Saravanan666/pypi-org huggingface dataset:
Package: bidscoin
BIDScoin is a user-friendly Python application suite that converts (“coins”) source-level (raw) neuroimaging data sets to standardized data sets that are organized according to the Brain Imaging Data Structure (BIDS) specification. Rather than depending on complex programmatic logic for source data-type identification, BIDScoin uses a mapping approach to discover the different source data types in your repository and convert them into BIDS data types. Different runs of source data are uniquely identified by their file system properties (e.g. file name or size) and by their attributes (e.g.ProtocolNamefrom the DICOM header). Mapping information can be pre-specified (e.g. per site), allowing BIDScoin to make intelligent first suggestions on how to classify and convert the data. While this command-line procedure exploits all information available on disk, BIDScoin presents aGraphical User Interface (GUI)for researchers to check and edit these mappings – bringing in the missing knowledge that often exists only in their heads.Data conversions are performed within plugins, such as plugins that employdcm2niix,spec2niiornibabel.BIDScoin requires no programming knowledge in order to use it, but users can use regular expressions and plug-ins to further enhance BIDScoin’s power and flexibility, and readily handle a wide variety of source data types.BIDScoin is developed at theDonders Instituteof theRadboud University.Features[x] DICOM source data[x] PAR/REC source data (Philips)[x] NIfTI source data[x] Physiological logging data*[x] MR Spectroscopy data**[x] PET/CT data[x] Field maps*[x] Multi-echo data*[x] Multi-coil data*[x] Plug-ins[ ] Stimulus/behavioural logfiles*  = Only DICOM source data** = Only Twix, SDAT/SPAR andP-filesource dataNoteAllsource codeis hosted atGithubandfreely availableunder the GPL-3.0-or-laterlicense.The full BIDScoindocumentationis hosted atRead the DocsFor citation and more information, see ourBIDScoin publicationinFrontiers in Neuroinformatics(DOI: 10.3389/fninf.2021.770608). Seeherefor citations of the plugins. A custom-made citation report can be generated with the help ofduecreditYou are encouraged topost issues or questions atGithuborNeuroStarsHow to contributeAre you a Python programmer with an interest in BIDS who knows about GE and/or Philips data? Are you experienced with parsing stimulus presentation log-files? Or do you have ideas to improve BIDScoin or its documentation? Have you come across bugs? In any case, you are more than welcome to provide feedback and tocontribute to this project.
Package: bids-derivatives
DocumentationCodeTestsPackagingPython package for querying BIDS Apps` processed derivatives.Free software: Apache Software License 2.0Installationpip install bids_derivativesYou can also install the in-development version with:pip install https://github.com/GalBenZvi/bids_derivatives/archive/main.zipDocumentationhttps://bids_derivatives.readthedocs.io/DevelopmentTo 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 tox
Package: bids-events
bids_eventsTool to export events from presentation log files.Installationpip install bids_eventsExample of useSimple examplefrombids_events.EventsimportEventHandlerevents_h=EventHandler('example_events.tsv')events_h.trials=[['onset','duration','condition'],[0,20,'STOP'],[20,20,'GO'],[40,20,'STOP'],[60,20,'GO'],[80,20,'STOP'],[100,20,'GO'],[120,20,'STOP'],[140,20,'GO'],[160,20,'STOP'],[180,20,'GO'],]events_h.export_bids()Extraction usingPresentationLOGSfrombids_events.presentationimportLogHandlerasLogcols=[['trial_type',Log.COL_CODE,r'cue.*'],['fix_after_cue',Log.COL_CODE,r'fixAfterCue',Log.COL_TIME],['reward',Log.COL_CODE,r'rew.*',Log.COL_CODE],['response',Log.COL_CODE,r'press',Log.COL_TTIME],['fix2',Log.COL_CODE,r'fix2',Log.COL_TTIME]]log=Log('S001-Run1.log')log.extract_trials(cols)log.export_bids('sub-S001_task-emotion_run-1')Check the./testsfolder to see more detailed examples.
