Saravanan666/pypi-org huggingface dataset:
Package: scvr
singlecellvrSingle cell visualization using Virtual Reality (VR)http://www.singlecellvr.com/SingleCellVR can be used with our preprocessed datasets found at the link above or by following the steps below to process your own dataset.SingleCellVR Preprocess:Prepare your data for the visualization on Single Cell VR websitehttps://singlecellvr.com/InstallationInstall and update using pip:pip install scvrUsage$ scvr --helpusage: scvr [-h] -f FILE -t {scanpy,paga,seurat,stream} -a ANNOTATIONS [-g GENES] [-o OUTPUT]

scvr Parameters

required arguments:
  -f FILE, --filename FILE
                        Analysis result file name (default: None)
  -t {scanpy,paga,seurat,stream}, --toolname {scanpy,paga,seurat,stream}
                        Tool used to generate the analysis result (default: None)
  -a ANNOTATIONS, --annotations ANNOTATIONS
                        Annotation file name. It contains the cell annotation key(s) 
                        to visualize in one column (default: None)

optional arguments:

  -g GENES, --genes GENES
                        Gene list file name. It contains the genes 
                        to visualize in one column (default: None)
  -o OUTPUT, --output OUTPUT
                        Output folder name (default: scvr_report)
  -h, --help            show this help message and exitExamples:Scanpy:To get single cell VR report for Scanpy :scvr-f./scanpy_result/scanpy_10xpbmc.h5ad-tscanpy-aannotations.txt-ggenes.txt-oscanpy_reportInput files can be foundhereTo generate thescanpy_10xpbmc.h5ad, check outScanpy analysis.(Make sure setn_components=3insc.tl.umap(adata,n_components=3))PAGA:To get single cell VR report for PAGA :scvr-f./paga_result/paga3d_paul15.h5ad-tpaga-aannotations.txt-ggenes.txt-opaga_reportInput files can be foundhereTo generate thepaga3d_paul15.h5ad, check outPAGA analysis.(Make sure setn_components=3insc.tl.umap(adata,n_components=3))Seurat:To get single cell VR report for Seurat :scvr-f./seurat_result/seurat3d_10xpbmc.loom-tseurat-aannotations.txt-ggenes.txt-oseurat_reportInput files can be foundhereTo generate theseurat3d_10xpbmc.loom, check outSeurat analysis.(Make sure setn.components = 3inpbmc <- RunUMAP(pbmc, dims = 1:10, n.components = 3))Velocity:To get single cell velocity report for scvelo:scvr-tvelocity-fexamples/pancrease_velocity.h5ad-aclustersSTREAM:To get single cell VR report for STREAM :scvr-f./stream_result/stream_nestorowa16.pkl-tstream-aannotations.txt-ggenes.txt-ostream_reportInput files can be foundhereTo generate thestream_nestorowa16.pkl, check outSTREAM analysis.Or use STREAM package, e.g.:importstreamasstst.save_vr_report(adata,ann_list=['label','kmeans','branch_id_alias','S4_pseudotime'],gene_list=['Gata1','Car2','Epx','Mfsd2b','Mpo','Emb','Flt3','Dntt'],file_name='stream_report')
Package: scvr-prep
SingleCellVR Preprocess:Prepare your data for the visualization on Single Cell VR websitehttps://singlecellvr.com/InstallationInstall and update using pip:pip install scvr-prepUsage$ scvr_prep --helpUsage: scvr_prep [-h] -f FILE -t {paga,seurat,stream} [-a ANNOTATIONS] [-g GENES] [-o OUTPUT]

scvr_prep Parameters

required arguments:
  -f FILE, --filename FILE
                        Analysis result file name (default: None)
  -t {paga,seurat,stream}, --toolname {paga,seurat,stream}
                        Tool used to generate the analysis result (default: None)

