Saravanan666/pypi-org huggingface dataset:
Package: cul-spectrum
CUL SpectrumAboutCUL Spectrum implements a Python CLI client for the Concordia University Library
Spectrum REST API.InstallClone this repo, change into the cloned directory, and install:cdcul-spectrum
pipinstall.UsageCUL Spectrum currently only implements a client for theset_uuidendpoint.To add a single AIP:spectrumset-uuid--uuid=f904e936-a347-4211-82b7-e2a3c4da8cb2--name=example1You will be prompted for the Spectrum server URL and authorization token.Environment variablesTo avoid being prompted for the server URL and authorization token on each
spectrum invocation, you can set environment variables for these values:exportSPECTRUM_URL=https://example.com/cgi/archivematicaexportSPECTRUM_TOKEN=secret123Input optionsYou can add a single AIP to Spectrum by specifying the--uuidand--nameoptions:spectrumset-uuid--uuid=f904e936-a347-4211-82b7-e2a3c4da8cb2--name=example1Warning: spectrum does no validation of the UUID and name values or
formats.You can also provide input data for multiple AIPs in CSV format by using the--csv-fileoption:spectrumset-uuid--csv-file=../cul_spectrum_test.csvThe CSV file must include auuidcolumn and either anamecolumn (for a
bare AIP name, e.g. "test1"), or acurrent_pathcolumn (for a
storage server path, e.g. "3db3/fc8b/0e60/46a2/89fb/2243/1315/b2f9/test1-3bd3fc8b-0e60-46a2-89fb-22431315b2f9.7z").Output optionsCUL Spectrum's default output format is CSV:$spectrumset-uuid--uuid=f904e936-a347-4211-82b7-e2a3c4da8cb2--name=example1
http_status,http_body200OK,"{""id"": ""1579""}"CUL Spectrum also supports JSON output with the--out-formatoption:$spectrumset-uuid--uuid=f904e936-a347-4211-82b7-e2a3c4da8cb2--name=example1--out-format=json{"http_status":"200 OK","http_body":"{\"id\": \"1012\"}"}To write spectrum's output to a file you can use stdout redirection:$spectrumset-uuid--uuid=f904e936-a347-4211-82b7-e2a3c4da8cb2--name=example1>results.csvDevelopmentTestingTo run all tests with tox:toxOr run tests directly with pytest:pipinstall-rrequirements/test.txt
pytestCreditsThis package was created withCookiecutterandArtefactual's forkof theaudreyr/cookiecutter-pypackageproject template.
Package: cult-cargo
cult-cargoCurated Stimela2 cargo for popular radio astronomy softwareRegular userland installPyPI package coming soon, then you can dopip install cult-cargo...to install both Stimela2 and cult-cargo.Poweruser installTo work off the repo versions:# activate virtualenv
$ pip install poetry
$ gh repo clone caracal-pipeline/stimela
$ cd stimela
$ poetry install
$ cd ..
$ gh repo clone caracal-pipeline/cult-cargo
$ cd cult-cargo
$ poetry installSample recipe:#!/usr/bin/env -S stimela run -l
_include: 
  - (cultcargo)wsclean.yml

dummy-recipe:
  info: a dummy recipe
  steps:
    image:
      cab: wscleanCab developers install$ poetry install --with builderThis makes thebuilder/build-cargo.pyscript available. The script is configured withbuilder/cargo-manifest.yml, which describes the images that must be built.build-cargo.py -awill build and push all images, or specify an image name to build a particular one. Use-bto build but not push, or-pfor push-only.Thecultcargofolder contains yml files with cab definitions.If you would like to maintain your own image collection, write your own manifest and Dockerfiles following the cult-cargo example, then use thebuild-cargo.pyscript to build your images.
