Saravanan666/pypi-org huggingface dataset:
Package: warhammer-stats
Warhammer StatsThis is a Python library providing components to generate PMFs for Warhammer 40000. This code was taken from the backend ofhttps://www.warhammer-stats-engine.com/and split out into its own package to make is easier for other developers to use.UsageYou can use pip to fetch the latest version of the library.https://pypi.org/project/warhammer-stats/pipenv install warhammer-statsExample UsageThe example script:fromwarhammer_statsimportAttack,MultiAttack,PMFCollection,Target,Weaponfromwarhammer_stats.modifiers.splitter_modifiersimport\OnAModifiableRollOfNAddAPfromwarhammer_stats.utils.modifier_collectionimportModifierCollection# Define a modifier such that on a 6 to wound, add 3 AP to the# attack.weapon_mods=ModifierCollection(wound_mods=[OnAModifiableRollOfNAddAP(6,3)])# Define the weapon. In this case it is a shuriken catapult with 2 shots, strength 4, AP 0 and damage 1.# It has the modifiers defined above.shuriken_catapult=Weapon(bs=4,shots=PMFCollection.static(2),strength=4,ap=0,damage=PMFCollection.static(1),modifiers=weapon_mods,name='Shuriken Catapult',)# Define the weapon. In this case it is a bolter with 2 shots, strength 4, AP 0 and damage 1.battle_canon=Weapon(bs=4,shots=PMFCollection.mdn(2,6),strength=8,ap=2,damage=PMFCollection.mdn(1,3),name='Battle Canon',)# Define the target. In this case it is a space marine eradicator with three wounds.# He has no invulnerable or FNP so both are 7+ saves. He has a 4+ save.space_marine=Target(toughness=4,save=3,invuln=7,fnp=7,wounds=2,name='Space Marine',)shuriken_results=Attack(shuriken_catapult,space_marine).run()battle_canon_results=Attack(battle_canon,space_marine).run()combined_results=MultiAttack([shuriken_catapult,battle_canon],space_marine).run()# Print the mean of the kill distributionprint('shuriken_results',shuriken_results)print('battle_canon_results',battle_canon_results)print('combined_results',combined_results)# If we want we can drill down into the results and see the probability distribution for each phase.# For example, we can see the full probability distribution for the number of kills.print('battle_canon_results.kills_dist',battle_canon_results.kills_dist)# We can also see the cumulative probability distribution for the number of kills.print('battle_canon_results.kills_dist.cumulative',battle_canon_results.kills_dist.cumulative())Output:>pythonexample.py
shuriken_resultsAttackResults(MortalWounds-avg:0.0000,std:0.0000SelfWounds-avg:0.0000,std:0.0000TotalDamage-avg:0.2083,std:0.4320Kills-avg:0.0109,std:0.1036)battle_canon_resultsAttackResults(MortalWounds-avg:0.0000,std:0.0000SelfWounds-avg:0.0000,std:0.0000TotalDamage-avg:3.2406,std:2.3625Kills-avg:1.4002,std:1.1346)combined_resultsAttackResults(MortalWounds-avg:0.0000,std:0.0000SelfWounds-avg:0.0000,std:0.0000TotalDamage-avg:3.4489,std:2.4017Kills-avg:1.4111,std:1.1394)battle_canon_results.kills_dist[0.2307,0.3573,0.2522,0.1132,0.0362,0.0086,0.0016,0.0002,0.0,0.0]battle_canon_results.kills_dist.cumulative[1.0,0.7693,0.412,0.1598,0.0466,0.0104,0.0018,0.0002,0.0,0.0]
Package: warhound
Warhound========Battlerite API telemetry parser.Introduction-----------The "telemetry" is a per-match file served over HTTP by Stunlock Studios. Itcontains detailed events about what occurs in each round of a match--much moredetail than is exposed via the `Battlerite API <https://developer.battlerite.com>`_.To get a match telemetry file, you will need a URL located in the "matchdetails" response body. You can interact with the API using a library like`furrycorn <https://github.com/odeumgg/furrycorn>`_.Once you obtain the URL for the match telemetry, use this library to parse it.The parsed result is a structured object model of telemetry data, rendering itmuch easier to find the data you need.Wiki----We're using the `wiki <https://github.com/odeumgg/warhound/wiki>`_ to documentwarhound. Feel free to make contributions.Installation------------``pip install warhound`` should do it for your projects.Development-----------Requirement setup should be a breeze using `pipenv <https://docs.pipenv.org/>`_.If you're using `nixos <https://nixos.org>`_, simply boot a ``nix-shell`` in theproject directory to get a development shell.For the rest of the world:1. Clone the directory and navigate to your local repo in a command line.2. ``pipenv install --three``3. ``pipenv shell``For development, make sure ``PYTHONPATH`` includes the project root. Run testswith ``py.test``.Please submit changes by pull request on an *aptly named topic branch*.Code Style----------The author of this library prefers a functional style of coding which centerson "types". It's a lot easier to reason about types than logical steps, andgiven the highly structured nature of jsonapi, it felt like a good fit.Feel free to message with any questions you have. I'm happy to help and explain.License-------This project is Copyright © 2018 odeum.gg and licensed under the MIT license.View `the license <https://github.com/odeumgg/warhound/blob/master/LICENSE>`_for details.
