Saravanan666/pypi-org huggingface dataset:
Package: pybencher
PyBencher - Python Bechmarker1. IntroductionPyBencher is a Python package that provides a suite of benchmark tests for measuring the performance of code snippets or functions. It allows you to easily define and run benchmark tests, and provides detailed timing information for analysis and comparison.TheSuiteclass represents a suite of benchmark tests. It allows you to add benchmark test functions, set various parameters, and run the tests.2. InstallationTo install PyBencher, you can use pip, the Python package manager. Open a terminal or command prompt and run the following command:pip install pybencher3. UsageTo use theSuiteclass in your Python script or module, you need to import it first. Here's an example:frompybencherimportSuiteOnce you have imported theSuiteclass, you can create an instance of it as follows:suite=Suite()4. Class ReferenceSuiteAttributestimeout(float): The number of seconds to run each function before exiting early. Timout is only checked after the end of a function call, a long running or infinite functions will not time out.max_itr(int): The maximum number of iterations to run each function. Maximum iterations is recorded function calls after cutting fastest and slowest.max_itr=1000withcut=0.1will run the function 1250 times and cut the top and bottom 125. Defaults to 1000 runs.min_itr(int): The minimum number of iterations to run each function. Takes priority over timeout and defaults to 3 runs.cut(float): The percentage of iterations to cut off from each end when calculating average time.Methodsadd(func, *args, **kwargs): Adds a benchmark test function to the suite.clear(): Clears the list of benchmark test functions in the suite.set_timeout(t): Sets the timeout value for each function in the suite.set_max_itr(n): Sets the maximum number of iterations to run each function.set_min_itr(n): Sets the minimum number of iterations to run each function.set_cut(n): Sets the percentage of iterations to cut off from each end when calculating average time.get_suite(): Returns a dictionary containing the details of the suite.5. ExamplesExample 1: Adding and running benchmark testsfrompybencherimportSuite# Create a new suitesuite=Suite()# Define benchmark test functionsdeftest_func1():# Code to be benchmarkedpassdeftest_func2():# Code to be benchmarkedpass# Add benchmark test functions to the suitesuite.add(test_func1)suite.add(test_func2)# Run the benchmark testssuite.run(verbose=True)This example demonstrates how to create a suite, define benchmark test functions, add them to the suite, and run the tests. Theverboseparameter is set toTrueto print additional details for each benchmark test.
Package: pybenchmark
When measuring execution time, the result depends on the computer hardware.
To be able to produce a universal measure, the simplest way is to benchmark the speed of a fixed sequence
of code and calculate a ratio out of it. From there, the time taken by a function can be translated to a
universal value that can be compared on any computer. Python provides a benchmark utility in its test
package that measures the duration of a sequence of well-chosen operations.
pybenchmark designed to provide a simple and pythonic way to get performance data.
Package: pybenchmarker
pybenchmarkerA simple utility for comparing the efficiency of functionally-equivalent
functions in Python.Installationpip install pybenchmarkerBenchmarkN classProblemInput: two lists of equal lengthlist_0,list_1.Output: alistof booleans encoding which items oflist_0are inlist_1.What's the fastest way to do this?importnumpyasnpfrompybenchmarkerimportBenchmarkN,sizesfromrandomimportrandint@sizes([2**kforkinrange(18)])defargfunc(n):return[randint(1,n)foriinrange(n)],[randint(1,n)foriinrange(n)]defnaive_lcomp(lists):return[xinlists[1]forxinlists[0]]defset_other(lists):s=set(lists[1])return[xinsforxinlists[0]]defnumpy_isin(lists):returnlist(np.isin(lists[0],lists[1]))if__name__=='__main__':title="list_3: list[bool], encoding which items in list_1 are in list_2"b=BenchmarkN(functions=[naive_lcomp,set_other,numpy_isin],argfunc=argfunc)b.plot(xlabel="n",title=title,fname="my_figure",transparent=True,dpi=300)This results in the following plot:InspirationThis project was inspired byperfplot,
which was used to contribute to"How do I efficiently find which elements of a list are in another list?"
