Saravanan666/pypi-org huggingface dataset:
Package: aqara-msg-push
aqara_msg_pushSDK for Aqara Message PushPackage hasPydantic models for Message Push Formatfunction for mapping custom json from message queue to Pydantic modelSimple consumer for RocketMQ with Aqara confiqurationInstallLibrary installs with command:pipinstallaqara-msg-pushFor consuming you will also need:rocketmq-client-python- tiny python lib - python wrapper for cpp liblibrocketmq - cpp lib (for installation guide checkrocketmq-client-python README.md)Example of Usage:fromaqara_msg_pushimportMessageConsumer,TopLevelMessagefromrocketmq.clientimportReceivedMessage,ConsumeStatus# Your params from https://developer.aqara.com/console/overviewADDRESS='some-broker1.aqara.com:9876'TOPIC='99...99'GROUP_ID='99..ce'ACCESS_KEY='K....'SECRET_KEY='nt..jg'KEY_ID=ACCESS_KEYclassMyMessageConsumer(MessageConsumer):defcallback(self,obj:TopLevelMessage,raw_msg:ReceivedMessage)->ConsumeStatus:print(type(obj),obj.data)returnConsumeStatus.CONSUME_SUCCESSMyMessageConsumer(group_id=GROUP_ID,access_key=ACCESS_KEY,secret_key=SECRET_KEY,topic=TOPIC,address=ADDRESS,).consume()"""Output:<class 'aqara_msg_push.schema.toplevel.DeviceAttributeMessage'> [DeviceStateMessage(raw_time='1659704748378', subject_id='lumi.9999999', resource_id='4.1.85', value='1', status_code=<TriggerResult.SUCCESS: 0>, trigger_source=TriggerSource(raw_time='1659704748', type=<TriggerType.CLOUD_REMOTE_COMMAND_CONTROL: 4>, id=None), attach=None)]<class 'aqara_msg_push.schema.toplevel.DeviceAttributeMessage'> [DeviceStateMessage(raw_time='1659704750046', subject_id='lumi.9999999', resource_id='4.1.85', value='0', status_code=<TriggerResult.SUCCESS: 0>, trigger_source=TriggerSource(raw_time='1659704749', type=<TriggerType.CLOUD_REMOTE_COMMAND_CONTROL: 4>, id=None), attach=None)]"""
Package: aqbt
Aquarium-SD2 Strain Builder Tools (aqbt)This repo contains many Aquarium-related tools for constructing new engineered strains.FeaturesAutomated design and Aquarium workflow submission of plasmid assembliesAutomated design and Aquarium workflow submission of yeast constructionsConversion of Aquarium strain definitions to engineered GFF with FASTA.JSON-schema validated serialization of Aquarium modelsAquarium <-> Benchling integrationAquarium <-> SynBioHub integration (coming soon)Common file type conversions GFF <> FASTA <> Genbank <> JSON <> Benchling <> Aq <> SBOL (planned)Aquarium database faker for unit testingUsageInstallationpip install .Install BLAST locally using the following:pyblast installCredentialsAqBuildTools (aqbt) requires acredentials.tomlfile to connect with
Aquarium, Benchling and SynBioHub (coming soon). The following
creates thedefaultscope for a aqbt session:[aquarium.production]
login = 'mylogin'
password = 'mypass'
url = 'http://aquarium.org'

[benchling.production]
apikey = 'sk_398dfg983nsdfsdflksj'
initials = 'UWBF'
schema = 'Aquarium DNA'
prefix = 'aq'
folder_id = 'lib_ILUNzz6N'
id = 'src_KE6uFvex'

[session.default]
aquarium = 'production'fromaqbtimportAquariumBuildToolsaqbt=AquariumBuildTools.from_toml('credentials.toml')ExamplesQuerying the Aquarium serverConnecting to Benchling and SynbiohubPlasmid constructionStrain constructionGenerating GFFsRelated repostrident,DASi,Benchling API,Terrarium,pyblast,primer3-py-plus
Package: aqdefreader
aqdef-readeris a Python module to read AQDEF (Q-DAS or qdas) ASCII files via Python. The package comes with data structures to cover the tranfer file format header elements such as parts (Teiletyp) and characteristics (Merkmale). As the ASCII files might already come with measured, values, the reader function can already read these values (Messwerte) and stores them as part of the characteristics described in the transfer file.