Package: cumason123-cloudevents
Python SDK forCloudEventsStatusThis SDK is still considered a work in progress, therefore things might (and
will) break with every update.This SDK current supports the following versions of CloudEvents:v1.0v0.3Python SDKPackagecloudeventsprovides primitives to work with CloudEvents specification:https://github.com/cloudevents/spec.Sending CloudEventsBelow we will provide samples on how to send cloudevents using the popularrequestslibrary.Binary HTTP CloudEventfromcloudevents.httpimportCloudEvent,to_binary_httpimportrequests# This data defines a binary cloudeventattributes={"type":"com.example.sampletype1","source":"https://example.com/event-producer",}data={"message":"Hello World!"}event=CloudEvent(attributes,data)headers,body=to_binary_http(event)# POSTrequests.post("<some-url>",data=body,headers=headers)Structured HTTP CloudEventfromcloudevents.httpimportCloudEvent,to_structured_httpimportrequests# This data defines a structured cloudeventattributes={"type":"com.example.sampletype2","source":"https://example.com/event-producer",}data={"message":"Hello World!"}event=CloudEvent(attributes,data)headers,body=to_structured_http(event)# POSTrequests.post("<some-url>",data=body,headers=headers)You can find a complete example of turning a CloudEvent into a HTTP requestin the samples directory.Request to CloudEventThe code below shows how to consume a cloudevent using the popular python web frameworkflask:fromflaskimportFlask,requestfromcloudevents.httpimportfrom_httpapp=Flask(__name__)# create an endpoint at http://localhost:/3000/@app.route("/",methods=["POST"])defhome():# create a CloudEventevent=from_http(request.get_data(),request.headers)# you can access cloudevent fields as seen belowprint(f"Found{event['id']}from{event['source']}with type "f"{event['type']}and specversion{event['specversion']}")return"",204if__name__=="__main__":app.run(port=3000)You can find a complete example of turning a CloudEvent into a HTTP requestin the samples directory.SDK versioningThe goal of this package is to provide support for all released versions of CloudEvents, ideally while maintaining
the same API. It will use semantic versioning with following rules:MAJOR version increments when backwards incompatible changes is introduced.MINOR version increments when backwards compatible feature is introduced INCLUDING support for new CloudEvents version.PATCH version increments when a backwards compatible bug fix is introduced.CommunityThere are bi-weekly calls immediately following theServerless/CloudEvents
callat
9am PT (US Pacific). Which means they will typically start at 10am PT, but
if the other call ends early then the SDK call will start early as well.
See theCloudEvents meeting minutesto determine which week will have the call.Slack: #cloudeventssdk channel underCNCF's Slack workspace.Email:https://lists.cncf.io/g/cncf-cloudevents-sdkContact for additional information: Denis Makogon (@denysmakogonon slack).MaintenanceWe use black and isort for autoformatting. We setup a tox environment to reformat
the codebase.e.g.pipinstalltoxtox-ereformatFor information on releasing version bumps seeRELEASING.md
Package: cumason-cloudevents
Python SDK forCloudEventsStatusThis SDK is still considered a work in progress, therefore things might (and
will) break with every update.This SDK current supports the following versions of CloudEvents:v1.0v0.3Python SDKPackagecloudeventsprovides primitives to work with CloudEvents specification:https://github.com/cloudevents/spec.Sending CloudEventsBelow we will provide samples on how to send cloudevents using the popularrequestslibrary.Binary HTTP CloudEventfromcloudevents.httpimportCloudEvent,to_binary_httpimportrequests# This data defines a binary cloudeventattributes={"type":"com.example.sampletype1","source":"https://example.com/event-producer",}data={"message":"Hello World!"}event=CloudEvent(attributes,data)headers,body=to_binary_http(event)# POSTrequests.post("<some-url>",data=body,headers=headers)Structured HTTP CloudEventfromcloudevents.httpimportCloudEvent,to_structured_httpimportrequests# This data defines a structured cloudeventattributes={"type":"com.example.sampletype2","source":"https://example.com/event-producer",}data={"message":"Hello World!"