optional arguments:
  -a ANNOTATIONS, --annotations ANNOTATIONS
                        Annotation file name. It contains the cell
                        annotation(s) used to color cells (default: None)
  -g GENES, --genes GENES
                        Gene list file name. It contains the genes to
                        visualize in one column (default: None)
  -o OUTPUT, --output OUTPUT
                        Output folder name (default: vr_report)
  -h, --help            show this help message and exitExamples:PAGA:To get single cell VR report for PAGA :scvr_prep-f./paga_result/paga3d_paul15.h5ad-tpaga-aannotations.txt-ggenes.txt-opaga_reportInput files can be foundhereTo generate thepaga3d_paul15.h5ad, check outPAGA analysis.(Make sure setn_components=3insc.tl.umap(adata,n_components=3))Seurat:To get single cell VR report for Seurat :scvr_prep-f./seurat_result/seurat3d_10xpbmc.loom-tseurat-aannotations.txt-ggenes.txt-oseurat_reportInput files can be foundhereTo generate theseurat3d_10xpbmc.loom, check outSeurat analysis.(Make sure setn.components = 3inpbmc <- RunUMAP(pbmc, dims = 1:10, n.components = 3))STREAM:To get single cell VR report for STREAM :scvr_prep-f./stream_result/stream_nestorowa16.pkl-tstream-ggenes.txt-ostream_reportInput files can be foundhereTo generate thestream_nestorowa16.pkl, check outSTREAM analysis.
Package: scw
The algorithmThis is an online supervised learning algorithm which utilizes all the
four salient properties:Large margin trainingConfidence weightingCapability to handle non-separable dataAdaptive marginThe paper ishere.SCW has 2 formulations of its algorithm which are SCW-I and SCW-II. They
can be accessed like below.scw.SCW1(C, ETA)
scw.SCW2(C, ETA)C and ETA are hyperparameters.Usagefrom scw import SCW1, SCW2