Package: aqipy
AQIPYA simple tool to get Air Quality Indices from around the world.InstallationGet an API tokenhere.Create an environment variable with your token:export AQIPY_TOKEN='<your_new_token>'From sourceClone this repository.From your new directory:pip3 install -e .From PyPIpip install aqipyUsageTo get the AQI for your current location (IP based):aqipyTo get the AQI for a specific location (latitude longitude):aqipy geo [--latlon / -l <lat lon>]Example$ aqipy geo --latlon 53.8 -7.4AttributionThis tool uses APIs provided by theWorld Air Quality Index Project.
Package: aqipy-atmotech
AQI calculation library (python)The library calculates the following indexes:AQI (US)AQHI (Canada)CAQI (Europe)DAQI (UK)AQI (Australia)CAI (South Korea)PSI (Singapore)AQHI (Hong Kong)AQI (Mainland China)AQI (India)InstallationFrom source:git clone --recursive https://github.com/atmotube/aqipy.git
cd python
python setup.py installFromPyPIdirectly:pip3 install aqipy-atmotechExamplescalculate US AQI:fromaqipyimportaqi_usaqi,aqi_data=aqi_us.get_aqi(o3_8h=0.07853333,co_8h=5)print('AQI:',aqi)print('AQI O3:',aqi_data['o3_8h'][0])print('Effects O3:',aqi_data['o3_8h'][1])print('Cautions O3:',aqi_data['o3_8h'][2])print('AQI CO:',aqi_data['co_8h'][0])print('Effects CO:',aqi_data['co_8h'][1])print('Cautions CO:',aqi_data['co_8h'][2])output will be:AQI: 126
AQI O3: 126
Effects O3: Increasing likelihood of respiratory symptoms and breathing discomfort in people with lung disease (such as asthma), children, older adults, people who are active outdoors (including outdoor workers), people with certain genetic variants, and people with diets limited in certain nutrients.
Cautions O3: People with lung disease (such as asthma), children, older adults, people who are active outdoors (including outdoor workers), people with certain genetic variants, and people with diets limited in certain nutrients should reduce prolonged or heavy outdoor exertion.
AQI CO: 56
Effects CO:
Cautions CO:UnitsPollutantUnitsCOppmO3ppmNO2ppmSO2ppmNH3ppmPbppmPM2.5μg/m3PM10μg/m3Summary (averages)IndexPM2.5PM10O3NO2COSO2NH3PbAQI (US)24h24h8h/1h1h8h1h--AQHI (Canada)3h3h3h3h----CAQI (Europe)1h/24h1h/24hmax in 1hmax in 1h8hmax in 1h--DAQI (UK)24h24h8h1h-15m--AQI (Australia)24h24h1h/4h1h8h1h--CAI (South Korea)24h24h1h1h1h1h--PSI (Singapore)24h24h8h1h8h24h--AQHI (Hong Kong)3h3h3h3h3h3h--AQI (Mainland China)24h24h1h/8h24h24h24h--AQI (India)24h24h8h24h8h24h24h24h
Package: aqiretrieve
aqiretrievePython package for AQI retrieval from EPA APIAQI Retrieve provides the data for the Air Quality Index of the United States from theAirNow.
The data collected is at a County level.Current air quality data for more than 500 cities across the U.S.The dataset that is generated consists of the following columns:StateCountyDateOzonePM 2.5PM 10Description for each of above item can be foundhereUsage:from aqiretrieve import getData

getData()Since we retrieve data for each state, it requires quite some time depending on the provided date range.This will create a .csv file with the aforementioned ColumnsAll we are doing here is getting the data from AirNow.gov and converting the same to a readable CSV file.Complete credit for all the data goes toAirNow
Package: aql
aqlSimple, async query library for modern PythonHighlightsaql is a simple, modern, and composable query builder, with support for asynchronous
execution of queries against multiple database backends using a unified API.