Package: bidskit
BIDSKITVersion 2023.2.16Python utilities for converting from DICOM to BIDS neuroimaging formats.Thebidskitconsole command takes a directory tree containing imaging series from one or more subjects (eg T1w MPRAGE, BOLD EPI, Fieldmaps), converts the imaging data to Nifti-1 format with JSON metadata files (sidecars) and populates a directory tree according to the latest BIDS specification.DocumentationInstallation InstructionsQuick Start GuideUseful FeaturesFlywheel SupportBugs and Feature RequestsLet us know about bugs and feature requests through this repo'sGitHub Issuespage.Related ProjectsheudiconvGeneral purpose heuristic DICOM converterdcm2bidsChristophe Beddetti's DICOM to BIDS converter
Package: bids-path
SnakebidsThis repository implements the Snakebids builder function for Bids Paths. You can install this library as a stand-alone package via pip (see below), however, its contents are repackaged in the mainsnakebids repository.Snakebids is a Python package that extendsSnakemake, enabling users to create reproducible, scalable pipelines for processing neuroimaging data in theBIDS format. Snakebids workflows expose a CLI that conforms to theBIDS Appguidelines.FeaturesThebids()function is a flexible, unopinionated tool to build valid bids paths in a clean, pythonic syntax. It tries to support all the official bids tags, but allows any arbitrary custom tags as well. Entities are automatically ordered according to thebids spec.InstallationSnakebids can be installed using pip:pipinstallbids_pathUsageTo use, just import thebids()function:frombids_pathimportbidsNote thatbids()is just one piece of the broadersnakebids. Ifsnakebidsis installed,bids()can be imported directly from thesnakebidsnamespace:fromsnakebidsimportbidsFor detailed instructions and examples, please refer to thedocumentation.ContributingSnakebids is an open-source project, and contributions are welcome! If you have any bug reports, feature requests, or improvements, please submit them to theissues page.To contribute, first clone the Github repository.bids_pathdependencies are managed with Poetry (version 1.2 or higher). Please refer to thepoetry websitefor installation instructions.Note:bids_pathmakes use of Poetry's dynamic versioning. To see a version number on locally installed Snakebids versions, you will have to also installpoetry-dynamic-versioningplugin to your poetry installation (`poetry self add "poetry-dynamic-versioning[plugin]"). This isnot requiredfor contribution.Following installation of Poetry, the development can be set up by running the following commands:poetryinstall
poetryrunpoesetupbids_pathusespoethepoetas a task runner. You can see what commands are available by running:poetryrunpoeTests are done withpytestand can be run via:poetryrunpoetestAdditionally,bids_pathuses pre-commit hooks (installed via thepoe setupcommand above) to lint and format code (we useblack,isortandruff). By default, these hooks are run on every commit. Please be sure they all pass before making a PR.Licensebids_pathis distributed under the MIT License.
Package: bidsschematools
BIDS Schema ToolsA Python library (available after installation in the Python interpreter asbidsschematools)
for working with theBrain Imaging Data Structure (BIDS)schema.Features:lightweightreference schema parsing implementation used for schema testingsimple CLI bindings (e.g.bst export)If you have questions, you can post them in one of several channels where BIDS members are active:theNeuroStarsdiscourse forumtheBrainHack Mattermost,
for instant messaging (see also thisnews item)theGoogle group,
for broader discussions surrounding BIDS
Package: bids_term_to_table
bids_terms_to_pdf_table: Utilty for creating Markdown table of BIDS terms and adding new BIDS terms
License
=======bids_terms_to_pdf_tableis licensed under the terms of the Apache License 2.0. See the file
“LICENSE” for information on the history of this software, terms & conditions
for usage, and a DISCLAIMER OF ALL WARRANTIES.
Package: bienabee-qtbot
Bienabee qTbotWelcome to Bienabee qTbot a Python wrapper for the Tricentis qTest REST APIGetting startedWill add more notes later, this is pre-alpha and is not publicly documented yet.
Please reach out to us for any questions, or qTest automation, test case migration,
or any other DevOps needs.Authors and acknowledgmentShow your appreciation to those who have contributed to the project.LicenseApache-2.0Project statusPre-Alpha, still a major work in progress.
Package: bieniciscraper
bieniciscraperbieniciscraperis a Python package that allows you to scrape all real estate listings from any Bien'Ici URL 💛TableFeaturesInstallationUsageCommand-line ArgumentsImportant NotesDisclaimerLicenseFeaturesAll search URLs acceptedAll listings collected13 attributes perlistingLimit the scope of scraping with the dynamic-largumentUse any search URL with the-udynamic argumentExport data with a customized file name using the-odynamic argumentA resilient structure with the appliedretrylogicExports data in a structured.csvfile formatInstallation$pip3installbieniciscraperNote: The installation will also install therequestsandretryexternal libraries.Usage$bieniciscraper-uhttps://www.bienici.com/recherche/achat/france/chateau-l10-odemo.csv
goingtopage:1totalresults:591totalresultstoscrape:10scraped:Châteauàvendredanslelotavecdépendancesetpiscine.
