile in your current working directory.Downloads the main image and places it in a folder of your choice relative to the location of the.mdfile.Do all that with one simple command:downrec 'Salmon With Courgette Ribbon & Feta Salad'(Or any other recipe of your choice)
Package: recipemd-extract
recipemd-extractrecipemd-extract extracts recipes from websites and saves them in therecipemdformat. It is based onrecipemd-cli.installationpip install recipemd-extractusagerecipemd-extract 'url-of-recipe'supported websiteschefkoch.deseriouseats.comAny Wordpress blog usingWP Recipe ManagerAny page supportingrecipe schemaAny page supported byrecipe-scrapers
Package: recipe-scrapers-sage
recipe-scrapers-sageThis is a helper package to save data acquired throughrecipe-scrapersin a format that is importable byRecipeSage(JSON-LD,implemented here).Installpipinstallrecipe-scrapers-sageUsageTo directly export a scraped recipe, use theexport_recipefunction:fromrecipe_scrapersimportscrape_mefromrecipe_scrapers_sageimportexport_recipescraper=scrape_me("<RECIPE URL>")sage_json:dict=export_recipe(scraper)# write `sage_json` to a file that RecipeSage can importIf you wish to modify a scraped recipe, use theRecipeSageclass:fromrecipe_scrapersimportscrape_mefromrecipe_scrapers_sageimportRecipeSagescraper=scrape_me("<RECIPE URL>")recipe_sage=RecipeSage.from_scraper(scraper)recipe_sage.creditText="<CREDIT TEXT>"sage_json:dict=recipe_sage.to_json_ld()# write `sage_json` to a file that RecipeSage can import
Package: recipe-searchers
recipe-searchersA simple web / api scraping tool for searching for recipe links, inspired by (and possibly for use with)recipe-scapers.To installpip install recipe-searchersTo usefromrecipe_searchersimportsearch_reciperesult=search_recipe("panna cotta")print(f"Found results:\n{result}")search_recipe()returns an object in the form of:@dataclassclassSearchResult:keyword:str# str = website, List = resultsresults:Dict[str,List[RecipeLink]]Where results is a pair of Website for every website it has found results and a list of results.Searchers available for:allrecipes.com- Through scrapingbbc.co.uk- Through scrapingbbcgoodfood.com- Through scrapingbonappetit.com- Through scrapingfood.com- Through REST APIthewoksoflife.com- Through scraping
Package: recipe-tagger
Recipe TaggerThis package provides a classification, a tagging system and a water footprint calculator for ingredients and recipes.The functioning of the package is based on a dataset containing more than 700 ingredients mapped with their own class and water footprint.
If a provided ingredient is not mapped into the dataset, the library search for it on wikipedia pages, into the dictionary and into NLTK Wordnet to find the best possible class.
The water footprint is computed based on its ingredients. Every ingredient has a water footprint, measured in l/kg.An ingredient could be classified in one of the following class:VegetableFruitLegumeMeatEggDiaryStapleCondimentNutSeafoodSnackMushroomDessertBeverageA recipe is tagged based on its ingredients class.
The library also provides a function to get the class percentage of recipe ingredients.Installationpip install recipe_taggerRecipe Tagger moduleHow to usefromrecipe_taggerimportrecipe_taggerGet the class of a single ingredientrecipe_tagger.get_ingredient_class('aubergine')# vegetableGet tags of a recipe (it is needed to provide all the ingredient of the recipe)recipe_tagger.get_recipe_tags(['aubergine','chicken'])# ['vegetable', 'meat']Get class percentage of a recipe (it is needed to provide all the ingredient of the recipe)recipe_tagger.get_recipe_class_percentage(['aubergine','chicken','beef'])# [('vegetable', '33.33%'), ('meat', '66.67%')]Recipe Water Footprint moduleHow to usefromrecipe_taggerimportrecipe_waterfootprintaswfGet the water footprint of a single ingredientwf.get_ingredient_waterfootprint("tomato",20,process=True,language="en")# 4.28Get the water footprint of a recipe (it is needed to prived all the ingredients and the quantity of the recipe)In order to provide a precise calculation of the WF, it is needed to provide also the quantity used for the ingredient in the recipe.
