Saravanan666/pypi-org huggingface dataset:
Package: boolean-question
Boolean QuestionGet accurate answer prediction for True / False question using this python pytorch model. The model takes a passage and question as input and returns either "True" or "False" as predicted answer. Model used isRoBERTathat is further trained onBoolQdataset.InstallationInstall it with python package installer pippipinstallboolean_questionor install the latest master branchpipinstallgit+https://github.com/Saadmairaj/boolean-questionUsageThe usage is simple and straight forward, importBoolQclass model and pass arguments to theBoolQ.predict(passage: str, question: str)method to predict the boolean answer "True" or "False"importpprintfromboolean_questionimportBoolQbq=BoolQ()passage="""A red dwarf is the smallest and coolest kind of star on the main sequence.Red dwarfs are by far the most common type of star in the Milky Way, atleast in the neighborhood of the Sun, but because of their low luminosity,individual red dwarfs cannot be easily observed."""question="Coolest star in the Milky way is a Red dwarf"# Predict the answer from the passage and the questionans=bq.predict(passage,question)print(ans)# After prediction extra details of the prediction can be seen with the below commandpprint.pprint(bq.prediction_details())View outputTrue
{'answer': True,
'confidence': None,
'false confidence': 0.01,
'passage': '\n'
            'A red dwarf is the smallest and coolest kind of star on the main '
            'sequence. Red dwarfs are by far the most common type of star in \n'
            'the Milky Way, at least in the neighborhood of the Sun, but '
            'because of their low luminosity, individual red dwarfs cannot '
            'be \n'
            'easily observed.',
'question': 'Coolest star in the Milky way is a Red dwarf',
'true confidence': 0.99}
Package: boolean-to-signed
boolean_to_signedReturns -1 if input is false, or 1  if input is true.Install$pipinstallboolean_to_signedUsagefromboolean_to_signedimportto_signedprint(to_signed(False));#=> -1print(to_signed(True));#=> 1# use casesx=y=value=0#  using naive conditional assignmentifx>0:y+=valueelse:y-=value;# using direct assignmenty+=to_signed(x>0)*value;AboutAuthorNajim IslamLinkedIn ProfileLicenseCopyright © 2021,Najim Islam.
Released under theMIT License.
Package: boolem
EM_BMFRobust Boolean matrix factorization via EM_BMF
The code is completely process-oriented. Sorry for contaminating your name space.Dependency: (I think it will work as long as Annaconda on Python3 is installed)numpy -- 1.11.3scipy -- 1.1.0numba -- 0.40.0Example usage:importnumpyasnpfromboolemimportboolemdefsynthesis(shape,latent_size,P,noise_p=0.0):'''In this synthesis, the probability of X was sampled from the joint probability of the latent factors.P is the parameter as Beta(1/(1-p),2) for generating the probability in latent factors.'''a=np.zeros((shape[0],latent_size))b=np.zeros((latent_size,shape[1]))X=np.zeros(shape)forlinrange(latent_size):a[:,l]=np.random.binomial(1,P[l],shape[0])b[l,:]=np.random.binomial(1,P[l],shape[1])X+=np.outer(a[:,l],b[l,:])X[X>1]=1flip=np.random.binomial(1,noise_p,X.shape)X_noisy=np.abs(X-flip)returnX_noisy,X,a,b# Generate a Boolean matrice with heterogeneous Boolean factors and uniform noise.X_noisy,X,a,b=synthesis((1000,1000),4,np.random.uniform(0.2,0.5,4),noise_p=0.2)# Feed the model with noisy matrix.# Latent_size: the dimension of latent Boolean factors.# alpha: the alpha for the beta prior. Default is recommended.# beta: the beta for the beta prior. Default is recommended.