Saravanan666/pypi-org huggingface dataset:
Package: brzipcode
brzipcodeé uma lib Python simples para retornar o endereço a partir do CEP, com dados provenientes do webservicebrzipcode.com.Para instalar execute:pip install brzipcodeE então usar conforme abaixo:>>> from brzipcode import BRZipCode
>>> print BRZipCode.get('04538132', token='ycmVyGJO3HAw...') # *
{u'status': True, u'city': u'S\xe3o Paulo', u'state': u'SP', u'neighborhood': u'Itaim Bibi', u'address': u'Avenida Brigadeiro Faria Lima - de 3252 ao fim - lado par'}** Para solicitar um token acessehttp://brzipcode.com/(gratuito) **Caso não encontre nenhum resultado:>>> print BRZipCode.get('00000000', token='ycmVyGJO3HAw...')
{u'status': False, u'error_message': u'not_found'}Suporte a projetos DjangoPara utilizar em seu projeto Django, incluaBRZIPCODE_TOKENe atualize oINSTALLED_APPSno arquivosettings.pyBRZIPCODE_TOKEN = 'ycmVyGJO3HAw...'

...

INSTALLED_APPS = (
    ...
    'brzipcode',
)Adicionar a url do serviço nourls.pyurlpatterns = patterns('',
    ...
    url(r'^brzipcode/', include('brzipcode.urls')),
)E acesse:http://localhost:8000/brzipcode/?zip_code=04538132
Package: bs2json
Convert HTML Tags of BeautifulSoup class to JSON data.InstallationThis package is available on PyPi. Just usepip install -U bs2jsonto install it. Then you can import it usingfrom bs2json import bs2json.Example Syntaxfrombs2jsonimportBS2Jsonhtml='<html><head><title>Page Title</title></head><body><h1>My First Heading</h1><p>My first paragraph.</p></body></html>'bs2json=BS2Json(html)# Convert soup to JSONjson_obj=bs2json.convert()# Save JSON to filebs2json.save()# Print prettified outputbs2json.prettify()Plus pointYou can also use the module methods as an extension to theelement.Tag.
For more information, see theexample_ext.pyfile from examplesWhat's newAbility to initialize the bs4 object from given stringConverts a single bs4 tag or a tag matching the given string to a JSON objectOption to include or exclude comments in the JSON representationOption to remove whitespaces from the start and end of textAbility to save the converted object to a fileAbility to prettify the output of the last converted objectOption to set custom labels for converting BeautifulSoup elements to JSONContributingWe appreciate all contributions. If you are planning to contribute any bug-fixes, please do so without further discussions.If you plan to contribute new features etc. please first open an issue or reuse an exisiting issue, and discuss the feature with us. We will discuss with you on the issue timely or set up conference calls if needed.We appreciate all contributions and thank all the contributors!
