Saravanan666/pypi-org huggingface dataset:
Package: infrasim-compute
Infrasim-compute: bare-metal server simulatorSystem Basic RequirementsInfrasim package can be installed in any physical machine or virtual
machines hosted by Virtualbox, ESXi, Parallel Desktop or cloud provider
like AWS, Linode and etc.The basic installation system requirements are:Ubuntu Linux 64bit OS (14.04/15.04/16.04)at least 4GB memoryat least 16GB disk sizeInstallationEnsure sources.list integrity then install dependency:sudo apt-get update
sudo apt-get install python-pip libpython-dev libssl-dev libaio-devUpgrade pip and install setuptools:sudo pip install --upgrade pip
sudo pip install setuptoolsTwo ways to install infrasim:install infrasim from source code:git clone https://github.com/InfraSIM/infrasim-compute.git

cd infrasim-compute

sudo pip install -r requirements.txt

sudo python setup.py installinstall infrasim from python library:sudo pip install infrasim-computeStart Infrasim ServiceInitialization (you need do it once)sudo infrasim initOptional arguments:-s, –skip-installation Ignore qemu/openipmi package installation-f, –force Destroy existing Nodes-c [CONFIG_FILE], –config-file [CONFIG_FILE] Use customized
yaml file for the default node-t [TYPE], –type [TYPE] Render specified node type for the
default nodeInfrasim Service Version:sudo infrasim versionInfrasim Node Configuration Management:Add configuration mapping to a nodesudo infrasim config add <node name> <config path>Delete configuration mapping of a nodesudo infrasim config delete <node name>Update configuration mapping of a nodesudo infrasim config update <node name> <config path>Edit configuration mapping with environment editorsudo infrasim config editList all configuration mappingssudo infrasim config listInfrasim Service Node CommandsStart a nodesudo infrasim node start [node name]Check node statussudo infrasim node status [node name]Stop a nodesudo infrasim node stop [node name]Restart a nodesudo infrasim node restart [node name]Stop a node and detroy its runtime workspacesudo infrasim node destroy [node name]The default node configuration is already added to configuration
mapping duringinfrasim init. In node commands, argument [node
name] is optional. If it’s not specified, it’s treated as node
“default”.Notice: You can use VNC to access the emulated legacy hardware, the
default VNC port is 5901
Package: infrasonar-appliance
InfraSonar Appliance ManagerThis tool simplifies the installation and management of InfraSonar appliances. It streamlines the process of setting up and running your InfraSonar infrastructure, making it easier to monitor and manage your IT environment.PrerequisitesBefore using the InfraSonar Appliance Manager, ensure you have the following prerequisites installed:Python(inclusing pip)CurlYou can install these prerequisites on Ubuntu or Debian-based systems using the following commands:sudo apt update
sudo apt install python curl pipAdditionally, Docker Compose is required for the InfraSonar appliance to function properly. You can install Docker Compose using the following command:sudo curl -sSL https://get.docker.com | bashInstallationTo install the InfraSonar Appliance Manager, use the following command:pip install infrasonar-applianceUsageOnce installed, simply start the tool using the following command:applianceThe tool will handle the installation and management of yourInfraSonar appliance, allowing you to focus on monitoring and managing your IT infrastructure.Additional NotesFor more detailed instructions and troubleshooting guidance, refer to the officialInfraSonar documentation.If you encounter any issues during installation or usage, feel free tocontactthe InfraSonar support team for assistance.
Package: infrastructure-diagrams
infrastructure-diagramsinfrastructure-diagrams is a python package that allows creating
infrastructure diagrams/graphs from configuration files (YAML and JSON).
The package utilizesGraphviz <https://www.graphviz.org/>__ to
generate the diagrams. The functionality is exposed in the command line
by the Unix command file.Note: Some features are currently undocumented.RequirementsThe package requirespython >= 3.6. It has only been tested on Linux
as the intended use was for automatically generating diagrams in a CI.InstallationThe current stable version of infrastructure-daigrams is available on
pypi and can be installed by runningpip install infrastructure-diagrams.Other sources:pypi:http://pypi.python.org/pypi/infrastructure-diagrams/github:https://github.com/kotlarz/infrastructure-diagrams/Usage.. code:: bash$ infrastructure-diagrams
usage: infrastructure-diagrams [-h] [-d DISPLAY] [-o OUTPUT] [-r RENDERER] file

