Saravanan666/pypi-org huggingface dataset:
Package: roadtraffic
roadtrafficOverviewTheroadtrafficPython package for traffic data processing and fundamental diagram estimation. A fundamental diagram is estimated using convex regression with the help of thepyStoNEDpackage. Themoseksolver is used for the estimation. For the academic purposes, you can obtain afree academic licensefor the solver. You can also use the free NEOS server for the estimation, but the computational time will be longer.Currently only data from Finnish roads, collected through this package is supported. The source of data isFintraffic / digitraffic.fi, license CC 4.0 BY.The package works on the raw data. The data can be aggregated over time and road direction/lane. The aggregated data is then bagged for computational efficiency. The estimation of the fundamental diagram is done on the bagged data. The availability of raw data depends on the traffic measurement station. The earliest data are from 1995. New data are available every day at 3 am (Helsinki time zone). The developers of the package are not affiliated with Fintraffic and can't influence the availability or quality of the data.InstallationThe installation of the package is avalable through the PyPI:pipinstallroadtrafficBasic usageThe package offers an opportunity to work with Finnish traffic data. You can select a traffic measurement station (TMS or LAM, in Finnish) from the officialmetadatausingtmsNumberfield or themaptaking the integer part orlamidfield.Let's take as an example the traffic management station number 162, located on Kehä II in Espoo, Finland and load, process the data and estimate the model for September 10-11, 2019.# Import dependenciesfromroadtrafficimportfintraffic# Traffic measurement station of interesttms_id=162# Initiate the list of days (tuples) of interest (Sep 10-11, 2019)days_list=[(2019,253),(2019,254),]# Specify the road direction# Information about the direction could be obtained from the metadata or the mapdirection=1# Initiate the class for Fintraffic datatms=fintraffic.TrafficMeasurementStation(tms_id,days_list)# Load raw data for the selected periodtms.raw.load()# Clean data for the directiontms.raw.clean(direction=direction)# Aggregate datatms.raw_to_agg(aggregation_time_period='5',aggregation_time_period_unit='min')# Bag datatms.agg_to_bag(num_bags_density=40,num_bags_flow=200)# Estimate the model for the mediantms.bag.estimate_model("quantile",[0.5],email="test@test.test")# you can specify your email to receive the log file# Obtain the resultstms.bag.models.get_estimate(0.5)# Estimate the model for the meantms.bag.estimate_model("mean",email="test@test.test")# Obtain the resultstms.bag.models.get_estimate("mean")AuthorsIaroslav Kriuchkov, Doctoral Researcher at Aalto University School of Business, FinlandTimo Kuosmanen, Professor at Turku University School of Economics, FinlandLicenseroadtraffic is licensed under the GNU GPLv3 License - see theLICENSEfile for details
Package: roadtrip
Route53 domain updates for humans.InstallationWith pip:$ pip install roadtripWith setuptools:$ easy_install roadtripRequirementsRoadtrip requiresPython 2.7and leans heavily on the shoulders ofBoto 2.25.0+.UsingYou can use roadtrip to update a round-robin A record, adding a new value if it doesn’t already exist:$ roadtrip --type A --zone example.com --name mycluster.example.com --value 1.2.3.4 --addThere is also a compact syntax for each option:$ roadtrip -t A -z example.com -n mycluster.example.com -v 1.2.3.4 -aYou can also remove a value from a list:$ roadtrip --type A --zone example.com --name mycluster.example.com --value 1.2.3.4 --deleteYou can also specify multiple values to be added, removed, or overwritten (which will discard all previous values):$ roadtrip --type A --zone example.com --name mycluster.example.com --value 1.2.3.4 --value 1.2.3.5 --overwriteYou can also get help:usage: roadtrip [-h] --type {A,AAAA,CNAME,MX,NS,PTR,SOA,SPF,SRV,TXT} --zone
                ZONE --name NAME --value VALUE [--ttl TTL]
                (--add | --delete | --overwrite) [--access-key ACCESS_KEY]
                [--secret-key SECRET_KEY] [--verbose]

Update a Route53 record, adding or removing values.

