Saravanan666/pypi-org huggingface dataset:
Package: cloudbench
Cloudbench is a library designed to make Cloud benchmarking easier.Cloudbench integrates with a web service (not yet publicly available) to upload
benchmark results, and compare your Cloud with other offerings.UsageFirst, define the configuration file for the benchmark:[environment]fio=Path to the fio binary [/usr/local/bin/fio]pidfile=Path to the pid file to use [var/run/cloudbench.pid]logfile=Path to the log file to use [/var/log/cloudbench.log]nobench=Comma-separated list of devices to not use in benchmark [][general]size=The size of the file to use in benchmarks [10G]ramp=The duration of the benchmark ramp time [15 seconds]duration=The duration of the benchmarks [600 seconds][reporting]endpoint=The endpoint to report data tousername=The username to authenticate with at the endpointapikey=The API key to authenticate with at the endpoint[benchmarks]blocksizes=Comma-separated list of block sizes to use during benchmarkingdepths=Comma-separated list of depths to use during benchmarkingmodes=Comma-separated list of modes to use during benchmarkingNext, execute cloudbench and point it to your configuration file$cloudbench-c/path/to/config/file.iniBy default, cloudbench looks for its config file in/etc/cloudbench.iniUse with ScalrFor simplified ease of use, it’s possible to use Cloudbench withScalr.Scalr can:Provision and attach volumes (on any platform)Install, Configure, and Launch CloudbenchBring infrastructure up and down at regular intervals to periodically run benchmarksLicenseSee LICENSE.
Package: cloud-bids-layout
Cloud-BIDS-LayoutCloud-BIDS-Layout is a lightweight wrapper for pybids' BIDS.Layout that can
grab BIDS studies from Amazon S3.MotivationTheBrain Imaging Data Structure (BIDS)is an intuitive, accessible, and community-driven data specification for
neuroimaging data.Pybidsis
an exceptionally written Python library that makes it easy for
researchers to query, summarize, and manipulate BIDS-compliant data.
However, it's workhorseBIDSLayoutclass doesn't index remote datasets
stored in the cloud. That's where Cloud-BIDS-Layout comes in.Cloud-BIDS-Layout allows its user to specify a remote location for
a BIDS-Compliant dataset. Currently only Amazon S3 locations are
supported but support for Google Cloud Storage and others is coming
soon. Cloud-BIDS-Layout creates a lightweight semblance of the remote
dataset, just enough to pass to pybids'BIDSLayoutfor indexing.
The user can then use pybids' familiar.get()method to select a
subset of the study that they wish to download to the host. See thedocumentationfor more details.This is the Cloud-BIDS-Layout development site. You can view the source
code, file new issues, and contribute to Cloud-BIDS-Layouts's development.
If you are just getting started, you should look at theCloud-BIDS-Layout
documentationContributingWe love contributions! Cloud-BIDS-Layout 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
Cloud-BIDS-Layout.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.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.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: cloud-blobstore
# cloud-blobstoreThis library provides an abstraction layer for the most basic functionality provided by the cloud providers.  These are the basic functions required by the [Human Cell Atlas](https://www.humancellatlas.org/) [Data Storage Service](https://github.com/HumanCellAtlas/data-store).## Development### Set up your python environment
Before you start, you may wish to set up a [virtualenv](https://virtualenv.pypa.io/en/stable/).  Runpip install -r requirements-dev.txt. Then set up the following environment variables:Environment variable    | Explanation |———————– | ———– |S3_BUCKET               | Points to the AWS S3 bucket where new files will be written.  It may be advisable to set up a cleanup policy for this bucket. |S3_BUCKET_FIXTURES      | Points to the AWS S3 bucket where static fixtures are stored. |S3_BUCKET_US_EAST_1     | Points to an AWS S3 bucket in the US_EAST_1 region.  This can overlap with one of the other buckets. |S3_BUCKET_NON_US_EAST_1 | Points to an AWS S3 bucket _not_ in the US_EAST_1 region.  This can overlap with one of the other buckets. |GS_BUCKET               | Points to the GCP GS bucket where new files will be written.  It may be advisable to set up a cleanup policy for this bucket. |GS_BUCKET_FIXTURES      | Points to the GCP GS bucket where static fixtures are stored. |### Set up test fixtures.
