Saravanan666/pypi-org huggingface dataset:
Package: cloudinary-upload
AboutThis library allows you to upload a signed image to cloudinary effectively.InstallationInstall the library to begin using it.pip install cloudinary-uploadConfigure.envwith your cloudinary credentials.CLOUDINARY_NAME=xxxxxxx
CLOUDINARY_API_KEY=xxxxxxxxxxx
CLOUDINARY_API_SECRET=xxxxxxxxx-xxxxxxxIn the file (.py) that you wish to use it, import the library.from cloudinary_upload import upload_image_cloudinary

upload_true = upload_image_cloudinary(image_file="/path/to/image.png")Theupload_truevariable is going to give you a bunch of meaningful information from cloudinary, you can get the image_url by printing:print("Image URL: ", upload_true['url'])ContributeAll contributions are welcome:Read the issues, Fork the project and do a Pull Request.Request a new topic creating aNew issuewith theenhancementtag.Find any kind of errors in theREADMEand create aNew issuewith the details or fork the project and do a Pull Request.Suggest a better or more pythonic way for existing examples.
Package: cloudinitd
This package can be considered the /etc/rc.d of the cloud!This libary helps users bootstrap many dependent VMs in a cloud (or many clouds).  Services are associated with
virtual machine images in a cloud and then organized into levels.  Each level is booted in order.  Booting a level
means launching and configuring all of the VMs needed for each service in the level to run.  Once level 1 is
booted and ready to go, booting begins on level 2.
Package: cloud-init-seed
cloud-init-seedis a command line tool to create seed images
which can be used together withcloud-init. This is eg. useful when using
Cloud images (which containcloud-init) together withlibvirt(which does
not have a metadata server which is usually used together with cloud-init).Notecloud-initin the image must have thenoclouddatasource enabled.Requirements and installationmkisofs or genisoimage (zypper in mkisofsfor openSUSE orapt install genisoimagefor Debian)when using virtual envs, just install via pippip3 install cloud-init-seedUsageCreate a seed image:cloud-init-seed createNow theseed.imgfile can be attached to a libvirt instance as a CDROM drive.
Package: cloudio-connector-python
cloudio-connector-pythonThis library is a helper to create python cloudioapplications.The cloudio project:http://cloudio.hevs.ch/The cloud.iO three layersCloud.iO is composed of 3 layers:The endpoints: distributed field devices that mainly measures and actuate things.Cloudio services: the cloud.iO server that communicate with the endpoints, stores the data and provide a http rest api to the applications.The applications: data analysis, controls the endpoint setpoints, ...This library is used to create applications.The cloud.iO data modelHere is a quick reminder of the cloud.iO data model:Note: You can have objects in objects, that's why an object list is needed to create an AttributeId.You can get the data model of an endpoint:cc = CloudioConnector("https://example.com", "user", "password")

sp = cc.get_endpoint_structure('ba3d3ec2-23b6-45a8-827a-3b3133a69076')Read/Write attributesExamplecc = CloudioConnector("https://example.com", "user", "password")

sp = AttributeId(uuid='ba3d3ec2-23b6-45a8-827a-3b3133a69076', node='myNode', 
                    objects=['myObject'], attribute='mySetPoint')
mea = AttributeId(uuid=cc.get_uuid('demo'), node='myNode', 
                    objects=['myObject'], attribute='myMeasure')

# get the last value of an attribute
last_val = cc.get_last_value(mea)
print(str(mea) + ' ' + str(last_val))

# get the mean value of the last 15 minutes
mean = cc.get_mean_value(mea, 15*60)

# write the value of an attribute
cc.write_value(sp, 1.0)Get attributes time seriesExamplecc = CloudioConnector("https://example.com", "user", "password")

sp = AttributeId(uuid='ba3d3ec2-23b6-45a8-827a-3b3133a69076', node='myNode', 
                    objects=['myObject'], attribute='mySetPoint')
mea = AttributeId(uuid=cc.get_uuid('demo'), node='myNode', 
                    objects=['myObject'], attribute='myMeasure')

tm_mea = TimeSeries(mea, start=datetime.now() - datetime.timedelta(hours=24), 
                    stop=datetime.now(), resample='15m')
tm_sp = TimeSeries(sp, start=datetime.now() - datetime.timedelta(hours=24), 
                    stop=datetime.now(), resample='15m')