optional arguments:
  -h, --help            show this help message and exit
  --type {A,AAAA,CNAME,MX,NS,PTR,SOA,SPF,SRV,TXT}, -t {A,AAAA,CNAME,MX,NS,PTR,SOA,SPF,SRV,TXT}
                        The type of record to update.
  --zone ZONE, -z ZONE  The domain name or zone ID.
  --name NAME, -n NAME  The name to update.
  --value VALUE, -v VALUE
                        The data to add or remove. This argument can be used
                        multiple times to add or remove multiple values.
  --ttl TTL, -l TTL     Non-default TTL value.
  --add, -a             Add the value.
  --delete, -d          Remove the value.
  --overwrite, -o       Overwrite all existing values with those provided.
  --access-key ACCESS_KEY, -k ACCESS_KEY
                        Your AWS access key. Will override the
                        AWS_ACCESS_KEY_ID environment variable.
  --secret-key SECRET_KEY, -s SECRET_KEY
                        Your AWS secret key. Will override the
                        AWS_SECRET_ACCESS_KEY envionrment variable.
  --verbose, -vv        Verbose output.You can set a non-default TTL value with--ttland enable verbose output with--verbose.Roadtrip will use theAWS_ACCESS_KEY_IDandAWS_SECRET_ACCESS_KEYenvironment variables if they are set. You
can provide these values yourself or override the environment variables by providing--access-keyand--secret-key.Under the hoodRoadtrip will do its best not to add an entry that already exists or delete an entry that doesn’t. It usesUPSERTto update the values based on the values that exist when you call it.WarningDue to the nature of eventual consistency there is a chance that the values that roadtrip sees when it is run
are different than the values stored in Route53.ROADTRIP MIGHT HELP YOU LOSE DATAif you are not careful.
Please be careful.
Package: roadwatch-data-processor
Roadwatch Data ProcessorThis is a small library build specifically for Project Roadwatch. This package is used to process, format and clean up the csv data on road accidents in France in order
to be integrated in a SQL database.Note:The scripts are adapted for csv files published between 2005-2017.Generate documentation$ make docNote:The documentation is generated usingsphinx.Run tests$ make testUsageProcessingcaracteristiques-2017.csvfile.In[1]:fromrw_data_procimportcaracteristicsIn[2]:df=caracteristics.process(path='files/caracteristiques-2017.csv')In[3]:df.head()Out[3]:lumaggintatmcoladrcommdepgpslatlongdatenum_acc20170000000152111ruenationale59477590M50.513262.921912017-01-1118:20:00201700000002123135ruesonneville59005590M50.536112.953142017-02-1316:30:0020170000000312915rueJulesGuesde59052590M50.521742.887862017-03-0711:50:002017000000041211646rueSonneville59005590M50.537232.957002017-04-2213:00:0020170000000512112Ruerogersalengro59011590M50.529992.937982017-05-2012:30:00AboutThis module is a part of a bigger project called 'Project Roadwatch'. Which is was in individual assignment as a part in the first year graduate program in Computer Science at Lille University, Faculty of Science and Technology.Supervising Professor:Mickael SalsonAuthor:Daniel SASUReferencesBase de données accidents corporels de la circulation.
Package: roamPy
roamPyA python library of API wrapper functions to retrieve data from theroam.plusplatform. Includes theRoampython class which has one method corresponding to each API endpoint including, Subscriptions, SubscriptionPeriods, Products and Licenses.Full focumentaion can be found here:roampy.readthedocs.ioInstallationpip install roamPyGet StartedHow to test connection to the Roam server:from roamPy import Roam



#API Key stored as system variable

token = = os.environ.get('Roam_API_Key')



#Instantiate object of Roam class

roam = Roam(url=<base url of roam instance>, token=token)



#Test connection

print(roam.checkHeartbeat())Successful Connection Output{'data': None, 'meta': {'message': 'API ready for requests'}}Request metadata for a given subscription using its id number:from roamPy import Roam



#API Key stored as system variable

token = = os.environ.get('Roam_API_Key')



#Instantiate object of Roam class

roam = Roam(url=<base url of roam instance>, token=token)



#Return Data for Subscription using ID.

sub = roam.getOneSubscription(id = 'id number')



print(sub)Retreive data for all subscription periods between two dates:from roamPy import Roam



#API Key stored as system variable

token = = os.environ.get('Roam_API_Key')



#Instantiate object of Roam class

roam = Roam(url=<base url of roam instance>, token=token)



allSPBetween = roam.getSubscriptionPeriodsBetween(startDate='2020-01-01', endDate='2021-01-01')



print(allSPBetween)Retreive all licenses and relations:from roamPy import Roam



#API Key stored as system variable

token = = os.environ.get('Roam_API_Key')



