Saravanan666/pypi-org huggingface dataset:
Package: hybrid-crypto
Python Hybrid CryptoPython module which exposes a simple hybrid cryptography abstraction on
top of KeyCzar and pycrypto.NoteThis module has NOT been extensively tested or audited so general usage is
strongly discouraged at this point.How it worksKey encapsulation schemeKey encapsulation scheme uses RSA-OAEP public-key cryptography with 2048 bit
key.This functionality heavily relies on public-key cryptography functionality
exposed by KeyCzar.Data encapsulation schemeData encapsulation scheme uses AES in CBC mode with 256 bit key.This release on primitives and functionality provided by pycrypto.Example UsageTBW.Questions and AnswersWhy do I need this, can’t I just use keyczar directly?KeyCzar exposes a higher level, safe and easy to use interface for handling
both, asymmetric and symmetric encryption, but it doesn’t provide a higher
level interface for handlinghybrid cryptography(well, that’s not 100%
accurate, because there is some support, but it’s experimental and only
available in Java).Changelog
Package: hybrid-django-react
Starter project template🤠⚛️ Dockerized hybrid Django React appStarter project template using Docker to build a Django app that serves React apps statically (as JavaScript files)Tech stackDjango (with Rest framework, PostgreSQL, SMTP gmail backend, whitenoise, etc.)React (bundled with webpack and transpiled with babel)DockerDeployment to HerokuPrerequisitesDockerpip, poetry, pyenv or a similar tool to accesspypiInstallationInstall with the following commandpip install hybrid-django-reactUsageRun the scripts with the following command:create-django-react-appYou will be prompted for some information like project name, email, etc. This data is needed to change the configuration files accordinglyAfter the script has run, you don't need this tool anymore 😀Simply start the docker container to start working:docker-compose up -dYou can then work as usual on your Django project.The entry point of the React render can be edited from the filefrontend/index.jsDebugging with Docker and VSCodeSupport for debugging remotely with VSCode is supported out-of-the-box.To debug with Docker:Run your Docker containers as usual:docker-compose up -d --buildStart the debug session from VS Code for the[django:docker] runserverconfiguration (either from the Debugger menu or withF5)Logs will redirect to your integrated terminal as well.Set some breakpoints in functions or methods executed when needed. Usually it's Model methods or View functionsAdding external librariesIt's better to install external libraries from from Docker directlyPython libraries:Production librariesdocker-compose exec web poetry add [pip_package]Development librariesdocker-compose exec web poetry add [pip_package] --devJavaScript libraries:Production librariesdocker-compose exec web npm install [npm_package]Development librariesdocker-compose exec web npm install -D [npm_package]Deploy to HerokuFirst setupCreate an accountandinstall Heroku CLICreate a new app on Herokuheroku createYour app will get a randomly generated name, likelazy-beyond-52146. Let's call this name[APP_NAME]Add environment variables that Django needs to read:DJANGO_ENVIRONMENT:heroku config:set DJANGO_ENVIRONMENT=productionDJANGO_SECRET_KEY:
You can create a safe secret keyusing this siteheroku config:set DJANGO_SECRET_KEY=[secret_key]DJANGO_DEBUG:heroku config:set DJANGO_DEBUG=FalseSet the stack to Docker containers using the app's nameheroku stack:setcontainer -a [APP_NAME]Create a managed postgresql database on Herokuheroku addons:create heroku-postgresql:hobby-dev -a [APP_NAME]Create a heroku remote repository and push changes to itheroku git:remote -a [APP_NAME]