Package: pybenchmarks
PyBenchmarksAutomate the creation of benchmark tables.The benchmark utility times one or more code snippets or functions by iterating
through input arguments or keyed variables. It returns a dictionary
containing the elapsed time (all platforms) and memory usage (linux only)
for each combination of the input variables. An argument or keyed variable
is iterated if and only if it is a list, a tuple, a generator or a range.Examples>>> import numpy as np
>>> from pybenchmarks import benchmark
>>> b = benchmark((np.empty, np.ones), (100, 10000, 1000000),
...               dtype=(int, complex))
empty: 100     dtype=int       1.62 us
ones : 100     dtype=int       3.61 us
empty: 100     dtype=complex   1.70 us
ones : 100     dtype=complex   5.42 us
empty: 10000   dtype=int       1.53 us
ones : 10000   dtype=int       7.53 us
empty: 10000   dtype=complex   2.33 us
ones : 10000   dtype=complex  16.29 us
empty: 1000000 dtype=int       1.87 us
ones : 1000000 dtype=int       1.84 ms
empty: 1000000 dtype=complex   2.19 us
ones : 1000000 dtype=complex   4.20 ms>>> b = benchmark(['np.empty(n, dtype=dtype)', 'np.ones(n, dtype=dtype)'],
...               dtype=(int, complex), n=(100, 10000, 1000000),
...               setup='from __main__ import np')
'np.empty(n, dt...: dtype=int     n=100       1.36 us
'np.ones(n, dty...: dtype=int     n=100       2.83 us
'np.empty(n, dt...: dtype=complex n=100       1.44 us
'np.ones(n, dty...: dtype=complex n=100       3.50 us
'np.empty(n, dt...: dtype=int     n=10000     1.22 us
'np.ones(n, dty...: dtype=int     n=10000     7.05 us
'np.empty(n, dt...: dtype=complex n=10000     1.35 us
'np.ones(n, dty...: dtype=complex n=10000    23.78 us
'np.empty(n, dt...: dtype=int     n=1000000   1.47 us
'np.ones(n, dty...: dtype=int     n=1000000   2.04 ms
'np.empty(n, dt...: dtype=complex n=1000000   2.91 us
'np.ones(n, dty...: dtype=complex n=1000000   4.26 ms>>> import time
>>> benchmark(time.sleep, (1, 2, 3))
1   1.00 s
2   2.00 s
3   3.00 s>>> shapes = (100, 10000, 1000000)
>>> setup = """
... import numpy as np
... a = np.random.random_sample(shape)
... """
>>> b = benchmark('np.dot(a, a)', shape=shapes, setup=setup)
shape=100       1.38 us
shape=10000     6.33 us
shape=1000000 855.44 us>>> shapes = (10, 100, 1000)
>>> setup="""
... import numpy as np
... a = np.random.random_sample((m, n))
... b = np.random.random_sample(n)
... """
>>> b = benchmark('np.dot(a, b)', m=shapes, n=shapes, setup=setup)
m=10   n=10     1.08 us
m=100  n=10     1.61 us
m=1000 n=10     6.91 us
m=10   n=100    1.48 us
m=100  n=100    4.16 us
m=1000 n=100   20.69 us
m=10   n=1000   4.42 us
m=100  n=1000  39.23 us
m=1000 n=1000 931.04 us>>> def f(x, n, start=1):
...     out = start
...     for i in range(n):
...         out *= x
...     return out
>>> b = benchmark(f, np.full(10, 2), xrange(10), start=2.)
0   1.09 us
1   4.15 us
2   5.25 us
3   5.53 us
4  13.10 us
5   9.23 us
6   9.69 us
7  10.46 us
8  13.03 us
9  10.77 us
Package: pybencoder
What is a Bencoded String?Bencode (pronounced like B encode) is the encoding used by the peer-to-peer file sharing system BitTorrent
for storing and transmitting loosely structured data.For more info on bencoding check outthis.It provides:decoding of the different bencoded elementsencoding of the allowed types (byte strings, integers, lists, and dictionaries).Requires Python 2.6 or later.