scraped:TurenneCollongeslarouge-DemeureduXVIIIsièclede300m²habitablessuruneparcelle1,9haàrénoverentièrement
scraped:Manoir15piècesBIVIERS
scraped:ChâteauduXVIèmesiècleetsonparcaucoeurdeLyon
scraped:Domaine3hectaresprocheEtretat
scraped:VenteChâteau19pièces
scraped:ANCIENNEDEPENDANCEDEL'ABBAYE DE CONQUES, CONSTITUEE D'UNCHATEAU
scraped:Château
scraped:VenteChâteau8pièces
scraped:DOMAINED'EXCEPTION MONTS DU LYONNAISlimit reachedcsv writtenelapsed: 1.20 s~~ success_       _         _| |     | |       | || | ___ | |__  ___| |_ __ __| |/ _ \| '_\/__|__/|'__|||(_)||_)\__\|_|||_|\___/|_.__/|___/\__||_|Command-line Arguments--url/-u: Specify your search URL.--limit/-l: Limit the number of items you want to scrape.--output/-o: Name the file in which data will be saved.Important NotesThis Python script collects data from the internal Bien'Ici API. It can convert any Bien'Ici search URL into an available API request using advanced website-side JS reverse-engineering.Beware: scraping is limited to2,500 ads per search url. Bien'ici allows access to a maximum of 100 pages and then limits the display. To bypass this limitation, split your main search link into smaller scoped links:For instance, to scrape all listings from Paris,divideby neighborhoods:75001 all listings75002 all listings... and so on.💇Always ensure that your usage adheres to the legal constraints relevant in your jurisdiction.
If you have package-related request, please contact us at:contact@lobstr.io.DisclaimerThis tool is intended for educational use. Always ensure that scraping a website is within your legal rights before using this or any other scraping tool. Respect therobots.txtof websites and be conscious of ethical and legal considerations.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.
Package: biensoxe
Library to validate and parse Vietnamese vehicle plate.This library is not a computer-vision-based license plate recognition software. It instead is used for validating output of such computer vision software. Imagine that you use camera to track all cars coming in and out off your parking lot, but you don’t want to save false result (due to wrong angle of camera, for example), you can use this library to check and remove them.Installpip3installbiensoxeUsageCallVietnamVehiclePlate.from_string, passing the number string, to createVietnamVehiclePlateobject.>>>frombiensoxeimportVietnamVehiclePlate>>>VietnamVehiclePlate.from_string('44A-112.23')VietnamVehiclePlate(compact='44A11223',vehicle_type=<VehicleType.DOMESTIC_AUTOMOBILE:1>,series='A',order='11223',locality='44',dip_country=None)>>>VietnamVehiclePlate.from_string('41-291-NG-01')VietnamVehiclePlate(vehicle_type=<VehicleType.DIPLOMATIC:9>,series='NG',order='01',locality='41',dip_country='291')The method raisesValueErrorif the string could not be parsed.To format the plate number as in daily life, passVietnamVehiclePlatetostr:>>>plate=VietnamVehiclePlate.from_string('72E101130')>>>plateVietnamVehiclePlate(compact='72E101130',vehicle_type=<VehicleType.DOMESTIC_MOTORCYCLE_50_TO_175CC:3>,series='E1',order='01130',locality='72',dip_country=None)>>>str(plate)'72-E1 011.30'DjangoThis library provides a field type,VietnamVehiclePlateField, for Django model. The field will return value asVietnamVehiclePlateobject. Here is example:frombiensoxe.djangoimportVietnamVehiclePlateFielddefdefault_plate_number():returnVietnamVehiclePlate.from_string('10A 00001')classVehicle(models.Model):plate_number=VietnamVehiclePlateField(max_length=20,default=default_plate_number,unique=True)def__str__(self):returnstr(self.plate_number)orself.pkNote that this field stores value internally as PostgeSQLCITextdata type, so you can only use this field with PostgreSQL.
You also need to activateCITextExtensionyourself.CreditBrought to you byNguyễn Hồng Quân.
Package: bienvenue
Python module for reading config from environment for12-factor apps.
Supports Python 3.4+RationaleIn a 12-factor app,config comes from the environment.