# mask: the matrix with the same shape as X. 0 means the correponding element in X is missing.# max_iter: the maximum iteration for gradient-based optimizationmodel=boolem(np.int8(X_noisy),latent_size=5,alpha=0.95,beta=0.95,mask=np.ones(X.shape,dtype=np.int8),max_iter=200)model.run()# After running factorization, the model will contain several new attributes as the output:# model.U: the latent factor with the shape (X.shape[0], latent_size)# model.Z: the latent facotr with the shape (latent_size, X.shape[1])# model.X_hat: reconstructed Boolean matrix from U and Z. Note that values in X_hat is continuous within [0,1]print('Reconstruction error:',np.abs((model.X_hat>0.5)-X).mean())
Package: boolexp
Boolexp provides “safe” evaluation of boolean expressions for use
cases where eval might be dangerous. Boolexp expressions are
context-free and mimic Python sytax. Only basic math opearations
and data structures are provided.InstalationTo install Boolexp, change to the directory where setup.py is
located and type:python setup.py installRequirements:Python 2.7pyparsing 1.5.0 or laterExpression Syntax OverviewBasic math operators*,/,+,-have highest priority>>>fromboolexpimportExpression>>>Expression("4 + 4 / 2").evaluate()>>>6>>>Expression("( 4 + 4 ) / 2 ").evaluate()>>>4Comparsion operators!=, ==, <, >, <=, >=, inare next in
priority. All comparsion operators have return type ofboolean,
which can be used as input forbooleanoperatorsand, or, notwith lowest priority.>>>fromboolexpimportExpression>>>Expression(2==1).evaluate()>>>False>>>Expression("2 * - 2 == - 4").evaluate()>>>True>>>Expression("not 2 == 3").evaluate()>>>True>>>Expression("3 <= 8 and 2 == 5").evaluate()>>>FalseExpresions with with variablesThis all would not be much of a fun without posibility to use
variables. Allowed types for variables arebool,int,float,str,list,dict>>>fromboolexpimportExpression>>>Expression("1 in v").evaluate(dict(v=[1,2])).evaluate()>>>True>>>Expression("one[1].part == 2").evaluate(dict(one=[1,dict(part=2)],two=1)).evaluate()>>>TrueDiclaimerThis project is now in a state of proof of concept only, thus far
from suitable for production enviroment.
Package: boolexpr
BoolExpr is a C++ library for symbolic Boolean algebra.Read the docs!System DependenciesThis code is known to compile on Ubuntu Trusty Linux.
Install the following dependencies:sudo apt-get install -y build-essential cmake doxygenGetting StartedTo get started using the code,
first clone the repository and itsthird_partydependencies:git clone --recursive https://github.com/cjdrake/boolexpr
cd boolexprCreate a local build directory, and runcmake:mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Coverage ..
makeRun TestsAfter the dependencies have been built,
to run the functional test suite:make do_testTo collect code coverage data:make coverThe coverage report will be inbuild/html/index.html.Build DocumentationThe documentation usesDoxygenandSphinx.
To build the html version:pip install sphinx
make pyhtmlThe documentation will be inbuild/python/build/sphinx/html/index.html.ContributingIf you have some idea you would like to see realized,
please email me.
Package: boolparser
This package defines a simple boolean parser using PyParsing that allows user defined variables and floating point numbers to be used in a nested boolean comparison. For example, if the variablesa,*b*, andcare defined then the following string can be parsed(a==1 & b<2) | c>4The resolution ofa,b, andcis left up to the user by inheriting from the classEvaluateVariableclass and overriding theevalfunction. This allows the variables to be references to (say) data stored in a file.BSD licensed.