Package: pybendt
pybendtBrownian Elastic Networks with Dynamic Topology.Copyright ©2023- Tomasz Skóratskora@sci.utah.eduWarningThe software is not extensively tested yet! It's just a prototype!FeaturesBrownian dynamics w/o hydrodynamic interactionscustomizable atom-atom (2-body) interactionscustomizable many-body interactionscustomizable event-driven bond topology changes[] input/output handlingQuick startTo install, type following commands in a terminal:$pip3installpybendtUnitsPhysical propertyUnitsTemperaturekelvin (K)Friction coefficientpicosecond times kilocalorie per mole per angstrom squared (ps kcal/mol/Å^2)Timepicosecond (ps)Distanceangstrom (Å)Energykilocalorie per mole (kcal/mol)Forcekilocalorie per mole per angstrom (kcal/mol/Å)Force constantkilocalorie per mole per angstrom squared (kcal/mol/Å^2)NoteThere is a separate functionfriction_from_hydrodynamic_radius_and_viscositywhich takes hydrodynamic radius in angstrom (Å) and viscosity in centipoise (cP) and returns friction coeffiient in picosecond times kilocalorie per mole per angstrom squared (ps kcal/mol/Å^2).AuthorsThe following people contributed to the development of pybendt.Tomasz Skóra --creator, lead developer(contact:tskora@sci.utah.edu)
Package: pybenzinaparse
Parses out and returns a limited set of MP4 boxesUsageParse boxesimportbitstringasbsfrompybenzinaparseimportParserbstr=bs.ConstBitStream(filename="my.mp4")forboxinParser.parse(bstr):printbox.header.type# Load the box content in memorybox.load(bstr)Check is MP4 fileReads the first box header at byte 0. ReturnsFalseif box header does not exist or is invalid>>>pybenzinaparse.Parser.is_mp4(filename='my.mp4')True>>>pybenzinaparse.Parser.is_mp4(filename='/etc/resolv.conf')False
Package: pybeoplay
Bang & Olufsen BeoPlay devices Python integration moduleBeoplay Python wrapper to integrate B&O speakers/TVs to Python that use the BeoPlay API. BeoPlay API is the 2nd generation B&O API, afterMasterlink Gatewayand beforeMozart. It is supported by devices built from the early 2000s to the late 2010s, including several BeoVision TV, BeoLab speakers and the NL/ML Converter.The API is wrapped in an object that can be used  to read the state and control BeoPlay devices. It includes both methods for blocking calls, and async calls with callbacks using aiohttp.Reference informationis on this page.Some more information on the Notifications stream is in theEVENTS.mdfile.Currently gets the following attributes:volumemutesourcesource listprimary experiencestatestandbytrack image (if available)artistalbumsong(name) (if available)description (if available)stand positionsThe following commands are available:set volumeset muteplaypausestopnextpreviousstandbyset sourcejoin experienceleave experienceplay queue itemset stand position
Package: pyberdrola
pyberdrolapyberdrolaallows to get info and invoices about the electric consumption.This info is obtained from thewww.iberdrola.esusing the same APIs that iOS app is using,
but in an easy way.Installationpyberdrolaisavailable at pypi, so you can install it usingpip3(it requires Python3).pip3installpyberdrolaUsing pyberdrolapyberdrolarequires two variables (IBUSERandIBPASS) to be able to log in.# the same that you're using to login in https://www.iberdrola.es/exportIBUSER='your_username'exportIBPASS='your_pass'After that, you can use the CLI:# Show a list of all your invoices (date, consumption and price)pyberdrolaall# Show info about your last invoicepyberdrolalast# Show the help menupyberdrola--helpLicenseRead theLICENSE file.