For example, on Heroku, config variables are set usingheroku config:seton the command line,
thenpassed to the application in the environment.Reading and parsing config from the environment is tedious and error-prone. For
example, a Django app hassettings.DEBUGwhich should be
eitherTrueorFalse. The operator runsheroku config:set DJANGO_DEBUG offintending to disable it, but the application only sees a non-empty string
and treats the value asTrue.This sort of problem can be handled case-by-case but doesn’t need to be. Clearly
a configuration setting with a fallback boolean value should be interpreted as
boolean from the environment. Likewise a fallback integer setting indicates the
associated environment variable should be converted from string to int.Sounds like a job for a small and well-tested Python module, right?InstallationInstall fromPyPI:pipinstallbienvenueUsageBienvenue provides the functionmake_env_readerwhich returns a new
function for accessing the environment. For example:frombienvenueimportmake_env_readerenv=make_env_reader(prefix='MY_')DEBUG=env('DEBUG',False)SECRET_KEY=env('SECRET_KEY','fallback-secret-for-dev')ALLOWED_HOSTS=env('ALLOWED_HOSTS',[])The env reader looks forMY_DEBUGinos.environ. If it’s not there,
the default valueFalsewill be returned. However if it’s found, then the
value there will be interpreted according to the type of the default, in this
case boolean. Common strings such as on/off, true/false and yes/no are
interpreted intoTrueorFalse.LikewiseSECRET_KEYwill be extracted fromMY_SECRET_KEYand then
interpreted as a string value.ALLOWED_HOSTSwill be extracted fromMY_ALLOWED_HOSTSand JSON
decoded as a list, since the default value is a list.If bienvenue encounters unknown types or values during parsing, it will log an
error and fall back to the provided default.LegalCopyright 2017Scampersand LLCReleased under theMIT license
Package: bierstadt
BierstadtA library and command line tool to handle CK2 portrait filesInstallInstall withpip install bierstadt. Make sure to usepip3if Python 3 isn't your default version.Use from command linebierstadt create *[files]*combines all listed files into a CK2-ready portrait sprite.bierstadt create *file* -t traitcreates a trait icon.bierstadt insert *source* *target* *index*inserts the source file into the existing target sprite at the specified index.Use from codebierstadt.libraryexposes classes to handle various image types.
Package: bi_etl
bi_etl Python ETL Framework for BIDocsPlease see the documentation site for detailed documentation.Python based ETL (Extract Transform Load) framework geared towards BI databases in particular.
The goal of the project is to create reusable objects with typical technical transformations used in loading dimension tables.Guiding Design PrinciplesDon’t Repeat Yourself (DRY).The source or target of an ETL owns the metadata (list of columns and data types). The ETL generally has no reason to define those again unless the ETL requires a change. If a datatype must be changed, only that one column’s new type should be specified. If a column name must be changed, only the source & target column names that differ should be specified.Data Quality is KingData quality is more important than performance. For example, the process should fail before truncating data contents (i.e. loading 6 characters into a 5 character field) even if that means sacrificing some load performance.Give helpful error messages.Make it as easy as possible to create re-usable modules.SQL is a very powerful transformation language. The Transform Extract Load (TEL) model should be supported.
Package: bifas
bifasSecure ledger system, near real-time payment processing time and market deterministic transaction fee all in BIFAS.Where to get itThe source code is currently hosted on GitHub at:https://github.com/jaaseoi/bifas.Code Standards for ContributionEnvironmentThe minimum Python version supported is3.9.Your code is expected to be executable onWindows,MacOSandLinux.State ManagementNo global states or variables, all stateful operations should be implemented asclasses.Limit the use of helper functionsonly to generic operations that are shared among multiple parts of the code.Avoid returning multiple valuesfrom a function, instead consider toreturning a class instance.#Name ConventionsAlways usesnake_caseforvariableandfunction name, and usePascalCaseforclass names,UPPERCASEforconstants.Try at all costs to give a proper,clear nameto yourvariables,functions,arguments, andclasses, from which the user can directly understand its purposes.Class initialization and function calls should usenamed arguments.DocumentationFor eachpublicly available class and functions,document their purpose, parameters, and returnsin the docstring format along with your code. Read thisguide.Keep the documentation simple and precise, no need to repeat what is already obvious in their names, no need to include implementation details (make in-line comments instead).Code CommitsCreate abranch for each featurethat you are working on. Submit aPull Requestto respective branch for merging.
Package: bifeatureanalysis
Package NameFast AnalysisUltimate Goal: Make Feature Engineering Analysis easy and fast as it should be.Installationpip install bifeatureanalysisHow to use it?Feature Engineering Analysis Common Usage Function ListLicensecopyright @ 2022 BDFDThis repository is licensed under the MIT license. See LICENSE for details.Referenceshttps://github.com/bdfd/Section5.3-PyPi_Feature_Engineering
Package: biffobear-circuitpython-as3935
IntroductionA CircuitPython driver library for the Franklin AS3935 lightning detector. The driver supports connections via SPI and I2C.NoteSparkfun foundI2C connections unreliableand chose not to support it in their product.See theAS3935 datasheetfor more details of chip operation.DependenciesThis driver depends on:Adafruit CircuitPythonBus DevicePlease ensure all dependencies are available on the CircuitPython filesystem.