Package: boolrule
boolruleSimple boolean expression evaluation engine.Free software: MIT licenseDocumentation:https://boolrule.readthedocs.io.FeaturesCompare simple boolean statements:>>> rule = BoolRule('5 > 3')
>>> rule.test()
True
>>> rule = BoolRule('5 < 3')
>>> rule.test()
FalseEvaluate boolean statements against a context dict:>>> can_buy_beer = BoolRule('user.age_years >= 18')
>>> can_buy_beer.test({'user':{'age_years': 12}})
False
>>> can_buy_beer.test({'user':{'age_years': 20}})
TrueCombine conditions with and and or operators to produce complex expressions:>>> is_hipster = BoolRule('address.postcode.outcode in ("E1","E2") or user.has_beard = true')
>>> address = {
>>>   'postcode': {
>>>      'outcode': 'E1'
>>>   }
>>> }
>>> is_hipster.test({'has_beard': False, 'address': address})
TrueCreditsMade possible by the excellentpyparsinglibrary.This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.3.5 (2024-02-09)Introduce not∩ operator0.3.4 (2021-09-24)Fixed error caused by early return when evaluating nested expressions.0.3.3 (2021-07-15)Upgrade dependencies.0.3.2 (2020-09-23)Add Type hinting.0.3.1 (2020-09-09)Raise an exception when the whole expression cannot be parsed. Previous behaviour would discard the segment
that didn’t match the expression grammar.0.3.0 (2018-01-15)Add None type and is/isnot operators (contributed by ocurero)0.2.0 (2016-10-27)Fixed error caused by refactor from internal codebase that was preventing deep context level values from being
referenced in a substitution value0.1.2 (2016-09-30)Improved documentation0.1.1 (2016-09-30)MadecontextoptionalImproved documentation0.1.0 (2016-09-30)First release on PyPI.
Package: booltest-rtt
Utility integrating BoolTest battery to the RTTConfigurationEnvironment variableRTT_PARALLELprecedestoolkit-settings.execution.max-parallel-testsin the configuration.Expected configuration inrtt-settings.json{"booltest":{"default-cli":"--no-summary --json-out --log-prints --top 128 --no-comb-and --only-top-comb --only-top-deg --no-term-map --topterm-heap --topterm-heap-k 256 --best-x-combs 512","strategies":[{"name":"v1","cli":"","variations":[{"bl":[128,256,384,512],"deg":[1,2,3],"cdeg":[1,2,3],"exclusions":[]}]},{"name":"halving","cli":"--halving","variations":[{"bl":[128,256,384,512],"deg":[1,2,3],"cdeg":[1,2,3],"exclusions":[]}]}]}}Configuration can be also specified per-job in the job config file:{"randomness-testing-toolkit":{"booltest":{"strategies":[{"name":"v1","cli":"","variations":[{"bl":[128,256,384,512],"deg":[1,2,3],"cdeg":[1,2,3],"exclusions":[]}]},{"name":"halving","cli":"--halving","variations":[{"bl":[128,256,384,512],"deg":[1,2,3],"cdeg":[1,2,3],"exclusions":[]}]}]}}}strategiesoverrides RTT-defined strategiesstrategies-auxadds another strategies to the RTT-defined
strategies
Package: bool-to-int8-ray
bool-to-int8-raybool to int8 serialization with ray.ioInstallationpip install bool-to-int8-rayUsageexportB2I8_PCT_CPU=0.6frombool_to_int8_rayimportbool_to_int8_batch,int8_to_bool_batchimportnumpyasnp# given lists of binary hasheshashvalues=np.array([[1,0,1,0,1,1,0,0],[1,1,0,0,0,0,0,1]])# convert to list of int8 valuesserialized=bool_to_int8_batch(hashvalues)# convert backdeserialized=int8_to_bool_batch(serialized)Speed Testsource.venv/bin/activateexportB2I8_PCT_CPU=0.6
pythontest/speedtest.pyResults4.776991 -- numpy version, hash to int8
 6.031101 -- numpy version, int8 to hash
 2.308446 -- ray.io version, hash to int8
 3.023865 -- ray.io version, int8 to hashAppendixInstallationThebool-to-int8-raygit repois available asPyPi packagepipinstallbool-to-int8-ray
pipinstallgit+ssh://git@github.com/ulf1/bool-to-int8-ray.gitInstall a virtual environmentpython3-mvenv.venvsource.venv/bin/activate
pipinstall--upgradepip
pipinstall-rrequirements.txt--no-cache-dir
pipinstall-rrequirements-dev.txt--no-cache-dir(If your git repo is stored in a folder with whitespaces, then don't use the subfolder.venv. Use an absolute path without whitespaces.)Python commandsJupyter for the examples:jupyter labCheck syntax:flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')Run Unit Tests:PYTHONPATH=. pytestRun Speed Test:python test/speedtest.pyPublish# pandoc README.md --from markdown --to rst -s -o README.rstpythonsetup.pysdisttwineupload-rpypidist/*Clean upfind.-typef-name"*.pyc"|xargsrm
find.-typed-name"__pycache__"|xargsrm-r
rm-r.pytest_cache
rm-r.venvSupportPleaseopen an issuefor support.ContributingPlease contribute usingGithub Flow. Create a branch, add commits, andopen a pull request.AcknowledgementsThe "Evidence" project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -433249742(GU 798/27-1; GE 1119/11-1).Maintenancetill 31.Aug.2023 (v0.1.1) the code repository was maintained within the DFG project433249742since 01.Sep.2023 (v0.2.0) the code repository is maintained by@ulf1.
