Saravanan666/pypi-org huggingface dataset:
Package: garpix-jira-pages
Garpix JiraИнтеграция с Jira Server.Быстрый стартУстановите через pipenv:pipenvinstallgarpix_jiraДобавьтеgarpix_jiraвINSTALLED_APPSи укажите адрес для миграций:# settings.pyfromgarpixcms.settingsimport*# noqaINSTALLED_APPS+=['garpix_jira',]MIGRATION_MODULES['garpix_jira']='app.migrations.garpix_jira'Создайте директории и файлы:backend/app/migrations/garpix_jira/backend/app/migrations/garpix_jira/__init__.pyСделайте миграции и мигрируйте:python3backend/manage.pymakemigrationspython3backend/manage.pymigrateПосле этого необходимо создать адрес сервера, с которым будем интегрироваться и ввести учетные данные администратора Jirahttp://localhost:8000/admin/garpix_jira/server/Теперь, можно забрать данные из Jira в ваш проект. Для этого выполните команду (она будет периодически запускать данные):python3backend/manage.pyjira_sync_allGarpix Jira PagesТакже, вы можете выводить статистику на страницы, используя garpixcms (https://github.com/garpixcms/garpixcms).Для этого, сделайте следующее:Установите через pipenv:pipenvinstallgarpix_jira_pagesДобавьтеgarpix_jira_pagesвINSTALLED_APPSи укажите адрес для миграций:# settings.pyfromgarpixcms.settingsimport*# noqaINSTALLED_APPS+=['garpix_jira_pages',]MIGRATION_MODULES['garpix_jira_pages']='app.migrations.garpix_jira_pages'Создайте директории и файлы:backend/app/migrations/garpix_jira_pages/backend/app/migrations/garpix_jira_pages/__init__.pyСделайте миграции и мигрируйте:python3backend/manage.pymakemigrationspython3backend/manage.pymigrateТеперь, вы можете создать в административной панели, в Структуре страниц страницу
“Jira - Затраченное время пользователей (страница)” и увидите на ней таблицу затреканного времени.Чтобы скрыть лишние записи, можно в админ-панели в Пользователях Jira выключить галку “Пользователь трекает время?”.ChangelogSeeCHANGELOG.md.ContributingSeeCONTRIBUTING.md.LicenseMITDeveloped by Garpix /https://garpix.com
Package: garpix-keycloak
Garpix KeycloakKeycloak uth module for Django/DRF projects. Part of GarpixCMS.Used packages:django rest frameworketc; see setup.pyQuickstartInstall with pip:pipinstallgarpix_keycloakAdd thegarpix_keycloakto yourINSTALLED_APPS:# settings.py# ...INSTALLED_APPS=[# ...'garpix_keycloak',]AddKeycloakUserMixinto yourUsermodel:fromdjango.contrib.auth.modelsimportAbstractUserfromgarpix_keycloak.mixinsimportKeycloakUserMixinclassUser(AbstractUser,KeycloakUserMixin):classMeta:verbose_name='Пользователь'verbose_name_plural='Пользователи'def__str__(self):returnself.usernameAddKeycloakAuthMiddlewaretoMIDDLEWAREsettings afterdjango.contrib.auth.middleware.AuthenticationMiddleware:# settings.pyMIDDLEWARE=[# ...'django.contrib.sessions.middleware.SessionMiddleware','django.contrib.auth.middleware.AuthenticationMiddleware','garpix_keycloak.middlewares.KeycloakAuthMiddleware',]Add authentication backend:AUTHENTICATION_BACKENDS=[# ...'garpix_keycloak.backends.KeycloakAuthenticationBackend']Add keycloak parameters tosettings.py:# settings.pyKEYCLOAK={'SERVER_URL':'your_server_url','REALM':'your_realm','CLIENT_ID':'your_client_id','CLIENT_SECRET_KEY':'your_client_secret_key'}Useget_keycloak_urlfromKeycloakServiceto generate keycloak log in link.garpix_keycloakcreatesUsermodel instance, usingcreate_keycloak_userclass method.