scw = SCW1(C=1.0, ETA=1.0)
scw.fit(X, y)
y_pred = scw.perdict(X)Xandyare 2-dimensional and 1-dimensional array respectively.Xis a set of data vectors. Each row ofXrepresents a feature vector.yis a set of labels corresponding withX.NoteThis package performs only binary classification, not multiclass
classification.Training labels must be 1 or -1. No other labels allowed.
Package: sc-weekly-points
A simple Python projectThis project provides a simple utility to calculate weekly points of sales.InstallationIt is possible to install the tool withpip:pip install sc-weekly-pointsConfigurationConfiguration files reading in this order, the first is the top most priority:production.xml in current directory,production.xml in <project_name> directory under User directory,production.xml in <project_name> directory under /var/opt/sc/ directory,default.xml in <project_name> directory under /var/opt/sc/ directory.The default configuration file looks like this:dev:
  # whether this program is running is development mode
  dev_mode: FalseLicenseThe script is released under the MIT License.  The MIT License is registered
with and approved by the Open Source Initiative[1].[1]https://opensource.org/licenses/MIT
Package: scw-gateway
Scaleway Serverless GatewayThe Scaleway Serverless Gateway is a self-hosted API gateway that runs on ScalewayServerless Containers.It lets you manage routing from a single base URL, as well as handle transversal concerns such as CORS and authentication.It is built onKong Gateway, giving you access to theKong plugin ecosystemto customize your deployments.You can read all about it inthis blog post.If you would like to join in the discussion on how we continue developing the project, or give us feedback, then join us on the#api-gateway-betachannel on the Scaleway Community Slack.📃 ContentsPlease seethe docsfor full documentation and features.💻 QuickstartTo deploy your gateway you need to install and configure theScaleway CLI, and theGateway CLIviapip:pip install scw-gatewayOnce done, the following steps can be run from the root of the project, and will deploy the gateway as a Serverless Container in your Scaleway account.The gateway image itself is packaged via our publicServerless Gateway Docker image.Deploy your gatewayTo deploy your gateway, you can run:scwgw infra deployFor more information on the deployment process, see thedeployment docs.Add a routeTo check your gateway is working, you can add and remove a route:#Checknoroutesareconfiguredinitiallyscwgw route ls#ChecktheresponsedirectlyfromagivenURLTARGET_URL=http://worldtimeapi.org/api/timezone/Europe/Pariscurl $TARGET_URL#AddaroutetothisURLinyourgatewayscwgw route add /time $TARGET_URL#Listroutestoseethatit'sbeenconfiguredscwgw route ls#CurltheURLviathegatewayGATEWAY_ENDPOINT=$(scwgw infra endpoint)curl https://${GATEWAY_ENDPOINT}/timeDelete your gatewayTo delete your gateway, you can run:scwgw infra delete🎓 ContributingWe welcome all contributions to our open-source projects, please see ourcontributing guidelines.Do not hesitate to raise issues and pull requests we will have a look at them.📬 Reach usWe love feedback. Feel free to:Open aGithub issueSend us a message on theScaleway Slack community, in the#serverless-functionschannel.
Package: scwidgets
ImportantSo far scicode-widget has been created by prototyping without much concern about the code quality. This resulted in faster development time but in cost of readability and maintanability of the code. Since we finished now the prototype phase and have converged on a set of functionalities we are satisfied with, we are in the process of refactoring the resulting code in this branch. While we are refactoring we recommend the usage of thevertical-slice branchtill all features have been implemented in the refactor.scicode-widgetsA collection of ipywidgets for the creation of interactive code demos and educational notebooks with exercises that can be checked and exported.Installationpipinstall.
Package: scw-py-client
Scaleway Python Clientprerequisites :Set the environment variables SCW_API_KEY_ID & SCW_API_KEY.Rdb :list_instancescreate_databasecreate_userset_user_privilegesupdate_userdelete_userdelete_databasefromscw_py_client.models.rdbimportPrivileges,User,Databasefromscw_py_client.coreimportRdbClientrdbClient=RdbClient()instances=rdbClient.list_instances()instance=instances[0]test_database=rdbClient.create_database(instance=instance,database=Database(name="test_database"))test_user=rdbClient.create_user(instance=instance,user=User(name="test_user"),password=User.Password("password1"))rdbClient.set_user_privileges(instance=instance,privileges=Privileges(database_name=test_database.name,user_name=test_user.name,permission=Privileges.Permission.ReadWrite))test_user=rdbClient.update_user(instance=instance,user=test_user,password=User.Password("password2"))rdbClient.delete_user(instance=instances[0],user=test_user)rdbClient.delete_database(instance=instance,database=test_database)Registry :list_imagesget_imageupdate_imagedelete_imagefromscw_py_client.coreimportRegistryClientregistryClient=RegistryClient()images=registryClient.list_images()Functions :list_containersget_containercreate_containerdeploy_containerupdate_containerdelete_containerlist_namespacesget_namespacecreate_namespaceupdate_namespacedelete_namespacelist_functionsget_functioncreate_functiondeploy_functionupdate_functiondelete_functionlist_cronsget_croncreate_cronupdate_crondelete_cronlist_logsfromscw_py_client.coreimportFunctionsClientfunctions_client=FunctionsClient()containers=functions.list_containers()Object Storage :list_bucketscreate_bucketenable_bucket_websiteupload_file_to_bucketfromscw_py_client.coreimportObjectStorageClientobject_storage_client=ObjectStorageClient.ObjectStorage()buckets=object_storage_client.list_buckets()object_storage_client.create_bucket("my_bucket_name")K8s :list_clustersfromsrc.scw_py_client.coreimportK8sClientk8s_client=K8sClient()clusters=k8s_client.list_clusters()
Package: scw-serverless
Serverless API FrameworkServerless API Framework is a tool that lets you write and deploy serverless functions in Python.
It bridges your code with the deployment configuration to make it a breeze to work with serverless functions.Starts by defining a simple Python function:fromscw_serverlessimportServerlessapp=Serverless("hello-namespace")@app.func(memory_limit=256)defhello_world(event,context):return"Hello World!"Deploy it withscw-serverless:scw-serverless deploy app.pyQuickstartInstallpip install scw-serverlessThis will install thescw-serverlessCLI:scw-serverless --helpWriting and configuring functionsYou can transform your Python functions into serverless functions by using decorators:importosimportrequestsfromscw_serverlessimportServerlessapp=Serverless("hello-namespace")API_URL=os.environ["API_URL"]@app.func(memory_limit=256,env={"API_URL":API_URL})defhello_world(event,context):returnrequests.get(API_URL)The configuration is done by passing arguments to the decorator.