Package: bs42frame
bs4 to pd.DataFrameTested against Windows / Python 3.11 / Anacondapip install bs42frameParseHTMLcontentandextractinformationusingBeautifulSoup.ThisfunctiontakesHTMLcontentasinput,parsesitusingBeautifulSoup,andextractsinformationabouttheHTMLstructure,tagattributes,tagtext,andtheBeautifulSoupobjectforeachelementfoundintheHTML.Args:html(str,bytes,orfilepath):TheHTMLcontenttobeparsed.Itcanbeprovidedasastring,bytes,orafilepath.Ifafilepathisprovided,thefunctionwillattempttoreadthefile.Returns:pandas.DataFrame:ADataFramecontainingtheextractedinformationfromtheHTML.TheDataFramecolumnsinclude'aa_tag'(HTMLtagname),'aa_attrs'(listoftagattributes),'aa_text'(textcontentofthetag),'aa_soup'(BeautifulSoupobjectforthetag),'aa_old_index'(originalindexofthetag),'aa_key'(attributekey),and'aa_value'(attributevalue).Example:frombs42frameimportparse_htmldf=parse_html(html=r"C:\Users\hansc\Downloads\Your Repositories.mhtml")#      aa_tag            aa_text                                          aa_soup  aa_old_index                     aa_key             aa_value# 1000   span  Import repository  [\r\n                Import repository\r\n\r\n]           274       ActionListItem-label                class# 1001     li                                                                  []           275               presentation                 role# 1002     li                                                                  []           275                       true          aria-hidden# 1003     li                                                                  []           275                       true  data-view-component# 1004     li                                                                  []           275  ActionList-sectionDivider                class
Package: bs4tag
This library is based on the sources and definitions of yattag with the fondamental difference that BeautifulSoup is used as the html renderer.Differences between bs4tag and yattag* At this time, only SimpleDoc has been converted, Doc class is work in progress. *No support for custom indentation (indent)stag_end option is not availableThe SimpleDoc/Doc object contains a BeautifulSoup intance in the soup attributeasis() and ttls() functions added to SimpleDoc( tutorial for both libraries:yattag.organdBS4)Basic exampleNested html tags, no need to close tags, same as yattag.frombs4tagimportDocdoc,tag,text=Doc().tagtext()withtag('html'):withtag('body',id='hello'):withtag('h1'):text('Hello world!')print(doc.getvalue())With BeautifulSoup added functionalitiesInsert bs4tag document into a BeautifulSoup instance.defbody_text():doc,tag,text=SimpleDoc().tagtext()withtag('h1'):text('Hello world!')returndoc.soupdoc,tag,text=SimpleDoc().tagtext()withtag('html'):withtag('body',id='hello'):passdoc.soup.find(id='hello').append(body_text())print(doc.getvalue())# <html><body id="hello"><h1>Hello world!</h1></body></html>Installationpip3 install bs4tagThis library is compatible with the tutorial onyattag.orgGitHub repo:https://github.com/ceprio/bs4tagDerived from:https://github.com/leforestier/yattag
Package: bsapi
bsapiA BrowserStack Rest Api ClientProvides wrapper classes for the BrowserStack rest apiSetupSet your username and key to environment variables.export BROWSERSTACK_USERNAME = <your username>
export BROWSERSTACK_KEY = <your key>or set them on the settings objectfrombsapiimportSettingsSettings.username=<yourusername>Settings.password=<yourkey>App AutomateAppiumGet the logs for a BrowserStack sessionimportosfromappiumimportwebdriverfrombsapi.app_automate.appiumimportAppAutomateSessionusername=os.getenv("BROWSERSTACK_USERNAME")key=os.getenv("BROWSERSTACK_KEY")desired_caps={"build":"Python Android","device":"Samsung Galaxy S8 Plus","app":"<your app url>","browserstack.networkLogs":"true","browserstack.deviceLogs":"true","browserstack.appiumLogs":"true","browserstack.video":"true"}url=f"https://{username}:{key}@hub-cloud.browserstack.com/wd/hub"driver=webdriver.Remote(url,desired_caps)session_id=driver.session_iddriver.quit()session=AppAutomateSession.by_id(session_id)session.save_session_logs("session.log")session.save_appium_logs("appium.log")session.save_device_logs("device.log")session.save_network_logs("network.log")session.save_video("session.mp4")Upload an application to BrowserStackapp=AppsApi.upload_app("MyApp.apk")Get the badge key for a projectprojects=ProjectsApi.recent_projects()project=[pforpinprojectsifp.name=="My Project"][0]badge_key=ProjectsApi.get_badge_key(project.project_id)badge_markdown=f"[![BrowserStack Status](https://app-automate.browserstack.com/badge.svg?badge_key={badge_key})](https://app-automate.browserstack.com/public-build/{badge_key}?redirect=true)"