Runpython tests/fixtures/populate.py –s3-bucket $S3_BUCKET_FIXTURES –gs-bucket $GS_BUCKET_FIXTURES#### Running tests
Runmake testin the top-level directory.
Package: cloudboot
Cloud Bootstrapper CLI - betaThis curated collection of scripts streamlines the development and deployment process for serverless applications on
Google Cloud Platform (GCP). These scripts facilitate seamless creation, configuration, and deployment of serverless
components, enabling developers to focus on building innovative solutions without getting bogged down by infrastructure
complexities.Key Features:Simplified Serverless Development: The scripts provide a streamlined approach to building serverless applications,
reducing the time and effort required to get applications up and running.Efficient Deployment Process: The scripts automate the deployment process, ensuring consistent and error-free
deployment of serverless components to GCP.Enhanced Productivity: Developers can focus on their core competencies – application logic and business processes –
while the scripts handle the intricacies of serverless infrastructure management.Available featuresCloud functions - GEN-2Boostrap Cloud functions from templates.Starter templates for GO, Java, Node.js, PHP, Python, Ruby.Set triggers.HTTP, Firestore, PubSub, Storage bucketCreate trigger resources automatically upon deployment.NextCloud Run support.Please note:This product is not officially endorsed by Google.
You should use this product at your own risk.Disclaimer:Google is not responsible for any damages caused by the use of this product.LicenseMIT, Cloud Bootstrapper 2023
Package: cloudbrain
StatusFeaturesCloudBrain is a platform for real-time sensor data analysis and
visualization.Stream sensor datain a unified format.Store sensor datain a central database.Analyze sensor datato find patterns.Visualize sensor dataand patterns in real-time.Using CloudBrainInstallingCloudbrain is available for download viaPyPIand may be installed usingpip:pip install cloudbrainInstalling additional modulesOptional CloudBrain modules can be installed:Analytics modules:pip install cloudbrain[analytics]Musesource module:pip3 install cloudbrain[muse](Python3.*only)Installing from sourceClone this repository and runpip install .from the root of the repo.If you plan toeditthe code, make sure to use the-eswitch:pip  install-e.Running the testspython setup.py testExamplesSeeREADME.mdincloudbrain/examplesfor more information about
how to use CloudBrain analytics modules.More docsFor more details on to setup and use CloudBrain, refer to thewiki.License
Package: cloudbreak
CloudBreak - Material UI for DelugeRequirementsPython 3 & pipLibtorrent & Libtorrent python bindingsDeluge 2.0.0pip3installdeluge==2.0.0NodeJS 12 or greater & NPMBuilding from sourceInstall deluge and libtorrentInstall dependenciespip3install-rrequirements.txtInstall frontend dependenciescdfrontend
npminstallBuild frontendnpmrunbuild
Package: cloud-bucket-adapter
Buckets AdapterBuckets Adapter Django module is a base for upload files on bucket for different web services e.g Google Cloud Platform or Amazon Web Services which will be used as a package in different projects.Building docsTo build sphinx documentation for this module, follow these steps.Pre-requisiteInstall sphinx module using the following command:pipinstallsphinxMake sure you have gcc insalled for runningmakefiles.Creating HTML documentFollow these steps the create HTML related document:Change your working directory todocs/Run the following command:makehtml
Package: cloudburst
cloudburst ⛈A cloudburst of data, gathered through scraping⏳ Installation🐍 Pippython3-mpipinstallcloudburst🗃 Sourcegitclonehttps://github.com/cwdt-us/cloudburst.gitcdcloudburst
python3-mpipinstall-e.DocumentationFor further information, see theusage guide.