To view which arguments are supported, head over to thisdocumentationpage.Local testingBefore deploying, you can run your functions locally with the dev command:scw-serverless dev app.pyThis runs a local Flask server with your Serverless handlers. If norelative_urlis defined for a function, it will be served on/namewithnamebeing the name of your Python function.By default, this runs Flask in debug mode which includes hot-reloading. You can disable this behavior by passing the--no-debugflag.DeployingWhen you are ready, you can deploy your function with thescw-serverlessCLI tool:scw-serverless deploy app.pyThe tool will use your Scaleway credentials from your environment and config file.What’s Next?To learn more about the framework, have a look at thedocumentation.
If you want to see it in action, we provide someexamplesto get you started.To run your Python functions locally, check outScaleway Functions Python.ContributingWe welcome all contributions.This project usespre-commithooks to run code quality checks locally. We recommended installing them before contributing.pre-commit install
Package: scx
SCxMIT'sSupply Chain Micromaster(SCx) Python PackageDocumentationTechnical documentationcan be foundhere.ExamplesAll Optimization ExamplesBasic ExamplesBlinky Examples (with video walkthroughs)Food On Wheels Examples (with video walkthroughs)Eco Pants Examples (with video walkthroughs)Miscellaneous ExamplesSetupCloud Setup (Google Colab)You can access google colabhereCreate a new notebookInstall thescxpackage by adding the following to a new code cell at thetopof your notebook and running it:pip install scxLocal SetupMake sure you have Python 3.7.x (or higher) installed on your system. You can download ithere.Recommended (but Optional) -> Expand this section to setup and activate a virtual environment.Install (or upgrade) virtualenv:python3 -m pip install --upgrade virtualenvCreate your virtualenv namedvenv:python3 -m virtualenv venvActivate your virtual environmentOn Unix (Mac or Linux):source venv/bin/activateOn Windows:venv\scripts\activatepip install scxOptimization Getting StartedSee all of the optimization exampleshere.Basic Usagefromscx.optimizeimportModelSimple Optimizationfromscx.optimizeimportModel# Create variablesproduct_1_amt=Model.variable(name="product_1",lowBound=0)product_2_amt=Model.variable(name="product_2",lowBound=0)# Initialize the modelmy_model=Model(name="Generic_Problem",sense='maximize')# Add the Objective Fnmy_model.add_objective(fn=(product_1_amt*1)+(product_2_amt*1))# Add Constraintsmy_model.add_constraint(name='input_1_constraint',fn=product_1_amt*1+product_2_amt*2<=100)my_model.add_constraint(name='input_2_constraint',fn=product_1_amt*3+product_2_amt*1<=200)# Solve the modelmy_model.solve(get_duals=True,get_slacks=True)# Show the outputs# NOTE: outputs can be fetched directly as a dictionary with `my_model.get_outputs()`my_model.show_outputs()Outputs:{'duals':{'input_1_constraint':0.4,'input_2_constraint':0.2},'objective':80.0,'slacks':{'input_1_constraint':-0.0,'input_2_constraint':-0.0},'status':'Optimal','variables':{'product_1':60.0,'product_2':20.0}}
Package: scylla
An intelligent proxy pool for humanities, only supports Python 3.6. Key features:Automatic proxy ip crawling and validationEasy-to-use JSON APISimple but beautiful web-based user interface (eg. geographical
distribution of proxies)Get started with only1 commandminimallySimple HTTP Forward proxy serverScrapyandrequestsintegration with only 1 line of code minimallyHeadless browser crawling对于偏好中文的用户，请阅读中文文档。For those who prefer to use Chinese, please read theChinese DocumentationDocumentationPlease read theDocumentation.Quick startInstallationInstall with Docker (highly recommended)dockerrun-d-p8899:8899-p8081:8081-v/var/www/scylla:/var/www/scylla--namescyllawildcat/scylla:latestInstall directly via pippipinstallscyllascylla--helpscylla# Run the crawler and web server for JSON APIInstall from sourcegitclonehttps://github.com/imWildCat/scylla.gitcdscyllapipinstall-rrequirements.txtnpminstall# or yarn installmakeassets-buildpython-mscyllaFor Windows user who fails at installingsanicdue touvloop does not support Windows at the moment:exportSANIC_NO_UVLOOP=trueexportSANIC_NO_UJSON=truepip3installsanicIf this also fails, yoi will need to manual install sanic from source.RoadmapPlease seeProjects.Development and Contributiongitclonehttps://github.com/imWildCat/scylla.gitcdscyllapipinstall-rrequirements.txtnpminstall# or `yarn install`makeassets-buildTestingIf you wish to run tests locally, the commands are shown below:pipinstall-rtests/requirements-test.txtpytesttests/You are welcomed to add more test cases to this project, increasing the robustness of this project.Naming of This ProjectScyllais derived from the name of a group of memory chips in the American TV series,Prison Break. This project was named after this American TV series to pay tribute to it.DonationIf you find this project useful, could you please donate some money to it?No matter how much the money is, Your donation will inspire the author to develop new features continuously! 🎉
Thank you!The ways for donation are shown below:PayPalAlipay or WeChat PayLicenseApache License 2.0. For more details, please read theLICENSEfile.
Package: scylla-api-client
Scylla-API-ClientScylla API Client is a command line utility implementing a thin client directly utilizing the Scylla REST APIRequirementspython > 3.8requestspytest (developers)Installationpip install scylla-api-clientUsageSeescylla-api-client --helpfor all options, below are some sample uses:Show all API modules$ scylla-api-client --list-modules
system
compaction_manager
gossiper
endpoint_snitch_info
storage_proxy
column_family
stream_manager
messaging_service
storage_service
cache_service
failure_detector
hinted_handoff
lsa
commitlog
collectd
error_injectionShow all API commands for specific modulesystem$ scylla-api-client --list-module-commands system
system/logger:
GET: Get all logger names
POST: Set all logger level
system/drop_sstable_caches:
POST: Drop in-memory caches for data which is in sstables
system/uptime_ms:
GET: Get system uptime, in milliseconds
system/logger/{name}:
GET: Get logger level
POST: Set logger levelGet loglevel for specific loggerhttpd$ scylla-api-client system/logger/{name} GET --name httpd
"info"Set loglevellevel=debugfor specific loggerhttpd$ scylla-api-client system/logger/{name} POST --name httpd --level debugTestspytest is used for writing and executing tests
to run tests you can execute:pip install -r dev-requirements.txt 
pytest -s -v tests/DesignReleaseReleases are published automatically by GitHub Actions when a tag (v**) is pushed to GitHub.Make sure you tag the correct commitPushing a tag to GitHub requires maintainers/admin privilegesgit tag v1.0 <some-commit-hash>
git push upstream v1.0
Package: scylla-cqlsh
scylla-cqlshCommand line tool to connect toscylladb(or Apache Cassandra)A fork of the cqlsh tool fromhttps://github.com/apache/cassandraQuickstartpipinstallscylla-cqlsh