Package: bsavi
BSAVIBSAVI (Bayesian Sample Visualizer) is a tool to aid likelihood analysis of model parameters where samples from a distribution in the parameter space are used as inputs to calculate a given observable. For example, selecting a range of samples will allow you to easily see how the observables change as you traverse the sample distribution. At the core of BSAVI is theObservableobject, which contains the data for a given observable and instructions for plotting it. It is modular, so you can write your own function that takes the parameter values as inputs, and BSAVI will use it to compute observables on the fly. It also accepts tabular data, so if you have pre-computed observables, simply import them alongside the dataset containing the sample distribution to start visualizing!InstallationDependenciesPython versions $\geq$ 3.8 and $<$ 3.11 are supported.Holoviews $\geq$ 1.15.4 (this package and its dependencies will be installed automatically)Bokeh 2.4.3BSAVI can be installed with pip:python -m pip install bsaviOr, if you want to test the latest changes, you can clone the repository withgit clone https://github.com/wen-jams/bsavi
cd bsavi
python setup.py installGetting StartedTest InstallationTo verify that bsavi and all the dependencies have been installed correctly, try running:import bsavi as bsvIf no errors appear, all the dependencies were installed correctly and we're ready to start visualizing!ExampleDownload and run thelive_data_examplenotebook in thetutorialsfolder to see an example of how bsavi can be used.Here's BSAVI being used in an astrophysics context! The parameters come from a cosmological model of dark matter, and the observables are the matter and CMB power spectra.ContributingMake feature requests and bug reports using the issue tracker:https://github.com/wen-jams/bsavi/issuesLicenseMIT LicenseContactjimmywen74@gmail.com
Package: bsb
Note:The scaffold framework is still under heavy development. Please check theKnown Issuessection at the bottom for important issues that fell victim to our
deadlines and will be solved at a later date.BSB: A scaffold modelling frameworkThis package is intended to facilitate spatially, topologically and morphologically
detailed simulations of brain regions developed by the Department of Brain and
Behavioral Sciences at the University of Pavia.InstallationpipThis software can be installed as a Python package from PyPI through pip:pip install bsbDevelopersDevelopers best use pip'seditableinstall. This creates a live link between the
installed package and the local git repository:git clone git@github.com:dbbs-lab/bsb
 cd bsb
 pip install -e .[dev]
 pre-commit installUsageThe scaffold framework can be used through the command line interface or as a python package.Command line interface (CLI)Run the framework in the command line with subcommandcompileto compile a network
architecture.bsb --config=mouse_cerebellum_cortex_noTouch.json compile -x=200 -z=200 -pTo run with different configurations, change the config argument to the relative path of a
.json config file. The-pflag indicates that the compiled network should be plotted
afterwards and can be omitted.Python packageThe central object is thebsb.core.Scaffoldclass. This object requires absb.config.ScaffoldConfiginstance for its construction. To emulate the CLI
functionality you can use theJSONConfigclass and provide the relative path to the
configuration file.frombsbimportScaffoldfrombsb.configimportJSONConfigconfig=newJSONConfig(file='mouse_cerebellum_cortex_noTouch.json')scaffoldInstance=newScaffold(config)This scaffold instance can then be used to perform the subcommands available in the CLI by
calling their corresponding functions:scaffoldInstance.compile_network()Plotting network architectureAfter callingcompile_networkthe scaffold instance can be plotted:scaffoldInstance.plot_network_cache()ContributingAll contributions are very much welcome.
Take a look at thecontribution guideKnown issuesNo configuration serializationWhen modifying the config object through scripts and then saving it to file, you'll store
the original configuration file text, and you won't actually serialize the modified objectWe will fix this by version 4.0If MPI is installed but mpi4py is not undefined behavior may occurThe amount of NEST virtual processes is determined by using mpi4py to get the amount of
MPI processes. But if the package is not installed it is assumed no MPI simulations will
be ran and the amount of virtual processes might be lower than expected when used in
combination with OpenMP. Be sure topip installusing the[MPI]requirement tag.