#Instantiate object of Roam class

roam = Roam(url=<base url of roam instance>, token=token)



licRel = roam.getLicenseswRels(['licensePeriods', 'publisher'])



print(licRel)
Package: roam-python
QuickStart GuideTo import packagefrom roam import ClientTo get locations for all users at project levelclient = Client(API_KEY=<API-KEY>)To get locations for one userclient = Client(API_KEY=<API-KEY>, USER_ID=<USER-ID>)To get locations for a list of users under the same projectUSER_LIST = ["user_id1", "user_id2", ...]
client = Client(API_KEY=<API-KEY>, USER_ID=<USER_LIST>)To get locations from a group of usersclient = Client(API_KEY=<API-KEY>, GROUP_ID=<GROUP_ID>)To start listening to locationsclient.sub()To stop listening to locationsclient.disconnect()By default the SDK prints out the locations. If the locations are required to any other output, then
please use a callback function.Define callback function and pass in client initializationdef custom_callback_function(payload):
    # print(payload)
    # save_to_file(payload)
    # log(payload)

client = Client(API_KEY=<API-KEY>, CALLBACK=<custom_callback_function>)
Package: roamrs
# RestCore [![CircleCI](https://circleci.com/gh/Roam-gg/RestCore/tree/develop.svg?style=svg)](https://circleci.com/gh/Roam-gg/RestCore/tree/develop) [![codecov](https://codecov.io/gh/Roam-gg/RestCore/branch/develop/graph/badge.svg)](https://codecov.io/gh/Roam-gg/RestCore)
This repository is designed to make developing REST API server, simpler.
Package: roan
Roan is a per-model url purging Django app. It connects to model signals and purge URLs wherever a model is saved, updated or deleted.Getting startedInstallationYou can installRoanusing pip:$ [sudo] pip install roanThe only dependency isrequests, that will be installed automatically bypip(if you don’t use the--no-depsargument).ConfigurationRoanuses only an optional setting:ROAN_PURGE_URL. If you don’t specify it, it’ll behttp://localhost/purge.Example of configuration:ROAN_PURGE_URL = 'http://nginx.souza.cc/clean'nginx proxy_cache supportSince Roan is based on a personal need, it’s based on nginx’sproxy_cache.Suppose you have the following purge mapping:location ~ /purge(/.*) {
    allow 127.0.0.1;
    deny all;
    proxy_cache_purge roan "$scheme://$host$1";
}Now suppose you have the followingDjangomodel:class Post(models.Model):
    title = models.CharField(max_length=100)
    content = models.TextField()And you have a URL/postswhere users can see a list of posts. How can you set a forever cache and expect the cache to be refreshed
whenever a new post is saved? Or whenever a post gets updated or deleted?Using Roan you’ll be able to connect one or more models to one or more URL. So you can connect thePostmodel with the/postsURL,
and whenever a Post gets saved, updated or deleted, Roan makes a request to the/purge/postsURL.UsageOnce you have Roan installed and configured, you just need to call it in a file that Django executes (e.g.: themodels.pyof your app).
Here is the code for the example above, of purging the/postsURL whenever a post gets saved or deleted:from roan import purge
from models import Post