}event=CloudEvent(attributes,data)headers,body=to_structured_http(event)# POSTrequests.post("<some-url>",data=body,headers=headers)You can find a complete example of turning a CloudEvent into a HTTP requestin the samples directory.Request to CloudEventThe code below shows how to consume a cloudevent using the popular python web frameworkflask:fromflaskimportFlask,requestfromcloudevents.httpimportfrom_httpapp=Flask(__name__)# create an endpoint at http://localhost:/3000/@app.route("/",methods=["POST"])defhome():# create a CloudEventevent=from_http(request.get_data(),request.headers)# you can access cloudevent fields as seen belowprint(f"Found{event['id']}from{event['source']}with type "f"{event['type']}and specversion{event['specversion']}")return"",204if__name__=="__main__":app.run(port=3000)You can find a complete example of turning a CloudEvent into a HTTP requestin the samples directory.SDK versioningThe goal of this package is to provide support for all released versions of CloudEvents, ideally while maintaining
the same API. It will use semantic versioning with following rules:MAJOR version increments when backwards incompatible changes is introduced.MINOR version increments when backwards compatible feature is introduced INCLUDING support for new CloudEvents version.PATCH version increments when a backwards compatible bug fix is introduced.CommunityThere are bi-weekly calls immediately following theServerless/CloudEvents
callat
9am PT (US Pacific). Which means they will typically start at 10am PT, but
if the other call ends early then the SDK call will start early as well.
See theCloudEvents meeting minutesto determine which week will have the call.Slack: #cloudeventssdk channel underCNCF's Slack workspace.Email:https://lists.cncf.io/g/cncf-cloudevents-sdkContact for additional information: Denis Makogon (@denysmakogonon slack).MaintenanceWe use black and isort for autoformatting. We setup a tox environment to reformat
the codebase.e.g.pipinstalltoxtox-ereformatFor information on releasing version bumps seeRELEASING.md
Package: cumberbatch
Generates names similar to “Benedict Cumberbatch”The module benedict provides three functions: first, last, and full.
All three have an optional parameter “clean” which defaults true.clean=Falseis passed, some of the results may not be child/boss friendly
(though most of them still will be, as in the use below).Usage>>> import cumberbatch
>>> cumberbatch.first()
'Boilerdang'
>>> cumberbatch.last()
'Cabbagepatch'
>>> cumberbatch.full()
'Bombadil Coggleswort'
>>> cumberbatch.full(clean=False)
'Barister Colonist'or from the command-line:$ python -m cumberbatch --first
Bandydoo
$ python -m cumberbatch --last
Snickersbar
$ python -m cumberbatch
Bumbleshack Cottagecheese
$ python -m cumberbatch --nsfw
Blenderdick CountrysideContributingFeel free to fork me and create a pull request athttps://github.com/brandones/cumberbatch
Package: cumdistf
A simple interface for building and using cumulative
distribution functions and quantile functions.A common use of a cumulative distribution
function is to map a uniform random variable into a
nonuniform distribution.An inverse cumulative distribution function or quantile
function does the opposite - it can map a nonuniformally
distributed random variable into a uniformly distributed
space.These two components can be used together to create
a mapping from one non-uniform space to a different one.In this module, the uniform side of a distribution
function has a domain of [0, 1].  The non-uniform side
may have any range.
Package: cumin
Cumin provides a flexible and scalable automation framework to execute multiple commands on multiple hosts in parallel.It allows to easily perform complex selections of hosts through a user-friendly query language which can interface
with different backend modules and combine their results for a fine grained selection. The transport layer can also be
selected, and can provide multiple execution strategies. The executed commands outputs are automatically grouped for an
easy-to-read result.It can be used both via its command line interface (CLI)cuminand as a Python 3 only library.
Cumin was Python 2 only before the 3.0.0 release, due to ClusterShell not yet being Python 3 compatible.The documentation is available onWikimedia DocumentationandRead the Docs. The details on how Cumin it’s used
at the Wikimedia Foundation are available onWikitech.