Package: bsb-core
:closed_book: Read the documentation on https://bsb.readthedocs.io/en/latestBSB: A component framework for neural modellingDeveloped by the Department of Brain and Behavioral Sciences at the University of Pavia,
the BSB is a component framework for neural modelling, which focusses on component
declarations to piece together a model. The component declarations can be made in any
supported configuration language, or using the library functions in Python. It offers
parallel reconstruction and simulation of any network topology, placement and/or
connectivity strategy.InstallationThe BSB requires Python 3.9+.pipThis software can be installed as a Python package from PyPI through pip:pip install "bsb>=4.0.0b0"DevelopersDevelopers best use pip'seditableinstall. This creates a live link between the
installed package and the local git repository:git clone git@github.com:dbbs-lab/bsb-core
 cd bsb
 pip install -e .[dev]
 pre-commit installUsageThe scaffold framework is best used in a project context. Create a working directory for
each of your modelling projects and use the command line to configure, reconstruct or
simulate your models.Creating a projectYou can create a quickstart project using:bsb new my_model --quickstart
cd my_modelReconstructing a networkYou can use your project to create reconstructions of your model, generating cell positions
and connections:bsb compile -pThis creates anetwork fileand plots the network.Simulating a networkThe default project currently contains no simulation config.ContributingAll contributions are very much welcome.
Take a look at thecontribution guideAcknowledgementsThis research has received funding from the European Union’s Horizon 2020 Framework
Program for Research and Innovation under the Specific Grant Agreement No. 945539
(Human Brain Project SGA3) and Specific Grant Agreement No. 785907 (Human Brain
Project SGA2) and from Centro Fermi project “Local Neuronal Microcircuits” to ED. We
acknowledge the use of EBRAINS platform and Fenix Infrastructure resources, which are
partially funded from the European Union’s Horizon 2020 research and innovation
programme through the ICEI project under the grant agreement No. 800858
Package: bsb-lookup
BSB LookupAustralian Bank State Branch number enricher used for validating and looking up bank names given a BSB number. Ideal for financial applications, banking software, and fintech solutions.Table of ContentsInstallationUsageBackgroundContributingLicenseContactInstallationBefore installing, ensure you have Python 3.x installed on your system. You can install BSB Lookup using pip:pipinstallbsb-lookupUsageHere's a simple example to get started with BSB Lookup:frombsbimportto_bank_inforesult=to_bank_info(bsb="082055")print(result)# >>> BankInfo(# ...     prefix_rule=BSBPrefixRule(key="NAB", abbreviation="National Australia Bank Limited", bsb_prefixes=["08"]),# ...     directory_entry=BSBDirectoryRow(# ...         bsb="082055",# ...         financial_institution_code="NAB",# ...         name="Private NSW Banking Suite",# ...         street="Level 5 2 Carrington St",# ...         suburb="Sydney",# ...         state="NSW",# ...         postcode="2000",# ...         payments_flag="PEH",# ...     ),# ...     npp_support=NPPSupport.SUPPORTED,# ... )BackgroundA BSB, or Bank State Branch number, is a six-digit code used to identify the specific branch of an Australian bank or financial institution. The BSB is normally used in association with the account number system used by each financial institution.ContributingContributions are welcome! If you have a suggestion or want to contribute code, please follow these steps:Fork the repositoryCreate your feature branch (git checkout -b feature/AmazingFeature)Commit your changes (git commit -am 'Add some AmazingFeature')Push to the branch (git push origin feature/AmazingFeature)Open a pull requestLicenseThis project is licensed under theMIT License- see the LICENSE file for details.ContactFor support or queries, reach out toilan@refundid.com