You can override it if you need some customization in your project.Enjoy!ChangelogSeeCHANGELOG.md.ContributingSeeCONTRIBUTING.md.LicenseMITDeveloped by Garpix /https://garpix.com
Package: garpix-order
Garpix Orderfromgarpix_order.modelsimportBaseOrder,BaseOrderItem,BasePaymentclassOrder(BaseOrder):passclassService(BaseOrderItem):defpay(self):passclassInvoice(BasePayment):passBaseOrder- основной класс заказа.items- метод для получения связанных OrderItem.items_amount- метод для получения суммы оплаты.BaseOrderItem- части заказа. В один заказ можно положить несколько сущностей.pay- метод вызовет у всех BaseOrderItem, когда оплачивается заказ.full_amount- метод возвращает полную сумма заказа.Invoice- Основная модель для отслеживания статуса оплаты (транзакция). Содержитstatusс типом FSM.
Package: garpix-package
Garpix PackCreate and upload packages to pypi.org.QuickstartInstall with pip:pipinstallgarpix_qaAdd thegarpix_packageto yourINSTALLED_APPS:# settings.pyINSTALLED_APPS=[# ...'garpix_package',]Create new package in your project.pythonmanage.pystartpackage<app_name>Upload package to pypi.org.pythonmanage.pypack<app_name>Examplepython manage.py startpackage my_app
python manage.py pack my_appChangelogSeeCHANGELOG.md.ContributingSeeCONTRIBUTING.md.LicenseMITDeveloped by Garpix /https://garpix.com
Package: garpix-profitbase
Garpix ProfitBaseПакет интеграции с profitbase.ruБыстрый стартУстановка:pipinstallgarpix_profitbaseДобавьтеgarpix_profitbaseвINSTALLED_APPS:# settings.pyINSTALLED_APPS=[# ...'garpix_profitbase',]Также, добавьте переменные окружения (файл.env) значениями, полученными от profitbase.ru:PROFITBASE_API_KEY=app-?????????PROFITBASE_CLIENT_NAME=???????PROFITBASE_COMPANY_ID=????ENABLE_GARPIX_AUTH=FalseТакже, в settings.py необходимо добавить миксины:GARPIX_PROFITBASE_CITY_MIXIN='garpix_profitbase.models.empty_mixin.EmptyMixin'GARPIX_PROFITBASE_HOUSE_MIXIN='garpix_page.models.BasePage'GARPIX_PROFITBASE_HOUSE_FLOOR_MIXIN='garpix_profitbase.models.empty_mixin.EmptyMixin'GARPIX_PROFITBASE_HOUSE_SECTION_MIXIN='garpix_profitbase.models.empty_mixin.EmptyMixin'GARPIX_PROFITBASE_PROJECT_MIXIN='garpix_page.models.BasePage'GARPIX_PROFITBASE_PROPERTY_MIXIN='garpix_page.models.BasePage'GARPIX_PROFITBASE_SPECIAL_OFFER_MIXIN='garpix_profitbase.models.empty_mixin.EmptyMixin'GARPIX_PROFITBASE_LAYOUT_PLAN_MIXIN='garpix_profitbase.models.empty_mixin.EmptyMixin'Если вам необходимо, чтобы помещения отправлялись на дальнейшую обработку при удалении/добавлении/изменении акции,
можно указать путь к функции.# example:GARPIX_PROFITBASE_RECALCULATE_NEW_PRICE='app.service.recalculate_new_price'RECALCULATE_NEW_PRICE
Нужно обратиться к администраторам profitbase.ru чтоб они добавили ваш ip в белый список.ИспользованиеДля получения данных от profitbase.ru используйте следующую manage.py команду:python3 backend/manage.py profitbase_updateChangelogСмотриCHANGELOG.md.ContributingСмотриCONTRIBUTING.md.LicenseMITDeveloped by Garpix /https://garpix.com
Package: garpix-vacancy
Garpix VacancyБыстрый стартУстановка:pipinstallgarpix_vacancyДобавьтеgarpix_vacancyвINSTALLED_APPS:# settings.pyINSTALLED_APPS=[# ...'garpix_vacancy',]Также, в settings.py необходимо добавить миксины:GARPIX_VACANCY_MIXIN='garpix_page.models.BasePage'GARPIX_CONTACT_MIXIN='garpix_page.models.BasePage'ChangelogСмотриCHANGELOG.md.ContributingСмотриCONTRIBUTING.md.LicenseMITDeveloped by Garpix /https://garpix.com
Package: garpunauth
This library simplifies using Garpun’s various server-to-server authentication
mechanisms to access Garpun APIs.InstallingYou can install usingpip:$ pip install garpunauthSupported Python VersionsPython >= 3.6Using# Use it for first auth with your scopesfromgarpunauth.clientimportGarpunCredentialscredentials,project_id=GarpunCredentials.authenticate_user(['cloud-platform'])print(u"credentials.access_token =%s"%str(credentials.access_token))print(u"credentials.access_token_expired =%s"%str(credentials.access_token_expired))print(u"credentials.refresh_token =%s"%str(credentials.refresh_token))# Refresh access_token if it expiredGarpunCredentials.refresh_credentials(credentials)print(u"credentials.access_token =%s"%str(credentials.access_token))For contributorsUsemake blackfor blacken the codeUsenoxfor run tests and other checksSet PyCharm default test runner to pytest