# get attribute time series
data = cc.get_time_series(tm_mea)
# data is the same as tm_mea.data

# convert cloudio time series to panda data frame
cc.data_frame(data, serie_name="My Measure")

# get multiple time series with multithreading
cc.get_multiple_time_series([tm_mea, tm_sp])
print(tm_mea.data)
print(tm_sp.data)Get notified for attribute new valueExampleclass Example(AttributeListener):
    def __init__(self):
        cc = CloudioConnector("https://example.com", "user", "password")
        cc.add_attribute_listener(self)

        attr = AttributeId(uuid=cc.get_uuid('demo'), node='myNode', 
                            objects=['myObject'], attribute='myMeasure'),
        
        # subscribe to attribute on change event
        cc.subscribe_to_attribute(attr)
        
    # this method is called when a subscribed attribute has changed
    def attribute_has_changed(self, attribute: AttributeId, value):
        print(str(attribute) + ' ' + str(value))
Package: cloudkitty
Team and repository tagsCloudKittyRating as a Service componentGoalCloudKitty aims at filling the gap between metrics collection systems like
ceilometer and a billing system.Every metrics are collected, aggregated and processed through different rating
modules. You can then query CloudKitty’s storage to retrieve processed data and
easily generate reports.Most parts of CloudKitty are modular so you can easily extend the base code to
address your particular use case.You can find more information on its architecture in the documentation,architecture section.StatusCloudKitty has been successfully deployed in production on different OpenStack
systems.You can find the latest documentation onreadthedocs.ContributingWe are welcoming new contributors, if you’ve got new ideas, suggestions or want
to contribute contact us.You can reach us thought IRC (#cloudkitty @ oftc.net), or on the official
OpenStack mailing listopenstack-discuss@lists.openstack.org.Astoryboardis available if you need to report bugs.Additional componentsWe’re providing an OpenStack dashboard (Horizon) integration, you can find the
files in thecloudkitty-dashboardrepository.A CLI is available too in thepython-cloudkittyclientrepository.Trying itCloudKitty can be deployed with devstack, more information can be found in thedevstack sectionof the documentation.Deploying it in productionCloudKitty can be deployed in production on OpenStack Kilo environments, for
more information check theinstallation sectionof the documentation. Due to
oslo libraries new namespace backward compatibility is not possible. If you
want to install it on an older system, use a virtualenv.Getting release notesRelease notes can be found in therelease notes sectionof the
documentation.
Package: cloudkitty-dashboard
Wiki:CloudKitty WikiIRC:#cloudkitty @ oftc.netHorizon dashboard for CloudKitty.Aboutcloudkitty-dashboard is an extension for OpenStack Dashboard providing UI for
CloudKitty.With CloudKitty dashboard, operators can easily define a rating policy for
their cloud without the use of a CLI.
Users can get information about their usage, and predict costs of an instance.ContributingWe are welcoming new contributors, if you’ve got new ideas, suggestions or want
to contribute, contact us.You can reach us through IRC (#cloudkitty @oftc.net), or on the official
OpenStack mailing listopenstack-discuss@lists.openstack.org.Astoryboardproject is available if you need to report bugs.Trying itCloudKitty can be deployed with devstack, more information can be found in thedevstack sectionof the documentation.
Package: cloudkitty-dev
Team and repository tagsCloudKittyRating as a Service componentGoalCloudKitty aims at filling the gap between metrics collection systems like
ceilometer and a billing system.Every metrics are collected, aggregated and processed through different rating
modules. You can then query CloudKitty’s storage to retrieve processed data and