cqlsh${SCYLLA_HOST}-e'SELECT * FROM system.local'# or just using it interactivelycqlsh${SCYLLA_HOST}# or using it with scylla-cloudcqlsh--cloudconf[pathtoconnectionbundledownloaded]# running with docker image interactivelydockerrun-itscylladb/scylla-cqlsh${SCYLLA_HOST}ContributingFeel free to open a PR/issues with suggestion and improvement
Try covering you suggested change with a test, and the instruction
for running tests are belowTestingDependentpython 2.7/3.x (recommend virtualenv)minimum java8pipinstall-e.
pipinstall-rpylib/requirements.txt# run scylla with dockerdockerrun-dscylladb/scylla:latest--cluster-nametestexportDOCKER_ID=$(dockerrun-dscylladb/scylla:latest--cluster-nametest)exportCQL_TEST_HOST=$(dockerinspect--format='{{ .NetworkSettings.IPAddress }}'${DOCKER_ID})while!nc-z${CQL_TEST_HOST}9042;dosleep0.1# wait for 1/10 of the second before check againdone# run scylla with CCMccmcreatecqlsh_cluster-n1--scylla--versionunstable/master:latest
ccmstart

pytestCreation of the repoA reference on how this we forked out of cassandra repo
So we can repeat the process if we want to bring change back itgitclone-btrunk--single-branchgit@github.com:apache/cassandra.git
sudoapt-getinstallgit-filter-repocdcassandra

