Saravanan666/pypi-org huggingface dataset:
Package: wexapi
Wex.nz REST API Python ClientWex.nzprovides REST APIs that you can use
to interact with platform programmatically.This API client will help you interact with Wex.nz by REST API.LicenseMIT LicenseWex.nz REST API ReferencePublic APITrade APIContributingTo create new endpoint -create issueorcreate pull requestHow to useGet ticker for each available pair (public api):conn=wexapi.common.WexConnection()info=wexapi.public.InfoApi(conn)api=wexapi.public.PublicApi(conn)forpairininfo.pair_names:ticker=api.get_ticker(pair,info)Get account info (trade api - require api keys)key_file="/var/www/keys.txt"withwexapi.keyhandler.KeyHandler(key_file)ashandler:ifnothandler.keys:print("No keys in key file.")else:forkeyinhandler.keys:print("Printing info for key{}".format(key))withwexapi.WexConnection()asconn:t=wexapi.trade.TradeApi(key,handler,connection=conn)r=t.get_info()Running the testspython -m unittest discover wexapiSetup dev environment with dockerInstallDockerandDocker Composecp /{proj_path}/Dockerfile.dist /{proj_path}/Dockerfile 
    cp /{proj_path}/docker-compose.yml.dist /{proj_path}/docker-compose.ymlInDockerfilechange{host_user}to your local user.Build and run docker containerdocker-compose build 
    docker-compose up -dLogin to docker containerdockerexec-ti-eCOLUMNS="`tput cols`"-eLINES="`tput lines`"wexapi_wexapi_1bashDonateIf you find the library useful and would like to donate, please send some coins here:BTC: 19nhMniZJ4p771ZvFHL3s8zoBML46LqFRv
BCH: qpsx260laq6wj4s99052nuy063v7j0sxsqxluur84z
ETH: 0x387D91F008dB992c7DAd9be8493dfA68E565706E
XRP: rpoi4dWSbEyQP2xmpsNMxCk2g2n5QvVSmM
Waves: 3PPXpTagbQCSXYZ3Y5h6vuFPj6RxHbnapmE
BTS: madmis-1Upgrade pip package (personal notes)python setup.py sdist
twine upload dist/*
Package: wexpect
wexpectWexpectis a Windows variant ofpexpect.Pexpectis a Python module for spawning child applications and controlling
them automatically.You need wexpect if...you want to control any windows console application from python script.you want to write test-automation script for a windows console application.you want to automate your job by controlling multiple application parallel, synchoronusly.Installpip install wexpectUsageTo interract with a child process usespawnmethod:importwexpectchild=wexpect.spawn('cmd.exe')child.expect('>')child.sendline('ls')child.expect('>')print(child.before)child.sendline('exit')For more information seeexamplesfolder.REFACTORRefactor has been finished!!!The default spawn class isSpawnPipefrom now. For more
information readhistory.What is wexpect?Wexpect is a Python module for spawning child applications and controlling
them automatically. Wexpect can be used for automating interactive applications
such as ssh, ftp, passwd, telnet, etc. It can be used to a automate setup
scripts for duplicating software package installations on different servers. It
can be used for automated software testing. Wexpect is in the spirit of Don
Libes' Expect, but Wexpect is pure Python. Other Expect-like modules for Python
require TCL and Expect or require C extensions to be compiled. Wexpect does not
use C, Expect, or TCL extensions.Original Pexpect should work on any platform that supports the standard Python pty module. While
Wexpect works on Windows platforms. The Wexpect interface focuses on ease of use so that simple
tasks are easy.DevThanks for any contributing!TestTo run test, enter into the folder of the wexpect's repo then:python -m unittestDeployThe deployment itself is automated and done byappveyor.
Seeafter_testsection inappveyor.ymlfor more details.The wexpect usespbrfor managing releasing procedures.
The versioning is handled by the pbr. The"master-version"is the git tag. Pbr derives the package
version from the git tags.