Package: cumin-py
Python Binding forcumin.setupfrom PyPIpipinstallcumin-pyfrom Githubclonethis,thenpipinstall.Usageimportcumincumin.loads("""
struct S { x: Int, y: Int = 0 }
let a = S(1);
[a, a]
""")# => [{'x': 1, 'y': 0}, {'x': 1, 'y': 0}]cumin.load("conf.cumin")# read ./conf.cumin
Package: cumo
cumoビルドyarn、protoc、poetryが必要です（.devcontainer/Dockerfile参照）。
以下のようにするとlib/distにtar.gzとwhlファイルが生成されます。
クライアントのHTML等はライブラリに埋め込まれています。$./build.shインストール$pipinstallpointcloud-viewerドキュメントsphinxでドキュメントの生成が可能です。$cdlib$poetryinstall$poetryrunsphinx-apidoc--append-syspath-F-o./docs.使用例lib/cumo/__main__.pyは3面図を撮る例です。$poetryrunpython-mcumopcl_logo.pcdopen: http://127.0.0.1:8082setup...resize window and press custom control button "start"saved: screenshot_x.pngsaved: screenshot_y.pngsaved: screenshot_z.pngREPLでの使用も可能です。$poetryrunpythonPython 3.8.7 (default, Apr  9 2022, 21:34:33)[GCC 9.4.0] on linuxType "help", "copyright", "credits" or "license" for more information.>>> from cumo import PointCloudViewer>>> viewer = PointCloudViewer()>>> viewer.start()>>> # open localhost:8082 on your browser>>> with open(filename, "rb") as f:>>>     b = f.read()>>>     viewer.send_pointcloud_pcd(b)
Package: cumulative
Cumulativeis an open source project and Python package that provides an intuitive in-memory interface to transform and analyse large collections of time series with composable pipelines.Documentation:https://elehcimd.github.io/cumulative/Source code:https://github.com/elehcimd/cumulativeKey featuresTransformations: Apply vectorized time series transformations as composable operationsInteroperability: Access the underlying data at any time as a Pandas data frameFlexibility: Implement custom transformations and store arbitrary metadataRequirementsPython >=3.10Installationpip install cumulativeLicenseThis project is licensed under the terms of theBSD 3-Clause License.
Package: cumulative-cost-boosting
AdaCC: Adaptive Cost-sensitive Boosting for Imbalanced DataOverviewAdaCC is a novel cost-sensitive boosting approach designed to address the challenge of class imbalance in machine learning. Traditional supervised learning models often exhibit bias towards the majority class, leading to under-performance in minority classes. Cost-sensitive learning attempts to mitigate this issue by treating classes differently, employing a fixed misclassification cost matrix provided by users. However, manually tuning these parameters can be daunting and might lead to suboptimal results if not done accurately.In this work, we introduce AdaCC, a groundbreaking method that dynamically adjusts misclassification costs over boosting rounds based on the model's performance. Unlike conventional approaches, AdaCC eliminates the need for fixed misclassification cost matrices, offering a parameter-free solution. By leveraging the cumulative behavior of the boosting model, AdaCC automatically adapts misclassification costs for subsequent boosting rounds, ensuring optimal balance between classes and enhancing predictive accuracy.The following example showcases how the weighting strategy of AdaCC differs from AdaBoost. Feel free to also read the technical paper of this approach"AdaCC: cumulative cost-sensitive boosting for imbalanced classification"Key FeaturesDynamic Cost Adjustment:AdaCC dynamically modifies misclassification costs in response to the boosting model's performance, optimizing class balance without the need for manual parameter tuning.Parameter-Free Solution:Eliminates the complexity of defining fixed misclassification cost matrices, providing a hassle-free experience for users without requiring domain knowledge.Theoretical Guarantees:AdaCC comes with theoretical guarantees regarding training error, ensuring the reliability and robustness of the boosting model across various datasets.How to UseInstallationpip install cumulative-cost-boostingUsagefrom cumulative_cost_boosting import AdaCC

clf = AdaCC(n_estimators=100, algorithm='AdaCC1')
clf.fit(X_train, y_train)

predictions = clf.predict(X_test)ExampleA detailed example is displayed in therun_example.pyfile.Contributions and IssuesContributions and feedback are welcome. If you encounter any issues or have suggestions for improvement, please feel free to create an issue in the repository or submit a pull request.Note:AdaCC is a cutting-edge solution for handling class imbalance, ensuring accurate and fair predictions in machine learning tasks. Thank you for considering AdaCC for your imbalanced data challenges. Let's empower your models together!