gitfilter-repo--pathbin/cqlsh--pathbin/cqlsh.py--pathpylib/
Package: scylla-driver
A modern, feature-rich and highly-tunable Python client library for Scylla Open Source (2.1+) and Apache Cassandra (2.1+) and
Scylla Enterprise (2018.1.x+) using exclusively Cassandra’s binary protocol and Cassandra Query Language v3.The driver supports Python versions 3.6-3.11.FeaturesSynchronousandAsynchronousAPIsSimple, Prepared, and Batch statementsAsynchronous IO, parallel execution, request pipeliningConnection poolingAutomatic node discoveryAutomatic reconnectionConfigurableload balancingandretry policiesConcurrent execution utilitiesObject mapperShard awarenessTablet awarenessInstallationInstallation through pip is recommended:$ pip install scylla-driverFor more complete installation instructions, see theinstallation guide.DocumentationThe documentation can be found onlinehere.Information includes:InstallationGetting started guideAPI docsPerformance tipsTrainingThe courseUsing Scylla DriversinScylla Universityexplains how to use drivers in different languages to interact with a Scylla cluster.
The lesson, Coding with Python (link), goes over a sample application that, using the Python driver, interacts with a three-node Scylla cluster.
It connects to a Scylla cluster, displays the contents of a  table, inserts and deletes data, and shows the contents of the table after each action.Scylla Universityincludes other training material and online courses which will help you become a Scylla NoSQL database expert.Object Mappercqlengine (originally developed by Blake Eggleston and Jon Haddad, with contributions from the
community) is now maintained as an integral part of this package. Refer todocumentation here.ContributingSeeCONTRIBUTING.Reporting ProblemsPlease report any bugs and make any feature requests by clicking the New Issue button inGithub.If you would like to contribute, please feel free to send a pull request.Getting HelpYour best options for getting help with the driver are themailing listand the Scylla UsersSlack channel.LicenseCopyright DataStax, Inc.Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed 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 and
limitations under the License.
Package: scylla-for-docker
ScyllaSpin up docker containers inline with python code for easier testingInstallgitclonehttps://github.com/talosiot/scylla.git
makeenvfrom IPython.core.display import display, HTML
import requests

import scyllaRun a docker container.  If there are ports that the container needs, specify them in a list.  If you want to wait until a certain port is available, you can specify that here as well.  For example, to run a small web server you need port 80 and you want to wait until it is available.container = scylla.run_container(image='httpd:alpine', ports=[80], block_until_port_available=80)
container.ports{'80/tcp': [{'HostIp': '0.0.0.0', 'HostPort': '8228'}]}The container is running and you can interact with it.host_d = scylla.lookup_host(container, container_port=80)
url = 'http://{HostIp}:{HostPort}'.format(**host_d)
resp = requests.get(url)
print(resp.text)
display(HTML(resp.text))<html><body><h1>It works!</h1></body></html>It works!Stop the container any time.  Or, it will automatically stop at the end of the program.container.stop()