Package: garpy
garpyis a simple app used to backup your data from Garmin Connect. It can be used to do incremental
backups of your data from Garmin Connect or to download one specific activity.Incremental backup of activitiesThe first time you use it, all the activities found on your Garmin Connect account will be downloaded to
the directory that you specify. Afterwards, each time you run the command, only the newly available
activities will be downloaded.The command is used as follows:garpydownload{backup-dir}Behind the scenes, this is what will happen:garpywill prompt you for your password and will then authenticate against Garmin Connect.It will first fetch the list of all your activities from garmin.It will check which activities have already been backed up on the givenbackup-dirIt will proceed to download all the missing activities.Downloading one activity from its IDIf you wish to download only one activity or simple you want to refresh an already downloaded activity,
use the ‘-a/–activity’ flag as follows:garpydownload--activity1674567326{backup-dir}This will download the activity in all existing formats to the givenbackup_dirFull CLI optionsFor more detailed usage, invoke the ‘–help’ command:$garpydownload--helpUsage:garpydownload[OPTIONS][BACKUP_DIR]DownloadactivitiesfromGarminConnectEntrypointfordownloadingactivitiesfromGarminConnect.Bydefault,itdownloadsallnewlycreatedactivitiessincethelasttimeyoudidabackup.IfyouspecifyanactivityIDwiththe"-a/--activity"flag,onlythatactivitywillbedownloaded,evenifithasalreadybeendownloadedbefore.Ifnoformatisspecified,theappwilldownloadallpossibleformats.Otherwiseyoucanspecifytheformatsyouwishtodownloadwiththe"-f/--formats"flag.Theflagcanbeusedseveraltimesifyouwishtospecifyseveralformats,e.g.,'garpy download [OPTIONS] -f original -f gpx
  [BACKUP_DIR]'willdownload.fitand.gpxfilesOptions:-f,--formats[original|gpx|fit|tcx|kml|summary|details]Whichformatstodownload.Theflagcanbeusedseveraltimes,e.g.'-f original -f
                                  gpx'-u,--username{username}UsernameofyourGarminaccount-p,--password{password}PasswordofyourGarminaccount-a,--activity{ID}ActivityID.Ifindicated,downloadonlythatactivity,evenifithasalreadybeendownloaded.Otherwise,doincrementalupdateofbackup--user-agent{user_agent}Useragenttobeusedbyrequests--helpShowthismessageandexit.Installationgarpyrequires Python 3.7 or higher on your system. For those who know your way around with Python, installgarpywith pip as follows:pipinstall-UgarpyIf you are new to Python or have Python 2 installed on your
computer, I recommend you installMiniconda. To my knowledge, it is the simplest way of installing a robust and
lightweight Python environment.AcknowledgementsThe library is based ongarminexport. I borrowed the GarminClient, refactored it to my taste and
created a package from it.
Package: garpyclient
Garpyclient: Basic library for authenticating and querying Garmin Connectgarpyclientis a simple library to communicate with Garmin Connect. It was extracted fromgarpyand the idea is for this to become the core client
library of it in a next iteration. Ideally,garpyclientis intended to be used by other python libraries that want to download their data from Garmin Connect. It is kept simple on purpose so that
end users can build upon it with their own workflows. As an example, the following code will fetch the
latest activity from your Garmin profile:fromgarpyclientimportGarminClientwithGarminClient(username="user",password="pass")asclient:activities=client.list_activities()response=client.get_activity(activities[0]["activityId"],fmt="original")The file content will be found inresponse.content. The format of the file will depend on the parameterfmtto which you can pass the following values:For an overview of the activities:summaryordetailsFor data points of the activity:gpx,tcx,original(usually fit format) andkml.Installationgarpyclientrequires Python 3.7 or higher on your system.
