Saravanan666/pypi-org huggingface dataset:
Package: behavioural-clusters
This is a distribution class for clustering of all the D2C customers using transactional and GA dataIt consist of two functions for now which areInstallationpip install behavioural_clustersExamplefrom behavioural_clusters import filter_data
from behavioural_clusters import create_customer_kpis
from behavioural_clusters import browsing_category
from behavioural_clusters import browsing_pivot
from behavioural_clusters import algo_data
from behavioural_clusters import generate_cluster_inputs
Package: behavython
To be used in conjunction withBonsai-RXto extract behavior from video·Report Bug·Request FeatureTable of ContentsAbout the projectBuilt WithGetting StartedPrerequisitesInstallationUsageContributingLicenseContactAcknowledgmentsAboutThis software was developed to be used in conjunction withBonsai-RXto extract behavior from video. It is a simple interface that allows the user to select the data and image files that were generated by Bonsai and then run the analysis. The results are saved in a csv file that can be used for further analysis.The software also implements bindings to theDeepLabCutpackage, allowwing users to run the analysis using pretrained models on their data.Built WithPythonQt DesignerGetting StartedPrerequisitesdeeplabcutseabornpyside6openpyxlscikit-imagepandasnumpymatplotlibtkscipyFor a simple way to keep up to date with requirements, reference the requirements.txt fileInstallation as a pip packageFor the installation you need a simple command that you can get by one of two ways:Copying and pasting from here:"pip install behavython" (without quotation[""] marks)Going to the Pypi site and copying from there:PyPi frontpageAt the moment, Behavython was mainly tested on WindowsUsageWindowsOpen the interface typing "behavython" on the command lineIf you installed it as a pip package you can just type "behavython" on the command lineIf you downloaded the source code you need to go to the folder where you downloaded it and type "python Bbehavython_front.py" on the command lineSelect all the photo-data pairs that you want to analyzeIn this step is important that you don't forget to verify that you got all the bonsai files, including the data and a image of the arena that you are analyzingWait for the program to finish the analysisCurrently the program looks like it freezed when running. It is expected behavior but we are looking into it. Right now you only need to wait a little bit.When finished the progress bar will show 100% and a preview of the results will be available on the rightSee theopen issuesfor a full list of proposed features (and known issues).ContributingContributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make aregreatly appreciated.If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue explaining what is the problem. Also, you can reach us by mail - listed at the end :)LicenseDistributed under the GNU General Public License v3.0. SeeLICENSE.txtfor more information.ContactJoão Pedro Carvalho Moreira -mcjpedro@gmail.comMatheus Costa -matheuscosta3004@gmail.comAcknowledgmentsFlávio Mourão:Github:Flávio MourãoTwitter:@F_Mourao_Lab:Núcleo de NeurociênciasDeveloped atNucleo de Neurociencias - NNCUniversidade Federal de Minas Gerais - UFMGBrazil
Package: be-helpers
BE HelpersCustom brainelectronics python helper modulesGeneralCollection of custom brainelectronics specific python helper modules.InstallationUsageContributingUnittestsCreditsInstallationpipinstallbe-helpersUsagefrombe_helpersimportModuleHelperimporttimefrompathlibimportPath# default name is 'be_helpers.module_helper'my_logger=ModuleHelper.create_logger()# set logger level to INFOModuleHelper.set_logger_verbose_level(logger=my_logger,verbose_level=3)# check 'a' to be an option of ['a', 'b', 'c'], result will be Trueresult=ModuleHelper.check_option_values(options=['a','b','c'],option='a')print('"a" is an option of ["a", "b", "c"]:{}'.format(result))# "a" is an option of ["a", "b", "c"]: True# get current unix timestamp and format itnow=ModuleHelper.get_unix_timestamp()time_format="%H:%M:%S"print('{}'.format(ModuleHelper.format_timestamp(timestamp=now,format=time_format)))# 11:30:01# create a random character number string of length 10print('{}'.format(ModuleHelper.get_random_string(length=10)))# 235LS5AY6BPC# convert