Package: weylchamber
The weylchamber packagePython package for analyzing two-qubit gates in the Weyl chamberDevelopment of theweylchamberpackage happens onGithub.
You can read the full documentation atReadTheDocs.InstallationTo install the latest released version of theweylchamberpackage, run this command in your terminal:$pipinstallweylchamberThis is the preferred method to installweylchamber, as it will always install the most recent stable release.If you don’t havepipinstalled, thisPython installation guidecan guide
you through the process.To install the latest development version ofweylchamberfromGithub.$pipinstallgit+https://github.com/qucontrol/weylchamber.git@master#egg=weylchamberUsageTo useweylchamberin a project:import weylchamberSee theTutorialfor details.History0.4.0 (2022-03-18)Drop: Support for Python 3.5-3.7Add: Support for Python 3.8-3.9Update: Use QuTiP 4.6This is a maintenance release updating to the latest versions of Python and QuTiP and dropping support of versions that have reached end-of-life0.3.2 (2019-08-02)Fix: adapt to changes in QuTiP 4.4Fix: adapt to changes in Sphinx (better-apidoc 0.3.1)0.3.1 (2019-02-15)Fix: the routinemake_PE_krotov_chi_constructornow returns a function that is compatible with a stricter interface forchi_constructorin thekrotovpackages (which now requires thatchi_constructorroutines accept keyword arguments).0.3.0 (2019-01-26)Add: routinemake_PE_krotov_chi_constructorfor calculating the boundary conditions for the backward propagation in an optimization towards a perfect entangler using Krotov’s method0.2.1 (2018-12-18)Bugfix: project metadata0.2.0 (2018-12-18)Add: Conversion between canonical basis and Bell basis: functionsbell_basis,gate, andmapped_basis0.1.0 (2018-11-22)Initial release
Package: wf-camera-calibration
# camera_calibrationSupport for calculating intrinsic and extrinsic camera calibration parameters using COLMAP and other tools## Task list
* Create endpoint for preparing COLMAP inputs
* Create endpoint for processing COLMAP outputs
* Add error checking to COLMAP calibrationbashscript
* Add more options to COLMAP calibrationbashscript
* Integrate Docker-based COLMAP processing
* Move Honeycomb functionality to separate package
* Move Wildflower-specific functionality into separate package
* Eliminate OpenCV dependency once necessary functionality is inwf-cv-utils
Package: wf-camera-capture
Camera-nodeAll software needed for a camera node in an environment. Includes pieces for both capture and delivery as well as proxy node that handles centralized processing of video, upload, and queuing in case of slow or down connectivity.ProxyFlask service that receives data from all other camera nodes and feeds and internal queue and that sends data to honeycomb and optionally processes videos to pull out frames that are also sent to honeycomb.CaptureService that runs on nodes that have cameras. Captures video clips in short segments and sends them to their internal queue where workers send the to the proxy.WorkersCelery service that performs tasks from the internal queue. Capture work is processed and sent to the proxy, unless it is a the proxy-node in which case it forwards the work to another task. Video segments are processes and sent to honeycomb. Processing includes tagging etc. Once uploaded the next set of processing happens, key frames are extracted at those are sent to honeycomb as child datapoint objects of the video.If running on more capable hardware the keyframes could be evaluated for things like pose detection or object tracking. This is not planned yet but isn't out of scope specifically.Radio-MonitorA python service that connects to a network of DWM1001 modules over BLE to collect data. That data is queued to be sent to honeycomb. It is expected that this service runs on the proxy node.CUWB-StreamLeverages fluentd to move Ciholas sensor data to S3Before deploying the service, update the Ciholas network config as follows:IPPortInterfaceConfig239.255.76.6776710.0.0.0Input239.255.76.6776670.0.0.0Output0.0.0.0322220.0.0.0PS: In order to resolve an issue with the anchors disconnecting and not reconnecting, you may need to set the interface IPs of the Config and Input rows to the ethernet device's IP (Useifconfig)Build and push servicemake build-cuwb-streamDeploy streaming service to k8# Install envsubtr, on MacOS install through the gettext pkg