easily generate reports.Most parts of CloudKitty are modular so you can easily extend the base code to
address your particular use case.You can find more information on its architecture in the documentation,architecture section.StatusCloudKitty has been successfully deployed in production on different OpenStack
systems.You can find the latest documentation onreadthedocs.ContributingWe are welcoming new contributors, if you’ve got new ideas, suggestions or want
to contribute contact us.You can reach us thought IRC (#cloudkitty @freenode.net), or on the official
OpenStack mailing listopenstack-discuss@lists.openstack.org.Astoryboardis available if you need to report bugs.Additional componentsWe’re providing an OpenStack dashboard (Horizon) integration, you can find the
files in thecloudkitty-dashboardrepository.A CLI is available too in thepython-cloudkittyclientrepository.Trying itCloudKitty can be deployed with devstack, more information can be found in thedevstack sectionof the documentation.Deploying it in productionCloudKitty can be deployed in production on OpenStack Kilo environments, for
more information check theinstallation sectionof the documentation. Due to
oslo libraries new namespace backward compatibility is not possible. If you
want to install it on an older system, use a virtualenv.Getting release notesRelease notes can be found in therelease notes sectionof the
documentation.
Package: cloudkitty-tempest-plugin
This project defines a tempest plugin containing tests used to verify the
functionality of a cloudkitty installation. The plugin will automatically load
these tests into tempest.DependenciesThis plugin tests the CloudKitty API. This supposes that the ‘rating’ role
exists in your OpenStack installation.DevelopersFor more information on cloudkitty, refer to:https://docs.openstack.org/cloudkitty/latest/For more information on tempest plugins, refer to:https://docs.openstack.org/tempest/latest/#using-pluginsBugsPlease report bugs to:https://storyboard.openstack.org/#!/project/890InstallingClone this repository and call from the repo:$ pip install -e .Running the testsTo run all the tests from this plugin, call from the tempest repo:$ cd <Tempest Directory>
$ tox -e all -- cloudkitty_tempest_pluginTo run a single test case, call with full path, for example:$ cd <Tempest Directory>
$ tox -e all -- cloudkitty_tempest_plugin.tests.api.test_cloudkitty_api.CloudkittyAdminAPITest.test_get_collector_mappingsTo retrieve a list of all tempest tests, run:$ cd <Tempest Directory>
$ testr list-tests
Package: cloudknot
cloudknotA knot is a collective noun for a group of snakes. Cloudknot is a python
library designed to run your existing python code onAWS Batch.Cloudknot takes as input a python function, Dockerizes it for use in an
Amazon ECS instance, and creates all the necessary AWS Batch constituent
resources to submit jobs. You can then use cloudknot to submit and view jobs
for a range of inputs.To get started using cloudknot, please see thecloudknot documentationThis is the cloudknot development site. You can view the source code, file new
issues, and contribute to cloudknot's development. If you are just getting
started, you should look at thecloudknot documentation.ContributingWe love contributions! Cloudknot is open source, built on open source,
and we'd love to have you hang out in our community.We have developed someguidelinesfor contributing to
cloudknot.Imposter syndrome disclaimer: We want your help. No, really.There may be a little voice inside your head that is telling you that
you're not ready to be an open source contributor; that your skills
aren't nearly good enough to contribute. What could you possibly offer a
project like this one?We assure you - the little voice in your head is wrong. If you can
write code at all, you can contribute code to open source. Contributing
to open source projects is a fantastic way to advance one's coding