This is easily achieved by downloadingthe Adafruit library and driver bundleor individual libraries can be installed usingcircup.Installing from PyPIOn supported GNU/Linux systems like the Raspberry Pi, you can install the driver locallyfrom
PyPI.
To install for current user:pip3installadafruit-circuitpython-as3935To install system-wide (this may be required in some cases):sudopip3installadafruit-circuitpython-as3935To install in a virtual environment in your current project:mkdirproject-name&&cdproject-namepython3-mvenv.envsource.env/bin/activatepip3installadafruit-circuitpython-as3935Running The UnittestsTo run the unittests on you will need to install Pytest and Pytest Mock.pip3installpytestpytest-mockTo install system-wide (this may be required in some cases):sudopip3installpytestpytest-mockUsage ExampleFor a SPI connection:"""Loop and wait for an event.

Note that the sensor only responds to lightning and certain kinds of noise,
so unless it is stormy, there's not much to see here.
"""importtimeimportboardimportbiffobear_as3935# Edit the chip select and interrupt pins to match the connections to your boardinterrupt_pin=board.D7# Connected to the sensor interrupt pin# For a SPI connection (recommended)spi=board.SPI()# Works for most Adafruit and Blinka boardscs_pin=board.D5# Connect to the sensor chip select pinsensor=biffobear_as3935.AS3935(spi,cs_pin,interrupt_pin=interrupt_pin)# For an I2C connection# i2c = board.I2C()  # Works for most Adafruit and Blinka boards# sensor = biffobear_as3935.AS3935_I2C(i2c, interrupt_pin=interrupt_pin)whileTrue:ifsensor.interrupt_set:# An event has occurred# The interrupt_status is cleared after a read, so assign it# to a variable in case you need the value later.event_type=sensor.interrupt_statusifevent_type==sensor.LIGHTNING:# It's a lightning eventprint(f"Strike Energy ={sensor.energy}")print(f"Distance to storm front ={sensor.distance}km")elifevent_type==sensor.DISTURBER:print("False alarm")else:print("No event detected")# Minimum time between strike events is 1 second so poll frequently!time.sleep(0.5)ContributingContributions are welcome! Please read ourCode of Conductbefore contributing to help this project stay welcoming.DocumentationFor information on building library documentation, please check outthis guide.
Package: biflux
# python-bifluxPython-biflux is a python wrapper around the BiFluX tool.Python-biflux supports the compilation of BiFluX updates into bidirectional transformations. It can also run both forward and backward transformations using the compiled updates.# DependenciesYou will need:
* GHC 7.8.4
* BiFluX 0.0.2
* python 3.x (may or may not work with python2)
Package: bifold
BiFold: A Python code for the calculation of double folded (bifold)potentials with density-in/dependent nucleon-nucleon interactionsBiFold calculates the density-dependent (DDM3Yn, BDM3Yn, CDM3Yn) or independent double folded potentials between two colliding spherical nuclei. It is written in a Python package form to give the ability to use the potentials directly in a nuclear reaction/structure code. In addition to using Woods-Saxon/Fermi or Gaussian functions, the code also allows for the definition of nuclear matter densities using pre-calculated densities in a data file.
Package: bifrost
Bifrost (pronounced bye-frost) is a set of Ansible playbooks that
automates the task of deploying a base image onto a set of known hardware usingironic. It provides modular utility for one-off operating system deployment
with as few operational requirements as reasonably possible.The mission of bifrost is to provide an easy path to deploy ironic in
a stand-alone fashion, in order to help facilitate the deployment of
infrastucture, while also being a configurable project that can consume
other OpenStack components to allow users to easily customize the
environment to fit their needs, and drive forward the stand-alone
perspective.Use cases include:Installation of ironic in standalone/noauth mode without other OpenStack
components.Deployment of an operating system to a known pool of hardware as
a batch operation.Testing and development of ironic in the standalone mode.Useful LinksBifrost’s documentation can be found at:https://docs.openstack.org/bifrost/latestRelease notes are at:https://docs.openstack.org/releasenotes/bifrost/The project source code repository is located at:https://opendev.org/openstack/bifrost/Bugs can be filed in launchpad:https://launchpad.net/bifrost