Install with pip as follows:pipinstall-UgarpyclientIf you are new to Python, I recommend you installMiniconda. To my knowledge, it is the simplest way of installing a robust and
lightweight Python environment.AcknowledgementsThe original library (garpy) is based ongarminexport. I borrowed the GarminClient, refactored it to my taste and created a package from it.
Package: garrison-server
Queue server base on RocksDB as a KV-Store backend and gRPC as an interfaceTable of ContentsTable of ContentsAbout The ProjectBuilt WithPrerequisitesInstallationUsageServerClientLicenseContactAbout The ProjectGarrison is a RocksDB wrapped in a gRPC service to expose some high level functionalities.
Garrison is also implments queue functionalities on the top of RocksDB KV store functionalities.Built WithgRPCRocksDBPrerequisitesIn order to pip install rocksdb you will need to install the following distro packagesUbuntu 18.04sudoaptinstalllibrocksdb-devlibsnappy-devliblz4-devInstallationpip3installgarrison-serverUsageServerpython3-mgarrison.server--database-path=/data/garrison_db--port=10000Clientimportgarrison.clientclient=garrison.client.GarrisonClient(host='127.0.0.1',port=10000,)# Sets a key inside the database - return whether the key is new or existedclient.key_set(key=b'key_name',value=b'value',)# Retrieving a key - return None if key does not existvalue=client.key_get(key=b'key_name',)# Deletes a key inside the database - return whether the key is deleted or wasn't existeddeleted_successfuly=client.key_delete(key=b'key_name',)# Push items into a queue.# Priority is either NORMAL or HIGH, and controls whether the items will be pushed on the top or buttom of the queueclient.queue_push(queue_name=b'queue_name',items=[b'item one',b'item two',b'item three',],priority='NORMAL',)# Get the number of items in the queuenumber_of_items=client.queue_length(queue_name=b'queue_name',)# Pulling items from the queue - return list of items. HIGH priority first.items=client.queue_pop(queue_name=b'queue_name',number_of_items=3,)# Deletes a key inside the database - return whether the key is deleted or wasn't existeddeleted_successfuly=client.queue_delete(queue_name=b'queue_name',)LicenseDistributed under the MIT License. SeeLICENSEfor more information.ContactGal Ben David -intsights@gmail.comProject Link:https://github.com/intsights/garrison
Package: garrus
In the middle of some calibrations...Garrus is a python framework for better confidence estimate of deep neural networks. Modern networks are overconfident estimators, that makes themselves unreliable and therefore limits the deployment of them in safety-critical applications.Garrus provides tools for high quality confidence estimation such as confidence calibration and ordinal ranking methods, helping networks toknow correctly what they do not know.Installation:pipinstall-UgarrusDocumentation:master v0.2.0develop v0.2.0Roadmap:Core:Calibration metrics:ECENLLBrierOrdinal Ranking Metrics:AURCE-AURCAUPREFPR-n%-TPRVisualizations:Reliability DiagramConfidence HistogramGarrus ProfilingConfidence Calibration:Scaling:PlattTemperatureBinning:HistogramIsotonic RegressionConfidence Regularization:Losses:Correctness Ranking LossFocal Entropy Penalized LossLanguage Model Beam SearchConfidence Networks:ConfidNetGarrusNetCitation:Please use this bibtex if you want to cite this repository in your publications:@misc{garrus,
    author = {Kalashnikov, Alexander},
    title = {Deep neural networks calibration framework},
    year = {2021},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/sleep3r/garrus}},
}References:Papers[1]Guo, Chuan, et al. "On calibration of modern neural networks." International Conference on Machine Learning. PMLR, 2017. APA[2]Moon, Jooyoung, et al. "Confidence-aware learning for deep neural networks." international conference on machine learning. PMLR, 2020.[3]Kumar, Ananya, Percy Liang, and Tengyu Ma. "Verified uncertainty calibration." arXiv preprint arXiv:1909.10155 (2019).