Package: cloudbypass
Cloudbypass SDK for Python开始使用Cloudbypass Python SDK 仅支持 Python 3.6 及以上版本。在psf/requests基础上封装的穿云SDK，支持穿云API服务的调用。通过内置的会话管理器，可以自动处理会话请求，无需手动管理Cookie等信息。使用get_balance方法可以查询当前账户余额。安装python3-mpipinstallcloudbypass-ihttps://pypi.org/simple发起请求Session类继承自requests.Session，支持requests的所有方法。增加初始化参数apikey和proxy，分别用于设置穿云API服务密钥和代理IP。定制用户可以通过设置api_host参数来指定服务地址。以上参数可使用环境变量CB_APIKEY、CB_PROXY和CB_APIHOST进行配置。fromcloudbypassimportSessionif__name__=='__main__':withSession(apikey="<APIKEY>",proxy="http://proxy:port")assession:resp=session.get("https://opensea.io/category/memberships")print(resp.status_code,resp.headers.get("x-cb-status"))print(resp.text)asyncAsyncSession类继承自aiohttp.ClientSession，支持aiohttp的所有方法。importasynciofromcloudbypassimportAsyncSessionasyncdefmain():asyncwithAsyncSession(apikey="<APIKEY>",proxy="http://proxy:port")assession:resp=awaitsession.get("https://opensea.io/category/memberships")print("Status:",resp.status)print("Content-type:",resp.headers['content-type'])html=awaitresp.text()print("Body:",html[:15],"...")if__name__=='__main__':loop=asyncio.get_event_loop()loop.run_until_complete(main())使用V2穿云API V2适用于需要通过JS质询验证的网站。例如访问https://etherscan.io/accounts/label/lido，请求示例：fromcloudbypassimportSessionif__name__=='__main__':withSession(apikey="<APIKEY>",proxy="http://proxy:port")assession:resp=session.get("https://etherscan.io/accounts/label/lido",part="0")print(resp.status_code,resp.headers.get("x-cb-status"))print(resp.text)asyncimportasynciofromcloudbypassimportAsyncSessionasyncdefmain():asyncwithAsyncSession(apikey="<APIKEY>",proxy="http://proxy:port")assession:resp=awaitsession.get("https://etherscan.io/accounts/label/lido",part="0")print("Status:",resp.status)print("Content-type:",resp.headers['content-type'])html=awaitresp.text()print("Body:",html[:15],"...")if__name__=='__main__':loop=asyncio.get_event_loop()loop.run_until_complete(main())查询余额fromcloudbypassimportget_balanceif__name__=='__main__':print(get_balance("<APIKEY>"))asyncimportasynciofromcloudbypassimportasync_get_balanceasyncdefmain():print(awaitasync_get_balance("<APIKEY>"))if__name__=='__main__':loop=asyncio.get_event_loop()loop.run_until_complete(main())提取代理通过CloudbypassProxy as Proxy类可以提取穿云动态代理IP和时效代理IP。copy()复制当前对象，使原有的对象不会受到影响。set_dynamic()设置为动态代理。set_expire(int)设置为时效代理，参数为IP过期时间，单位为秒。set_region(str)设置代理IP地区。clear_region()清除代理的地区。format(str)格式化代理IP，参数为格式化字符串，例如{username}:{password}@gateway。limit(int, str)返回一个代理IP字符串迭代器，参数为提取数量及代理格式化字符串。loop(int, str)返回一个代理IP字符串循环迭代器，参数为实际数量及代理格式化字符串。fromcloudbypassimportProxyif__name__=='__main__':proxy=Proxy("username-res:password")# 提取动态代理print("Extract dynamic proxy: ")print(str(proxy.set_dynamic()))print(str(proxy.set_region('US')))# 提取时效代理并指定地区print("Extract proxy with expire and region: ")print(str(proxy.copy().set_expire(60*30).set_region('US')))# 批量提取print("Extract five 10-minute aging proxies: ")pool=proxy.copy().set_expire(60*10).set_region('US').limit(5)for_inpool:print(_)# 循环提取print("Loop two 10-minute aging proxies: ")loop=proxy.copy().set_expire(60*10).set_region('US').loop(2)for_inrange(10):print(loop.__next__())关于重定向问题使用SDK发起请求时，重定向操作会自动处理，无需手动处理。且重定向响应也会消耗积分。关于服务密钥请访问穿云控制台获取服务密钥。
Package: cloudcheck
CloudCheckA simple Python utility to check whether an IP address or hostname belongs to a cloud provider.cloud_providers.jsoncontains lists of domains and up-to-date CIDRs for each cloud provider (updated daily via CI/CD).Used byBighuge BLS OSINT Tool (BBOT).InstallationpipinstallcloudcheckUsage - CLI$cloudcheck168.62.20.37168.62.20.37belongstoAzure(cloud)(168.62.0.0/19)$cloudchecktest.evilcorp.azurewebsites.net
test.evilcorp.azurewebsites.netbelongstoAzure(cloud)(azurewebsites.net)Usage - Pythonimportcloudcheckprovider,provider_type,subnet=cloudcheck.check("168.62.20.37")print(provider)# "Azure"print(provider_type)# "cloud"print(subnet)# IPv4Network('168.62.0.0/19')Supported cloud providersAmazon (source)Azure (source)Google (source)Oracle Cloud (source)DigitalOcean (source)Cloudflare (source)Akamai (source)Github (source)Zoho (source)Fastly (source)
Package: cloud-check1