a string to a "uint16_t" list, useful for Modbus communicationsresult=ModuleHelper.convert_string_to_uint16t(content="test")print('"test" as uint16_t:{}'.format(result))# "test" as uint16_t: [29797, 29556]# check for valid files or foldershere=ModuleHelper.get_full_path('.')ModuleHelper.check_file(here/'README.md','.md')# TrueModuleHelper.check_folder(here)# True# load YAML or JSON files as dictionariesconfig=ModuleHelper.load_dict_from_file(here/'tests/data/valid.json')config=ModuleHelper.load_dict_from_file(here/'tests/data/valid.yaml')# {'key': 'val', 'key2': {'key_nested': 'val_nested'}, 'key3': ['asdf', 123, {'key4': 'val4'}]}# save dictionaries as JSON or YAML filesModuleHelper.save_dict_to_file(path=here/'example/cfg.json',content=config)ModuleHelper.save_dict_to_file(path=here/'example/cfg.yaml',content=config)# TrueContributingUnittestsRun the unittests locally with the following command after installing this
package in a virtual environment# run all testsnose2--configtests/unittest.cfg# run only one specific testsnose2tests.test_module_helper.TestModuleHelper.test_set_logger_verbose_levelGenerate the coverage files withpythoncreate_report_dirs.py
coveragehtmlThe coverage report is placed atbe-helpers/reports/coverage/html/index.htmlCreditsBased on thePyPa sample project.
Package: be-holder
Description:A python dectorater to enforce type checks on your python functions for your stupid colleagues who pass int type when you clearly told them to pass string.
ヽ(ಠ_ಠ)ノYou can define parameter and return types for your python functions using type hints (check them out here :https://mypy.readthedocs.io/en/stable/cheat_sheet_py3.html) and the watcher decorator over them to handle the dirty work.Currently we only support positional arguments only and single return types but will add support for keyword arguments and mutiple return types.Raise and issue in the gitrepo if you find any bugs or need a feature.Types Checking Supported forPositional ParametersSingle return typesUser defined data typesExamplefrombe_holderimportwatcher@watcherdeff():# Will work as normalreturn"pass"@watcherdeff1(a:str,b):#Will be typed checked and will raise TypeError if types do not matchreturn"pass"@watcherdeff2(a:str,b:int):return"pass":@watcherdeff3()>str:#Will raise a type error due to return type not matching function definitionreturn1@watcherdeff4(a:str)->str:return"pass"if__name__=="__main__":f4(1)f2("s",1)f2(1,1)
Package: beholder-client
beholder-pyPython client library forbeholder.BuildThis project is built withPoetry.You can build the project with the following command:poetrybuildThis will create adist/directory with the builtbeholderpackage.InstallYou can install the built package with the following command:pipinstalldist/beholder-<VERSION>.whlDevelopmentTo configure the project for development, install Poetry and runpoetryinstall
poetryshellThis will create a virtual environment for the project, install all dependencies into it, then spawn a new shell with the environment activated.© Monterey Bay Aquarium Research Institute, 2022
Package: behvpn
A fast tunnel proxy that help you get through firewalls.中文说明InstallYou’ll have a client on your local machine, and install a server on a
remote server.ClientWindows/OS
XAndroid/iOSOpenWRTServerDebian / Ubuntu:apt-get install python-pip python-m2crypto
pip install shadowsocksCentOS:yum install m2crypto python-setuptools
easy_install pip
pip install shadowsocksConfigurationOn your server create a config file/etc/shadowsocks.json. Example:{
    "server":"my_server_ip",
    "server_port":8388,
    "local_address": "127.0.0.1",
    "local_port":1080,
    "password":"mypassword",
    "timeout":300,
    "method":"aes-256-cfb",
    "fast_open": false,
    "workers": 1
}Explanation of the fields:NameExplanationserverthe address your server listensserver_portserver portlocal_addressthe address your local listenslocal_portlocal portpasswordpassword used for encryptiontimeoutin secondsmethodencryption method, “aes-256-cfb” is recommendedfast_openuseTCP_FASTOPEN, true / falseworkersnumber of workers, available on Unix/LinuxRunssserver-c/etc/shadowsocks.jsonon your server. To run it in
the background, useSupervisor.On your client machine, use the same configuration as your server, and
start your client.If you use Chrome, it’s recommended to useSwitchySharp.