purge("/posts").on_save(Post)
purge("/posts").on_delete(Post)
Package: roaring-landmask
The Roaring LandmaskHave you ever needed to know whether you are in the ocean or on land? And you
need to know it fast? And you need to know it without using too much memory or
too much disk? Then try theRoaring Landmask!Theroaring landmaskis a Rust + Python package for quickly determining
whether a point given in latitude and longitude is on land or not. A landmask
is stored in a tree ofRoaring Bitmaps. Points
close to the shore might still be in the ocean, so a positive
value is then checked against the vector shapes of the coastline.(source)The landmask is generated from theGSHHG shoreline
database(Wessel, P., and W. H.
F. Smith, A Global Self-consistent, Hierarchical, High-resolution Shoreline
Database, J. Geophys. Res., 101, 8741-8743, 1996).An alternative is theopendrift-landmask-data,
which is slightly faster, is pure Python, but requires more memory and disk
space (memory-mapped 3.7Gb).PerformanceMicrobenchmarks:test tests::test_contains_in_ocean         ... bench:          24 ns/iter (+/- 0)
test tests::test_contains_on_land          ... bench:       3,795 ns/iter (+/- 214)Many points, through Python:------------------------------------------------------------------------------------------------------ benchmark: 5 tests -----------------------------------------------------------------------------------------------------
Name (time in us)                       Min                     Max                    Mean                StdDev                  Median                   IQR            Outliers           OPS            Rounds  Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_landmask_many_par          34,335.6220 (>1000.0)   39,922.9660 (>1000.0)   36,167.6438 (>1000.0)  1,602.6359 (>1000.0)   35,658.2270 (>1000.0)  1,722.6990 (>1000.0)       9;1       27.6490 (0.00)         30           1
test_landmask_many             130,760.1480 (>1000.0)  131,155.3400 (>1000.0)  130,863.7110 (>1000.0)    137.1064 (598.03)   130,809.7410 (>1000.0)    135.3770 (>1000.0)       1;1        7.6415 (0.00)          8           1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------The parallel version is significantly faster, while the sequential version is
slightly slower than the equivalent benchmark inopendrift-landmask-data,
which uses about120 ms.Usage from Pythonfromroaring_landmaskimportRoaringLandmaskl=RoaringLandmask.new()x=np.arange(-180,180,.5)y=np.arange(-90,90,.5)xx,yy=np.meshgrid(x,y)print("points:",len(xx.ravel()))on_land=l.contains_many(xx.ravel(),yy.ravel())Building & installingPre-built wheels are available on PyPI:pip install roaring-landmaskTo build from source, you can use pip:pip install .or maturin:Installmaturin.Build and installmaturin build --release
pip install target/wheels/... # choose your whl
Package: roarquery
FeaturesQuery ROAR runsDownload ROAR runs and trialsList ROAR Firestore collectionsRequirementsPython 3.9+fuegoInstallationYou can installRoarqueryviapipfromPyPI:pip install roarqueryRoarqueryalso requires you to installfuego, a command line firestore client.
Please see thefuego documentationfor complete installation instructions.On a Mac, follow these steps:Ensure you have a working go installation. Ifgo versionreturns something, then you are good to go. If not, install go with homebrew:/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
brew install goThen installfuegogit clone https://github.com/sgarciac/fuego.git
cd fuego
go build .
go install .Finally, modify your PATH variable to include the go installation directory, which can be done with the following incantation:echo $HOME/go/bin | sudo tee -a /private/etc/paths.d/goYou may need to open a new terminal window or tab for these changes to take effect.UsageAuthenticationBefore you can useRoarquery, you need to provide authentication details:Roarqueryworks with both the current and legacy ROAR assessment databases.
For example, theroarquery runssubcommand accepts a–legacyparameter to access the legacy database.
If you would like to use roarquery with both databases, you will need to follow
the steps below in both the legacy and current assessment Firebase projects.Retrieve or generate a Service Account key file.go to yourFirebase project console,go to “Project settings” (in the little gear menu next to “Project Overview”),click on the “Service accounts” tab,click on the “Generate new private key” button.Save these files to somewhere on your computer. For example, presuming the previous commands downloaded the files to “$HOME/Downloads/private_key.json” and “$HOME/Downloads/legacy_private_key.json”mkdir-p"$HOME/.firebaseconfig"mv"$HOME/Downloads/private_key.json""$HOME/.firebaseconfig/private_key.json"mv"$HOME/Downloads/legacy_private_key.json""$HOME/.firebaseconfig/legacy_private_key.json"Set the environment variableROAR_QUERY_CREDENTIALS(orROAR_QUERY_LEGACY_CREDENTIALSfor the legacy database) to point to these files.echo"export ROAR_QUERY_CREDENTIALS=\"$HOME/.firebaseconfig/private_key.json\"">>~/.zprofileecho"export ROAR_QUERY_CREDENTIALS=\"$HOME/.firebaseconfig/private_key.json\"">>~/.bash_profileecho"export ROAR_QUERY_LEGACY_CREDENTIALS=\"$HOME/.firebaseconfig/legacy_private_key.json\"">>~/.zprofileecho"export ROAR_QUERY_LEGACY_CREDENTIALS=\"$HOME/.firebaseconfig/legacy_private_key.json\"">>~/.bash_profileCommand-line UsagePlease see theCommand-line Referencefor details.ContributingContributions are very welcome.
To learn more, see theContributor Guide.LicenseDistributed under the terms of theMIT license,Roarqueryis free and open source software.IssuesIf you encounter any problems,