Package: pyberny
PyBernyPyBerny is an optimizer of molecular geometries with respect to the total energy, using nuclear gradient information.In each step, it takes energy and Cartesian gradients as an input, and returns a new equilibrium structure estimate.The package implements a single optimization algorithm, which is an amalgam of several techniques, comprising the quasi-Newton method, redundant internal coordinates, an iterative Hessian approximation, a trust region scheme, and linear search. The algorithm is described in more detailed in thedocumentation.Several desirable features are missing at the moment but planned, some of them being actively worked on (help is always welcome):crystal geometries,coordinate constraints,coordinate weighting,transition state search.PyBerny is available inPySCF,ASE, andQCEngine.InstallingInstall and update usingPip:pip install -U pybernyExamplefrombernyimportBerny,geomliboptimizer=Berny(geomlib.readfile('geom.xyz'))forgeominoptimizer:# get energy and gradients for geomoptimizer.send((energy,gradients))LinksDocumentation:https://jhrmnn.github.io/pyberny
Package: pybert
pybert安装>pipinstallpybert预训练模型下载地址：bert_Chinese 模型文件:https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-chinese.tar.gz词表https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-chinese-vocab.txt【备用】百度网盘：https://pan.baidu.com/s/1HPZBvkMAyu0nDUqHWsb0SA?pwd=abbn所需文件：pytorch_model.binbert_config.jsonvocab.txt放到 bert_pretrain 文件夹中训练数据下载THUCNews可以任意指定文件夹名称，训练数据的格式要和上面一致训练和预测训练frompybert.modelsimportbertfrompybert.train_evalimportload_and_traindataset='THUCNews'# 数据集logfile='log.txt'# 日志文件config=bert.Config(dataset,logfile=logfile)load_and_train(config)预测# coding: UTF-8importpybert.models.bertasbertfrompybert.train_evalimportPredictionconfig=bert.Config(dataset='THUCNews')prediction=Prediction(config)sentences=['野兽用纪录打爆第二中锋 掘金版三巨头已巍然成型','56所高校预估2009年湖北录取分数线出炉']predict_label,score=prediction.predict(sentences)print("predict label:")print(predict_label)对应论文[1] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Package: pybess-grpc
pybesspybessis a Python library which lets you interact with BESS using gRPC.InstallationYou can install the library directly using pip/pip3:pip3installpybess_grpcUsageAs mentioned abovepybesscan be used to communicate with BESS over gRPC.An example of usage of this library is to list all BESS ports remotely:importsysfromgoogle.protobuf.json_formatimportMessageToDictfrompybess_grpc.bessimportBESSbess=BESS()try:bess.connect(grpc_url="%s:10514"%sys.argv[1])ports=bess.list_ports()print(MessageToDict(ports)["ports"])finally:bess.disconnect()
Package: pybet365
pybet365Python Wrapper for Bet365 APIFree software: MIT licenseDocumentation:https://pybet365.readthedocs.io.InstallationFrom source$gitclonehttps://github.com/leonkozlowski/pybet365.git$cdpybet365$python3.8-mvenvvenv$sourcevenv/bin/activate$pipinstall-e.# For test dependencies$pipinstall-rrequirements_dev.txtFrom build$pipinstallpybet365FeaturesGET Request to Upcoming Events Endpointfrompybet365importBet365client=Bet365(api_host="someHost",api_key="someKey")upcoming_events=client.upcoming_events(sport_id="49")print(upcoming_events)Response{"success":1,"pager":{"page":1,"per_page":50,"total":102},"results":[{"id":"88107197","sport_id":"92","time":"1586480400","time_status":"0","league":{"id":"10036652","name":"Moscow Liga Pro"},"home":{"id":"10423098","name":"Evgenii Kryuchkov"},"away":{"id":"10433218","name":"Aik Lulikyan"},"ss":null,"our_event_id":"2297143","updated_at":"1586478473"}]}Access response objects with dot notationfrompybet365importBet365client=Bet365(api_host="someHost",api_key="someKey")upcoming_events=client.upcoming_events(sport_id="49")print(upcoming_events.success)>>>1Access of array typeresultsobjectsfrompybet365importBet365client=Bet365(api_host="someHost",api_key="someKey")upcoming_events=client.upcoming_events(sport_id="49")print(upcoming_events.results[0].id)>>>"88107197"Environment VariablesBET365_HOST$ export BET365_HOST=yourHostBET365_KEY$ export BET365_KEY=yourSecretKeyTesting# Test with pytestmaketests# Lint with flake8makelintCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-07-25)First release on PyPI.
Package: pybetaface
pybetafacePython libary for using the BetaFace API.To install dopip install pybetafaceExample Usage# Import the LibaryfrompybetafaceimportFaceData# Initialise FaceDataf=FaceData()# Upload the file with the default API Keydata=f.uploadFile("https://www.williamd47.net/betaface/man.jpg",key="d45fd466-51e2-4701-8da8-04351c872236")# Print the outputprint(data)
Package: pybetting
pybettingDocumentation:https://mattflow.github.io/pybettingSource Code:https://github.com/mattflow/pybettingPyPI:https://pypi.org/project/pybetting/Betting toolsInstallationpipinstallpybettingDevelopmentClone this repositoryRequirements:PoetryPython 3.7+Create a virtual environment and install the dependenciespoetryinstallActivate the virtual environmentpoetryshellTestingpytestDocumentationThe documentation is automatically generated from the content of thedocs directoryand from the docstrings
of the public signatures of the source code. The documentation is updated and published as aGithub project pageautomatically as part each release.ReleasingTrigger theDraft release workflow(pressRun workflow). This will update the changelog & version and create a GitHub release which is inDraftstate.Find the draft release from theGitHub releasesand publish it. When
a release is published, it'll triggerreleaseworkflow which creates PyPI
release and deploys updated documentation.Pre-commitPre-commit hooks run all the auto-formatters (e.g.black,isort), linters (e.g.mypy,flake8), and other quality
checks to make sure the changeset is in good shape before a commit/push happens.You can install the hooks with (runs for each commit):pre-commitinstallOr if you want them to run only for each push:pre-commitinstall-tpre-pushOr if you want e.g. want to run all checks manually for all files:pre-commitrun--all-filesThis project was generated using thewolt-python-package-cookiecuttertemplate.