positional arguments:
  file                  path to diagram file

optional arguments:
  -h, --help            show this help message and exit
  -d DISPLAY, --display DISPLAY
                        display the diagram after rendering
  -o OUTPUT, --output OUTPUT
                        output path for the diagram, including filetype (.svg, .png, etc.)
  -r RENDERER, --renderer RENDERER
                        output renderer used for rendering (cairo, gd, etc.)Example:$ infrastructure-diagrams -o example.png examples/example.yamlConfiguration filesThe configuration files extend the GraphvizNode, Edge and Graph Attributes <https://www.graphviz.org/doc/info/attrs.html>__, meaning
you can customize the diagram / graph as needed.Examples:example.yaml|Output of example.yaml|misc.yaml|Output of misc.yaml|iot.yaml|Output of iot.yaml|Example diagram configuration files can be found under theexamples/ <https://github.com/kotlarz/infrastructure-diagrams/>__
directory... |Output of example.yaml| image::https://raw.githubusercontent.com/kotlarz/infrastructure-diagrams/master/examples/example.png.. |Output of misc.yaml| image::https://raw.githubusercontent.com/kotlarz/infrastructure-diagrams/master/examples/misc.png.. |Output of iot.yaml| image::https://raw.githubusercontent.com/kotlarz/infrastructure-diagrams/master/examples/iot.png
Package: infra-surveyor
Infra SurveyorA tool to survey existing cloud infrastructure and document what exists.
This project is still in development and is not yet in use on a production system.  Diagrams are against AWS at the moment but this might not be required in the future.InstallationTo Install this on  Mac OSX install graphviz then the requiremewnts and the library.brewinstallgraphviz
pipinstallinfra_surveyorInstallation for developmentThis project uses optional dependancies for development, documentation and release.
To develop on this project please clone the repository setup your virtual environment then run the followingpipinstall-e".[dev]"Installation for documentation developersTo work on the documentation on this project please clone the repository setup your virtual environment then run the followingpipinstall-e".[docs]"This will install mkdocs which can be used to host the docs locally during writing.  The command below will host the docs in html format on your machine.mkdocsserveReleasingpipinstall-e".[dev]"semantic-releasepublish--minorThis command will:bump the verison numbercreate the git tag for the releasepush the tagA github action will kick in to create the release in github when the tag is pushed.  The release will contain the files in the dist directory created by flit and license file.Running the toolPrequisites:AWS accountAWS profile setupAWS login with PROFILE and REGION defined in your environment via environment variables.This is a self documenting commandline application so once installed you can run the command below to explore the project.infra_surveyor--helpDependenciesGraphviz - Graphing libraryBoto3 - AWS SDK libraryClick - A command line building libraryThe following are not required dependencies for using the tool but are used in developmentToolDescriptionblackcode lintercoverageused to generate code coverage statsdockerused to mock lambdasflitPython package buildingGithub actionsCI/CD processesmkdocsDocumentation buildermotoAWS Mocking Librarypytesttest runnerpython-semantic-releaseVersion management
Package: infura
Infura.io API wrapperAn Infura.io API wrapper, for Python.With a default cache supported byrequests-cacheInstallationpip3 install infuraUsageimportinfuraifr=infura.Client(project_id='your-project-id',project_secret='your-project-secret',network='mainnet',cache_expire_after=5,)gas_price=ifr.eth_get_gas_price()balance=ifr.eth_get_balance('0x39eB410144784010b84B076087B073889411F878')block_number=ifr.eth_get_block_number()block=ifr.eth_get_block_by_number(block_number,show_transaction_details:bool=False)
Package: infuradj
infuradjinfuradjis a Python library that is used for sending transactions to Ethereum network via Infura.io.InstallTo install the library you can do:pip install infuradjorpip install git+https://github.com/dastanbeksamatov/django-infura.gitCredentials and authorization keysIt is recommended to store your private keys, project ids as an environment variable rather than using it directly. For that we can usepython-decouplepackage:pipinstallpython-decoupleThen you will have to create a file named.envinside the root directory of the project or in any place where you are callinginfuradjfunctions:touch.envInside the.envfile place your keys like this (following values are for demo purposes):PRIVATE_KEY="0x454b8f49fdd53a57d556d2f445149a47902257409c0789e6f2e45ada0b8cd793"