pleasefile an issuealong with a detailed description.CreditsThis project was generated from@cjolowicz’sHypermodern Python Cookiecuttertemplate.
Package: roaskins
Rivals of Aether skin packageThis is a fan-made package to generate skins for the game Rivals of Aether.FeaturesGenerate new skins from color codeGenerate skins with random colorGet the valid in-game color code of skinsGenerate preview imagesShow preview images in windowPrint preview images to fileDocumentationYou can find the documentation here:https://htmlpreview.github.io/?https://github.com/ErrorThreeOThree/roaskins/blob/master/docs/build/html/index.htmlExample Application: Discord chat botI have provided an example application using this library. This application is a discord chat bot that can generate random skins and post preview images in discord. You can find the source code here:https://github.com/ErrorThreeOThree/ROASkinBot
Package: roast
ROASTROAST is an open-source Python framework that simplifies the development of complex validation test suites. To accomplish this, ROAST provides a collection of interfaces that allows test developers to build
test suites in a highly structured manner.Key features:Compose systems from Xilinx or custom componentsDefine systems composed from various configuration sourcesHeirarchical configuration systemRandomized data provider for randomized testingGeneric APIs for simplified usage and accessPlugin system for extensibilityROAST consists of three packages:roast: Core functionality that includes interfaces, plugin framework, configuration
management, and moreroast-xilinx (recommended: plugin for roast that includes Xilinx specific functionality such as
board acquisition, PetaLinux building, Vitis wrapper, and more.pytest-roast (optional): plugin for pytest that includes pytest fixtures for accelerated test
development when using pytest as a test runner. Features includes target automation, scenario
generation, and configuration generation.Example test flow with package breakdown:
Package: roastedbyai
RoastedByAIThis is anunofficialPython package forhttps://roastedby.aito roast and get roasted by AI.How to installInstall the package using one of these pip commands (they both
install the same package, the first command just does not always
work properly on all devices, the second one should always work)pipinstallroastedbyaiWindows:python-mpipinstallroastedbyaiLinux:python3-mpipinstallroastedbyaiUsagefromroastedbyaiimportConversation,Styleconvo=Conversation(Style.valley_girl)user_input=input("Start by roasting the AI:\n>>> ")response1=convo.send(user_input)print(response1)user_input=input("\nRoast the AI again:\n>>> ")response2=convo.send(user_input)print(response2)convo.kill()# This step isn't necessary, the moment you don't use the `convo` object# anymore, python will automatically handle itprint("\n---\nHistory:\n")formsginconvo.history:print(msg["role"],msg["content"],sep=": ")ContributingFeel free to open Pull Requests with new features, improvements or fixes.Disclaimer/CreditsI am not affiliated withhttps://roastedby.ai, all credits for the AI go to them.LicenseThis work is licensed under aCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Package: roast-xilinx
ROASTROAST is an open-source Python framework that simplifies the development of complex validation test suites. To accomplish this, ROAST provides a collection of interfaces that allows test developers to build
test suites in a highly structured manner.Key features:Compose systems from Xilinx or custom componentsDefine systems composed from various configuration sourcesHeirarchical configuration systemRandomized data provider for randomized testingGeneric APIs for simplified usage and accessPlugin system for extensibilityROAST consists of three packages:roast: Core functionality that includes interfaces, plugin framework, configuration
management, and moreroast-xilinx (recommended: plugin for roast that includes Xilinx specific functionality such as
board acquisition, PetaLinux building, Vitis wrapper, and more.pytest-roast (optional): plugin for pytest that includes pytest fixtures for accelerated test
development when using pytest as a test runner. Features includes target automation, scenario
generation, and configuration generation.Example test flow with package breakdown:
Package: roax
RoaxRo·ax /ˈɹoʊ.æks/: A lightweight Python resource-oriented framework.IntroductionRoax is a lightweight framework for building resource-oriented applications in Python.
By composing your application as a set of resources that expose operations through a uniform
interface, they can be automatically exposed through a REST and/or command line interface.FeaturesResource operations accessed through WSGI based REST API.Command-line interface to resource operations.GeneratesOpenAPIinterface description, compatible withSwagger UI.Schema enforcement of resource operation parameters and return values.Authorization to resource operations enforced through imperative security policies.Quick startInstallationpip install roaxHello worldHere is a minimal application that responds with"Hello world!"when the
client accesseshttp://localhost:8000/hello.importroax.schemaasschemafromroax.resourceimportResource,operationfromroax.wsgiimportAppfromwsgiref.simple_serverimportmake_serverclassHelloResource(Resource):@operation(returns=schema.str(),security=[])defread(self):return"Hello world!"app=App("/","Hello","1.0")app.register_resource("/hello",HelloResource())if__name__=="__main__":make_server("",8000,app).serve_forever()Developpoetry install
poetry run pre-commit installTestpoetry run pytest