git push heroku mainMigrate Database and create superuserheroku run python manage.py migrate
heroku run python manage.py createsuperuserAfter deployment, check that the site'ssecurity audit shows no warningsConsecutive deployments to productionDeploy by pushing to Heroku git repository:git push heroku main
Package: hybridizer
This Python package (hybridizer) creates a class named Hybridizer to
communcate with and control the Janelia Hybridizer. The hybridizer
uses two hardware control devices, the mixed_signal_controller
modular_device, and the bioshake_device. The
mixed_signal_controller both switches the valves and reads the
analog signals from the cylinder hall effect sensors. The
bioshake_device controls the heater/shaker.Authors:Peter Polidoro <polidorop@janelia.hhmi.org>License:BSDExample Usage:from hybridizer import Hybridizer
hyb = Hybridizer('example_calibration.yaml','example_config.yaml')
hyb.run_protocol()
Package: hybridJaccard
# hybrid-jaccardImplementation of hybrid jaccard similarityPackage files:||-> __init__.py||-> hybrid_jaccard.py: contains the base class for hybrid jaccard string matching||-> jaro.py & typo_tables.py: contain the methods for jaro distance calculation||-> munkres.py: contains the hungarian matching algorithm||-> eye_config.txt: contains the configuration info for the hybrid-jaccard class||-> eye_reference.txt: contains the reference eye colors||-> input.txt: a sample input file for testing the program||-> README.md||-> LICENSEUsage:You should import "HybridJaccard" in your code. The main class is HybridJaccard.The class constructor gets two arguments, path to reference and config files respectively.The "findBestMatch" method returns the best match for the input string among those in thereference file if one exists, and returns "NONE" otherwise. A sample usage might be like:sm = HybridJaccard()match = sm.findBestMatch("beautiful light bluish eyes")about eye_config.txt:-- it has a field "type" which is for now always "hybrid_jaccard"-- it has a field "partial_method" which can be "jaro" or "levenshtein"-- it has a field "threshold" which determines how picky we want to be in hybrid jaccard algorithm before doing the matching
Package: hybridmethods
hybridmethodsA library for the creation of hybrid methods. Methods that can be called as either class methods or instance methods.Usagefromhybridmethodsimportcl,hybridmethod,instanceclassTest1:@hybridmethoddefmethod(this):ifinstance(this):# Run when called as instance methodpasselse:# Run when called as class methodpassclassTest2:@cl.assmethoddefmethod(cls):pass@method.instancedef_(self):pass
Package: hybrid-pool-executor
HybridPoolExecutorHybridPoolExecutor is a parallel executor that supports thead, process and async three operating models at the same time.Example:importasyncioimporttimeimportrandomfromhybrid_pool_executorimportHybridPoolExecutordefsolve(v:int)->int:print(f"You give worker a value{v}")time.sleep(random.randint(1,4))print(f"The square of value{v}is{v*v}")returnvasyncdefsolve_async(v:int)->int:print(f"You give async worker a value{v}")awaitasyncio.sleep(random.randint(1,4))print(f"The square of value{v}is{v*v}")returnvasyncdefmain():pool=HybridPoolExecutor()# run in a threadfuture0=pool.submit(solve,0)# run in a process by setting "_mode" to "process"future1=pool.submit(solve,1,_mode="process")# or you can use a more precise approach: submit_taskfuture2=pool.submit_task(solve,kwargs={"v":2},mode="process")# run in an async workerfuture3=pool.submit(solve_async,3)# run as a coroutine# you can also submit a coroutinefuture4=pool.submit(solve_async(4))# async function/coroutine can be executed in thread/process too# run coroutine in a threadfuture5=pool.submit(solve_async(5),_mode="thread")# or in a processfuture6=pool.submit(solve_async,6,_mode="process")# all futures can be get either synchronously or asynchronouslyawaitfuture0# result from a thread workerawaitfuture1# result from a process workerfuture2.result()# result from a async worker# ......if__name__=="__main__":asyncio.run(main())