Package: boomber
boomberОткрытый и бесплатный СМС бомберУстановка•Расширенное использованиеДокументацияУстановкаAPIАргументы командной строкиПроекты, использующие b0mb3rКогда что то идёт не такКанал с новостями о разработке в Telegram:@b0mb3rch.ЛицензияПроект распространяется под лицензиейMozilla Public License 2.0. Скачивая программное обеспечение изэтогорепозитория, вы соглашаетесь с ней. По условиям лицензии вы обязаны выкладывать исходный код ваших модификаций под той же лицензией.Contributors ✨Thanks goes to these wonderful people (emoji key):Nikita💬🐛💻🎨📖🔍🤔🚇🚧📦📆👀Dmitry💻its5Q💻Даниил Николаев💻📖💵🤔🔧👀Kirill Link💻🎨cxiodev💻Mikhail Kuznetsov📖asinedd💻aiexz💻GameTrue🐛💻Antsiferov Bogdan💻🎨Alex Sokol📖This project follows theall-contributorsspecification. Contributions of any kind welcome!
Package: boombig
BoombigBoombig Library Python=> Install and Update:pipinstall-Uboombing=> STARTdoc: github.com/onlyradSocial Media:Mohammad Mehrabi RadTelegram: @OnlyRadgithub: github.com/OnlyRadrubika: rubika.ir/OnlyMamadAmir kamankeshTelegram: @paytowin_prgrubika: rubika.ir/paytowin
Package: boomerang-client
Boomerang.io Python API client==============Installing______________.. code:: pythonpip install boomerang-clientExample usage--------------.. code:: pythonimport calendarimport datetimefrom boomerang.client import BoomerangClientbc = BoomerangClient(<projectid>, <apikey>)future = datetime.datetime.utcnow() + datetime.timedelta(minutes=5)date = calendar.timegm(future.timetuple())params = { "url": "http://theurl.com", "msg": "the message", "run_at": date }print bc.create_boomerang(params).textprint bc.get_all_boomerangs().text
Package: boompy
boom.pyis a simple command line utiilty for storing text snippets under simple, memorable key names.
It is conceptually similar toboombyZach Holman.InstallationThe easiest way to installboom.pyis viapip:pip install boompyYou can also install it the old-fashioned way, if that’s more your speed:git clone https://github.com/epochblue/boom.py
cd boom.py
python setup.py installUsageTo create a new snippet, provide both the key name and a value for the key.$>boomnew_keynew_value'new_key' is now 'new_value'.To retrieve the value for a key once it’s been set, simply provide the key name. The value will be automatically copied to the system clipboard.$>boomnew_key'new_key' successfully copied to clipboard.If you attempt to set a value for an existing key,boom.pywill return with an error.$>boomnew_keynew_valueError: Key 'new_key' already exists.If you’d like to update an existing key, use the--overwriteor-oflag:$>boom--overwritenew_keyupdated_value'new_key' is now 'updated_value'.And if you’d like to delete a key/value pair, use the--deleteor-dflag.$>boom--deletenew_key'new_key' has been removed.By default,boom.pystores its “database” in a file located at$HOME/.config/boom/boomdb.