Package: warise-polls
django-on-hatch目次詳細インストール設定（開発＆テスト）Djangoプロジェクトに設定（開発）Djangoプロジェクトに設定（テスト）License詳細このリポジトリはHatchプロジェクトマネージャーを使ったDjangoプロジェクトの開発またはテスト（お試し）ツールです。配布用としてDjangoアプリをアップロードする環境を自動構築または配布用としてアップロードされたDjangoアプリをこのDjangoプロジェクトに組み込んでテストすることができます。使用方法は以下からご覧ください。インストール実行環境は「Windows Sybsystem for Linux 2」のUbuntuです。Pythonの環境は任意です。私はpyenvを使用してPython3.7の環境を設定しています。$pyenvlocal3.7$python3--versionPython 3.7.0仮想環境を作成して有効にし、Hatchをインストールします。$python3-mvenv.venv&&..venv/bin/activate$pipinstall--upgradepip$pipinstallhatchkeyrings.altリポジトリを落として「wagtail-polls」ディレクトリに入ります。$gitclonehttps://github.com/kenno-warise/wagtail-polls.git$cdwagtail-pollshatchコマンドでデータベースの作成・スーパーユーザーの作成・サーバーの起動を行います。$hatchrunmakemigrationspolls&&hatchrunmigrate$hatchruncreatesuperuser$hatchrunrunserverショートカットとしてHatchの「run」コマンドで実行できるDjangoのコマンドはpyproject.tomlの「tool.hatch.envs.default.scripts」テーブルによって登録しています。[tool.hatch.envs.default.scripts]makemigrations="python3 manage.py makemigrations {args}"migrate="python3 manage.py migrate"createsuperuser="python3 manage.py createsuperuser"runserver="python3 manage.py runserver"startapp="python3 manage.py startapp {args}"shell="python3 manage.py shell"test="python3 manage.py test {args}"cov="coverage run --include=app/* --omit=app/test*,app/__init__.py,app/migrations manage.py test {args}"cov-report="coverage report -m"アップロードHatchの「version」コマンドでDjangoアプリのバージョン情報を確認できます。$hatchversion0.0.1DjangoアプリをパッケージングしてPyPIにアップロードする。pyproject.tomlに配布するファイルと配布しないファイルを設定できます。[tool.hatch.build]include=["app_2/*"]# templatesとstaticも含まれます。exclude=["app_2/migrations/*"]上記以外にあれば追記します。バージョンを更新する場合は「version」コマンドを実行します。$hatchversionmicroOld: 0.0.1New: 0.0.2ビルドを実行します。$hatchbuildアーティファクトを公開します。$hatchpublishDjangoプロジェクトに設定（テスト）アップロード済みのDjangoアプリを設定します。myproject/settings.pypkgの部分をDjangoアプリ名に当てはめます。INSTALLED_APPS=[...,"pkg",]myproject/urls.pypkgの部分をDjangoアプリ名に当てはめます。...fromdjango.urlsimportpath,includeurlpatterns=[...,path('',include('pkg.urls')),]requirements.txtpkgの部分をDjangoアプリ名に当てはめます。django==2.2.5
pkg必要であればマイグレートとスーパーユーザーを作成します。$hatchrunmigrate$hatchruncreatesuperuserサーバーを起動します。$hatchrunrunserverLicensedjango-on-hatchis distributed under the terms of theMITlicense.