Package: hybrid-recommender
Hybrid RecommenderThis package usage multiple algorithms and parameters to accomodate different set of use cases.Parameters:item_clusters: int
The number of clusters for item matrix generation. This parameter can be tunedtop_results: int
Number of recommendations needed. Default value is 10ratings_weightage: int
Weightage for user ratings score. Default is 1content_weightage: int
Weightage for content score. Default is 1null_rating_replace: str
Value to be used as replacement for missing ratings. Default is 'mean', other acceptable values are 'zero','one', and 'min'Returns:DataFrame having top recommended results for the list of usersApproach:Create an instance of the hybrid recommender class
mr = hybrid_recommender()Call fit method on the defined object by passing on ratings and content data
mr.fit(ratings_df,content_df)Call the predict method
recommended_df = mr.predict()ExampleCreate Ratings DataFrameitem_id=[1,7,9,10,12,2,4,6,8,10,12,3,6,9,12,14,10,13,12,14,11,2,5,7,8,9,10,12]user_id=[1,1,1,1,1,2,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4,5,5,5,5,5,5,5]rating=[4,5,2,3,5,2,3,2,3,4,4,5,1,2,3,1,2,4,5,3,5,3,1,3,5,3,5,3]ratings=pd.DataFrame({'user_id':user_id,'item_id':item_id,'rating':rating})Create Content DataFrameitems=[1,2,3,4,5,6,7,8,9,10,11,12,13,14]cols=['col1','col2','col3','col4','col5']feats=[[1,0,0,1,1],[1,1,0,0,1],[0,1,1,0,0],[0,1,1,1,0],[1,0,1,1,1],[1,1,1,0,0],[0,1,0,1,0],[0,0,0,1,0],[0,1,1,0,0],[1,1,1,0,1],[0,0,0,1,1],[0,1,0,1,0],[0,1,1,0,1],[0,0,1,1,1],]item_df=pd.DataFrame(feats,index=items,columns=cols)Ratings DataFrameratings.head()Content DataFrameitem_df.head()Fitting and predictionCreating the recommender objectmy_recommender=hybrid_recommenders(item_clusters=4,top_results=5)Fitting the datamy_recommender.fit(ratings,item_df)Recommend for few usersmy_recommender.predict([1,2,3])Recommendations for All usersmy_recommender.predict()
Package: hybrid-rsa-aes
hybrid-rsa-aeshybrid-rsa-aesis a helper for hybrid AES-RSA encryption.Installationhybrid-rsa-aes is available on PyPI.
Use pip to install:$ pip install hybrid-rsa-aesBasic Usagefromcryptography.hazmat.backendsimportdefault_backendfromcryptography.hazmat.primitives.asymmetricimportrsafromhybrid_rsa_aesimportHybridCipherrsa_private_key=rsa.generate_private_key(public_exponent=65537,key_size=2048,backend=default_backend())rsa_public_key=rsa_private_key.public_key()encrypt_message=HybridCipher().encrypt(rsa_public_key=rsa_public_key,data={"test":"demo"})decrypt_message=HybridCipher().decrypt(rsa_private_key=rsa_private_key,cipher_text=encrypt_message)assert"test"indecrypt_messageanddecrypt_message["test"]=="demo"Licensehybrid-rsa-aes is developed and distributed under the Apache 2.0 license.Reporting a Security VulnerabilitySee oursecurity policy.
Package: hybrid-search
hybrid search instructionsCreated following this articlehttps://opensearch.org/blog/hybrid-search/Installation:With conda or micromamba setup the environment:micromamba create -f environment.yaml
micromamba activate hybrid_searchFor the OpenSearch itself there are several installation options.From docker-composeThis repository goes with a test two nodes open-search cluster together with a dashboard.Optional: change OPENSEARCH_JAVA_OPTS=-Xms2512m -Xmx2512m according to your RAM availability, usually it is recommended to have them equal in side.