Package: cumulio
Cumulio-Python-SDK:warning::warning: DEPRECATION NOTICE :warning::warning:The library had been replaced byluzmo-sdk. You can find the new package on the GitHub repoluzmo-official/luzmo-sdk-python.Python PackageYou will needPython Version >= 3.6pip install cumulioDocumentationFor detailed documentation, please visit theCumul.io Developer DocsUsage and ExamplesCreate a Cumul.io dataset:from cumulio.cumulio import Cumuliokey = "Your Cumul.io key"token = "Your Cumul.io token"client = Cumulio(key, token)dataset = client.create("securable", {"type": "dataset", "name" : {"en":"Example with python sdk"}})client.update("securable", dataset[" "], {"description":{"en":"This is an example description"}})Optionally for people working with VPC or on our US multitenant environment, you can also define an api_host while creating the client. If not it will default to "https://api.cumul.io"E.g.:client = Cumulio(key, token, "https://api.us.cumul.io")There is also the option of adding a dictionary of proxies while creating the API client.Update description of dataset:client.update("securable", dataset["id"], {"description":{"en":"Joost edited"}})Create a column in the dataset:burrito_column = client.create('column', { "type": 'hierarchy', "format": '',"informat": 'hierarchy', "order": 0,"name": {"nl": 'Type burrito'}})client.associate("securable", dataset["id"], "Columns", burrito_column["id"])Add Values to the column:client.create("data", dataset["id"], {"securable_id": dataset["id"],"type": "append", "data": [["sweet"], ["sour"]]})Replace Values in the column:client.create("data", {"securable_id": dataset["id"],"type": "replace", "data": [["bitter"], ["salty"]]})DocumentationThe API documentation (available services and methods) can be found athttps://developer.cumul.io
Package: cumulus
Cumulus Deployment Suite========================**Cumulus**.. image:: https://pypip.in/v/cumulus/badge.png:target: https://pypi.python.org/pypi/cumulus/:alt: Latest Version.. image:: https://pypip.in/d/cumulus/badge.png:target: https://pypi.python.org/pypi/cumulus/:alt: Downloads.. image:: https://pypip.in/license/cumulus/badge.png:target: https://pypi.python.org/pypi/cumulus/:alt: License**Cumulus Bundle Handler**.. image:: https://pypip.in/v/cumulus-bundle-handler/badge.png:target: https://pypi.python.org/pypi/cumulus-bundle-handler/:alt: Latest Version.. image:: https://pypip.in/d/cumulus-bundle-handler/badge.png:target: https://pypi.python.org/pypi/cumulus-bundle-handler/:alt: Downloads.. image:: https://pypip.in/license/cumulus-bundle-handler/badge.png:target: https://pypi.python.org/pypi/cumulus-bundle-handler/:alt: LicenseCumulus is a deployment suite used to deploy and manage environments built with AWS CloudFormation. Cumulus will help you bundle your code and configuration and unpack the bundle to new instances on CloudFormation.Documentation-------------The Cumulus documentation is hosted at `http://cumulus-ds.readthedocs.org/ <http://cumulus-ds.readthedocs.org/>`__.Installation------------Cumulus consists of two parts, ``cumulus`` which is used to manage the softwarebundling and deployment and the ``cumulus-bundle-handler`` which handlesthe software installation on the target servers.Installing ``cumulus``^^^^^^^^^^^^^^^^^^^^^^Install Cumulus via PyPI:::pip install cumulus``cumulus`` will now be available as a global command.Installing ``cumulus-bundle-handler``^^^^^^^^^^^^^^^^^^^^^^Install Cumulus Bundle Handler via PyPI:::pip install cumulus-bundle-handler``cumulus-bundle-handler`` will now be available as a global command.Attribution-----------This project is written and maintained by `Sebastian Dahlgren <http://www.sebastiandahlgren.se>`_ (`GitHub <https://github.com/sebdah>`_ | `Twitter <https://twitter.com/sebdah>`_ | `LinkedIn <http://www.linkedin.com/in/sebastiandahlgren>`_).Cumulus development is supported by `Skymill Solutions <http://www.skymillsolutions.com>`__.License-------APACHE LICENSE 2.0Copyright 2013-2014 Skymill SolutionsLicensed under the Apache License, Version 2.0 (the "License");you may not use this file except in compliance with the License.You may obtain a copy of the License at`http://www.apache.org/licenses/LICENSE-2.0 <http://www.apache.org/licenses/LICENSE-2.0>`__Unless required by applicable law or agreed to in writing, softwaredistributed under the License is distributed on an "AS IS" BASIS,WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.See the License for the specific language governing permissions andlimitations under the License.