brew install gettext
brew link --force gettext 

# Create a config and secrets file with S3 and AWS ENV keys
kubectl apply -f ./k8s/kube-logging.yml
kubectl apply -f ./private/aws-s3-write-auth-config.yml
kubectl apply -f ./private/aws-s3-write-auth-secret.yml
kubectl apply -f ./k8s/fluentd.yml
kubectl apply -f ./k8s/fluentd-s3-config.yml
kubectl apply -f ./k8s/fluentd-s3.yml

TIMEZONE=US/Pacific envsubst < ./k8s/fluentd-s3-scheduler.yml | kubectl apply -f -

kubectl apply -f ./k8s/cuwb-service.ymlSetup cluster with Docker Hub robotFirst login and then copy creds into the cluster:docker login
# Provide username and PAT (personal access token)

kubectl create secret generic regcred --from-file=.dockerconfigjson=/home/wildflowertech/.docker/config.json --type=kubernetes.io/dockerconfigjson
Package: wfcommons
A Framework for Enabling Scientific Workflow Research and DevelopmentThis Python package provides a collection of tools for:Analyzing instances of actual workflow executions;Producing recipes structures for creating workflow recipes for workflow generation; andGenerating synthetic realistic workflow instances.InstallationWfCommons is available onPyPI.
WfCommons requires Python3.6+ and has been tested on Linux and macOS.Installation using pipWhilepipcan be used to install WfCommons, we suggest the following
approach for reliable installation when many Python environments are available:$ python3 -m pip install wfcommonsRetrieving the latest unstable versionIf you want to use the latest WfCommons unstable version, that will contain
brand new features (but also contain bugs as the stabilization work is still
underway), you may consider retrieving the latest unstable version.Cloning fromWfCommons's GitHubrepository:$ git clone https://github.com/wfcommons/wfcommons
$ cd wfcommons
$ pip install .Optional RequirementsGraphvizWfCommons usespygraphvizfor generating visualizations for the workflow task graph.
If you want to enable this feature, you will have to install thegraphvizpackage (version 2.16 or later).
You can install graphviz easily on Linux with your favorite package manager,
for example for Debian-based distributions:sudo apt-get install graphviz libgraphviz-devand for RedHat-based distributions:sudo yum install python-devel graphviz-develOn macOS you can usebrewpackage manager:brew install graphvizThen you can install pygraphviz by running:python3 -m pip install pygraphvizGet in TouchThe main channel to reach the WfCommons team is via the support email:support@wfcommons.org.Bug Report / Feature Request:our preferred channel to report a bug or request a feature is viaWfCommons'sGithub Issues Track.Citing WfCommonsWhen citing WfCommons, please use the following paper. You should also actually read
that paper, as it provides a recent and general overview on the framework.@article{coleman2021fgcs,
    title = {{WfCommons: A Framework for Enabling Scientific Workflow Research and Development}},
    author = {Coleman, Tain\~a and Casanova, Henri and Pottier, Lo\"ic and Kaushik, Manav and Deelman, Ewa and Ferreira da Silva, Rafael},
    journal = {Future Generation Computer Systems},
    volume = {128},
    number = {},
    pages = {16--27},
    doi = {10.1016/j.future.2021.09.043},
    year = {2022},
}
Package: wfconnect
WEBFLEET.connectThis library enables you to interact with WEBFLEETs developer API calledWEBFLEET.connectQuick Startapi = WfConnect(self.url)
api.setAuthentication(
    self.account,
    self.username,
    self.password,
)
...