Package: garrysampleproject
A sample project that exists as an aid to thePython Packaging User Guide’sTutorial on Packaging and Distributing
Projects.This projects does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.The source for this project is available here.Most of the configuration for a Python project is done in thesetup.pyfile, an example of which is included in this project. You should edit this
file accordingly to adapt this sample project to your needs.This is the README file for the project.The file should use UTF-8 encoding and be written usingreStructuredText. It
will be used to generate the project webpage on PyPI and will be displayed as
the project homepage on common code-hosting services, and should be written for
that purpose.Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not
a good idea, although a simple “What’s New” section for the most recent version
may be appropriate.
Package: garser
Wrapper around the HTMLParser python moduleDocumentationâ€¢Basic usageâ€¢AboutGarser is one of the more advanced tools to scan and parse html. It stores all html entities in objectsFeaturesParses HTML in nested object formatAttributes are stored as data membersNested and Non-Nested Entity searchEntity Search based on attributesIntelligent nesting for non closing html entitiesObjects can be converted to JSON FormatInspired by SeleniumLicenseThis tool is licensed under the GNU General Public License v3.0.Some parts of this code comes fromHTMLParser
Package: gars-field
GARS -Global Area Reference SystemField - Corteva Agriscience farming reference.Bugs/QuestionsReport bugs/feature requests:https://github.com/corteva/gars-field/issuesAsk questions:https://github.com/corteva/gars-field/discussionsUsageNoteSee the module docstrings for more details.GARSField: determine GARS grids based on bounding boximportgeopandasimportshapely.geometryfromgars_fieldimportGARSFieldgeom_bounds=shapely.geometry.box(minx=-175,miny=-76,maxx=-174,maxy=-75)garsf=GARSField(geom_bounds)# 6 deg grids (extension)grids_6deg=garsf.gars_6deg# 3 deg grids (extension)grids_3deg=garsf.gars_3deg# 1 deg grids (extension)grids_1deg=garsf.gars_1deg# 30 min gridsgrids_30min=garsf.gars_30min# 15 min gridsgrids_15min=garsf.gars_15min# 5 min gridsgrids_5min=garsf.gars_5min# 1 min grids (extension)grids_1min=garsf.gars_1min# convert to geopandasgeopandas.GeoDataFrame({"gars_id":[str(grid)forgridinfield.gars_1min]},geometry=[grid.polygonforgridinfield.gars_1min],crs="EPSG:4326",)GARSGridGrid cell sizes: 1, 5, 15, 30 minutesfromgars_fieldimportGARSGrid# from latlonggrid=GARSGrid.from_latlon(-89.55,-179.57,resolution=5)# from GARS IDggrid=GARSGrid("001AA23")# get bounding polygrid_poly=ggrid.polygon# get GARS IDgars_id=str(ggrid)# UTM CRS EPSG Codeepsg_code=ggrid.utm_epsgEDGARSGridThis is the extended degree grid system.Grid cell sizes: 1, 3, 6 degreesfromgars_fieldimportEDGARSGrid# from latlonggrid=EDGARSGrid.from_latlon(-89.55,-179.57,resolution=3)# from GARS IDggrid=EDGARSGrid("D01AA23")# get bounding polygrid_poly=ggrid.polygon# get GARS IDgars_id=str(ggrid)# UTM CRS EPSG Codeepsg_code=ggrid.utm_epsgGEDGARSGridThis is the giant extended degree grid systemGrid cell sizes: 30, 60 degreesfromgars_fieldimportGEDGARSGrid# from latlonggrid=GEDGARSGrid.from_latlon(-89.55,-179.57,resolution=3)# from GARS IDggrid=GEDGARSGrid("GD1A")# get bounding polygrid_poly=ggrid.polygon# get GARS IDgars_id=str(ggrid)CreditsGARSGridwas inspired by:https://github.com/mil-oss/GARSutilshttps://github.com/Moustikitos/gryd/blob/c79edde94f19d46e3b3532ae14eb351e91d55322/Gryd/geodesy.py
Package: gartersnake
GarterSnakeGarterSnake is a set of functions that helps with usingsetuptoolsinsetup.py. It includesdynamically retrieving version info from VCS withdunamaiinstalling packages
fromChristoph Gohlke's Windows binarieswithpipwininstalling packages usingcondaUsagefromsetuptoolsimportfind_packages,setupfromgartersnakeimportinstall_conda_requirements,\install_windows_requirements,is_conda,is_windows,missing_requirements,\vcs_versionREQUIREMENTS={'fiona':['gdal'],'numpy':[],'requests':[],}MISSING=missing_requirements(REQUIREMENTS)ifis_conda():install_conda_requirements(MISSING)MISSING=missing_requirements(REQUIREMENTS)ifis_windows():install_windows_requirements(MISSING)__version__=vcs_version()setup(name='<package_name>',version=__version__,authors='<package_authors>',url='<package_url>',packages=find_packages(),python_requires='>=3.6',setup_requires=['dunamai','setuptools>=41.2'],install_requires=list(REQUIREMENTS),)
Package: garuda
Microservices are fun. But what would make them even more fun to work with,is if we can avoid duplicating the data layer across your micro-services.