KOVAN_ID="6872e87746174c819fcca0b3ff2b3272"
POLYGON_ID="fc8295815e4f4ab4a17e2719353cfef1"
PUBLIC_KEY="0xe36bb11402231eBD171D5F459f095F9A248f0122"python-decoupleautomatically loads the environemnt variables and it's usage inpythonfiles are demonstrated below in examples section.ExamplesSome usage examples of the library:# decouple package is used for loading environment variablesfromdecoupleimportconfigfrominfuradjimportsend_tx,get_tx_details,NETWORK_IDS"""You have to have funds for gas fees in Kovan network"""tx_hash=send_tx(config('PUBLIC_KEY'),"some message",config('KOVAN_ID'),config('PRIVATE_KEY'),'kovan')print(tx_hash)"""You have to have funds for gas fees in Polygon network to send the transaction"""poly_hash=send_tx(config('PUBLIC_KEY'),"polygon message",config('POLYGON_ID'),config('PRIVATE_KEY'),'polygon-mainnet')print(poly_hash)"""Gets details about transaction by hashFor example, you can use it to get the input of the transaction, blockNumber, etc."""details=get_tx_details("0x3d6cb7e4dd0df34a11786be638b3b975e09f549b688a6a4ff994fef5a026b35b",'kovan',config('KOVAN_ID'))data=bytes.fromhex(details.get('input')[2:]).decode()print("tx input:{}".format(data))# tx input: some message"""NETWORK_IDS is a map of network name to its chain_id"""print("networks:{}".format(NETWORK_IDS.keys()))# networks: dict_keys(['mainnet', 'kovan', 'rinkeby', 'goerli', 'ropsten', 'polygon-mainnet'])APIsend_tx(to, message, project_id, private_key, network, value=0, gas=90000)Main exposed function that prepares the transaction and sends it toinfura.ionetworksto: string- account to sent tomessage: string- data to append to txproject_id: string-infuraproject idprivate_key: string- account private keys for signing the txnetwork: string- eth network (mainnet, polygon, kovan, etc.)value: integer- amount to send (defaults to 0)gas: integer- gas to spend (defaults to 90000)get_tx_details(tx_hash, network, project_id)Gets transaction details using the given hash. If tx is not mined yet or in a wrong format it raisesNotFoundexceptiontx_hash: string- hash of the transactionproject_id: string-infuraproject idnetwork: string- eth network (mainnet, polygon, kovan, etc.)NETWORK_IDSConstant of map type that maps network name to its respectivechain_idIssuesIf you have any issues or bugs with the project, feel free to open an issue.
Package: infuse
# Infuse[![Build Status](https://travis-ci.org/bregman-arie/infuse.svg?branch=master)](https://travis-ci.org/bregman-arie/infuse)Infuse is nothing at this point. We’ll update you once it becomes something[Requirements](#requirements)[Installation](#installation)## RequirementsPython >= 2.7## Installationpip install .## Initialize the databaseinfuse-db## Run the flask serverinfuse-server## ConfigurationInfuse loads configuration in this order:Default config.py - built-in. Part of Infuse code base.
Environment varliabes - any of the environment vairables specified in the table below that the user export (e.g.export INFUSE_SERVER_PORT=80)
Configurtion file - the default configuration file (/etc/infuse/infuse.com) or the file you mentioned with parser/environment variable.
Parser - arguments you pass with infuse command-line invocation.Name | Description |—- | ———– |INFUSE_CONFIG_FILE| The configuration file from where to load additional configurationINFUSE_DEBUG| Turn on DEBUGINFUSE_SERVER_PORT| The port to use when running Infuse serverINFUSE_DATABASE_URL| The database URL where we can connect to, defaults to sqlite local db file: infuse.db# ContributionsTo contribute use github pull requests.
Package: infuseai-metastore