vehicles = api.showObjectReportExtern("your-group-name")
Package: wf-cv-utils
# cv_utilsMiscellaneous utilities for working with camera data:Utilities for working with images and videos (many of which use OpenCV “under the hood”)Functions which support basic visualization of image and object pointsFunctions which support camera calibration using OpenCV and/or COLMAP## Task listAdd option toproject_points()to include points that are projected inside the frame with distortion but just outside the frame withoutIntegrate (Docker-based?) version of OpenCV which supports proprietary codecs (primarilymp4)Consider implementing additional objects/classes (e.g.,Camera)Move Wildflower-specific functionality into separate packageAdd additional functions so we can eliminate OpenCV as dependency forwf-process-pose_data,wf-video-io,wf-camera-calibration, etc.Implement more performant replacement forcv.triangulatePoints()Augment drawing functions so they can handle multiple objects,Nanvalues, etc.Get ride of unused/buggy functions incoreClean up color conversion helper functions (use OpenCV functions?)Move 3D projection code into its own submoduleConvert drawing functions incoreto object-oriented Matplotlib interface?Convert drawing functions incoreto OpenCV drawing API?Fix comments ingenerate_camera_pose()(currently describes yaw inaccurately)Clean up handling of coordinates (shouldn’t OpenCV accept numpy arrays?)Clean up handling of large integer coordinates
Package: wf-data-monitor
wf-data-monitorAnalyze important Wildflower data streams/sources and raise alerts when known issues ariseDevelopmentRequirementsPoetryjustInstallpoetry installInstall w/ Python Version from PyEnv# Specify pyenv python version
pyenv shell --unset
pyenv local <<VERSION>>

# Set poetry python to pyenv version
poetry env use $(pyenv which python)
poetry cache clear . --all
poetry installTask listTBD
Package: wfdb
The WFDB Python PackageIntroductionA Python-native package for reading, writing, processing, and plotting physiologic signal and annotation data. The core I/O functionality is based on the Waveform Database (WFDB)specifications.This package is heavily inspired by the originalWFDB Software Package, and initially aimed to replicate many of its command-line APIs. However, the projects are independent, and there is no promise of consistency between the two, beyond each package adhering to the core specifications.Documentation and UsageSee thedocumentation sitefor the public APIs.See thedemo.ipynbnotebook file for example use cases.InstallationThe distribution is hosted on PyPI at:https://pypi.python.org/pypi/wfdb/. The package can be directly installed from PyPI using either pip or poetry:pipinstallwfdb
poetryaddwfdbOn Linux systems, accessingcompressedWFDB signal files requires installinglibsndfile, by runningsudo apt-get install libsndfile1orsudo yum install libsndfile. Support for Apple M1 systems is a work in progess (seehttps://github.com/bastibe/python-soundfile/issues/310andhttps://github.com/bastibe/python-soundfile/issues/325).The development version is hosted at:https://github.com/MIT-LCP/wfdb-python. This repository also contains demo scripts and example data. To install the development version, clone or download the repository, navigate to the base directory, and run:# Without dev dependenciespipinstall.
poetryinstall# With dev dependenciespipinstall".[dev]"poetryinstall-Edev# Install the dependencies onlypoetryinstall-Edev--no-rootSee thenoteabout dev dependencies.DevelopingPlease see theDEVELOPING.mddocument for contribution/development instructions.CitingWhen using this resource, please cite the softwarepublicationon PhysioNet.
Package: wfdserver
Winter Field Day log aggregating serverTOCWinter Field Day log aggregating serverTOCWhat is itNo really what is itScreenshotInstallationConfiguration and first runWhat is itWinter Field Dayis a once a year 24hr
emergency preparidness event for radio amateurs (Hams). During the event, we try
and make as many radio contacts with other Hams in a 24 hour period. Bonus
points are awarded for operating outside or using alternate power sources, such
as battery/solar/wind. You can find out more about Winter Field Day by visiting
theWFDA. You can find out more about amateur radio
by visiting theARRL.No really what is itThis server listens to multicast logging packets generated by multiplewfdloggerclients. So a group or club can submit a group cabrillo log.ScreenshotInstallationpipinstallwfdserverusage: wfdserver [-h] [-l]

Winter Field Day aggregation server.