Change the proxy settings toprotocol: socks5
hostname: 127.0.0.1
port:     your local_portIf you can’t installSwitchySharp,
you can launch Chrome with the following arguments to force Chrome to
use the proxy:Chrome.exe --proxy-server="socks5://127.0.0.1:1080" --host-resolver-rules="MAP * 0.0.0.0 , EXCLUDE localhost"If you can’t even download Chrome, find a friend to download aChrome
Standaloneinstaller for you.Command line argsYou can use args to override settings fromconfig.json.sslocal -s server_name -p server_port -l local_port -k password -m bf-cfb
ssserver -p server_port -k password -m bf-cfb --workers 2
ssserver -c /etc/shadowsocks/config.jsonList all available args with-h.Wikihttps://github.com/clowwindy/shadowsocks/wikiLicenseMITBugs and IssuesTroubleshootingIssue
TrackerMailing list
Package: beibo
Beibo, predict the stock market 💸Beibois aPythonlibrary that uses severalAI prediction modelsto predictstocks returnsover a defined period of time.It was firstly introduced in one of my previous package calledEmpyrial.Disclaimer: Information is provided 'as is' and solely for informational purposes, not for trading purposes or advice.How to install 📥pipinstallbeiboHow to use 💻frombeiboimportoracleoracle(portfolio=["TSLA","AAPL","NVDA","NFLX"],#stocks you want to predictstart_date="2020-01-01",#date from which it will take data to predictweights=[0.3,0.2,0.3,0.2],#allocate 30% to TSLA and 20% to AAPL...(equal weighting  by default)prediction_days=30#number of days you want to predict)OutputAbout AccuracyMAPEInterpretation<10Highly accurate forecasting 👌10-20Good forecasting 🆗20-50Reasonable forecasting 😔>50Inaccurate forecasting 👎Models availableModelsAvailabilityExponential Smoothing✅Facebook Prophet✅ARIMA✅AutoARIMA✅Theta✅4 Theta✅Fast Fourier Transform(FFT)✅Naive Drift✅Naive Mean✅Naive Seasonal✅Stargazers over timeContribution and IssuesBeibo uses GitHub to host its source code.Learn more about theGithub flow.For larger changes (e.g., new feature request, large refactoring), please open an issue to discuss first.If you wish to create a new Issue, thenclick here to create a new issue.Smaller improvements (e.g., document improvements, bugfixes) can be handled by the Pull Request process of GitHub:pull requests.To contribute to the code, you will need to do the following:ForkBeibo- Click theForkbutton at the upper right corner of this page.Clone your own fork.  E.g.,git clone https://github.com/ssantoshp/Beibo.gitIf your fork is out of date, then will you need to manually sync your fork:Synchronization methodCreate a Pull Requestusingyour forkas thecompare head repository.You contributions will be reviewed, potentially modified, and hopefully merged into Beibo.Contributions of any kind are welcome!AcknowledgmentsUnit8forDarts@ranroussiforyfinanceThis random guy on Python's Discord server who helped me@devnull10 on Reddit who warned me when I called the package The OracleContactYou are welcome to contact us by email atsantoshpassoubady@gmail.comor in Beibo'sdiscussion spaceLicenseMIT
Package: beiboot
Getdeck BeibootGetdeck Beiboot(or just Beiboot for brevity) is a Kubernetes-in-Kubernetes solution. It was born from the idea to
provide Getdeck users a simple yet flexible solution to spin uphybrid cloud developmentinfrastructure. This is
useful for Kubernetes development workloads which grew too large to run on a development machine (or with pony workloads
on MacOS and Windows machines).Beiboot ClientThe Beiboot client is a Python API to manage Beiboot clusters. It can set up and tear down Kubernetes instances
as well as establish connections.
Package: beige
Python native Exchange engineBeigeWhy Beige?Because it's not particularly attractive,
there's probably a better color out there,
but it kinda works.
