Saravanan666/pypi-org huggingface dataset:
Package: evolutionsimulator
Welcome to the Evolution Simulator!This tool allows you to simulate the natural process of evolution in a simplified, artificial environment. Essentially, the tool simulates an environment filled with mice and owls. The mice strive to survive by eating grass, while the owls prey on the mice. Both animals are capable of propagating and pass down their genes to the offspring. Let evolution do its work, and see the marvelous effects of natural selection!Every simulation is based on a number of settings that you will specify before beforehand - or you can choose a pre-determined configuration if you like!The tool has two different modes:Interactive mode, where you can see evolution working in real-time.Simulation mode, where you can test a range of different custom configurations, figuring out which variables are important for stimulating evolution.In the environment, male and female mice are coloured dark and light blue respectively, while male and female owls are colored red and orange respectively. Each animal is given a number, indicating its level of speed. If the number is underlined, it means the animal is currently pregant, and will soon produce offspring.How to run:Install the necessary packages listed in requirements.txt via PIPNavigate to root folder and run "pythonw app.py" for smoothest experienceFollow instructions and enjoy!Variables:Environmentdimensions - number of vertical and horizontal tiles in the environmentrock_chance - the probability in percent that a tile is an obstructive rock instead of grassgrass_grow_back - number of ticks before grass grows back after being eatenSimulation mechanicsrand_catch - determines if catching is probability based or deterministicin_medias_res - determines if simulation is started cold or warmrand_variance_trait - the amount in percentage that offspring can vary in the speed trait from the average of its parentsspeed - determines whether or not the speed trait is inheritedMicem_number - number of mice upon start of simulationm_die_of_hunger - number of ticks before a given mouse dies of hungerm_preg_time - number of ticks that a female mouse is pregnantm_max_age - number of ticks before a mouse dies of old ageOwlso_numbero_die_of_hungero_preg_timeo_max_ageTick_time (only for interactive mode)slow_mode_sleep_time - time between each tick when slow-mode is enabledAuto_testing (only for simulation mode)ticks - number of ticks desired to be run for the simulationrepetitions - number of repetitions to be run for each given configuration
Package: evolution-simulator
Welcome to the Evolution Simulator!This tool allows you to simulate the natural process of evolution in a simplified, artificial environment. Essentially, the tool simulates an environment filled with mice and owls. The mice strive to survive by eating grass, while the owls prey on the mice. Both animals are capable of propagating and pass down their genes to the offspring. Let evolution do its work, and see the marvelous effects of natural selection!Every simulation is based on a number of settings that you will specify before beforehand - or you can choose a pre-determined configuration if you like!The tool has two different modes:Interactive mode, where you can see evolution working in real-time.Simulation mode, where you can test a range of different custom configurations, figuring out which variables are important for stimulating evolution.In the environment, male and female mice are coloured dark and light blue respectively, while male and female owls are colored red and orange respectively. Each animal is given a number, indicating its level of speed. If the number is underlined, it means the animal is currently pregant, and will soon produce offspring.How to run:Install the necessary packages listed in requirements.txt via PIPNavigate to root folder and run "pythonw app.py" for smoothest experienceFollow instructions and enjoy!Variables:Environmentdimensions - number of vertical and horizontal tiles in the environmentrock_chance - the probability in percent that a tile is an obstructive rock instead of grassgrass_grow_back - number of ticks before grass grows back after being eatenSimulation mechanicsrand_catch - determines if catching is probability based or deterministicin_medias_res - determines if simulation is started cold or warmrand_variance_trait - the amount in percentage that offspring can vary in the speed trait from the average of its parentsspeed - determines whether or not the speed trait is inheritedMicem_number - number of mice upon start of simulationm_die_of_hunger - number of ticks before a given mouse dies of hungerm_preg_time - number of ticks that a female mouse is pregnantm_max_age - number of ticks before a mouse dies of old ageOwlso_numbero_die_of_hungero_preg_timeo_max_ageTick_time (only for interactive mode)slow_mode_sleep_time - time between each tick when slow-mode is enabledAuto_testing (only for simulation mode)ticks - number of ticks desired to be run for the simulationrepetitions - number of repetitions to be run for each given configuration
Package: evolvcli
Evolv CLIThe experiment management CLI provides functionality to create and maintain Evolv experiments.SetupPre-requisites: You must have Python 3.7 installed on your computer.Create a Python virtual environment and install the cli.python3-mvenv.venvsource.venv/bin/activate