Package: cumulus-bundle-handler
Cumulus Deployment Suite========================**Cumulus**.. image:: https://img.shields.io/pypi/v/cumulus.svg:target: https://pypi.python.org/pypi/cumulus/:alt: Latest Version.. image:: https://img.shields.io/pypi/dm/cumulus.svg:target: https://pypi.python.org/pypi/cumulus/:alt: Downloads.. image:: https://img.shields.io/pypi/l/cumulus.svg:target: https://pypi.python.org/pypi/cumulus/:alt: License**Cumulus Bundle Handler**.. image:: https://img.shields.io/pypi/v/cumulus-bundle-handler.svg:target: https://pypi.python.org/pypi/cumulus-bundle-handler/:alt: Latest Version.. image:: https://img.shields.io/pypi/dm/cumulus-bundle-handler.svg:target: https://pypi.python.org/pypi/cumulus-bundle-handler/:alt: Downloads.. image:: https://img.shields.io/pypi/l/cumulus-bundle-handler.svg:target: https://pypi.python.org/pypi/cumulus-bundle-handler/:alt: LicenseCumulus is a deployment suite used to deploy and manage environments built with AWS CloudFormation. Cumulus will help you bundle your code and configuration and unpack the bundle to new instances on CloudFormation.Documentation-------------The Cumulus documentation is hosted at `http://cumulus-ds.readthedocs.org/ <http://cumulus-ds.readthedocs.org/>`__.Installation------------Cumulus consists of two parts, ``cumulus`` which is used to manage the softwarebundling and deployment and the ``cumulus-bundle-handler`` which handlesthe software installation on the target servers.Installing ``cumulus``^^^^^^^^^^^^^^^^^^^^^^Install Cumulus via PyPI:::pip install cumulus``cumulus`` will now be available as a global command.Installing ``cumulus-bundle-handler``^^^^^^^^^^^^^^^^^^^^^^Install Cumulus Bundle Handler via PyPI:::pip install cumulus-bundle-handler``cumulus-bundle-handler`` will now be available as a global command.Attribution-----------This project is written and maintained by `Sebastian Dahlgren <http://www.sebastiandahlgren.se>`_ (`GitHub <https://github.com/sebdah>`_ | `Twitter <https://twitter.com/sebdah>`_ | `LinkedIn <http://www.linkedin.com/in/sebastiandahlgren>`_).Cumulus development is supported by `Skymill Solutions <http://www.skymillsolutions.com>`__.License-------APACHE LICENSE 2.0Copyright 2013-2014 Skymill SolutionsLicensed under the Apache License, Version 2.0 (the "License");you may not use this file except in compliance with the License.You may obtain a copy of the License at`http://www.apache.org/licenses/LICENSE-2.0 <http://www.apache.org/licenses/LICENSE-2.0>`__Unless required by applicable law or agreed to in writing, softwaredistributed under the License is distributed on an "AS IS" BASIS,WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.See the License for the specific language governing permissions andlimitations under the License.