options:
  -h, --help  show this help message and exit
  -l, --log   Generate logConfiguration and first runWhen executed for the first time, the server will not find a configuration file.
When this happens, the server will place a fresh copy in the local directory.
Press CTRL-C to end the program then edit the configuration file now found at./server_preferences.json. Unless you have good reason to, don't change the
multicast settings.{"ourcall":"W1AW","ourclass":"3O","oursection":"ORG","name":"Hiram Maxim","address":"225 Main Street","city":"Newington","state":"CT","postalcode":"06111","country":"USA","email":"Hiram.Maxim@arrl.net","bonus":{"altpower":false,"outdoors":false,"notathome":false,"antenna":false,"satellite":false},"mullticast_group":"224.1.1.1","multicast_port":2239,"interface_ip":"0.0.0.0","node_red_server_ip":"127.0.0.1","node_red_server_port":12062}Under the bonus section, if your group qualifies for a bonus, puttruenext
to the type of bonus.Save the file and relaunch the wfdserver application.
Package: wfepy
WfEpy (Workflow Engine for Python)is Python library for creating workflows
and automating various processes. It is designed to be as simple as possible so
developers can focus on tasks logic, not how to execute workflow, store state,
etc.Individual steps in workflow are simply functions with decorator and transitions
between tasks are also defined by decorators. Everything what developer needs to
do is add few decorators to functions that implements tasks logic. This library
is then used to build graph from tasks and transitions and execute tasks in
workflow by traversing graph and calling task functions. Context passed to each
function is arbitrary user object that can be used to store data, connect to
other services or APIs, …@wfepy.task()@wfepy.start_point()@wfepy.followed_by('make_coffee')defstart(context):...@wfepy.task()@wfepy.followed_by('drink_coffee')defmake_coffee(context):...@wfepy.task()@wfepy.followed_by('end')defdrink_coffee(context):...@wfepy.task()@wfepy.end_point()defend(context):...WfEpy does not provide any server scheduler or something like that. It was
designed to be used in scripts, that are for example periodically executed by
cron. If workflow have task that cannot be finished in single run library
provides way how to store current state of runner including user data and
restore it on next run.importcoffee_workflowwf=wfepy.Workflow()wf.load_tasks(coffee_workflow)runner=wf.create_runner()ifrestore_state:runner.load('state-file')runner.run()runner.dump('state-file')This simple design provides many options how to execute your workflow and
customize it. This was also reason why this library was created, we don’t want
to manage new service/server that executes few simple workflows. We would like
to use service we already have, for example Jenkins, cron, …InstallationInstall it using pippip3 install wfepyor clone repositorygit clone https://github.com/redhat-aqe/wfepy.git
cd wfepyand install Python package including dependenciespython3 setup.py install
Package: wfetch
wfetchwfetch is a Minimal Windows system information tool written in Python (Only works on Windows)InstallationFirst of all have python installed.https://www.python.org/Then install MesloLGS NF Fonts:MesloLGS NF Regular.ttfMesloLGS NF Bold.ttfMesloLGS NF Italic.ttfMesloLGS NF Bold Italic.ttfI use font size 11.Use Windows Terminal.pipinstallwfetchUsagewfetchContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.LicenseMITBuy Me a Coffee
Package: wfetch-cli
wfetch-cliTo install:pip install wfetch-cliDescriptionwfetch-cliis a tool for reliable downloading of files from the internet.Tool downloads files from the internet.Uses .netrc for authentication.Optionally expected file sha256 can be supplied. The tool will verify downloaded file hash, and will fail if it does not match.If file exists, and hash matches, it won't be downloaded.