Quanities must be provided matching the following pattern: "{number}{unit}". Unit can be one of ml, gr, kg, l, ounce, teaspoon, tablespoon, cup, pint quart, gallon, pound, clove, lb, or their abbreviation.wf.get_recipe_waterfootprint(["tomato","apple","chicken"],["20gr","5ml","1l"],language="en")# 4329.28Get the water footprint of a recipe and informations about the ingredients water footprintwf.get_recipe_waterfootprint(["tomato","apple","chicken"],["20gr","5ml","1l"],language="en",information=True,)# (4329.28, {"tomato": 4.28, "apple": 0.0, "chicken": 4325.0})Language supportEvery method of the package provide the language support. Use the "language" parameter along with the abbreviation of a supported language.
Default language is English, if the "language" argument is not provided.English ("en")Italian ("it")TodoHandling of Wikipedia pages.Better search over dictionary and Wikipedia pages of ingredient.Calculate the water foorprint of a recipeAdd the possibility to add an ingredient after search if it is not present into the embedding.An explanation in order to provided an other language.A method for automatic translation when providing another language.
Package: recipies
🥧ReciPys🐍The ReciPys package is a preprocessing framework operating on Pandas dataframes.
The operation of this package is inspired by the R-packagerecipes.
This package allows the user to apply a number of extensible operations for imputation, feature generation/extraction,
scaling, and encoding.
It operates on modified Dataframe objects from the established data science package Pandas.InstallationYou can install ReciPys from pip using:pip install recipiesNote that the package is calledrecipiesand notrecipyson pip due to a name clash with an existing package.You can install ReciPys from source to ensure you have the latest version:conda env update -f environment.yml
conda activate recipys
pip install -e .Note that the last command installs the package calledrecipies.UsageTo define preprocessing operations, one has to supplyrolesto the different columns of the Dataframe.
This allows the user to create groups of columns which have a particular function.
Then, we provide several "steps" that can be applied to the datasets, among which: Historical accumulation,
Resampling the time resolution, A number of imputation methods, and a wrapper for anyScikit-learnpreprocessing step.
We believe to have covered any basic preprocessing needs for prepared datasets.
Any missing step can be added by following the step interface.📄PaperIf you use this code in your research, please cite the following publication:@article{vandewaterYetAnotherICUBenchmark2023,
	title = {Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML},
	shorttitle = {Yet Another ICU Benchmark},
	url = {http://arxiv.org/abs/2306.05109},
	language = {en},
	urldate = {2023-06-09},
	publisher = {arXiv},
	author = {van de Water, Robin and Schmidt, Hendrik and Elbers, Paul and Thoral, Patrick and Arnrich, Bert and Rockenschaub, Patrick},
	month = jun,
	year = {2023},
	note = {arXiv:2306.05109 [cs]},
	keywords = {Computer Science - Machine Learning},
}This paper can also be found on arxiv:https://arxiv.org/pdf/2306.05109.pdf
Package: recipipe
Improved pipelines for data science projects.Getting startedWhy Recipipe?It has cool features, like selecting columns using Unix patterns:or getting beautiful output column names instead of numeric indexed outputs:or fitting a different transformer per group:Read the tutorials and other examples to learn more.Install from PyPIpip install recipipeAll the dependencies will be installed automatically.Install from sourceClone the repository and run:pip install .Install the package in a dev environment with:pip install -e .All the dependencies will be installed automatically.Tutorials and examplesExplore a notebook with alist of things you can do with Recipipe.Learn how totransform Titanic data.Learn how to use Recipipe analyzing data from weird creatures from another
planet:Recipipe getting started tutorial.Running the testsRun all the test using:pytestRun an specific test file with:pytest tests/<filename>Run tests with coverage using:coverage run --source=recipipe -m pytestWhat's the meaning of Recipipe?It comes from a beautiful R library calledrecipesand the concept
ofpipelines.recipes + pipelines = recipipeThat explains the logo of a muffing (recipes) holding some pipes (pipelines).LicenseThis project is licensed under theMIT License, see theLICENSEfile for details.Authorguiferviz, contributions are more than welcome.