Package: bscal
Bikram Sambat CalendarInstallationUsing pippip install bscalUsing pipxpipx install bscalUsageDisplay calendar in BS format$bscalPoush 2080Su Mo Tu We Th Fr Sa1  2  3  4  5  6  78  9 10 11 12 13 1415 16 17 18 19 20 2122 23 24 25 26 27 2829[!TIP]
You can provideyearto display a calendar for that year, and also optionally specify themonthfor a specific month's calendar.Display the current BS date:$bsdateTue Poush 17 09:14:14 +0545 2080Display a specific date (from given ISO format)$bsdate2016-09-08Thu Bhadra 23 09:17:21 +0545 2073Display a specific date (represented as a Unix timestamp):$bsdate1473305798Thu Bhadra 23 09:21:38 +0545 2073Convert BS date to AD format$bsdate-c2073-05-23Thu Sep  8 09:19:00 +0545 2016
Package: bscc
Look at the world from perspective of one shipwright who come fromBSCCPlease take a look at our documentation for how to install and use bscc:InstallationUsageUpdates are released regularly, with a new version every 3 months. More details can be found in our documentation:Release notesRelease processIf you find bugs, need help, or want to talk to the developers please use our mailing lists or chat rooms:Issue trackingUser IRCDiscourse channelIf you want to get involved head over to GitHub to get the source code, look at our development documentation and feel free to jump on the developer mailing lists and chat rooms:GitHub pageDev documentationDev mailing listDev IRCCode of ConductEveryone interacting in the bscc project’s codebases, issue trackers, chat
rooms, and mailing lists is expected to follow theBSCC Code of Conduct.
Package: bscearth.utils
bscearth.utils is a package with shared code and tools for various BSC-ES department projects.Get involved or contact us:GitLab:	        https://earth.bsc.es/gitlab/ces/bscearth.utilsMailing List:	ces@bsc.esHOW TO DEPLOY/SETUP===================- bscearth.utils has been tested:with the following Operating Systems:* Linux Debian* Linux OpenSUSE- Install bscearth.utils> pip install bscearth.utilsor download, unpack and "python setup.py install"Check the bscearth.utils documentation provided in the 'docs' folder of the package, in PDF format.
Package: bsc-etl
Ethereum ETLEthereum ETL lets you convert blockchain data into convenient formats like CSVs and relational databases.Do you just want to query Ethereum data right away? Use thepublic dataset in BigQuery.Full documentation available here.QuickstartInstall Ethereum ETL:pip3installethereum-etlExport blocks and transactions (Schema,Reference):>ethereumetlexport_blocks_and_transactions--start-block0--end-block500000\--blocks-outputblocks.csv--transactions-outputtransactions.csv\--provider-urihttps://mainnet.infura.io/v3/7aef3f0cd1f64408b163814b22cc643cExport ERC20 and ERC721 transfers (Schema,Reference):>ethereumetlexport_token_transfers--start-block0--end-block500000\--provider-urifile://$HOME/Library/Ethereum/geth.ipc--outputtoken_transfers.csvExport traces (Schema,Reference):>ethereumetlexport_traces--start-block0--end-block500000\--provider-urifile://$HOME/Library/Ethereum/parity.ipc--outputtraces.csvStream blocks, transactions, logs, token_transfers continually to console (Reference):>pip3installethereum-etl[streaming]>ethereumetlstream--start-block500000-eblock,transaction,log,token_transfer--log-filelog.txt\--provider-urihttps://mainnet.infura.io/v3/7aef3f0cd1f64408b163814b22cc643cFind other commandshere.For the latest version, check out the repo and call>pip3install-e.>python3ethereumetl.pyUseful LinksSchemaCommand ReferenceDocumentationExporting the BlockchainQuerying in Amazon AthenaQuerying in Google BigQueryQuerying in KaggleAirflow DAGsPostgres ETLRunning Tests>pip3install-e.[dev,streaming]>exportETHEREUM_ETL_RUN_SLOW_TESTS=True
>pytest-vvRunning Tox Tests>pip3installtox
>toxRunning in DockerInstall Dockerhttps://docs.docker.com/install/Build a docker image> docker build -t ethereum-etl:latest .