aql uses modern, type annotated data structures for both table definitions and queries.aql is still in early alpha. Not all features are available or finalized.Define tables:@table("objects")classObject:id:PrimaryKey[AutoIncrement[int]]name:Unique[str]description:textcreated:datetimeBuild queries:query=(Object.select().where(Object.id>=25).order_by(Object.name).limit(5))sql,params=SqlEngine.prepare(query)# "select * from `objects` where `id` >= ? order by `name` asc limit 5", (25)Execute queries:asyncwithconnect(...)asdb:cursor=db.execute(Object.select().where(Object.id<100))asyncforrowincursor:print(f"{row.id}{row.name}{row.description}")Simple actions:asyncwithconnect(...)asdb:rows=awaitdb.get(Object,Object.id==100)rows[0].description+="updated"awaitdb.modify(Object,rows)Licenseaql is copyrightJohn Reese, and licensed under
the MIT license.  I am providing code in this repository to you under an open
source license.  This is my personal repository; the license you receive to
my code is from me and not from my employer. See theLICENSEfile for details.
Package: aql-builder
ArangoDB AQL builderPython AQL builder forArangoDB, a scalable multi-model
database natively supporting documents, graphs and search.RequirementsPython version 3.7+Installationpipinstallaql-builder--upgradeGetting StartedHere are simple usage examples:>>>fromaql_builderimportAQLBuilderasAB>>>>>>AB.for_('my').in_('mycollection').return_('my._key').to_aql()'FOR my IN mycollection RETURN my._key'>>>>>>AB.for_('u').in_('users').replace('u').in_('backup').to_aql()'FOR u IN users REPLACE u IN backup'>>>>>>AB.for_('u').in_('users')....filter(...AB.ref('u.active').eq(True)....and_(AB.ref('u.age').gte(35))....and_(AB.ref('u.age').lte(37))...)....remove('u').in_('users')....to_aql()'FOR u IN users FILTER (((u.active == true) && (u.age >= 35)) && (u.age <= 37)) REMOVE u IN users'>>>Working with query parameters:>>>fromaql_builderimportAQLBuilderasAB>>>>>>AB.for_('user').in_('@@users').filter(AB.ref('user.age').gte('@min_age')).return_('user._key').to_aql()'FOR user IN @@users FILTER (user.age >= @min_age) RETURN user._key'>>>Working with graph:>>>fromaql_builderimportAQLBuilderasAB>>>>>>AB.for_('v').in_graph(...graph='knowsGraph',...direction='OUTBOUND',...start_vertex=AB.str('users/1'),...min_depth=1,...max_depth=3...)....return_('v._key')....to_aql()'FOR v IN 1..3 OUTBOUND "users/1" GRAPH "knowsGraph" RETURN v._key'>>>More complex examples:>>>fromaql_builderimportAQLBuilderasAB>>>>>>AB.for_('i').in_(AB.range(1,1000))....insert({...'id':AB(100000).add('i'),...'age':AB(18).add(AB.FLOOR(AB.RAND().times(25))),...'name':AB.CONCAT('test',AB.TO_STRING('i')),...'active':False,...'gender':(...AB.ref('i').mod(2).eq(0).then('"male"').else_('"female"')...)...}).into('users')....to_aql()'FOR i IN 1..1000 INSERT ''{"id": (100000 + i), ''"age": (18 + FLOOR((RAND() * 25))), ''"name": CONCAT(test, TO_STRING(i)), ''"active": false, ''"gender": (((i % 2) == 0) ? "male" : "female")} ''INTO users'>>>>>>>>>AB.for_('u').in_('users')....filter(AB.ref('u.active').eq(True))....collect({...'ageGroup':AB.FLOOR(AB.ref('u.age').div(5)).times(5),...'gender':'u.gender'...}).into('group')....sort('ageGroup','DESC')....return_({...'ageGroup':'ageGroup',...'gender':'gender'...})....to_aql()'FOR u IN users ''FILTER (u.active == true) ''COLLECT ageGroup = (FLOOR((u.age / 5)) * 5), gender = u.gender INTO group ''SORT ageGroup DESC ''RETURN {"ageGroup": ageGroup, "gender": gender}'>>>AcknowledgementsAQL builder is a free software project hosted athttps://foss.heptapod.net. Thanks
to the support ofClever Cloud,Octobusand the sponsors of theheptapod project.