Start docker-compose:dockercomposeupOpenhttp://localhost:5601/to explore the dashboard, "admin" is used both as user and passport by default.Manual installationGo tohttps://opensearch.org/downloads.htmland download OpenSearch choose the installation variant you like. OpenSearch Dashboards is a convenient tool but not mandatory.Install the latest JavaFor Windows unpack the archive. In opensearch_folder/config/opensearch.yml make sure plugins.security.ssl.http.enabled: true. Because it works correctly only with ssl on, despite some functionality still being available with http. Launch opensearch-windows-install.bat, despite the name it is not an installer but a main launcher.For Linux use docker or follow instructions in the documentation.Usage:Launch open-search either with docker-compose or javaLaunch index.py for the initial indexing test dataset. It creates an index and pipeline for hybrid search.Activate environmentmicromambaactivatehybrid_search#to activate environmentpipinstall-e.#[optional] install current package locallyLaunch search to perform test search.pythonindex.py#to indexpythonsearch.py# to search, uses default queryYou can also tune index.py parameters. For example:python index.py main --url https://agingkills.eu:9200 --user admin --password admin --index_name index-bge-test_rsids_10k --embedding BAAI/bge-base-en-v1.5If you want to use another embedding, for example specter2, try:pythonindex.pyspecter2TestsRSID testThere are text pieces deliberately incorporated into tacutu papers data ( /data/tacutopapers_test_rsids_10k )
In particular for rs123456789 and rs123456788 as well as similar but misspelled rsids are added to the documents:10.txt contains both two times11.txt contains both one time12.txt and 13 contain only one rsid20.txt contains both wrong rsids two times21.txt contains both wrong rsids one time22.txt and 23 contain only one wrong rsidYou can test them by:python search.py test_rsidsComics superheroes testAlso, similar test for "Comics superheroes" that will test embeddings:Only 114 document has text about superheroes, but text did not contain words 'comics' or 'superheroes'You can test them by:python search.py test_heroesRight now testing is not automated and you have to call CLI to testTroubleshootingIf something is not working with OpenSearch, read log messages carefully. For example, if you have small disk space it can block writing (watermark issue) that will cause failing with different final error message.
Package: hybridset
Hybrid SetHybridSetis aMutableSetthat stores apart hashable and unashable values.It's fully compatible with the builtinssetandfrozenset>>>fromhybridsetimportHybridSet>>>hs=HybridSet([3,'thing',[True],{3,4},{1:'one',2:'two'}])>>>s={3,4,5}>>>s|hsHybridSet(hashables={3,4,5,'thing'},unhashables=[[Ture],{3,4},{1:'one',2:'two'}])>>>s&hsHybridSet(hashables={3})Know IssuesDon't passHybridSetinstances to explicit methods of builtins, it may cause aTypeErrorbecause of the unhashable values present in theHybridSet.>>>hs=HybridSet([[6],[7]])>>>s.union(hs)Traceback(mostrecentcalllast):...TypeError:unhashabletype:'list'>>>s.isdisjoint(hs)Traceback(mostrecentcalllast):...TypeError:unhashabletype:'list'Always use operators instead.Forisdisjoint(), test the emptiness of the intersection:>>>ifnots&hs:...print('disjoint')...else:...print('not disjoint')disjointFor more information, see the class and methods docstrings.
Package: hybrid-type-system
The Hybrid Type SystemRow + Implicit arguments + MLF(WIP).Notes about System FBefore implementing MLF:choose: forall a. a -> a -> a
auto  : forall a. a -> a
(choose auto) : (forall a. a —> a) -> (forall a. a -> a)


// if auto is defined without annotations, polymorphisms of lambdas get lost
auto2 : a -> a
(choose auto) : (a -> a) -> (a -> a)Notes about System F-OmegaKind checker is not implemented.Usagefromhybridts.tc_stateimportTCStatefromhybridts.type_encodingimportrow_of_map,record_of_row,poly_row,empty_rowtctx={}tcs=TCState(tctx)x1=tcs.new_var()x2=tcs.new_var()int_t=tcs.mk_new_type("base.int")# nominal typetcs.unify(x1,int_t)tcs.unify(x1,x2)asserttcs.infer(x1)==int_tasserttcs.infer(x2)==int_tx3=tcs.new_var()r1=row_of_map({'a':x1,'b':x3},empty_row)r1=record_of_row(r1)tho=tcs.new_var()r2=row_of_map({'a':x3},poly_row(tho))r2=record_of_row(r2)tcs.unify(r1,r2)print(tcs.infer(r1))print(tcs.infer(r2))# (RecordT, (RowConsT, 'b', (NomT, 'base.int'), (RowConsT, 'a', (NomT, 'base.int'), (RowMonoT,))))# (RecordT, (RowConsT, 'a', (NomT, 'base.int'), (RowPolyT, (RecordT, (RowConsT, 'b', (NomT, 'base.int'), (RowMonoT,)
Package: hybrid-vector-model
A Hybrid Gravity and Route Choice Model to Assess Vector Traffic in Large-Scale SystemsThis package provides an implementation of the hybrid gravity and route choice
model introduced byFischer et al. (2019). If you use this package
in research that leads to a scientific publication, we kindly ask you to
cite the publication.The package is licensed under theLGPL-v3. For documentation please refer tothe project's documentation page on github. Please report any bugs onthe project's bug tracker. You are welcome to adjust the provided
files to your needs and to improve the code. It is encouraged that you share any
improvements onthe github pageif possible.