I was surprised that there is no package existing with the namebeigeyet!A simple, slow, exchange libraryBeige is a pretty simple library that provides the full functionality of a matching engine, with features for tracking account balances and ongoing quote.ExampleImport the right bits, and spin up the enginefrombeigeimportEngine,Order,Market,Limit,Side# Create the engineeng=Engine()Account balances can be initialized at the start of the market session# Start a person off with some given account balanceeng.accounts.init('person-a',{'$':100.01,'TSLA':1})# Person is missing 1 dollar, and owns 10 'what?'eng.accounts.init('person-b',{'$':-1,'what?':10})Then orders can be submitted in a fairly intuitive way:# Limit buy order for 'what?' security, 1# Store the ID, and we can query its status lateroid=eng.submit(Order(instrument='what?',type_=Limit(10),side=Side.Sell,quantity=5,entity='person-b',))# Submit a market order thateng.submit(Order('WHAT?',Market(),Side.Buy,1,'person-a',))Once the ID for an order has been retrieved, we can see the full information on the order at any time:o=eng.status(oid)# type(o) == dict# o.keys() == ['sym','price','side','qty','acct','id','submitted','filled','averagepx','filledtime','status']A full chronological transaction dataset is availabledf=eng.txs# df.columns = ['qty','px','time','sym']At any point, a quote can be requested.
Note thatNonewill be returned for any value that isn't available, for example,lastwill be empty if no transactions have taken place yet.bid,ask,last,bidsize,asksize,lastsize=eng.quote('TSLA')LimitationsSpeed. The software hasn't been fully optimized and many of the data structures could really benefit from a bit of love and care.Integer-only quantitiesAll account entities and securities are case insensitive, and will be displayed in all capsthe "$" security encodes cash, and is the base unit for all security transactions. Sorry ex-USA users!TestingCorrectness =>python3 tests.pySpeed =>python3 tests.py speedProfiler =>python3 tests.py profileI'm averaging about 0.15 ms per order execution.
This works in the sequential market I'm working on, but this may be orders of magnitude slower than needed in your use case.
Feel free to improve the speed, but please pull request back to me.
Package: beipack
beipackbeipackis a collection of utilities to assist with packaging and launching Python programs in unusual ways.The motivating force behind this project is the desire to execute a complex multi-module Python program — specifically,Cockpit— on a computer where it's not installed.beipackis being developed as a freestanding project in hopes that it might be helpful to others.Some key goals:ability to package large multi-file or multi-module Python programs into a single standard Python file (beipack)ability to send and execute this file via the stdin of the Python interpreter in another environment, viassh,flatpak-spawn, or other container toolsscripts compatible with the Python REPL, which allows injecting them topython -i, without sending EOF, allowing stdin to be used by the script, after it has been sentself-replicating ability: the target script should have access to its own source code, so that it can send itself on to further invocationsno requirement for any ability to write to disk (and no temporary files) but an optional ability to cache the sent program in~/.cache/to avoid the need to send large files over slow connections on future invocationssupport for compressing Python programs to reduce the amount of data to be sent over slow connectionsThe intent is to develop the above features in a way that's as modular as possible, to allow mix-and-match of the required functionalities.
Package: beizer-curves
beizer-curvesA python library for generating beizer curves.Installationpipinstallbeizer-curvesUsagedefbeizer_curve(points,output_points_count:int,destructive:bool=False,dtype:np.dtype=np.int64,):Generate a beizer curve.points- Knots in format:[[x1, x2, ..., xn], [y1, y2, ..., yn], [z1, z2, ..., zn]].output_points_count- How many points of the curve to generate.destructive- Allow function to modifypointsarray. Don't set to true, if you want to usepointsarray later.dtype- dtype of array of returned points of the curve.Points of a curve are returned in format:[[x1, x2, ..., xn], [y1, y2, ..., yn], [z1, z2, ..., zn]], where n isoutput_points_count.defrandom_beizer_curve(start_point,end_point,output_points_count:int,random_points_count:int=1,point_spread:float=1,noise_max_offset:float=0,noise_rate:float=0.5,dtype=np.int64,return_forming_points:bool=False,):Generate