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.AWS Hardening Standards & Best Practiceshttps://codaglobal.atlassian.net/l/cp/UP1BxJTrAWS Tagging Standardshttps://codaglobal.atlassian.net/l/cp/oj0NgsdbAWS Naming Standardshttps://codaglobal.atlassian.net/l/cp/s99nYLECAudit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal.Specify the region name if you need to perform the audit for services in a specific region by mentioning the region name as argument while running the program.If no region is specified us-east-1 is taken as default region and audit checks are performed for the services in us-east-1.If you need to check tags. Update the Config.Json file by mentioning the tags in the account tags provided.Audit Tool ExecutionCreating Virtual Environmentpython3 -m venv venvActivating the virtual environmentsource venv/bin/activateInstalling the dependencies in the virtual environmentpip install -r requirements.txtRun the following commandpython3 src/main.py --region {region_name}Test Cases ExecutionnosetestsFinal ReportThe overall report is provided as a HTML document.sample report
Package: cloud-check2
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.Audit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal.Specify the region name if you need to perform the audit for services in a specific region by mentioning the region name as argument while running the program.If no region is specified us-east-1 is taken as default region and audit checks are performed for the services in us-east-1.If you need to check tags. Update the Config.Json file by mentioning the tags in the account tags provided.Audit Tool ExecutionCreating Virtual Environmentpython3 -m venv venvActivating the virtual environmentsource venv/bin/activateInstalling the dependencies in the virtual environmentpip install -r requirements.txtRun the following commandpython3 src/main.py --region {region_name}Test Cases ExecutionnosetestsFinal ReportThe overall report is provided as a HTML document.sample report
Package: cloud-check3
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.Audit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal.Specify the region name if you need to perform the audit for services in a specific region by mentioning the region name as argument while running the program.If no region is specified us-east-1 is taken as default region and audit checks are performed for the services in us-east-1.If you need to check tags. Update the Config.Json file by mentioning the tags in the account tags provided.Audit Tool ExecutionCreating Virtual Environmentpython3 -m venv venvActivating the virtual environmentsource venv/bin/activateInstalling the dependencies in the virtual environmentpip install -r requirements.txtRun the following commandpython3 src/main.py --region {region_name}Test Cases ExecutionnosetestsFinal ReportThe overall report is provided as a HTML document.sample report
Package: cloud-check4
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.Audit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal or give the session credentials through the arguments of the command line by specifying --access_key, --secret_key and --session_token.You can specify the region name, config file path, report file path and tags through --region, --config_path, --report_path arguments respectively while running the program.If no region is specified us-east-1 is taken as default region, Similarly if no config file path and report path is given current working directory path is taken as default and the audit checks are performed for the services accordingly.To check tags, we can pass as argument --tags while running the tool and we can also update the config.json file by mentioning the tags in the account tags provided. Moreover the tags passed as the argument through the command line takes the first priority.Tags that are passed through the argument in command line should be separated using commas (,)Audit Tool ExecutionCommand to Run the audit tool in the command line after installing the package.cloud-audit-toolArguments that can be passedcloud-audit-tool --region {region_name} --config_path {config_path} --report_path {report_path} --access_key {access_key} --secret_key {secret_key} --session_token {session_token} --tags {tag1,tag2,..}Final ReportThe overall report is provided as a HTML document in the path specified in the report_path argument. If no path is specified report is generated in the current working directory.