Package: aqtlib
AQTLib (Asynchronous Quantitative Trading Library) is an event-driven algorithmic trading library written in Python,
that supports backtesting, as well as live trading via Interactive Brokers.RequirementsPython>=3.6IB-insync(sync/async framework for Interactive Brokers API,
tested to work with >=0.9.56)A runningTWSorIB Gatewayapplication (version 972 or higher)
Package: aquaaristonremotethermo
Aqua Ariston NET remotethermo APIThin integration is a side project which works only with 1 zone climate configured. It logs in to Ariston website (https://www.ariston-net.remotethermo.com) and fetches/sets data on that site.
You are free to modify and distribute it. It is distributed 'as is' with no liability for possible damage.
See alsohttps://pypi.org/project/aquaaristonremotethermo/.
This API is for Aqua Ariston NET, for Ariston NET refer tohttps://github.com/chomupashchuk/ariston-remotethermo-api.DonationsIf you like this app, please consider donating some sum to your local charity organizations or global organization like Red Cross. I don't mind receiving donations myself (you may conact me for more details if you want to), but please consider charity at first.API and Home AssistantAPI was created in order to be used by Home Assistant. Example of API use for Home Assistant can be found:https://github.com/chomupashchuk/ariston-aqua-remotethermo-home-assistantAPI slow natureAPI connect to the website, which then connect via gateway to the boiler. The bus has problem handling high bandwidth and thus requests are sent after some specific periods of time. Periods were selected based on tests where not much of interfence was seen when using Ariston Net application or Google Home application or usinghttps://www.ariston-net.remotethermo.com. Still interfences occaionally take place. It is normal to occasionally get connection errors due to devices chain involved.AquaAristonHandler was tested works with:Ariston Velis (NOTE THAT THERE ARE 2 TYPES OF VELIS. FOR VELIS WITH NUMBER OF SHOWERS IN APPLICATION USE TYPEvelis, WHILE FOR VELIS WITH TEMPERATURE SETTING IN APPLICATION USE TYPElydos).Ariston LydosAriston Lydos HybridCheck which version to useYour boiler works withAqua Ariston NETand notAriston NET, then potentially it could work.API useAPI importInstall package:pip install aquaaristonremotethermoImport classAquaAristonHandler:from aquaaristonremotethermo.aristonaqua import AquaAristonHandlerAPI dependenciesrequests- used for HTTPS requests towardshttps://www.ariston-net.remotethermo.com.AquaAristonHandler start communicationfrom aquaaristonremotethermo.aristonaqua import AquaAristonHandler

ApiInstanceAqua = AquaAristonHandler(
            username='username',
            password='password'
        )

ApiInstanceAqua.start()Seehelp(AquaAristonHandler)on how to properly initiate API.AquaAristonHandler stop communicationApiInstanceAqua.stop()API propertiesSeehelp(AquaAristonHandler).AquaAristonHandler change of data on remote serverApiInstanceAqua.set_http_data(parameter1=value1,parameter2=value2,...)Method sets values for specific parameter names (see propertysupported_sensors_set_valuesfromhelp(AquaAristonHandler)) on the remote server.AquaAristonHandler change of data exampleApiInstanceAqua.set_http_data(mode="manual")Version "1.0.49"Update urlsVersion "1.0.48"Login fixVersion "1.0.46"Structure cleanupVersion "1.0.44"Split API for Aqua Ariston fromhttps://pypi.org/project/aristonremotethermo/;
Package: aqua-astrocytes
aqua-astrocytesA Python interface for astrocyte quantification and analysisFor details of AQuA for Matlab, seehttps://github.com/yu-lab-vt/AQuAInstallationpip install aqua-astrocytesTodoaqua.statscurrently has features mostly-implemented that are super cool (e.g., inhomogeneous rate function estimation and statistical comparison, kernel regression estimation and statistical comparison) but are not fully documented.It would be nice to pull the MATLAB conversion scripts in here somehow.