Django ORM is amazing. Let’s share the joy of Django ORM with other languages.
I have written a tool to automatically expose Django ORM to other languages
and which can also generate respective client libraries in other languages.
I heavily rely on Protobuf and gRPC and a lot of AST parsing.
Package: gasbullet
gasbulletAdd a short description here!A longer description of your project goes here…Making Changes & ContributingThis project usespre-commit, please make sure to install it before making any
changes:pip install pre-commit
cd gasbullet
pre-commit installIt is a good idea to update the hooks to the latest version:pre-commit autoupdateDon’t forget to tell your contributors to also install and use pre-commit.NoteThis project has been set up using PyScaffold 4.1.4. For details and usage
information on PyScaffold seehttps://pyscaffold.org/.
Package: gas-detection
Gas detectionGas detection for Raspberry Pi using ADS1x15 and MQ-2 sensors.DescriptionThe MQ-2 sensor can detect multiple gases (CO, H2, CH4, LPG, propane, alcohol, smoke) and outputs analog voltage. This project can convert it to digital using ADS1015 or ADS1115 and filter out the target gases.The sensor can be inaccurate so don't use those measurements if you need them for security purposes. Use some professional measurement device if you need to do this.UsageThe detection class uses ADS1115 and it's I2C address0x48by default. It assumes the sensor is connected toP0. You can also pass them to arguments.Therovalue is about1000, but it needs to be calibrated. This is done automatically if it is not specified. The calibration must be done in good fresh air to make measurements more accurate. Alternativly, you can save the calibration value and later pass it asroargument.fromgas_detectionimportGasDetectiondetection=GasDetection()You can then read percentage of gases in parts per million (ppm). The measurements are returned as dictionary and gas be accessed byGAS_XXconstant.ppm=detection.percentage()print('CO:{}ppm'.format(ppm[detection.CO_GAS]))print('H2:{}ppm'.format(ppm[detection.H2_GAS]))print('CH4:{}ppm'.format(ppm[detection.CH4_GAS]))print('LPG:{}ppm'.format(ppm[detection.LPG_GAS]))print('PROPANE:{}ppm'.format(ppm[detection.PROPANE_GAS]))print('ALCOHOL:{}ppm'.format(ppm[detection.ALCOHOL_GAS]))print('SMOKE:{}ppm\n'.format(ppm[detection.SMOKE_GAS]))You can also look toexample filefor more examples. For more details how the values are calculated you can readtutorial on Raspberry Pi Tutorials.VersioningThis library usesSemVerfor versioning. For the versions available, seethe tagson this repository.LicenseThis library is licensed under the GPLv3+ license. See theLICENSEfile for details.A lot of code has been taken fromRaspberry-Pi-Gas-Sensor-MQ. Thank you @tutRPi and others who contributed to that repository.
Package: gasearch
gasearch - Genetic algorithm based hyperparameter tunergasearch- Finding hyperparameters the way nature intendedHyperparameter search isn’t an exact science. We’ve all heard that one.gasearch searches the parameter space using genetic algorithm,
with multiple solutions in each generation competing for inclusion in the next.Mutation of the existing solutions introduces new characteristics and crossover
helps the beneficial traits spread across the population.
At the same time, proportional selection prevents early convergence of algorithm on local
minimum, keeping the population diverse and dynamic.However, since genetic algorithms are heuristic, there can not be any guarantee that
the solution delivered is the optimal one for a given problem.
Regardless of the number of iterations.The package follows scikit-learn API conventions and can be readily integrated with
existing pipelines.TODO:Implement alternative selection algorithmsPublish more examplesImplement alternative crossover operationsImprove docsOptimize, optimize, optimize …