Package: hybrid-vocal-classifier
hybrid-vocal-classifiera Python machine learning library for animal vocalizations and bioacousticsGetting StartedYou can install with pip:$ pip install hybrid-vocal-classifierFor more detail, please see:https://hybrid-vocal-classifier.readthedocs.io/en/latest/install.html#installTo learn how to usehybrid-vocal-classifier, please see the documentation at:http://hybrid-vocal-classifier.readthedocs.ioYou can find a tutorial here:https://hybrid-vocal-classifier.readthedocs.io/en/latest/tutorial.htmlA more interactive tutorial in Jupyter notebooks is here:https://github.com/NickleDave/hybrid-vocal-classifier-tutorialProject Informationthehybrid-vocal-classifierlibrary (hvcfor short)
makes it easier for researchers studying
animal vocalizations and bioacoustics
to apply machine learning algorithms to their data.
The focus on automating the sort of annotationsoften used by researchers studyingvocal learningsetshvcapart from more general software tools for bioacoustics.In addition to automating annotation of data,hvcaims to make it easy for you to compare different models people have proposed,
using the data you have in your lab,
so you can see for yourself which one works best for your needs.
A related goal is to help you figure out
just how much data you have to label to get "good enough" accuracy for your analyses.You can think ofhvcas a high-level wrapper around
thescikit-learnlibrary,
plus built-in functionality for working with annotated animal sounds.SupportIf you are having issues, please let us know.Issue Tracker:https://github.com/NickleDave/hybrid-vocal-classifier/issuesContributeIssue Tracker:https://github.com/NickleDave/hybrid-vocal-classifier/issuesSource Code:https://github.com/NickleDave/hybrid-vocal-classifierCHANGELOGYou can see project history and work in progress in theCHANGELOGLicenseThe project is licensed under theBSD license.CitationIf you use this library, please cite its DOI:Backstoryhvcwas originally developed inthe Sober labas a tool to automate annotation of birdsong (as shown in the picture above).
It grew out of a submission to theSciPy 2016 conferenceand later developed into a library,
as presented in this talk:https://youtu.be/BwNeVNou9-s
Package: hybridvut
hybridvutThis package provides functionalities to deal with hybrid IO-LCA based on the Make and Use framework.Key features are:hybridization of a foreground and a background systemunit handling usingiam_units(pintunits)functions for data handling (e.g. region aggregation, RAS)basic IO calculations (e.g. transaction and multiplier matrices)preprocessing to bring raw data into the right format (i.e. message-ix data)Additional hybridization procedures might be implemented in future work. Furthermore, functions can be also applied just to a single system.Installationhybridvut is registered at PyPI. You can install it in your pathon environmnet by:pipinstallhybridvutThe source-code is available as aGitLab repository.
You can also fork and install it.DocumentationYou can find a more detailed documentationhere.
Package: hyccup
HyccupHyccup is a port ofHiccupforHy, a Lisp embed in Python.It allows you to represent HTML into data structure and to dump it.=>(importhyccup[html])=>(html["div"{"class""my-class""id""my-id"}"Hello Hyccup"])"<div class=\"my-class\" id=\"my-id\">Hello Hyccup</div>"Hyccup can also be used in Python:>>>fromhyccupimporthtml>>>html(['div',{'class':'my-class','id':'my-id'},'Hello Hyccup'])'<div class="my-class" id="my-id">Hello Hyccup</div>'More information in thedocumentation.