If you’d like to save your snippets to a different location, you can use the-dbor--databaseflag:$>boom--database./snip.dbnew_keynew_value'new_key' is now 'new_value'If you provide no argument or options toboom.py, it will print all the currently-stored records to the screen.$>boomnew_key     new_value
new_key2    new_value2
example     example_valueIt’s not much, but that’s all there is toboom.py.Licenseboom.pyis MIT licensed. Please see the includedLICENSEfile.AuthorsBill Israel -@epochblue-http://billisrael.info/
Package: boondh
boondhA Personal LibraryEncapsulate boilerplate codeData processing codeML Frameworks (NLP tasks - SeqClassification, Entity Extractions etc.)installpip3install-UboondhFor nightlygitclonehttps://github.com/rohit-mehra/boondh.gitcdboondh
pipinstall.sample useParallelize any functionfromboondhimportmp_func# Any function to be applied on each element of datadefbase_func(value,sq=True):ifsq:returnvalue**2returnvalue# Any datadata=[0,1,2,3,4]# Collected results - Ordered by defaultresults=mp_func(base_func,# apply this in parallel'value',# the data argument name in above functiondata,# contains elements to be processedsq=True# any arg of the `to be applied` function)# configure chunksize and set ordered as False for perfromance gainresults=mp_func(base_func,'value',data,chunksize=200,ordered=False,sq=True)Arrange files in your directory (usually theDownloaddirectory.. :smile:)This will scan the directory and createtype folderslikecsv_,txt_etc.Move respective filetypes into these folders.python-mboondh.utils.arrange_files-D"$(pwd)"ORpython-mboondh.utils.arrange_files-D/Users/<myusername>/Downloads/
Package: boonli-api
Boonli APIThis API allows you to retrieve the menus that were chosen onBoonli.UsageTo get the menu information run:> boonli_api/api.py -c <customer_id> -u <username> -p <password>Wherecustomer_idis the first part of the domain name where you login, likemy_schoolinhttps://myschool.boonli.com.To enable a lot of debug logging you can add-v.Web APII have also created an API that can be deployed on Google Cloud Function that returns the menus as an iCalendar here:https://github.com/beaufour/boonli_calendarNotesBoonli does not have an official API, so I reverse engineered it. It involves parsing two web pages which is always fragile. So it will probably break at some point.
Package: boonnano
Python SDK DocumentationThis python package allows ease of access to calls to the BoonLogic Nano API.Website:boonlogic.comDocumentation:Boon Docs Main PageClustering: [Clustering with the expert-python-sdk]({{ site.baseurl}}/docs/Tutorial_The_General_Pipeline.md)Autotuning: [Autotuning with the expert-python-sdk]({{ site.baseurl}}/docs/How_To_Autotune_Data.md)Results: [Results after clustering]({{ site.baseurl}}/docs/How_To_Generate_Cluster_Results.md)SDK Functional Breakdown: [expert-python-sdk classes and methods]({{ site.baseurl}}/docs/boonnano/index.html)(docs/boonnano/index.html)InstallationThe BoonNano SDK is a Python3 project and can be installed via pip.pip install boonnanoLicense setupNote: A license must be obtained from Boon Logic to use the BoonNano Python SDKThe license should be placed in a file named ~/.BoonLogic.license{"default":{"api-key":"API-KEY","server":"WEB ADDRESS","api-tenant":"API-TENANT"}}TheAPI-KEY,WEB ADDRESS, andAPI-TENANTwill be unique to your obtained license.The .BoonLogic.license file will be consulted by the BoonNano Python SDK to successfully find and authenticate with your designated server.Connectivity TestThe following Python script provides a basic proof-of-connectivity:connect-example.pyimportboonnanoasbnimportjsonimportsys## connectivity example for boonnano#try:# create client handlenano=bn.ExpertClient.from_license_file(license_id='default')# open/attach to nanoinstance_id='my-instance'nano.open_nano(instance_id)# retrieve server versionresponse=nano.get_version()print(json.dumps(response,indent=4))# close/detach the nano instancenano.close_nano(instance_id)exceptbn.BoonExceptionasbe:print(be.message)sys.exit(1)Running the connect-test.py script should yield something like:%pythonconnect-example.py{"release":"dev","api-version":"/expert/v3","nano-secure":"3c40f1d6","builder":"f5db0682","expert-api":"f6643822","expert-common":"c0575a50","swagger-ui":"914af396"}
Package: boopyboop
BoopyBoop======Automatically make awesome names that will also not collide too much.Interface is simple. Create the object BoopyBoop (it will convert mongoids by default, but you can use any old number), and then pop out the human-friendly names with `BoopyBoop.id_to_string(words, settings)`By "not collide too much", I mean "someone can probably figure it out, depending on how many of the words you use and how strong, etc your hash or whatever is in the first place". This is not really an encryption anything, really. If you can't deal with 17 or whatever words, then cut them down to 4, bearing in mind the risk of an easier attack. This should really be used for things that don't matter.