Package: pybettor
Tools for Sports BettingThis package contains tools and functions to help sports bettors make more money!InstallationYou can install pybettor fromPyPiwith:pipinstall"pybettor"Running TestspipinstallpytestpytestRunning Lintingpipinstallflake8flake8.--count--max-complexity=15--max-line-length=128--statisticsExamplesImplied ProbabilityImplied probabilities, or break-even win percentage, can easily be found with this function. Here is an example with given odds of -300 (US Odds), 2.5 (Decimal Odds), 4.9 (Decimal Odds), 7/1 (Fractional Odds).implied_prob(-300,category="us")[0.75]implied_prob(2.5,category="dec")[0.4]implied_prob(7/1,category="frac")[0.125]Odds from ProbabilitiesLetâ€™s say you believe a bet has a 75% chance to cover, what would the price be? Using the implied odds function can give you the price based on your probability.implied_odds(0.75,category="us")[-300]implied_odds(0.75,category="dec")[1.33]implied_odds(0.75,category="frac")['1/3']implied_odds(0.75,category="all")American  Decimal Fraction  Implied Probability
0    -300.0     1.33   33/100                 0.75Converting OddsLetâ€™s say you want to convert the American Odds you see on the screen (-175) to another type.convert_odds(-175)American  Decimal Fraction  Implied Probability
0      -175     1.57      4/7             0.636364Special ThanksTo the entireA.I. Sportsteam!
Package: pybex
PythonBotEXpression (PyBEX)A simple Interpreted Dynamic Programming Language for describing chat bot commands and behavior.Installing PyBEXPyBEX is available on PyPI:python -m pip install -U pybexLanguage ElementsString"Hello, World"

'single or double - doesn\'t matter'

"""multiline
ones"""

'''are
supported'''Number# integers
69
420
1_000_000  # 1000000

# and floats
3.1415
5e-10Variableargs
sender
_underscoreFuncallsf()
f(g())
f(69, 420, 3.1415)
f("can take in any other language element")Interactive modeuse command:python -m pybexbex> say(99,
 ... "bottles of beer",
 ... "on the wall.")
99 bottles of beer on the wall.
bex> if(1, "pi", 3.1415)
'pi'Interpret from the fileuse command:python -m pybex <file_path>(replace <file_path> with path of your script file)say(if(
    int(input()),
    "non-zero input",
    "zero input"
))Inspiration for the project
Package: pybfc
PybfcPybfc - BranFuck compiler write in pythonTable of ContentsRequirementsInstallationWith PyPiWith GitHubUsageDiscussionsIssuesDonatingLicenseRequirementsPython>= 3.8InstallationPyPi$pip3installpybfcGitHub$gitclonehttps://github.com/TheAwiteb/pybfc
$cdpybfc
$python3setup.pyinstallUsageUsage: pybfc [OPTIONS] FILE_PATH

  Python BranFuck Compiler 🐍⚙

Arguments:
  FILE_PATH  BranFuck path to execute it.  [required]

Options:
  -d, --debug    Enable debugging with execution.
  -V, --version  Print Pybfc version and exit.