Package: hychan48-google-foobar-2023-q4
google-foobar-2023-q4ProductionInstallation# https://replit.com/@jasonchan51/hychan48-google-foobar-2023-q4pipxinstallhychan48-google-foobar-2023-q4

hychan48-cake-is-not-a-lie--help
hychan48-cake-is-not-a-lieabab
hychan48-dont-get-volunteered01Level 1readme_q1_the-cake-isnot-a-lie.mdhychan48-cake-is-not-a-lieabab# GitHub action runs the PyTests:pytestlevels/q1/tests/solutions_test.py# JavaScript solutionpnpmruntest:q1level 2Question 1readme_q2_dont-get-volunteered.mdSimplified Knight's Tour problemTextbook BFS, but I wanted to animate itBFS WikiKnight's Tour GameExperimented with ILP. Good example to teach withhychan48-dont-get-volunteered01# Returns 3pytest./levels/q2/tests/solutions_bfs_test.pyBackgroundhttps://github.com/hychan48/google-foobar-2023-q4I searched proxy vs load balancer. and at first I found it mad sketchhad to verify it's SSL/TLS cert and Google was foobar was.AssumptionsSo far it looks like it's either Python 2.7 or Java 8I'm going to use Python 3.11.6, using basic syntax it should be backwards compatible with 2.7Also, I have PyCharm installed alreadyTDD with PyTestQuick ChecklistDocumentationSave Original Question/api/v1/files/ (.json)convert to .yaml and .htmlReword Question and Keywordsreadme_q.template.mdPrinciplesTDDQuick and dirtyUnless the question piques my research interest7 days per question seems like a lot of timePrioritiesJSDoc @typedef but for PythonMetadataAuthorGitHub RepoEnvironmentTime / Space Complexity (if applicable)Validation / Error handlingTest cases / Unit TestsWorkflow with GitHub actionsLint - Flake8Unit Tests - PyTestdev setup# there's also some helperscondaactivate./venv# newer method# pull# bats installs differently? weird# mostly for batsgitpull--recurse-submodule## bats clones to test/ by default## first time# pipx / conda(mamba) / poetrygitsubmoduleaddhttps://github.com/bats-core/bats-core.gittest/bats
gitsubmoduleaddhttps://github.com/bats-core/bats-assert.gittest/test_helper/bats-assert
gitsubmoduleaddhttps://github.com/bats-core/bats-support.gittest/test_helper/bats-support
gitcommit-m'Add bats-support library'treetest/bats/bin
mkdir-p~/.local/bin
rm~/.local/bin/bats
ln-s$PWD/test/bats/bin/bats~/.local/bin/batsln-s$PWD/test/bats/bin/bats/usr/local/bin/bats
ln-s./test/bats/bin/bats/usr/local/bin/bats
ls-l/usr/local/bin/bats
batsexportPATH=$PATH:~/.local/bin# git submodule add https://github.com/ztombol/bats-support test/test_helper/bats-support# cygwin / windows 11pnpmi# haha didnt work:condacreate-nfoobar-py27python=2.7condacreate-ngoogle-foorbar-2023-q4python=3.11condaactivategoogle-foorbar-2023-q4# update pipxpipx--versionpython-mpipinstall--userpipxpython-mpipxensurepath# poetry... too basic to need it... todo: move to other section# might not be needed after all...pipxinstallpoetrypoetry--versionpoetryinit# poetry might not be needed after all...poetryaddpytest--groupdev#poetry shell# 3.11.4 vs 3.11.6... interestingInstall pytestcondaactivategoogle-foorbar-2023-q4
python-mpipinstallpytest

python-mpipinstall-rrequirements.txtAppendix/api/v1/files/
Package: hycli
HycliThis repository contains a Python package/CLI tool to batch extract documents through the Hypatos API and to compare the results.Quickstartpip install hycli
hycli extract path-to-files [to-xlsx|to-csv|to-json] url
hycli compare workbook1 workbook2
hycli evaluate -gt ground-truth-workbook -m1 model1-workbook -m2 model2-workbookFor more information without leaving the cli usehycli --helpAPI Reference and User GuideavailableDevelopmentRequirementpoetryInstallingpoetry install
poetry shell
hycli --helpRunning the testspoetry run pytestVersioningUsesbump2version:bump2version --verbose [patch|minor|major]  # add --dry-run to have a preview
git push --follow-tagsDocumentationIs build with sphinx, can be seen/worked on locally by:cd docs
make html
open build/html/index.htmlLicenseHypatos