Package: booq
booqPython implementation of booq - a tool calculating binary year to date metrics with monthly cumulative slices.License: MITDocumentationUser and developerdocumentation of booq.Bug TrackerFeature requests and bug reports are best entered in thetodos of booq.Primary Source repositoryThe primary source repository ofbooq is at sourcehuta collection of tools useful for software development.StatusExperimental.Note: The default branch isdefault.
Package: booru
BooruPython bindings for Booru imageboardsBooruFeaturesFeatures availabilityUsagePrerequisitesInstallationExamplesearchsearch_imagefind_tagsbooru.resolve()Import specific booru clientTesting casesThe coreTags completionDocumentationLegalPython bindings for the imageboards.
It is takes a much more functionalities to interacts with ease, and featureful. Making your interaction significantly tidier, less of pain, and hopefully will be reusable.Contributing•Documentation•Report IssuesFeaturesPlenty of imageboardsSearch random & gacha returnsTags block, resolved safety tags concernsTags finder, tags & query completionParses and returns the image onlyDocumented and testedEasy to use, check your intelisenseUsageAsync context, and it's recommended useasyncio/https://sinkaroid.github.io/booruPrerequisitesNOTE:Python 3.7 or aboveInstallationpip install booruThis library vs. the CompetitionFeatures availabilityfor this libraryBooruStatusRandomTags blockTags finderGet imagesGachaGelbooruYesYesYesYesYesDanbooruYesYesYesYesYesRule34YesYesYesYesYesRealbooruYesYesYesYesYesTbibYesYesYesYesYesXbooruYesYesYesYesYesSafebooruYesYesYesYesYesYandereYesYesYesYesYesLolibooruYesYesYesYesYesKonachanYesYesYesYesYesKonachan.netYesYesYesYesYesHypnohubYesYesYesYesYesE621YesNoNoYesYesE926YesNoNoYesYesDerpibooruYesNoNoYesYesFurbooruYesNoNoYesYesATFbooruYesYesYesYesYesBehoimiYesNoNoYesYesPahealYesNoNoYesYesExamplesearch()Takes parameter(query: str, block: str = "", limit: int = 100, page: int = 1, random: bool = True, gacha: bool = False)importasyncioimportbooruasyncdefmain():dan=booru.Danbooru()res=awaitdan.search(query="cat_girl",block="futanari")print(res)## this is <class 'str'>print(booru.resolve(res))## this is <class 'list'>asyncio.run(main())You will never gets content which contains futa tags.You can also import specific booru client.frombooruimportRule34some_booru=Rule34()## do with r34search_image()Takes parameter(query: str, block: str = "", limit: int = 100, page: int = 1)importasynciofrombooruimportRule34asyncdefmain():r34=Rule34()img=awaitr34.search_image(query="cat_girl",block="futanari")print(img)asyncio.run(main())This will parses image url only, instead objectfind_tags()You want to wildcard or query completion like the browser do?What browser looks likeThis library alsoimportasynciofrombooruimportDanbooru,resolveasyncdefmain():dan=Danbooru()find_tags=awaitdan.find_tags("jeanne")## arbitrary tagswildcard=resolve(find_tags)print(wildcard)asyncio.run(main())Get thewildcard[0]for the best match.booru.resolve()You will need this for every object, this library designed to be neat and clean returns, although it must be reparsed to the string first, that's whybooru.resolve()exist.DocumentationThe documentation can be foundhttps://sinkaroid.github.io/booruLegalThis tool can be freely copied, modified, altered, distributed without any attribution whatsoever. However, if you feel
like this tool deserves an attribution, mention it. It won't hurt anybodyLicence: WTF.