skills. Writing perfect code isn't the measure of a good developer (that
would disqualify all of us!); it's trying to create something, making
mistakes, and learning from those mistakes. That's how we all improve,
and we are happy to help others learn.Being an open source contributor doesn't just mean writing code, either.
You can help out by writing documentation, tests, or even giving
feedback about the project (and yes - that includes giving feedback
about the contribution process). Some of these contributions may be the
most valuable to the project as a whole, because you're coming to the
project with fresh eyes, so you can see the errors and assumptions that
seasoned contributors have glossed over.Citing cloudknotIf you use cloudknot in a scientific publication, please see ourcitation
instructions.CreditsCloudknot development is supported through a grant from theGordon
and Betty Moore Foundationand from theAlfred P. Sloan Foundationto theUniversity of
Washington eScience Institute, as
well as NIH Collaborative Research in Computational Neuroscience grant
R01EB027585-01 through the National Institute of Biomedical Imaging and
Bioengineering to Eleftherios Garyfallidis (Indiana University) and
Ariel Rokem (University of Washington).This package was created withshablona.The imposter syndrome disclaimer was originally written byAdrienne Lowefor aPyCon
talk, and was
adapted based on its use in the README file for theMetPy
project.
Package: cloudlab_client
Cloudlab ClientThis package is a client for the Cloudlab service. Cloudlab is a cloud for
academic institutions. Because I could not (yet) find any working API for
Cloudlab, the current client relies on username / password authentication and
web scraping.Usage# Create new client and loginusername=os.environ.get("CLOUDLAB_USERNAME")password=os.environ.get("CLOUDLAB_PASSWORD")cloudlab_client=CloudlabClient()cloudlab_client.login(username,password)# List experimentsexperiments=cloudlab_client.experiment_list()print(experiments)# List an experiment's nodesnodes=cloudlab_client.experiment_list_nodes("my-experiment")print(nodes)# Request an extension (e.g., for 6 days). Reason must be at least 120 characters.reason=("Important experiment needed for research, conducted under advisor"" <fill_your_advisor>. Particular machines are needed because"" <fill_your_reasons>.")cloudlab_client.experiment_extend("my-experiment",reason,hours=6*24)
Package: cloudlabeling
Cloudlabeling APIcondacreate-ncloudlabelingpythonpip
condaactivatecloudlabeling
pipinstallcloudlabelingHow to use (Python)fromcloudlabelingimportcloudlabelingcloud_labeler=cloudlabeling.CloudLabeling()results=cloud_labeler.infer_remotely(image_path,project_id="MSCOCO")Results output in JSON format{"detection":[#listofdetections{"box":[268.44647216796875,#xmin4.61001443862915,#ymin2401.08740234375,#xmax1919.837646484375#ymax],"label":"bowl",#classname"label_idx":45,#classID"confidence":0.7302282#confidencescore},...],"labels":[#listoflabelsindetection"dining table","bowl","cake"],"error":None#error(ifany)}
Package: cloudlaunch-cli
===============CloudLaunch CLI===============.. image:: https://travis-ci.org/CloudVE/cloudlaunch-cli.svg?branch=master:target: https://travis-ci.org/CloudVE/cloudlaunch-cli.. image:: https://coveralls.io/repos/github/CloudVE/cloudlaunch-cli/badge.svg?branch=master:target: https://coveralls.io/github/CloudVE/cloudlaunch-cli?branch=master.. image:: https://img.shields.io/pypi/v/cloudlaunch_cli.svg:target: https://pypi.python.org/pypi/cloudlaunch_cli.. image:: https://readthedocs.org/projects/cloudlaunch-cli/badge/?version=latest:target: https://cloudlaunch-cli.readthedocs.io/en/latest/?badge=latest:alt: Documentation Status.. image:: https://pyup.io/repos/github/CloudVE/cloudlaunch_cli/shield.svg:target: https://pyup.io/repos/github/CloudVE/cloudlaunch_cli/:alt: UpdatesCommand line client to the CloudLaunch API.