Package: aquacrop1
AquaCrop-OSPySoil-Crop-Water model based on AquaCrop-OS.fromaquacropimportAquaCropModel,Soil,Crop,InitialWaterContentfromaquacrop.utilsimportprepare_weather,get_filepathweather_file_path=get_filepath('tunis_climate.txt')model_os=AquaCropModel(sim_start_time=f"{1979}/10/01",sim_end_time=f"{1985}/05/30",weather_df=prepare_weather(weather_file_path),soil=Soil(soil_type='SandyLoam'),crop=Crop('Wheat',planting_date='10/01'),initial_water_content=InitialWaterContent(value=['FC']),)model_os.run_model(till_termination=True)model_results=model_os.get_simulation_results().head()print(model_results)AboutAquaCrop-OSPy is a python implementation of the popular crop-water model AquaCrop, built from the AquaCrop-OS source code.AquaCrop-OS, an open source version of FAO’s multi-crop model, was released in August 2016 and is the result of collaboration between researchers at the University of Manchester, Water for Food Global Institute, U.N. Food and Agriculture Organization, and Imperial College London.AquaCrop-OSPy has been designed in way that users can conduct cutting edge research with only basic python experience. In particular for the design and testing of irrigation stratgeies.Open access journal articlehereIt is built upon the AquaCropOS crop-growth model written in Matlab (paper,webpage) which itself itself is based on the FAO AquaCrop modelWebpage. Comparisons to both base models are shownhere.Aforumhas also been created so that users of AquaCrop-OSPy and AquaCrop-OS can discuss research, bugs and future development.There is also an extensivedocumentationfor the modelInstallpipinstallaquacropQuickstartA number of tutorials has been created (more to be added in future) to help users jump straight in and run their first simulation. Run these tutorials instantly on Google Colab:Running an AquaCrop-OSPy modelEstimation of irrigation water demandsOptimisation of irrigation management strategiesProjection of climate change impactsAquaPlanThe latest development is a streamlit-based web application AquaPlan, a powerful crop management tool that enables farmers, businesses, and governments to make more informed decisions about water management, irrigation investments, and climate risks.You can access AquaPlan using the following link:https://tinyurl.com/aquaplan.More information, including screenshots and gifs, can be found at The University of Manchester'sarticle, Tim Foster's mediumpost, or twitterthread.A seperatecategoryinside the AquaCrop-OSPy forum has been created to discuss
AquaPlan, including any issues, questions, or suggestions.
Package: aquacropeto
aquacrop-etois an actively developed fork of PyETo (https://github.com/woodcrafty/PyEToPython) for calculating reference crop evapotranspiration
(ETo).
The library provides numerous functions for estimating missing meteorological
data.Three methods for estimating ETo/PET are implemented:FAO-56 Penman-Monteith (Allen et al, 1998)Hargreaves (Hargreaves and Samani, 1982; 1985)Thornthwaite (Thornthwaite, 1948)` pip installaquacrop-eto`
Package: aquacrop-pacs27
AquaCrop-OSPySoil-Crop-Water model based on AquaCrop-OS.fromaquacrop.coreimportAquaCropModel,get_filepath,prepare_weatherfromaquacrop.entities.soilimportSoilfromaquacrop.entities.cropimportCropfromaquacrop.entities.inititalWaterContentimportInitialWaterContentweather_file_path=get_filepath('tunis_climate.txt')modelOs=AquaCropModel(sim_start_time=f"{1979}/10/01",sim_end_time=f"{1985}/05/30",weather_df=prepare_weather(weather_file_path),soil=Soil(soilType='SandyLoam'),crop=Crop('Wheat',planting_date='10/01'),initial_water_content=InitialWaterContent(value=['FC']),)modelOs.initialize()modelOs.step(till_termination=True)modelOsResult=modelOs.Outputs.final_stats.head()print(modelOsResult)ABOUTAquaCrop-OSPy is a python implementation of the popular crop-water model AquaCrop, built from the AquaCrop-OS source code.AquaCrop-OS, an open source version of FAO’s multi-crop model, was released in August 2016 and is the result of collaboration between researchers at the University of Manchester, Water for Food Global Institute, U.N. Food and Agriculture Organization, and Imperial College London.AquaCrop-OSPy has been designed in way that users can conduct cutting edge research with only basic python experience. In particular for the design and testing of irrigation stratgeies.Open access journal articlehereIt is built upon the AquaCropOS crop-growth model written in Matlab (paper,webpage) which itself itself is based on the FAO AquaCrop modelWebpage. Comparisons to both base models are shownhere.Aforumhas also been created so that users of AquaCrop-OSPy and AquaCrop-OS can discuss research, bugs and future development.There is also an extensivedocumentationfor the modelInstallpipinstallaquacropQuickstartA number of tutorials has been created (more to be added in future) to help users jump straight in and run their first simulation. Run these tutorials instantly on Google Colab:Running an AquaCrop-OSPy modelEstimation of irrigation water demandsOptimisation of irrigation management strategiesProjection of climate change impacts
