Saravanan666/pypi-org huggingface dataset:
Package: avroc
avrocavrocis a Python just-in-time compiler for reading and writing Avro data.It aims to be:Completely correct to the Avro specification.Very, very fast when compiled. Our goal is to be the fastest library
available in Python for dealing with Avro.Ergonomic and simple to use, with a small API that's clear.InstallationInstall with pip:pip install avrocBasic usageimportavroc# Make up a schemaschema={"type":"record","name":"Weather","fields":[{"name":"temperature","type":"double"},{"name":"wind_speed","type":"double"},{"name":"location","type":"string"},]}# Make up some recordsrecords=[{"temperature":71.2,"wind_speed":0.5,"location":"San Diego"},{"temperature":8.2,"wind_speed":13.4,"location":"North Pole"},{"temperature":-66.0,"wind_speed":14.4,"location":"Mars"},]# Write records to a filewithopen("data.avro, "wb") as f:avroc.write_file(f,schema,records)# Read records from a filewithopen("data.avro","rb")asf:formsginavroc.read_file(f):print(f'The temperature in{msg["location"]}is{msg["temperature"]}')# Encode a single record as raw bytesencoder=avroc.compile_encoder(schema)raw_bytes=encoder(records[0])# Decode a raw bytes as a single recorddecoder=avroc.compile_decoder(schema)rec=decoder(io.BytesIO(raw_bytes))For a lot more detail, see the documentation:avroc.readthedocs.io
Package: avrofastapi
AddAvro encodingsupport to your FastAPI application with a one-line setup- app = FastAPI()+ app = AvroFastAPI()Installationpip install avrofastapiUsageSERVERfromavrofastapiimportAvroFastAPIfromdatetimeimportdatetime,timezonefrompydanticimportBaseModelapp=AvroFastAPI()classTestResponseModel(BaseModel):A:strB:intC:datetime@app.get('/',response_model=TestResponseModel)defv1Example():returnTestResponseModel(A='ayy',B=1337,C=datetime.now(timezone.utc),)if__name__=='__main__':fromuvicorn.mainimportrunrun(app,host='0.0.0.0',port=5000)CLIENTfromavrofastapi.gatewayimportGatewayfromdatetimeimportdatetimefrompydanticimportBaseModelimportrequestsimportasyncioclassTestResponseModel(BaseModel):A:strB:intC:datetimerequests.get('http://localhost:5000/').json()# returns: {'A': 'ayy', 'B': 1337, 'C': '2023-01-22T10:01:00.543317+00:00'}gateway=Gateway('http://localhost:5000/','v1Example__get',response_model=TestResponseModel)asyncio.run(gateway())# returns: TestResponseModel(A='ayy', B=1337, C=datetime.datetime(2023, 1, 22, 10, 2, 29, 641314, tzinfo=<avro.timezones.UTCTzinfo object at 0x7efbe9cdb580>))DevelopmentFork the parent repository athttps://github.com/kheina-com/avrofastapiand edit like any other python project.Tests are run withpytestin the command line and input sorting is run viaisort .LicenseThis work is licensed under theMozilla Public License 2.0, allowing for public, private, and commercial use so long as access to this library's source code is provided. If this library's source code is modified, then the modified source code must be licensed under the same license or anapplicable GNU licenseand made publicly available.