* Free software: MIT license* Documentation: https://cloudlaunch-cli.readthedocs.io.Quickstart==========1. Create a virtual environment and activate it::python3 -m venv venvsource venv/bin/activate2. Install ``cloudlaunch-cli`` with pip::pip install cloudlaunch-cli3. The CloudLaunch CLI requires two config settings. First is the URL ofthe API root:::cloudlaunch config set url https://launch.usegalaxy.org/cloudlaunch/api/v14. Second config setting is an auth token. To get an auth token, firstlog into CloudLaunch, for example, by going tohttps://launch.usegalaxy.org/login. Then navigate to the``/api/v1/auth/tokens`` API endpoint, for example,https://launch.usegalaxy.org/cloudlaunch/api/v1/auth/tokens/.Copy the token out of the JSON response and then run the following(substituting your own token instead):::cloudlaunch config set token b38faadf2ef6d59ce46711ed73e99d6...5. Now you should be able to list your deployments::cloudlaunch deployments list6. You can create a deployment as well::cloudlaunch deployments create my-ubuntu-test ubuntu \amazon-us-east-n-virginia --application-version 16.04Installing for development==========================1. ``python3 -m venv venv``2. ``source venv/bin/activate``3. ``pip install -r requirements_dev.txt``Now you can run ``cloudlaunch``.Release process===============::bumpversion patch# or `bumpversion minor` or `bumpversion major`git pushgit push --tagsmake releaseCredits---------This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template... _Cookiecutter: https://github.com/audreyr/cookiecutter.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage=======History=======0.2.0 - 2018-11-14 - (sha 331e58f756145316334049100f582dd4316055fb)------------------* Major refactoring.* Backward compatibility with Python 2.* Integration tests with CloudLaunch.0.1.0 - 2018-01-09------------------* First release on PyPI.
Package: cloudlaunch-server
CloudLaunchCloudLaunch is a ReSTful, extensible Django app for discovering and launching
applications on cloud, container, or local infrastructure. A live version is
available athttps://beta.launch.usegalaxy.org/.CloudLaunch can be extended with your own plug-ins which can provide custom
launch logic for arbitrary custom applications. Visit the live site to see
currently available applications in the Catalog. CloudLaunch is also tightly
integrated withCloudBridge, which makes
CloudLaunch natively multi-cloud.CloudLaunch has a web and commandline front-end. The Web UI is maintained in theCloudLaunch-UIrepository.
The commandline client is maintained in thecloudlaunch-clirepository.This is an all-new version of CloudLaunch that replaces the original
BioCloudCentral launcher. Code for that version is available in theBioCloudCentral branch.Install Production VersionInstall the cloudlaunch django server$pipinstallcloudlaunch-serverOnce installed, You can run django admin commands as follows:$cloudlaunch-serverdjangoCopycloudlaunchserver/settings_local.py.sampletocloudlaunchserver/settings_local.pyand make any desired configuration
changes.Make sure to changethe value forFERNET_KEYSvariable
because it is used to encrypt sensitive database fields.Prepare the database with:$cloudlaunch-serverdjangomigrate$cloudlaunch-serverdjangocreatesuperuser$cloudlaunch-serverdjangorunserverStart the development server and celery task queue (along with a Redis
server as the message broker), each process in its own tab.$pythonmanage.pyrunserver$redis-server&celery-Acloudlaunchserverworker-linfo--beatVisithttp://127.0.0.1:8000/admin/to define your application and
infrastructure properties.Visithttp://127.0.0.1:8000/api/v1/to explore the API.You will probably also want to install the UI for the server. The default UI
is available athttps://github.com/galaxyproject/cloudlaunch-ui.Install Development VersionCloudLaunch is based on Python 3.6 and although it may work on older Python