Package: aquacroppy
AquaCropPyCrop growth model to address food security and assess the effect of the environment and management on crop production. Python code to run an AquaCrop simulation. AquaCrop was developed by the The Food and Agriculture Organization (FAO).Building with tests includedThis module wasbuiltto be tested, released and installed like any otherpython package. Someday users will be able topip installit from Pypi.For now, developers will need to download the repo and instal it in 'editable mode' to avoid having to re-build it:pip install -e .Running testsLeveragingpytestwith the pytest-cov module:pytest -v --cov=aquacroppyAlternatively, you could run the unit tests withnose:nosetests  --with-coverage --cover-package=aquacroppy -vTest Driven DevelopmentThe idea is to only write code that meets a specification. Generally speaking, the specifications are the tests.Here is a sample workflow:start with a test suite that passeswrite a test for code that does not yet existrun the test, (confirm that it fails)write the minimal amount of code to get the test to passrun the entire test suite again (confirm that new code doesn't break other parts of the application)commit code repositoryrepeatBuilding distributionAfter checking out the repo, run the following command if you want to generate distributions:python3 setup.py sdist bdist_wheel
Package: aquaduct
AQUA-DUCTAqua-Ducta new tool facilitating analysis of the flow of solvent
molecules in molecular dynamic simulations.Visit our homepage ataquaduct.pl.OverviewAqua-Ductcomprises of several applications build on top ofaquaductPython module:valve- performs most of core calculations including tracing of molecules.kraken- performs additional analysis of results.pond- calculates pockets, hotspots, and energy profiles.Aqua-Ductcomes also with simple GUI interface -valveconfig- allowing to setup calculations in a convenient way.AvailabilityAqua-Ductis licensed underGNU GPL v3 license <https://www.gnu.org/licenses/gpl-3.0.en.html>.Source code is available atgithub.com/TUNNELING-GROUP/aqua-duct.Summary of the most important changes is available in ourchangelog.InstallationAqua-Ductcan be easily installed via PyPi:pip install aquaductDetailed instructions onAqua-Ductinstallation are available ataquaduct.pl/installation.To start using Aqua-Duct type:valve.py --helpTroubleshootingIf you encounter any problems with installation do not hesitate to
contact us atinfo@aquaduct.pl. We areREALLYwilling to help!You can also contact us atgithub.com/TUNNELING-GROUP/aqua-duct.DocumentationDocumentation can be found on our homepageaquaduct.pl/documentation.The most recent documentation is also available atTUNNELING-GROUP.github.io/aqua-duct.
Package: aquaipy
A module for working with the AquaIllumination range of aquarium lights.
The following functions are currently supportedSupport for the HD range of lights, including single lights, paired
lights (of the same model) and paired lights (with mixed models)Enabling/Disabling the scheduleQuerying the current brightness of the lightsSetting the brightness of the lightsThis library has been primarily tested with Prime HD and Hydra 26HD
lights, as that is what the author owns. Hydra 52 HDs should work but
haven’t been validated. Also the non-HD range of lights are not
currently supported, although it should be possible to add that support.
If you would like to help fix either of these cases, please contact me
via GitHub or by email.This module is in no way endorsed by AquaIllumination and you use it at
your own risk. It could, and probably does, invalidate your warranty.Generated documentation can be foundhereQuickstartInstall aquaipy usingpip:$ pip install aquaipy. Once that is
complete you can import the AquaIPy class and connect to your lights.In this guide synchronous calls are shown but v2.0.0 of AquaIPy was a
we-write, to provide async support. Synchronous functions are still
supported but they are just wrappers of the async functions.>>>fromaquaipyimportAquaIPy>>>ai=AquaIPy()>>>ai.connect("192.168.1.100")Once the class is initialised and connected, you can query and update
your light.>>ai.get_colors_brightness(){'blue':18.7,'cool_white':4.4,'deep_red':1.0,'green':1.3,'royal':18.4,'uv':46.3,'violet':46.8}>>>ai.update_color_brightness('cool_white',33.333)<Response.Success:0>>>>ai.update_color_brightness('deep_red',-15.2)<Response.Success:0>Issues & QuestionsIf you have any issues, or questions, please feel free to contact me, or
open an issue on GitHub