Package: avro-object-furlan
AvroObjectâ€™s documentation!LinksGitHub AvroObjectPyPi avro-object-furlanExamplesBasic SerializationSchema SerializationBasic DeserializationSchema DeserializationAvroObjectclass avro_object.AvroObject(data, schema=None)Helper class for AVRO objectsParametersdata(JSON as string*,Dict object,Filename/URL as string with JSON content, *Avro as bytes with binary serialized content) â€“ (un)serialized dataschema(JSON as string*,Dict object, *Filename/URL as string with JSON content) â€“ Avro schemaproperty data()ReturnsNative unserialized dataReturn typedictproperty json()ReturnsJSON serialized dataReturn typestrproperty last_error()ReturnsLast error messageReturn typestrproperty ok()ReturnsAvro Object successfull creationReturn typeboolproperty origin()ReturnsSource of data (str, file, URL, Avro binary)Return typestrproperty schema_origin()ReturnsSource of schema (str, file, URL)Return typestrto_avro()ReturnsAVRO bytes serialized data (when schema is informed)Return typebytesto_json()ReturnsJSON serialized dataReturn typestrAvroToolsclass avro_object.AvroTools()Tools for AvroObjectclassmethod add_fetch_method(method)Add custom fetch methodParametersmethodâ€“ (str source) -> (bool Success, str JSON/Error, str origin name)ReturnsSuccessReturn typeboolstatic create_schema(data: dict, name: str, namespace: str = 'namespace.test', doc: str = None)Create schema from object (incomplete)Parametersdataâ€“ source objectnameâ€“ Name of schemanamespaceâ€“ Namespace of schemadocâ€“ DocumentationReturnsSchemaReturn typedictclassmethod fetch_json(source: str)Load JSON string from various medium and returns as stringParameterssourceâ€“ string JSON, file name, URL, another registered source by add_fetch_methodReturn typetuple (bool Success, str JSON or error message, origin)static fetch_json_file(source: str)Try to parse json from fileParameterssourceâ€“ str with file nameReturns(bool Success, str JSON or Error, origin)static fetch_json_url(source: str)Try to parse json from urlParameterssourceâ€“ str with URLReturns(bool Success, str JSON or Error, origin)classmethod reset_fetch_methods()Resets default fetch methods (File, URL and string)AuthorÂ©2019, Guionardo Furlanhttps://github.com/guionardo
Package: avro.py
avro.pyA modern Pythonic implementation of the popular Bengali phonetic-typing softwareAvro Phonetic.⚡ Overviewavro.pyprovides a fully fledged, batteries-included text parser which can parse, reverse and even convert English Roman script into its phonetic equivalent (unicode) of Bengali. At its core, it implements an extensively modified version of theAvro Phonetic Dictionary Search LibrarybyMehdi Hasan Khan.The original project (pyAvroPhonetic) can only be used on versions up toPython 2.7and doesn't contain proper support for Python's third major version AKA Python 3. It is noteworthy that Python 2 has officially been deprecated by the original maintainers and its usage is being discouraged overall.✨ InspirationsThis package is inspired from Rifat Nabi's jsAvroPhonetic library and derives from Kaustav Das Modak's pyAvroPhonetic.🔨 InstallationThis package requiresPython 3.8 or higherto be used inside your development environment.# Install / upgrade.$pipinstall-Uavro.py🔖 Usage Guide1.parse()This is the most basic use case for avro.py, which includes parsing English Roman script to unicode Bengali:# Imports.importavro# Parsing some text.output=avro.parse('ami banglay gan gai.')print(output)2.parse(bijoy=True)Alternatively, we can generate the same output, but in compliance with the Bijoy Keyboard format:# Parsing some text in Bijoy!output=avro.parse('tumi emon keno?',bijoy=True)3.to_bijoy()We can also use avro.py to convert existing unicode Bengali to its Bijoy Keyboard equivalent:# Converting some text.bijoy_text=avro.to_bijoy('আমি বাংলায় গান গাই।')4.reverse()Finally, you can reverse unicode Bengali to English as well (newly added).# Reversing back!reversed_text=avro.reverse('আমার সোনার বাংলা।')🛠️ Contributing:octocat:Fork -> Do your changes -> Send a Pull Request, it's that easy!Additional Developer NotesIn short, avro.py doesn't depend on any third-party libraries. However, if you'd like to contribute to the project, you'll need a handful of such useful tools.ruff- linterpytest- testing framework# Installing the required developer toolchain.$python3-mpipinstall-rrequirements-dev.txt# Running pytest.$python3-mpytest--verbose# The results should appear onwards.# The --verbose / -v flag is used to show all the test results in detail.🐛 We're looking for bug hunters, by the way!If you come across any kind of bug or wanna request a feature, please let us know by opening an issuehere. We do need more ideas to keep the project alive and running, don't we? :P👑 AcknowledgementsMehdi Hasan Khanfor originally developing and maintainingAvro Phonetic.Rifat Nabifor porting it to Javascript.Sarim Khanfor writing ibus-avro which helped to clarify my concepts further.Kaustav Das Modakfor porting Rifat Nabi's JavaScript iteration to Python 2.Md Enzam Hossain for helping him understand the ins and outs of the Avro dictionary and the way it works.📋 LicenseLicensed under theMIT License.
Package: avro-python3
# Deprecation Notice[avro-python3](https://pypi.org/project/avro-python3/) is no longer maintained and is deprecated in favor of [avro](https://pypi.org/project/avro/). Avro is maintained and has full support for recent versions of Python.## Apache Avro™Apache Avro™ is a data serialization system. To learn more, please visit our [website](https://avro.apache.org/).### DocumentationApache Avro documentation is maintained on our [wiki](https://cwiki.apache.org/confluence/display/AVRO/Index).### ContributingTo contribute to Avro, please read [How to Contribute](https://cwiki.apache.org/confluence/display/AVRO/How+To+Contribute) on the wiki.### License, Credits and AcknowledgementsLicense, credits and acknowledgements are maintained in the [LICENSE.txt](https://github.com/apache/avro/blob/master/LICENSE.txt) and [NOTICE.txt](https://github.com/apache/avro/blob/master/NOTICE.txt) in the source code repository. Those files are also included with the installed package.