versions, 3.6 is the only supported version. Use of virtualenv is also highly advised.Checkout cloudlaunch and create environment$mkdirlauncher&&cdlauncher$virtualenvvenv-ppython3.6--prompt"(cloudlaunch)"&&sourcevenv/bin/activate$gitclone-bdevhttps://github.com/galaxyproject/cloudlaunch.git$cdcloudlaunch$pythonsetup.pydevelop$cddjango-cloudlaunch$pythonmanage.pymigrate$pythonmanage.pyrunserver$pythonmanage.pycreatesuperuserFollow step 2 onwards from the production instructions aboveHistory2.0.0 (2017-01-28)First release of the rewritten CloudLaunch on PyPI.
Package: cloudlib
Date:2013-09-05 09:51tags:cloud, library, generalcategory:*nixMiddleware for in application useEver wish you didn’t have to develop some general purpose libraries and or
middleware which you simply tote around between applications making simple
tweaks when appropriate or blindly copying and pasting as needed? If so,
then this is a library you can sink your code into.WhyI built this because I use the same code over and over again and I’m tired of
copying the same bits between projects. So now, if I have something that’s
general purpose enough I’m going to put it in library which I’ll use throughout
my applications as I develop them.FeaturesArgument parsing for CLI applicationsHTTP requestsUniversal loggingOutbound email messagingLinux package installationConfiguration file parsingShell commandsVarious utilitiesInfoProject Url:https://github.com/cloudnull/cloudlibIssues:https://github.com/cloudnull/cloudlib/issuesPull requests are always welcome.Building the DocsClone the repo, navigate to the docs directory and execute the following.sphinx-build-bhtml-d_build/doctrees._build/htmlOnce complete the docs will be in thedocs/_build/htmldirectory.TestingTo run tests, go to the root directory of thecloudlibmodule and execute
the commandtox. this will automatically run all tests for Python 2.6 - 2.7Doc tests are also used in this library. To run doc tests, go to the docs
directory in this root of this module and executemake doctest.
Package: cloudlink
CloudLink PythonThis is the original, Python-based codebase for CloudLink server.💡 Features 💡🪶 Fast and lightweightCloudLink can run on minimal resources. At least 25MB of RAM and any reasonably capable CPU can run a CloudLink server.🌐 Essential networking toolsUnicast and multicast packets across clientsExpandable functionality with a built-in method loader📦 Minimal dependenciesAll dependencies below can be installed usingpip install -r requirements.txt.🐍 Python >=3.11🧵 asyncio (Built-in)📃"ujson" ultrajson🔍pyeve/cerberus❄️"snowflake-id" vd2org/snowflake🌐aaugustin/websockets🔋Batteries includedThe CloudLink Python server comes with full support for the CL4 protocol and the Scratch cloud variable protocol.
Just download, setup, and start!🧱 Plug-and-play modularityYou can easily extend the functionality of the server using classes and decorators.
Here's an example of a simple plugin that displays "Foobar!" in the console
when a client sends the message{ "cmd": "foo" }to the server.# Import the serverfromcloudlinkimportserver# Import default protocolfromcloudlink.server.protocolsimportclpv4# Instantiate the server objectserver=server()# Set logging levelserver.logging.basicConfig(level=server.logging.DEBUG)# Load default CL protocolclpv4=clpv4(server)# Define the functions your plugin executesclassmyplugin:def__init__(self,server,protocol):# Example command - client sends { "cmd": "foo" } to the server, this function will execute@server.on_command(cmd="foo",schema=protocol.schema)asyncdeffoobar(client,message):print("Foobar!")# Load the plugin!myplugin(server,clpv4)# Start the server!server.run()
Package: cloudmask
Cloud MaskCloud mask with Landsat 8 and Sentinel 2.View Demo•Report Bug•Request FeatureEnglish•简体中文Love the project? Please considerdonatingto help it improve!DemoFeaturesCloud mask with Landsat 8.Cloud mask with Sentinel 2.InstallpipinstallcloudmaskUsage$ cloudmaskChangelogSeeCHANGELOG.mdLicenseMIT LicenseDependenciesProduction DependenciesDevelopment dependencies