Package: wf-fastapi-auth0
Wildflower FastAPI/Auth0 integrationBasic token verification for FastAPI and Auth0.  Also includes support for the Wildflower Permissions API, which provides centralized Role/Domain based access control.Environment ConfigurationAUTH0_DOMAINDomain to auth against within Auth0API_AUDIENCEAudience the tokens should targetCLIENT_IDClient ID for machine-to-machine authenticatio for checking user ProfilesCLIENT_SECRETClient Secret for machine-to-machine authenticatio for checking user ProfilesFor permissions-api integration (optional)TOKEN_EMAIL_DOMAINDomain to add to client_credentials for email address forwf_permissionsintegrationTOKEN_DOMAINDomain to add to client_credentials forwf_permissionsintegrationPERMS_API_URIURI for permissions APIPERMS_API_AUDAudience to auth against with machine-to-machine tokens
Package: wfgenes
wfGenes:wfGenes is a tool to generate various type of workflow management systems (WMSs) by parsing single workflow configuration file called WConfig.
Naturally, workflows are defined in human readable format, JSON or YAML, with efficient and concise structure to generate different type of WMSs by performing dependency analysis and automatic code generation for specific WMS.
This approach enables users to examine different type of WMS based on the application requirement and available computing environment.Installing wfGenes on Local machine:The recommended way to install wfGenes is to use pip package manager.pip install wfgenesTo use the GUI run the following line in a Jupyter notebook cell:from wfgenes import wfgenes_guiWebsite (including documentation):https://wfgenes.gitlab.io/wfgenes/Source:https://git.scc.kit.edu/th7356/wfgenes
Package: wf-honeycomb-io
honeycomb_ioTools for working with data in Wildflower's Honeycomb databaseInstallationpip install wf-honeycomb-ioTask listIntegrate Honeycomb IO functions fromwf-inference-helpersIntegrate Honeycomb IO functions fromcuwb_sensorIntegrate Honeycomb IO functions fromwf-inference-airflow?Integrate Honeycomb IO functions fromwf-video-stream-consumer?Integrate Honeycomb IO functions fromwf-pose-producer?Integrate Honeycomb IO functions fromhoneycomb-geom-processor?Integrate Honeycomb IO functions fromhoneycomb-video-streamer?Integrate Honeycomb IO functions fromwf-honeycomb-service-event-producer?Integrate Honeycomb IO functions fromclassroom-video-uploader?Redesign architecture so user doesn't need to create a clientCreate a function for each basic verb:objects()get_object()find_objects()Create corresponding functions for each verb/object combination?Rewrite existing external functions to use the basic functions aboveConsider replacing existing external functions with the basic functions above (changes API)
Package: wf-honeycomb-rds-client
honeycomb_rds_clientA client for communicating with the RDS database underlying HoneycombInstallationpip install wf-honeycomb-rds-clientDevelopmentRequirementsPoetryjustInstallpoetry installInstall w/ Python Version from PyEnv# Specify pyenv python version
pyenv shell --unset
pyenv local <<VERSION>>

# Set poetry python to pyenv version
poetry env use $(pyenv which python)
poetry cache clear . --all
poetry installTask listTBD
Package: wfiuh
WFIUHCurve fitting width function IUH (WFIUH) in HydrologyResults can be foundhere.CDFModelSuccess FitsBeta11069 / 11069DoublePower11066 / 11069DoubleTriangular11069 / 11069Frechet11062 / 11069Gamma11062 / 11069Hill11059 / 11069Hoerl11069 / 11069InverseGaussian11066 / 11069Kumaraswamy11069 / 11069Logistic11062 / 11069Multistage11065 / 11069NormalGaussian11069 / 11069Polynomial11069 / 11069Rational11069 / 11069ShiftedLogPearson311051 / 11069Weibull11069 / 11069PDFModelSuccess FitsBeta11061 / 11069DoublePower11065 / 11069DoubleTriangular11063 / 11069Frechet11039 / 11069Gamma11065 / 11069Hill11068 / 11069Hoerl11059 / 11069InverseGaussian11064 / 11069Kumaraswamy11069 / 11069Logistic10754 / 11069Multistage11065 / 11069NormalGaussian11069 / 11069Polynomial11069 / 11069Rational11064 / 11069ShiftedLogPearson311027 / 11069Weibull11065 / 11069