pipinstallevolvcliEnsure the CLI is properly installed by calling the cli. You must be in the virtual environment
you created to use the cli.evolvYou should see a help menu appear in your terminal.QuickstartTo start using the CLI obtain your account id from Evolv staff.Export your account id as an environment variable.exportEVOLV_ACCOUNT_ID=<youraccountid>To test the cli is working use the "get account" command.evolvgetaccountThe system will prompt you to enter your Evolv email and password.Once logged in you will not have to login again till your credentials expire.Other CommandsTo find out more about the CLI commands and how to use them use the--helpoption.For example:evolv get --helpPossible sub commands include:evolvget
evolvlist
evolvcreate
evolvupdateDevelopingWhen developing theres some key things to know.SetupCreate a Python virtual environment and install the cli.python3-mvenv.venvsource.venv/bin/activate
pipinstall-rrequirements.txt
pipinstall-rrequirements-dev.txt
pythonsetup.pydevelopEnsure the CLI is properly installed by calling the cli. You must be in the virtual environment
you created to use the cli.evolvYou should see a help menu appear in your terminal.Uploading to PyPiMake sure you are at the project root for these steps.Update the version of the package found in: [./setup.py] (Make sure to check this in.)Enter your virtual environment and upload the package.source.venv/bin/activate
pythonsetup.pysdist
twineuploaddist/*Twine will prompt you for credentials, get these from the Evolv Engineering Team.
Package: evolvedominion
evolvedominionA text-based interface for evolving---and, playing against---strategies for Dominion.This project was created as a proof of concept that minimally sophisticated agents
which rely only on local information could attain competent play through the use
of a genetic algorithm.InstallationBefore installing it is recommended to create and activate avirtualenvusing a version ofPython>= 3.8.12.Install from PyPI usingpippython -m pip install -U pip
python -m pip install -U evolvedominionInstall from GitClone the repository using eithergit clone https://github.com/evolvedominion/evolvedominion.gitorgit clone git@github.com:evolvedominion/evolvedominion.gitNavigate to the top level of the package and install usingpipcd evolvedominion
python -m pip install .Note: The tests will require additional dependencies.python -m pip install -r requirements_dev.txtUpdating evolvedominion to the latest release can be done
by navigating to the repository and usinggit pull
Package: evolven
Evolven API PythonEvolven API Python is a client library for Evolven's server APIs. It provides an abstraction on top of raw Evolven API calls to interact with Evolven Server.  To get started, check out the examples or read the documentation:Evolven API Python documentation:Show examplesHTTP API documentation:https://customers.evolven.comEvolven Software:https://www.evolven.comInstallationTo install from pip:pip install evolvenTo install from source:python setup.py installEvolven APIThe library provides a Python wrapper around the Evolven API and the Evolven data model. The library utilizes models to represent API calls to various objects:api.Hostapi.Environmentapi.CIapi.Changeapi.AgentThe results are returned either as pythonobjects,json,stringor PandasDataFrame. Fields for particular model match specified fields in Evolven API documentation.The API is exposed via theapi.EvolvenAPIclass. To create an instance of theapi.EvolvenAPIwith login credentials:importevolvenapi=evolven.EvolvenAPI("my-server.evolven.com",port=443,username="...",password="...")api.Host.search("US3ALSQL004")print(d.Next.Environment[0].name)>>>US3ALSQL004print(d.Next.Environment[0].env_id)>>>128439UsageBelow are examples of common tasks.Authenticate with session idAPI authentication can be achieved usingSecurityKeyparameter as follows:importevolvenapi=evolven.EvolvenAPI("my-server.evolven.com",port=443,session="1870b4b....")Define return typeYou can define object return type on class initialization as follows:api=evolven.EvolvenAPI("my-server.evolven.com",port=443,session="1870b4b....",return_type="DataFrame")All options are:"DataFrame"- returns data in normalized form as Pandas DataFrame object"object"- returns data as python object, fields are accesible as class properties"JSON"- returns data in JSON format"string"- returns string representation as returned by HTTP APIList all hostshosts=api.Host.list()hostsOutput:| Host        | HostType | EnvId | Os                     | ... |
|-------------|----------|-------|------------------------|-----|
| NYUATOLD002 | Prod     | 847   | Windows 7              | ... |
| US3ALENG005 | Prod     | 512   | Windows Server 2008 R2 | ... |
| ...         | ...      | ...   | ...                    | ... |Query Evolven Searchhosts=api.Search.search("Host where cpu-count > 8 | Hotfixes")hostsOutput:| CIName    | Host         | EnvId | Os                     | ... |
|-----------|--------------|-------|------------------------|-----|
| KB4580325 | NYUATOLD002  | 847   | Windows 7              | ... |
| KB4580325 | US3ALENG005  | 512   | Windows Server 2008 R2 | ... |
| ...       | ...          | ...   | ...                    | ... |Additional examplesAdditional examples are shown inJupter notebooks here.