a random beizer curve, which starts at start_point and ends at end_point.start_point,end_point- coordinates of start and end points of curve in format[x, y, z, ...].output_points_count- How many points of the curve to generate.ifoutput_points_count<0:output_points_count=math.ceil(distance/-output_points_count)Wheredistanceis distance between start and end.random_points_count- How many knots to generate.point_spread- A scale of a rectangular figure with corners of start_point and end_point, in bounds of which random knots are generated. Has to be > 0.noise_max_offset- Max offset of a curve point.ifoutput_points_count<0:output_points_count=math.ceil(distance/-output_points_count)Wheredistanceis distance between start and end.noise_rate- A part of curve points to apply noise offset to. Has to belong to [0; 1].dtype- dtype array of returned points of the curve.return_forming_points-return points, curve if return_forming_points else curve, wherepointsare randomly generated knotsUsage exampleimportrandomimportmatplotlib.pyplotaspltimportnumpyasnpfrombeizer_curvesimport*defplot_curve(points_count,i):start=[random.randrange(1,2000),random.randrange(1,2000)]noise=-200*iend=[random.randrange(1,2000),random.randrange(1,2000)]points,curve=random_beizer_curve(start,end,output_points_count=50,random_points_count=points_count,noise_max_offset=noise,noise_rate=0.25,dtype=np.float64,return_forming_points=True,)fig=plt.figure()plt.axis("equal")plt.scatter(curve[0],curve[1])plt.scatter(points[0],points[1],color='red')fig.savefig(f"example_{points_count}_{i+1}.png")Example curves
Package: bejjoeqq
# BejjoLib## IntroductionBeta Version of BejjoLib Python, Stay with us.## Code Samplesbejjo.string(char=8,count=1,upper=True,lower=True,numeric=True)
- char : length of random string
- count : return a list if count>1
- upper : upper case is True as default
- lower : lower case is True as default
- numeric : numeric is True as defaultbejjo.char(count=1,upper=True,lower=True,numeric=True)
- count : return a list if count>1
- upper : upper case is True as default
- lower : lower case is True as default
- numeric : numeric is True as default## InstallationWindows pip
- pip install bejjoeqqChange Logv1.1(01/07/2020)First Releasev.4(14/07/2020)Beta Version
Package: bekeshbiron
A VERY useful package that suppresses warnings!Free software: GNU Lesser General Public License v3 or later (LGPLv3+)Installationpip install bekeshbironYou can also install the in-development version with:pip install git+ssh://git@https://github.com/Salehbigdeli/bekeshbiron/Salehbigdeli/bekeshbiron.git@masterDocumentationTo use the project:importbekeshbironDevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.0 (2020-08-11)First release on PyPI.
Package: beku-stackabletech
bekuVersion: 0.0.9InstallationWe recommend to usepipx:pipx install beku-stackabletechBut you can also usepip:# from PyPI
pip install beku-stackabletech
# from GitHub
pip install git+https://github.com/stackabletech/beku.py.git@masterUsagecd <stackable operator directory>
rm -rf tests/_work && beku
cd tests/_work && kubectl kuttl testAlso see theexamplesfolder.DescriptionFast Kuttl tests expander for Stackable integration tests.beku -i tests/test-definition.yaml -t tests/templates/kuttl -k tests/kuttl-test.yaml.jinja2 -o tests/_workRelease a new versionUpdate the version in:pyproject.tomlversion.pyREADME.md: version and pip install command.Update the CHANGELOG.
Commit and tag.
Build and publish:rm -rf dist/
python -m build --wheel .
twine upload dist/*
Package: bel
Informational badgesBEL Python PackageMain documentation is at<http://bel.readthedocs.io/en/latest/>.Currently handles BEL 2.0.0, but it is easily extensible to new versions of BEL.Installpip install belPlanned features[Done] Allow multiple BEL Specification files for different BEL versions (including experimental versions)[Done] Provide a standard EBNF file for parser generation for each BEL Specification[Done] Identify syntax issues in the statement and provide suggestions on fixing them[Done] Identify semantic issues in the statement and provide suggestions on fixing them[Done] Identify unknown Namespaces or Namespace values[Done] Convert BEL statements into an AST and then back into a BEL StatementProvide autocompletion suggestions given a location in the BEL StatementRead a Nanopub and validate the full Nanopub, e.g. the BEL statement, Annotations, Citation, etcBEL Pipeline - Process new Nanopubs in NanopubStore into Edges and load in EdgeStore[Done] Convert BELScript into BEL NanopubsCommand line interface (partially done)