Package: avroSchemaToCsvConvertor
avroSchemaToCsvConvertoravroSchemaToCsvConvertor is a utility to convert from Avro schema to CSV.Dependenciesavro-python3==1.9.1pycodestyle==2.8.0How to RunImport avroSchemaToCsvUse function as so -avroSchemaToCsv.avscToCsv(file=<path to .avsc Avro Schema files>)Current LimitationsIn the Avro Schema file (.avsc), the format should be like this -{ "type": "record", "name": "SampleRecord", "namespace": "com.example.avro", "doc": "An autonomous vehicle (AV) debug record.", "fields": [ { "name": "id", "doc": "The unique identifier for the record.", "type": "int" }, { "name": "timestamp", "doc": "Timestamp (datetime) of the record.", "type": "long" } ] }
Package: avro-service-clients
Avro Service Clients Library============================Quick start example:Create an Avro file and compile it into a schema:protocol FooService {string my_function(string my_arg);}Wire that up into an Avro IPC responder (e.g. https://github.com/packagelib/flask-avro)Dump the schema into `/path/to/avro/schema/files/foo.avpr`Set environment variables:AVRO_SERVICE_CLIENTS_LOCAL_REGISTRY_PATH=/path/to/avro/schema/filesAVRO_SERVICE_CLIENTS_FOO_HOST=localhostAVRO_SERVICE_CLIENTS_FOO_PORT=8080AVRO_SERVICE_CLIENTS_FOO_PATH=/my/service/endpointThen use the library to make a client:import avro_service_clientsclient = avro_service_clients.get_client("foo")client.my_function(my_arg="bar")-------------------------------------------------------------------------------0.0.4--------------------------------------------------------------------------------  Change version file setup.-------------------------------------------------------------------------------0.0.3--------------------------------------------------------------------------------  Initial public version.-------------------------------------------------------------------------------
Package: avro-to-bigquery
Avro to BigqueryAbout The ProjectAvro to bigquery is a simple project to create a bigquery schema from an avro schema.Getting StartedInstallation`pipinstallavro-to-bigqueryUsageWith avro_schema.avsc:{"type":"record","name":"User","namespace":"example.avro","fields":[{"name":"favorite_number","type":"int","doc":"Favorite number"}]}>>>importjson>>>frompathlibimportPath>>>fromavro_to_bigqueryimportconvert_schema>>>schema=json.loads(Path("avro_schema.avsc").read_text())>>>print(convert_schema(schema))(SchemaField('favorite_number','INTEGER','NULLABLE','Favorite number',(),()),)RoadmapSee theopen issuesfor a 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. For detailed contributing guidelines, please seehttps://github.com/wayfair-incubator/avro-to-bigquery/blob/main/CONTRIBUTING.mdLicenseDistributed under theMITLicense. SeeLICENSEfor more information.ContactProject Link:https://github.com/wayfair-incubator/avro-to-bigquery/
Package: avro-to-markdown
Avro to MarkdownAbout The ProjectAvro to markdown is a very simple project that generates readable markdown from an avro schema. This is useful
to be able to generate readable, always up-to-date documentation on the schemas you use to exchange messages within
your organization.Getting StartedTo get a local copy up and running follow these simple steps.InstallationClone the repogitclonehttps://github.com/wayfair-incubator/avro-to-markdown.gitInstall packagepipinstallavro-to-markdownUsage...RoadmapSee theopen issuesfor a 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. For detailed contributing guidelines, please seeCONTRIBUTING.mdLicenseDistributed under theMITLicense. SeeLICENSEfor more information.ContactColm O'ConnorProject Link:https://github.com/wayfair-incubator/avro-to-markdown/AcknowledgementsThis template adapted fromhttps://github.com/othneildrew/Best-README-Template
Package: avrotool
# AvroToolA python commandline tool to manipulate Avro files## Installationpip install avrotoolNote: if you have build issues on OSX, trybrew install snappy
CPPFLAGS=”-I/usr/local/include -L/usr/local/lib” pip install python-snappy
pip install avrotool## Usage (Basic)To print the avro usageavro
avro -help, -hTo print detailed information about a commandavro -help-command COMMANDTo print the versionavro version## Print SchemaTo print the avro schema :avro schema -f AVRO_FILE (-format json|text)## Extract DataTo extract named columns to STDOUTavro extract -f AVRO_FILE -columns a,b,c,d,e## CHANGELOG2017-03-19 0.0.1 Initial Prerelease.schemaandextractfunctionality only.