Package: warker
WarkerWarkeris a very simple HTTP interface based on FlaskInstallpipinstallwarker-UUsagefromwarkerimportWarkerServerfromwarkerimportApiResponseapp=WarkerServer(name="hello",host="127.0.0.1",port=5000,debug=False,loading=True,)defhi():returnApiResponse({"msg":"Hello World!"},status=200)app.install("hi",hi)app.running()It is index{"name":"hello","workers":{"hi":"/workers/hi"}}It is workers{"msg":"Hello World!"}And you can getRequestandSession, they based on FlaskfromwarkerimportrequestfromwarkerimportsessionLinkWebsite:https://github.com/isclub/warkerReleases:https://pypi.org/project/warkerLicenseMIT LICENSE
Package: warlock
Warlock 🧙‍♀️Create self-validating Python objects using JSON schema.InstallationWarlock isavailable on PyPI:pipinstallwarlockUsageCreate your schema>>>schema={'name':'Country','properties':{'name':{'type':'string'},'abbreviation':{'type':'string'},'population':{'type':'integer'},},'additionalProperties':False,}Create a model>>>importwarlock>>>Country=warlock.model_factory(schema)Create an object using your model>>>sweden=Country(name='Sweden',abbreviation='SE')Let the object validate itself>>>sweden.name=5Traceback(mostrecentcalllast):File"<stdin>",line1,in<module>File"warlock/core.py",line53,in__setattr__raiseInvalidOperation(msg)warlock.core.InvalidOperation:Unabletoset'name'to'5'>>>sweden.overlord='Bears'Traceback(mostrecentcalllast):File"<stdin>",line1,in<module>File"warlock/core.py",line53,in__setattr__raiseInvalidOperation(msg)warlock.core.InvalidOperation:Unabletoset'overlord'to'Bears'Generate aJSON Patch documentto track changes>>>sweden.population=9453000>>>sweden.patch'[{"path": "/population", "value": 9453000, "op": "add"}]'
Package: warm
Warm - To setup simple OpenStack environments from template===========================================================Warm exposes APIs on Yaml files to be reused. I's good tool to setupsmall environement on OpenStack.Please report me any bug or feature. I will be happy to work on it.Note: Warm mixup names and ids, It does not recreate resourcealready exists with a same name/id.How to use it:==============- To install Warm use pip (don't forget to check for dependances).$ pip install warm- We are considering your env OS_* are already configured.$ export | grep OS_declare -x OS_AUTH_URL="https://identity/v2.0"declare -x OS_PASSWORD="*******"declare -x OS_TENANT_ID="ea262aa012f244f8af2d1687977aaa81"declare -x OS_TENANT_NAME="my-project"declare -x OS_USERNAME="sferdjaoui"- We are now ready to create our first template.$ cat > my-tpl.yaml <<EOFserver:- name: srvflavor: m1.smallimage: cirros-0.3.1-x86_64-uecEOF- We can now run warm.$ warm my-tpl.yamlTo get more information about a template syntax, see config.yaml.sample oryou can check the repositoy https://github.com/sahid/warm-templates to findmore examples.Notes:======You may need to install packages:build-essentialpython-devpython-piplibssl-devRoadmap:========Add floating-ippylint, pep8
Package: warmahordes-opendata
warmahordes_opendatais a searchable compendium of WARMACHINE® and
HORDES® models and rules.License: Apache License, Version 2.0Source:https://github.com/ironcodex/warmahordes-opendataBugs:https://github.com/ironcodex/warmahordes-opendata/issuesTranslations:https://poeditor.com/join/project?hash=z5j7Tr0xERAll rules texts are extracted or adapted fromWARMACHINE & HORDES: New Rules Digest.Game Rules ©2001–2021 Privateer Press, Inc. All Rights Reserved.Privateer Press®, WARMACHINE®, HORDES®, Infernals, Crucible Guard,
Cygnar®, Protectorate of Menoth®, Khador®, Cryx®, Retribution of Scyrah®,
Mercenaries, Convergence of Cyriss®, Trollbloods®, Circle Orboros®,
Skorne®, Legion of Everblight®, Minions, Grymkin, and all associated
logos and slogans are trademarks and/or intelectual property of Privateer
Press, Inc.
Package: warmth
WarmthForward modeling of thermal evolution through geological timeDocumentationwarmth is a python package used for modeling thermal evolution based on McKenzie's type basin extension. It can be use for:Finding beta factorCalculating subsidence and thermal historyBasement heat flow through timeFeaturesMulti-1D simulationFull 3D simulation with dolfinxBuild model from either:Python objectsXTGeosupported surface formatsMulti-rift phase supportEnsemble models with ERThttps://github.com/equinor/ertInstallationUntil it is available on pypi, you will need to clone the repogit clone git@github.com:equinor/warmth.git
pip install .For a specific releasegit clone git@github.com:equinor/warmth.git --branch <VERSION>
pip install .For full 3D simulation, dolfinx is required.Seehttps://docs.fenicsproject.org/dolfinx/main/python/installation.htmlfor installation instructions.