PoC for MetaStoreYou need to prepare two things to make ake it runninga kaffka in the local and a createddream-1topica s3 credential to access the storagehttps://kafka.apache.org/quickstartSetup MetaStore API serverRun the docker-compose to setup meta-store API serverdocker-composeup-dCurrently, the API server only contains Kafka, PostgreSQL, and Hasura.Kafka: Serve for event subscriptionPostgreSQL: Store all the relationshipHasura: Dev tool for PostgreSQL and serve GraphQL endpointhelloworld.pyIt is a sample to write the event handler@on('dataset',event='updated',filter={'name':'demo-dataset-1'})defon_dataset_available():print(f'on_dataset_available invoked')dataset=project.get('dataset','demo-dataset-1')model=project.create('model','model-1',{'dataset':dataset})model.update()returnonwait for adatasetartifact increatedevent and filtering byname=dataset-1after training, we createModeland send a message to notify other handlerssend.event.py# in PoC, we don't handle the kafka# the Project object is a facade to everything {event sender, event listener runner, access to object store}project=Project('dream-1',profile='local')dataset=project.get('dataset','demo-dataset-1')ifnotdataset:dataset=project.create('dataset','demo-dataset-1')dataset.update()
Package: infusevideo-cli
infusevideo-cliThis is a simple CLI utility for the Infuse Video API.InstallationRequirementsPython3.9 or newerSetting up the virtualenvIt is recommended to use a virtualenv to install this package and dependencies. This ensures your
normal system stays clean and none of the dependencies conflict with other packages on your
system.Choose a directory where you want to install the CLI, and then runpython3 -m venv infusevideoor, on Windows,python.exe -m venv infusevideoThis will create a directoryinfusevideocontaining the virtualenv.Installing the dependencies and the package itselfSimply runinfusevideo/bin/pip install infusevideo-clior, on Windows,infusevideo\Scripts\pip install infusevideo-cliand all the dependencies will be retrieved and installed automatically, after which the latest
version of the CLI is installed as well. At this point, the executables have been installed ininfusevideo/bin/ivc
infusevideo/bin/ivsor, on Windows:infusevideo\Scripts\ivc.exe
infusevideo\Scripts\ivs.exePATHIn order to invoke the executables directly using justivcandivs, you can simply create a
symbolic link to them in a directory in your PATH, or alternatively (not recommended) you can copy
or move them into such a directory.UsageThere are two executables,ivcwhich is the normal CLI application, andivswhich is the same
as runningivc --script, as a convenience for running in scripts or any other environment where
human input is not available.Runninginfusevideo/bin/ivc --helpor, on Windows:infusevideo\Scripts\ivc --helpwill show the program usage.API documentationPlease refer tothe current API documentationfor an
overview of available actions on the API, request parameters and expected return values.UpgradingUpgrading is as simple as runninginfusevideo/bin/pip install --upgrade infusevideo-clior, on Windows:infusevideo\Scripts\pip install --upgrade infusevideo-cliUninstallingRemoving the application is as simple as removing theinfusevideodirectory created when making
the virtualenv. Your configuration file and token cache are stored in the.infusevideosub-directory of your home directory, and may also be removed.
Package: infusevideo-sdk
infusevideo-sdkThis is the Infuse Video SDK for Python.At the moment, this is a very basic initial version that takes care of authentication, and
otherwise exposes a simple REST client. More features and documentation are going to come soon.RequirementsPython3.9 or newerInstallationIt's always advisable to setup avirtualenvwhen
working with third-party packages, in order to keep this package and dependencies from cluttering
the globally installed packages, and vice versa. If you do not know how to set one up, refer to thePython documentation on venv.After creating and also activating the virtualenv, installation is as simple aspip install infusevideo-sdkThis will install a package namedinfusevideo, containing the SDK, into the virtualenv.UpgradingUpgrading is as simple as runningpip install --upgrade infusevideo-sdkUsageIn the current state, this is a simple wrapper around a REST/HTTP client. TheInfuseVideoclass
exposes five methods (get,post,patch,putanddelete) indicating their respective HTTP
counterparts.API documentationPlease refer tothe current API documentationfor an
overview of available actions on the API, request parameters and expected return values.
Authentication is already taken care of by the SDK, so that section of the API documentation may
be skipped.Example codeSimple code that calls theList mediaroute on the Media endpoint:import infusevideo