Package: avro-to-python-types
avro-to-python-typesA library for converting avro schemas to python types.Currently, it supports convertingrecords toTypedDict. If you would like to see more features added, please open up an issue.Why would I want this?This library is targeted to people writing code generation for python apps that are usingavro.UsageThis library doesone thing, it converts Avro schemas to python types.To get up and running quickly, you can use this to simply load schemas and print out the python
code that is generated.importglobfromavro_to_python_typesimporttyped_dict_from_schema_fileschema_files=glob.glob("schemas/*.avsc")forschema_fileinschema_files:types=typed_dict_from_schema_file(schema_file)print(types)For a real world example of syncing a directory of schemas into a directory of matching python typed dictionaries
check out the example apphereTo try it out, simply clone this repo and run:poetry env use 3.9This must be done as this library only supports Python 3.9 and above for type generation. You can still use this library in apps that use a lower Python version, as long as Python 3.9 is the active version when the types are generated (either locally or in your CI system).poetry installpoetry run sync-exampleFor some more advanced examples, like referencing other schema files by their full name take a look at the testshereReferencing schemasThis library supports referencing schemas in different files by their fullname.In order for this behaviour to work, all schemas must be in the same directory and use the following naming convention:namespace.name.avsc. Note that is the same asfullname.avscFor more on this checkout the docs for fastavrohere.An example of this can be found in the tests.Example outputThe following example shows the type generated for a given schema.{"namespace":"example","type":"record","name":"User","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["null","int"]},{"name":"favorite_color","type":["null","string"]},{"name":"address","type":{"type":"record","name":"AddressUSRecord","fields":[{"name":"streetaddress","type":"string"},{"name":"city","type":"string"}]}},{"name":"other_thing","type":{"type":"record","name":"OtherThing","fields":[{"name":"thing1","type":"string"},{"name":"thing2","type":["null","int"]}]}}]}fromtypingimportTypedDict,Optional# total=False allows us to skip passing optional fields into the constructorclassExampleAddressUSRecord(TypedDict,total=False):streetaddress:strcity:strclassExampleOtherThing(TypedDict,total=False):thing1:strthing2:Optional[int]classExampleUser(TypedDict,total=False):name:strfavorite_number:Optional[int]favorite_color:Optional[str]address:AddressUSRecordother_thing:OtherThingTestingTo run unit tests, runpoetry run pytest.You can also run tests in docker viamake testRequirementsPython 3.9 or greater.
Package: avrsim
This project is designed to build a simulator for the Arduino Uno processor
used in projects in my COSC2325Computer Architecture and Machine Languageclass at Austin Community College.The project is written in Python (tested on py2.7 and py3.5). It uses the MyHDL
hardware description library to build a simulation that can be converted to
real hardware using an FPGA. The current project targets the Basys3 (Artix 7
FPGA) board produced byDigilent.For more information on the project, contact the author:Roie Black
Professor, Computer Science
Austin Community College
Austin, Texas

email: rblack@austincc.edu
web: www.austincc.edu/rblack
GitHub: http://github.com/rblack42/AVRsim
Package: avrtsb
AVRTSB is Python implementation of TinySafeBoot - A tiny and safe
Bootloader for AVR-ATtinys and ATmegas [1]. AVRTSB version 0.2
now supports make custom firmwares. If you want compile the
firmware yourself, please download from [1].The console script run with the command pytsb. For more
information run: pytsb –helpThe benefit of AVRTSB is automatic reset of MCU with DTR or RTS line.