Package: evolvepy
EvolvePyEvolvePy is a Python module created to allow the easy creation and execution of evolutionary algorithms.Documentation:EvolvePy's documentation.Presentation video (Portuguese, click on the image):Features(Links to example using the feature)Allows to create complex individual generators using different strategies:Crossover(one-point, n-point, mean)Mutation (sum, multiplication,binary)Dynamic mutationElitismRandomic predationIncremental evolutionDefine individuals with different chromosomes, with different types, ranges, sizes and parameters in the generator.Evaluate individuals usingsimple functionsormultiple processes.Fitness cacheto avoid evaluate the same individual several times.Fitness functions with different scores, which can be aggregated with different strategies.Evaluate the same individual several times to avoid noise.Log the evolution data to analyze later.Integrations with other modules:WandbTensorflow/KerasGymUnity ML Agents(using Gym)InstallationEvolvePy can be installed using pip:pipinstall--upgradepip
pipinstallevolvepyFor install with all integrations dependecies (gym, tensorflow, wandb, gym_unity):pipinstall--upgradepip
pipinstallevolvepy[all_integrations]For installing from the repository:gitclonehttps://github.com/EltonCN/evolvepycdevolvepy
pipinstall--upgradepip
pipinstall.ExamplesThe"examples"folder have a lot of examples of how to use EvolvePy.AuthorsCreated by students from Unicamp's Institute of Computing (IC-Unicamp) as a project for theevolutionary systems subjectat ICMC-USP, taught by prof. Eduardo do Valle Simoes.EltonCNJoão BonucciThiago Lacerda
Package: evolve-words
Evolve WordsIntroductionMany moons ago, back in 2008, while in a debate on an atheist-oriented phpBB
site (as was the fashion back then), I ended up writinga couple of
scripts, in ruby, to illustrate a point
about how mutation and selection can, given enough time, result in something
with the appearance of design.The code was far from a mic-drop body of evidence (it wasn't meant to be), I
think it did an okay job of showing how nothing more than just mutating
something and selecting for the "fitter" options can get you somewhere
meaningful given enough time.No matter, either you get the illustration or you don't. That's not
important.Fast forward 15 years and I was thinking that a Textual version of the code
might be fun.This is a version ofselection2.
Turns out itisfun!InstallationIf you want to play with this, the best method is going to be to install
withpipx:$pipxinstallevolve-wordsthen simply runevolve-words.RequirementsWhile this codeshouldwork fine on any operating system, it's really
coded to work on a system that provides one of the two following files:/usr/dict/words/usr/share/dict/wordsThat does, of course, mean it's unlikely to work fine on Windows given
neither of them will be there. At some point in the very near future I'll
add support for loading words from a file whose name is passed on the
command line, or something similar.