Package: cloudcheckr
cloudcheckcloudcheck is a CLI utility to check if IP addresses in a file are associated with a cloud or CDN network.Installation•Usage•Getting Started•Coming SoonThanksInstallationcloudcheck supports all major operating systems and can be installed from PyPi using the following command:pipx install cloudcheckGetting StartedThe utility supports the following cloud and CDN providers:AkamaiAWS CloudfrontAzure FrontDoorCloudflareFastlyGoogleSuccuriIncapsulaOn run, the tool first requests IP ranges from API endpoints hosted by each provider. These ranges are then stored in a dictionary for processing. With this, the ranges are then searched to determine if the input IP addresses are contained within the stored CIDRs.UsageTo use cloudcheck, execute a command similar to what is shown below:cloudcheck cdn all /tmp/targets.txt /tmp/output.jsonThe tool will request IP ranges from from the supported providers and then search for your target IPs in the requested IP ranges.Coming SoonSome planned features coming in the next release:Support checking all cloud IP rangesSupport checking only CDN IP ranges (Done)Support searching specific providers onlyJSON output support (Done)DNS supportCaching for ranges (Done)Support silent mode (Done)Thanks0xdade's tool,sephirothprojectdiscovery's GO librarycdncheck
Package: cloudcix
cloudcixis a Python client for the CloudCIX REST API for rapidly building secure, scalable CloudCIX applications.For more information about CloudCIX, seehere.InstallationPrerequisitesCreate an account on the CloudCIX PlatformRegisterRetrieve your API KeyUnder theMy Membershiptab in the sidebar, click onMember DetailsTheAPI Keyshould be available at the top of the formEnsure that you have both Python and pip installedAs of right now, thecloudcixmodule is available at different versions for Python2 and Python3We recommend you use Python3 and the latest version of thecloudcixmodulePythonpipInstalling thecloudcixlibraryThe cloudcix library is installed using thepipmodule.Depending on your version of Python, you need to install different versions ofcloudcixPython3pip3 install-UcloudcixPython2pip install-U'cloudcix<0.3'The 0.2 releases are the last to support Python2.
If you still use Python2 we recommend you upgrade to Python3 as support will be dropped for these versions in time.Required settingsIn order to run a project, the module requires some settings to exist.The variables required are as follows:CLOUDCIX_API_URL- The base url of the Python2 API
- Usuallyhttps://api.cloudcix.com/but could change over timeCLOUDCIX_API_V2_URL- The API name is prepended to this url after thehttps://for the Python3 API.
- Usuallyhttps://api.cloudcix.com/but could change over timeCLOUDCIX_API_VERSION= 2
- The version of the apiCLOUDCIX_API_USERNAME- The email of the account that you signed up withCLOUDCIX_API_PASSWORD- The password associated with your CloudCIX accountCLOUDCIX_API_KEY- The API key associated with your CloudCIX Member (seePrerequisites)These variables can be declared in a settings file, as follows# In main python scriptimportosos.environ.setdefault('CLOUDCIX_SETTINGS_MODULE','my_project.my_settings')# In my_project/my_settings.pyCLOUDCIX_API_URL='https://api.cloudcix.com/'CLOUDCIX_API_V2_URL=CLOUDCIX_API_URLCLOUDCIX_API_USERNAME='EMAIL'# CloudCIX loginCLOUDCIX_API_PASSWORD='PASSWORD'# CloudCIX passwordCLOUDCIX_API_KEY='NUMBER/CHARACTER STRING'# CloudCIX api keyCLOUDCIX_API_VERSION=2# CloudCIX versionExamplesSeeherefor examples on how to use this library.
Package: cloud-cloner
A tool for cloning data from cloud storage providers in a configurable way.Example config file:base_path:/base_pathclones:-name:clone_one_folderpaths:-src:path/to/remote/folderdest:path/to/local/folderdefault:true-name:clone_filespaths:-src:files/file.txtdest:remote_files/file_renamed.txt-src:files/file2.txtdest:remote_files/The config file is expected to be in the current working directory and namedcloud_cloner.yaml. This location can be set with--config-path.A valid rclone config is expected at~/.rclone. This location can be set with--rclone-config-path.Then clone withpython -m cloud_cloner cloneorpython -m cloud_cloner clone clone_one_folder.Seepython -m cloud_cloner --helpfor more options.