 > docker image lsRun a container out of the image> docker run -v $HOME/output:/ethereum-etl/output ethereum-etl:latest export_all -s 0 -e 5499999 -b 100000 -p https://mainnet.infura.io
 > docker run -v $HOME/output:/ethereum-etl/output ethereum-etl:latest export_all -s 2018-01-01 -e 2018-01-01 -p https://mainnet.infura.ioRun streaming to console or Pub/Sub> docker build -t ethereum-etl:latest -f Dockerfile .
 > echo "Stream to console"
 > docker run ethereum-etl:latest stream --start-block 500000 --log-file log.txt
 > echo "Stream to Pub/Sub"
 > docker run -v /path_to_credentials_file/:/ethereum-etl/ --env GOOGLE_APPLICATION_CREDENTIALS=/ethereum-etl/credentials_file.json ethereum-etl:latest stream --start-block 500000 --output projects/<your-project>/topics/crypto_ethereumProjects using Ethereum ETLGoogle- Public BigQuery Ethereum datasetsNansen by D5- Analytics platform for Ethereum
Package: bsch
bschA Python package to support my random collection of Bosch devices.
Most of this code was created by investigating the device communication
and their exported files.Installation:This package can be installed or upgraded from the Python Package Index
with the help of thepipcommand:pipinstall--upgradebsch[plotting]For any plotting, the package relies on matplotlib/numpy.
Those packages are only installed if the "extra" plotting
is specified in square brackets after the package name.Bosch GTC 400 CIR / Thermography CameraImplemented features:Open the JPEG files saved by the IR camera and
extract the embedded binary thermography data,
I call this data 'thermoblob'.Extract metadata and the temperature matrix from
the thermoblob.Export a thermography plot (tool:gtc400c-thermogram).Interactive plot of the thermography data (tool:gtc400c-plot).Create a custom blend of thermography data on top
of the real photo (tool:gtc400c-blend).Download images via FTP when connected to the device
via WiFi (tool:gtc400c-ftp).Planned SupportI own the laser distance measurement toolBosch GLM 50-27 CG.
It has a BLE (Bluetooth Low Energy) interface and I successfully
reverse engineered the protocol. Needs some polishing though.
Package: bsci
Bootstrapped Confidence Intervals (bsci)A frequentist approach to construct confidence intervals by sampling with replacement.The statistical boostrap method was first introduced by
B. Efron, "Bootstrap methods: another look at the jackknife", Annals of Statistics, 1979,link to pdf.These lecture notesprovide a nice entry-level introduction. More references are given in the code.CitingIf you use code or ideas from this repository for your projects or research, please cite it.@misc{Muratore_bsci,
  author = {Fabio Muratore},
  title = {bsci - Constructing frequentist confidence intervals using the statistical bootstrap},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/famura/bsci}}
}InstallationTo install the core part of the package runpip install bsciFor (local) development install the dependencies withpip install -e .[dev]Getting StartedPlay around with the model's parameters in thedemo.pyscriptcd examples
python demo.py
Package: bsd-calendar
The calendar utility reads events from plain text files and outputs today’s
events. The files look something like this:#include <holiday>
#include <birthday>

06/15\tJune 15
Thu\tEvery Thursday.
15\t15th of every month.

05/Sun+2\tsecond Sunday in May (Muttertag)
04/Sun-1\tlast Sunday in April

Easter-2\tGood Friday (2 days before Easter)
Paskha\tOrthodox EasterThis implementation adds some new features while dropping others, most notably,
the date formats are not completely compatible:# added formats
1999/06/15\tJune 15 1999
1999/06/15*\tJune 15 (usefull for birthdays)
1999/05/Sun+2\tsecond Sunday in May 1999
1999/06/15+2\tJune 15 1999 and every second week since then

# removed formats (mostly alternative formats)
Jun. 15\t06/15
15 June\t06/15
Thursday\tThu
June\t06/01
15 *\t15

May Sun+2\t05/Sun+2
04/SunLast\t04/Sun-1