api = infusevideo.InfuseVideo()
result = api.get("/media")
print(result)Create a new Media and upload a video file:import infusevideo

api = infusevideo.InfuseVideo()
result = api.post("/media", data={"name": "A name", "metadata": "Example metadata"})
mediaId = result["mediaId"]

result = api.put(f"/media/{mediaId}", fileName="/path/to/my/file.mp4")
print(result)Creating a sample configuration fileBy default, the SDK will connect to the API, ask for your credentials interactively, and
attempt to obtain an authorization token with all permissions that were granted to you. If you have
access to multiple accounts, the token will be valid only for your default account. In order to
easily use multiple accounts, choose a different, limited, set of permissions or use non-interactive
M2M authentication, you will need to customise a profile in the configuration file. This
configuration file is normally located in the.infusevideo/directory in your home directory. If
you have not yet created this file, you can do so using the following code:import infusevideo

path = infusevideo.Config.generate_sample_config()
print(path)This will create a sample configuration file with a default profile and a separate sample profile
for M2M authentication. It will then print the path where the configuration file was created, for future reference. There will be some inline comments explaining the various configuration options
that are available.
Package: infusionsoft-client
A simple-to-useInfusionsoft XML-RPC APIclient, with included stubs for code sense. Python 3.5+ only (but pull requests welcome :smirk:).Installationpipinstallinfusionsoft-clientQuickstartFirst, initialize the client with your app name and API key:importinfusionsoftinfusionsoft.initialize('myapp','098f6bcd4621d373cade4e832627b4f6')And use theinfusionsoftlike a regularxmlrpc.client.ServerProxy:importinfusionsoftcontact_id=infusionsoft.ContactService.add({'FirstName':'Johnny'})Setting XML-RPC Client OptionsAny extra kwargs passed toinitialize()will be passed along toxmlrpc.client.ServerProxy.importinfusionsoftinfusionsoft.initialize('myapp','098f6bcd4621d373cade4e832627b4f6',use_builtin_types=True)Some kwargs of interest are:use_builtin_types: whether to utilize native Python types, rather than wrappers such asxmlrpc.client.DateTimeorxmlrpc.client.Binary.I recommend turning this on. It will be turned on by default in the next major/breaking release.verbose: set toTrueto print out the request and response bodies for each RPC call.allow_none: whether to allowNoneto be sent over the wire. Infusionsoft, in general, doesn’t allowNone(which isnilin XML-RPC parlance). If a field in a response is null, Infusionsoft will simply not send it.retries: number of times to retry failed requests. Requests are retried on connection/socket errors, and “InvalidConfig” faults (if you’ve never seen them, I envy you). Any other type of fault will still raise an exception.Seethe docsfor more info.Usage with Djangoinfusionsoft-clientincludes a Django integration out of the box. Just add it to yourINSTALLED_APPS:INSTALLED_APPS=(# ...'infusionsoft.contrib.django',)And add your app name and API key to your settings:INFUSIONSOFT_APP_NAME='myapp'INFUSIONSOFT_API_KEY='098f6bcd4621d373cade4e832627b4f6'Pass extra configuration to the XML-RPC client withINFUSIONSOFT_CLIENT_OPTIONS:INFUSIONSOFT_CLIENT_OPTIONS={'use_builtin_types':True,}Getting All Rows of a QuerySome API calls are paginated, and require multiple calls to retrieve all results. This can be a pain, and you may find yourself writing the same code over and over. To this end,infusionsoft-clientprovides aconsume()generator function, which will consume all pages of any query function.To use it, create a lambda (or regular) function takingpageandlimitas arguments which performs your paginated API call, and pass it toconsume():importinfusionsoftfrominfusionsoft.queryimportconsumequery_fn=lambdapage,limit:(infusionsoft.DataService.query('mytable',limit,page,['Id']))# Use with a for-loop, to avoid storing all rows in memory:forrowinconsume(query_fn):do_stuff(row)# Or retrieve all rows at onceall_rows=list(consume(query_fn))Generate Code StubsShipped withinfusionsoft-clientis code to download the official Infusionsoft XML-RPC docs, parse them withBeautifulSoup, and generate Python 3.5-compatible stubs for all methods.To generate these yourself, first install the extra requirements:pipinstall-rstub-requirements.txtThen run thegenerate_stubs()function, which will return a string:frominfusionsoft.gen_stubsimportgenerate_stubssource=generate_stubs()
Package: infynipy
InfynipyAn API wrapper for theInfynitymortgage broker system.Infynipy currently supports the following endpoints:Client AccountsFinancialsReferrer and Referrer GroupsGetting StartedInstall using pip:pip install infynipyBasic usage:frominfynipyimportInfynityclient=Infynity("USERNAME","API_KEY")print(client.broker(10).individuals)# Returns an array of Individual models# To turn them into dictionariesforindividualinclient.broker(10).individuals:print(individual.to_dict())View the rest of thedocumentation here.DevelopmentClone from GitHub and run the tests:git clone https://github.com/beanpuppy/infynipy.git
cd infynipyRun the tests and linter:toxLicenseMIT
Package: ing0-spawn
ing0's spawnUsageUsage:ing0availableing0createNAMEDISTRIBUTIONRELEASEARCHing0execNAME[EXTRA...]Getting startedsudoaptinstallsystemd-containerqemu-user-staticsudoing0createmy-arch-arm64-release-envarchcurrentarm64sudoing0execmy-arch-arm64-release-envpacman-Sy--noconfirmbase-develgitlz4util-linux-libszlibsudoing0execmy-arch-arm64-release-env--chdir=/mnt./configure'sudoing0execmy-arch-arm64-release-env--chdir=/mntmake-j7
Package: ingaia-libs
How to usepip installingaia-libs==0.0.52How to deploy to pypi.org???First: you need to install two python libraries:bumpversionandtwine.Second: execute the filedeployand put the pypi.org username and passwordSee “Operations Team Secret Resources“ to get pypi login infoLibrariesSee the Readme file in subdirectories to know these libraries:Google Cloud UtilsRequest Logger