Package: evomaster-client
EvoMaster Client for PythonAbout EvoMaster:EvoMasteris the first open-source AI-driven tool for automatically generating system-level test cases (also known as fuzzing) for web/enterprise applications. Currently targeting whitebox and blackbox testing of REST APIs.Evomaster-Client for Python FlaskThis library will let you integrate your Flask restful application to the EvoMaster core in order to automatically generate test cases for your API endpoints using theunittesttesting framework for Python.Quick StartInstallation:pip3installevomaster-clientAfter the installation, a CLI is available to be run from a Python environment to use the EvoMaster driver.You can access the CLI help using:python-mevomaster_client.cli-hFor now, the CLI supports two commands:run-instrumentedrun-em-handlerRunning the instrumented version of your application:python-mevomaster_client.clirun-instrumented[OPTIONS]For example:python-mevomaster_client.clirun-instrumented--package-prefix'evomaster_benchmark.ncs'--flask-module'evomaster_benchmark.ncs.app'--flask-app'app'--instrumentation-level2where:package-prefix is the prefix used to define the modules that will be instrumentedflask-module is the main module of your appflask-module is the name of your Flask object defined in flask-module, used to start your appinstrumentation-level can be [0..2] where a higher value means the code instrumentation is richerRunning the EvoMaster handler to generate white-box tests for your application:python-mevomaster_client.clirun-em-handler[OPTIONS]For example:python-mevomaster_client.clirun-em-handler--handler-module'evomaster_benchmark.em_handlers.ncs'--handler-class'EMHandler'--instrumentation-level2where:handler-module is the module where the driver class, extending from FlaskHandler, was implementedhandler-class is name of the driver class defined in handler-moduleflask-module is the name of your Flask object defined in flask-module, used to start your appinstrumentation-level can be [0..2] where a higher value means the code instrumentation is richerOnce you have the handler running, white-box tests can be generated using:java-jar../core/target/evomaster.jar--maxTime[time]--outputFolder[path_to_tests]--outputFormatPYTHON_UNITTESTThen you can run your generated tests using:pip3 install unittest requests
python -m unittest [path_to_tests]
Package: evomatic
EvomaticEvomatic is an genetic algorithm tool for the development of new alloys.InstallationThe evomatic package can be installed frompypiusing pip:pip install evomaticEvomatic makes heavy use of themetallurgypackage to manipulate
and approximate properties of alloys. Thecerebralpackage can be used by
evomatic to obtain predictions of alloy properties on-the-fly during evolution.UsageBasic usage of evomatic involves setting some targets and running an evolution,
the following example shows evolution of a small population towards alloys with
high mass:>>>importevomaticasevo>>>evolver=evo.Evolver(targets={"maximise":["mass"]},population_size=50)>>>history=evolver.evolve()>>>history["alloys"]alloymassgenerationrankfitnessOg100295.000000701.000000Og92.4Fl7.6294.5440001110.998433Og91.4Lv7.4Cm1.2294.276000920.997512Og78Mc14Lv6.2Hs1.8293.7260001130.995622Lv100293.000000240.993127...............Ar38.8Li28.5B24.9Sc5.7I2.125.396895105870.073521Si79H2122.398830105880.063218Li83.7Zr16.320.67829265890.057305Li97.9Db2.112.46426055900.029078He1004.00260245910.000000In this simple example, there is no better material for the objective of maximum
mass than pure Oganesson.DocumentationDocumentation is availablehere.
Package: evoml.framework
EVO-CC: An Open-Source Classification-Based Nature-Inspired Optimization Clustering Framework in PythonDescription: The framework is an open source and cross-platform framework implemented in Python which uses the classification technique with the evolutionary clustering approach provided by the EvoCluster framework. The goal of this framework is to provide a user-friendly and customizable implementation of the classification-based evolutionary clustering which can be utilized by experienced and non-experienced users for different applications. The framework can also be used by researchers who can benefit from the framework for their research studies.Framework folders and files:EvoCluster folderDataset folderClassification fileExamples files
Package: evomo-mqtt
Evomo PythonThis is a Python library to simplify the connection to Evomo IoT Platform. For more information about the platform itself, please visit thehttps://evomo.jeager.io.InstallationMake sure you have Python (2 or 3) and pip installed.pip install evomo-mqttUsage ExampleSend datafromevomo_mqttimportevomomyData={'T':77,'H':10}evomo.send(myData,'your-client-id','your-device-id')API Referencesend(data, clientID, deviceID)Send data to your Evomo project. This can be a python dictionary or string.return: response data from evomo
Package: evonik-apitest
apitestThis repo contains the python moduleapitest.