  --help         Show this message and exit.DiscussionsQuestion, feature request, discuss about pybfchereIssuesYou can report a bug fromhereDonatingNote: These addresses are for BEP20 tokensCurrencyAddressBinanceBNB0x4ab0974c7dfcdcdf24d8323a93b061d41e9cf3f0Binance USDBUSD0x4ab0974c7dfcdcdf24d8323a93b061d41e9cf3f0TetherUSDT0x4ab0974c7dfcdcdf24d8323a93b061d41e9cf3f0BitcoinBTC0x4ab0974c7dfcdcdf24d8323a93b061d41e9cf3f0Bitcoin CashBCH0x4ab0974c7dfcdcdf24d8323a93b061d41e9cf3f0LicenseGNU Affero General Public Version 3License
Package: pybfcontrol
#exampleimportpygamepygame.init()frompybfcontrol.bf_buttonimportBFButtonscreen=pygame.display.set_mode((600,420))defdo_click1(btn):pygame.display.set_caption('i click%s,ctl id is%s'%(btn._text,btn.ctl_id))btn.text='be click'btn=BFButton(screen,(20,20,160,40),text=u'test',click=do_click1)whileTrue:foreventinpygame.event.get():ifevent.type==pygame.QUIT:pygame.quit()exit()btn.update(event)screen.fill((255,255,255))btn.draw()pygame.display.update()
Package: pybfd3
PyBFD3This clone ofPyBFDmainly adds support for Python 3.x while keeping compatibility with Python 2.x. To prevent conflicts and possible confusion, the name of the module/package has changed topybfd3Because it seems thatpybfdis no longer maintained, I decided to create my own independent repository.ChangelogVersion 0.1.5Remove legacy distutils usage (thanks to @Bidski)Version 0.1.4Update PyBFD3 to be compatible with binutils > 2.29 (thanks to @Bidski)RequirementsThebinutils-devpackage must be installed first.InstallMethod 1: Via Python Package Index (PyPI).$ pip install pybfd3Method 2: Local installation.$ git clone https://github.com/b-2-r/pybfd3.git
$ pip install ./pybfd3Note:Depending on your pip version, you may need to add pip's--egginstall option to successfully complete the installation.Sample Session$ cd pybfd3/examples
$ chmod +x sample-session.py
$ ./sample-session.py
Usage : ./sample-session.py <binary>
$ ./sample-session.py `which sudo`
[+] Creating BFD instance...
[+] File format     : Linker/assembler/compiler output.
[+] Architecture    : Intel 386 (9)
[+] BFD target name : elf64-x86-64
[+] Entry point     : 0x403970
[+] Sections        : 27
[+] Selected section information:
	Name   : .text
	Index  : 13
	Length : 59 Kbytes
0x402B60 SZ=2 BD=0 IT=1	push   r15
0x402B62 SZ=2 BD=0 IT=1	push   r14
0x402B64 SZ=2 BD=0 IT=1	push   r13
0x402B66 SZ=2 BD=0 IT=1	push   r12
0x402B68 SZ=1 BD=0 IT=1	push   rbp
0x402B69 SZ=1 BD=0 IT=1	push   rbx
0x402B6A SZ=5 BD=0 IT=1	mov    ebx,0x63ec80
0x402B6F SZ=3 BD=0 IT=1	mov    rbp,rsi
0x402B72 SZ=7 BD=0 IT=1	sub    rsp,0xb8
[...]TODOsimproveget_symbolsto not throwing an error if no symbols are presentmacOS testing
Package: pybfe
Pybatfish EnterprisePybatfish Enterprise is a Python client forBatfish Enterprise.For the Python client for open-source Batfish, seePybatfish.PrerequisitesPybatfish Enterprise requires aBatfish Enterprisebackend to work.Installing Pybatfish EnterpriseWe highly recommend that you install Pybatfish Enterprise in a Python 3 virtual environment. Details on how to set one up can be foundhere.Once your virtual environment is setup and activated, run:python3 -m pip install pybfeUsing Pybatfish EnterpriseDocumentation on using Pybatfish Enterprise is bundled with the Batfish Enterprise service. Go tohttps://<BFE-HOST>/docs/pybfe.html, where <BFE-HOST> is the hostname or IP address where the Batfish Enterprise is hosted.
Package: pybfilter
=========`pybfilter` is a module that include a Bloom Filter data structure.A Bloom filter is a space-efficient probabilistic data structure that is used to test whether an element is a member of a set.usage----->>> import pybfilter>>> bf = pybfilter.BloomFilter(n=1000, error=0.01)>>> bf.add(1)True>>> bf.add(1)False>>> 1 in bfTrue>>> 2 in bfFalseKeywords: Bloom FilterPlatform: UNKNOWNClassifier: Development Status :: 3 - AlphaClassifier: Intended Audience :: DevelopersClassifier: License :: OSI Approved :: MIT LicenseClassifier: Programming Language :: Python :: 3Requires-Python: >=3