The second line is set to HIGH value (+12V) for power RS232<->TTL
convertor directly from serial port.  All parameters are given only
from command line without user interraction. This makes AVRTSB perfect
for integration with IDE for automatic upload new firmware after
compilation.TinySafeBoot is great bootloader bacause of:Small size - only 512 byteSoftware emulated serial interface a thus configurable for use
with all MCU pins.Secure access by passwordMore information can be found [1].[1] Original website of TinySafeBoothttp://jtxp.org/tech/tinysafeboot_en.htm
Package: avryp
Avryp is a Python package to build and flash AVR and Arduino code.Getting StartedPrerequisitesAvryp needs AVR tools to work, you can install them by running the
following command.sudoapt-getinstallavr-libcavrdudebinutils-avrgcc-avrInstallingAvryp is on PyPI so installing it is easy withpip.sudo pip install avrypExamplesExamples can be found in theexamplesdirectory.ConfigurationAvryp reads ~/.avryprc for binaries and Arduino library path.If not given, the default values are the following:#[arduino]
#haa = /path/to/hardware/arduino/avr/  #no default, but optional
[binaries]
avrdude = avrdude
avrdude_progtype = linuxgpio
avrobjcopy = avr-objcopy
avrsize = avr-size
avrgcc = avr-gcc
avrgpp = avr-g++LicenseThis project is licensed under the MIT License - see theLICENSEfile
for details
Package: avrzero
AVR ZeroA simple AVR instruction set IDE and simulator for educational purposes.WarningThis is in no way an accurate representation of the AVR instruction set and
the AVR assembly. Programs that work in this simulator are not guaranteed to
work on an actual AVR chip.Starting GuideThe project is available on PyPI, simply install it withpip.python -m pip install avrzeroThen, you can run the graphics user interface withpython -m avrzero.guiOr you can run the command line tools withpython -m avrzeroInstall from SourceFirst, you need to clone the GitHub repository.At the project root, runpython -m buildThe artifacts will be in thedistdirectory. Install withpython -m pip install --no-deps dist/avrzero-0.1.0-py3-none-any.whl
Package: avsim2D
Autonomous Vehicule Simulator 2DPurposeThis package is a 2D simulator for autonomous vehicule. The simulator is based on pygame.The main purpose is to train students on CAN-Bus and to introduce them self-driving vehicule problematics. The vehicule is piloted by CAN drive-by-wire.
Important to know : Self-driving features are not developped as they are supposed to be done by students. This package is done for educationnal purposes.Drive-by-wire featuresActuatorsPowertrainAccelerateBrakeTurnLightings :Blink leftBlink rightLow beamHigh BeamSensorsDashboardSpeedMotor SpeedGear selectionSDV sensorFront camera with semantic segmentation with following masks :roadstopyieldcrossingcar_parkAuthor and collaboratorsThe author, Raphaël LEBER, is a robotic teacher at CPE Lyon (a French engineering school).A few students from CPE Lyon collaborated on some features :Baptiste BrejonMarion DeshayesYann VilleAubin JousselinBenjamin Damarius
Package: av-slice
Silence RemoverAn automated video editing tool that removes lengths of silence.Free software: MIT licenseDocumentation:https://av-slice.readthedocs.io.Important to note, I don’t /really/ know what I’m doing in terms of a lot of the
packaging environment, so pull requests are very welcome.FeaturesAutomatically edit audio or video clips to remove silent or quiet sectionsInstallationInstall with pip:` pip install av_slice `or clone and install from source:` git clonehttps://github.com/hixan/av_slice.gitcd av_slice make install `Useautomatically remove silence fromvideo.mp4:` python-mav_slice video.mp4--output_file=shorter_video.mp4`the script will run for a while calculating changes and composing the video.
When it is finished,shorter_video.mp4will be saved to the disk. If–output_fileis omitted it will be saved tovideo_modified.mp4.CreditsHeavily inspired by CarkyhsJumpcutterlibrary.This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.Todotesting (get a good example video)get ffmpeg installed on travis to enable proper testingGUI interfacePY2EXE implementation?Wishlistautomatic detection of appropriate thresholdHistory0.1.0 (2019-06-08)First release on PyPI.
Package: avstudio
AV Studio APIThis repo contains:/avstudio: Python wrapper for AV Studio API/docs: API reference/device_api.ipynb: Python notebook with API tutorial/device_api.html: static version of the tutorial (link)Installation$ git clone https://github.com/epiphan-video/avstudio_api.git
$ cd avstudio_api
$ pip install -r requirements.txtRunning the interactive tutorialJupyter has to be installed.$ cd avstudio_api
$ python -m notebookDocumentationAPI documentation is available via Github Pages:https://epiphan-video.github.io/avstudio_apiHow to update docsDocumentation source is stored indocs-source-slatefolder.Build a slate builder container (once):$cdslate
$dockerbuild-tslate-builder.(optional) Start doc server:dockerrun-it--rm\-v$(pwd)/docs-source-slate/:/slate/source\-v$(pwd)/docs:/slate/build\-p4567:4567\slate-builderbundleexecmiddlemanserver...and openhttp://localhost:4567/in your browser.When editing is done, use the container to build static docs:dockerrun-it--rm-v$(pwd)/docs-source-slate/:/slate/source-v$(pwd)/docs:/slate/buildslate-builderThis command will update files indocsfolder, if necessary.git commit and pushExporting notebook tutorial:jupyter nbconvert --to html --execute device_api.ipynb --ExecutePreprocessor.timeout=-1