It is publically available on the python package index as the packageevonik-apitest.Repo Structureapitest/           # source code of apitest
examples/          # examples for the use of apitest
notebooks/         # jupyter notebooks with examples and doc
LICENSE            # MIT license file
README.md          # this readme
setup.py           # pypi setup scriptInstallationUse the package managerpipto installapitestas the packageevonik-apitest.pipinstallevonik-apitestUsagefromapitestimportProperty,Properties,EndpointsfromapitestimportComponent,Instance,ComponentTestfromapitest.utilimportrand_str,rand_int...TestTo test the current implementation, execute the following:pytest \
    apitest/component.py \
    apitest/component_test.py \
    apitest/endpoints.py \
    apitest/instance.py \
    apitest/properties.py \
    apitest/property.py \
    apitest/util.py \
    apitest/test_basic.pyBuild & UploadTo build the package and upload a new version to pypi, execute the following commands:rm -rf build dist evonik_apitest.egg-info
python3 setup.py sdist bdist_wheel --universal
twine upload dist/*LicenseMIT
Package: evonik-crudl
crudlThis repo contains the python modulecrudl.
It is publically available on the python package index as the packageevonik-crudl.Repo Structurecrudl/             # source code of crudl
LICENSE            # MIT license file
README.md          # this readme
setup.py           # pypi setup scriptInstallationUse the package managerpipto installcrudlas the packageevonik-crudl.pipinstallevonik-crudlUsagefromapitestimportSqliteDB,MysqlDB...An example for the use of SqliteDB can be found incrudl/tet.py.TestTo test the current implementation, execute the following:pytest crudl/test.pyNote that this only tests the SqliteDB wrapper.Build & UploadTo build the package and upload a new version to pypi, execute the following commands:rm -rf build dist evonik_crudl.egg-info
python3 setup.py sdist bdist_wheel --universal
twine upload dist/*Open / Known Issuesgeneralization of filter comparatorsadd filter operators (and/or/...)LicenseMIT
Package: evonik-dummy
evonik-dummyThis repo contains the python moduleevonik.dummy.
It is publically available on the python package index as the packageevonik-dummy.The module contains python classes to generate dummy data. These classes and their attributes / arguments are designed with the properties of data elements inOpenAPIin mind. They can be used to generate example data for testing and showcasing APIs, including REST and GQL.Repo Structureevonik/            # source code of evonik-dummy
notebooks/         # jupyter notebooks with examples and doc
LICENSE            # MIT license file
README.md          # this README
setup.py           # pypi setup script
requirements.txt   # list of dependenciesInstallationUse the package managerpipto installevonik.dummyas the packageevonik-dummy.pipinstallevonik-dummyUsagefromevonik.dummyimportString,Integerprint(String().valids(5))print(Integer().invalids(exhaustive=True))TestTo test the current implementation, execute the following:pytest evonik/dummyBuild & UploadTo build the package and upload a new version to pypi, execute the following commands:rm -rf build dist evonik_dummy.egg-info
python3 setup.py sdist bdist_wheel --universal
twine upload dist/*LicenseMIT
Package: evonik-test-crudl
evonik-test-crudlThis repo contains the python moduleevonik.test.crudl.
It is publically available on the python package index as the packageevonik-test-crudl.The module contains python classes to test CRUDL APIs, including REST and GQL.
It heavily used the packageevonik-dummy, availablehere.Repo Structureevonik/            # source code of evonik.test.crudl
notebooks/         # jupyter notebooks with examples and doc
LICENSE            # MIT license file
README.md          # this README
setup.py           # pypi setup script
requirements.txt   # list of dependencies for local testing / developmentInstallationUse the package managerpipto installevonik.test.crudlas the packageevonik-test-crudl.pipinstallevonik-test-crudlTestTo test the current implementation, execute the following:pip install -r requirements.txt
pytest evonik/test/crudlBuild & UploadTo build the package and upload a new version to pypi, execute the following commands:rm -rf build dist evonik_dummy.egg-info
python3 setup.py sdist bdist_wheel --universal
twine upload dist/*LicenseMIT