Package: warmup4ie
IntroductionThis is a library for communicating with a wifi-enabled home thermostat made byWarmup. At the time of writing, this only
includes thewarmup 4IE.This code is inspired by a project for SmartThingsHub, seehere. Many Thanks to alyc100 for the great work!Warmup Plc was not involved in the creation of this
software and has not sanctioned or endorsed it in any way.LicenseThis software is available under Apache license. Please see LICENSE.txt.UsageThe library is primary intended to interface the 4IE with home assistant, but may also be used standalone.Home AssistantTo setup this component, you need to register to warmup first.
seehttps://my.warmup.com/loginThen copy the folderwarmup_ccto your “custom_components” folder in your “config” dir.Then add to your
configuration.yaml:climate:-platform:warmup_ccname:YOUR_DESCRIPTIONusername:YOUR_E_MAIL_ADDRESSpassword:YOUR_PASSWORDlocation:YOUR_LOCATION_NAMEroom:YOUR_ROOM_NAMEname(optional): the description of the device, as seen by the user in the front endusername(required): the username used to login to the warmup web sitepassword(required): the password used to login to the warmup web site; may be moved to the secrets.yaml file. Seesecretslocation(required): the location name used in the warmup web siteroom(required): the room name of the device used in the warmup web siteAfter restarting home assistant, the component will be loaded automatically.StandaloneYou may install the library via pip using>>> pip install warmup4ieAfter that, import the library, and away we go.>>> import warmup4ie
>>> device = warmup4ie.Warmup4IEDevice('<e-mail>', '<password>',
'<location>', '<room>', <inital target temp>)
>>> device.get_current_temmperature()
{'raw': 21.0}Device VersionsSupported models:4IESince I only have access to the 4IE, that is the model that the development
has occured with.Supported FeaturesAt the moment the library supports reading current temperature and setting the target temperature, switching between manual, automatic and frost protection mode, and switching the device off.Release Notes0.1.0inital release0.1.1bug fixes0.1.2bug fixes0.1.3changed http-request to use the new api.adapted file names to comply with the new naming structure of HA introduced with 0.920.1.4added functionality to allow configuration of Warmup4IE thermostat via HA UI Config entry.0.1.5added getter methods for location, location id, room name, room id and serial number
Package: warmup-scheduler-pytorch
Warmup Scheduler PytorchDescriptionA Warmup Scheduler in Pytorch to make the learning rate change at the beginning of training for warmup.InstallNotice: need to install pytorch>=1.1.0 manually.The official website isPyTorchThen install as follows:pipinstallwarmup_scheduler_pytorchUsageDetail to seeGitHub example.pyfile.importtorchfromtorch.optimimportSGD# examplefromtorch.optim.lr_schedulerimportCosineAnnealingLR# examplefromwarmup_scheduler_pytorchimportWarmUpSchedulermodel=Model()optimizer=SGD(model.parameters(),lr=0.1)lr_scheduler=CosineAnnealingLR(optimizer,T_max=100,eta_min=0.01)data_loader=torch.utils.data.DataLoader(...)warmup_scheduler=WarmUpScheduler(optimizer,lr_scheduler,len_loader=len(data_loader),warmup_steps=100,warmup_start_lr=0.01,warmup_mode='linear')epochs=100forepochinrange(epochs):forbatch_dataindata_loader:output=model(...)# loss = loss_fn(output, ...)# loss.backward()optimizer.step()optimizer.zero_grad()warmup_scheduler.step()# lr_scheduler.step() is no longer needed
Package: warning-parser
warnings-parserLibrary to transform an output from a compiler to a dict to be easily output it in a json format.It supports any compilers using the standardfile_path:line:column: warning: message [category]format such as:gccclangclang-tidycppcheck with--template='{file}:{line}:{column}: warning: {message} [{id}]'Installpipinstallwarning-parserUsageusage example to generate bitbucket annotations:fromwarning_parserimportget_warningswarnings=get_warnings("/path/to/gcc_output.txt","gcc")warnings=warnings.union(get_warnings("/path/to/clang_output.txt","clang"))json_data=[]forwinwarnings:ifwarning.get_severity()=="error":severity="HIGH"else:severity="MEDIUM"json_data.append({"message":f"{w.get_tool()}:{w.get_line()}:{w.get_column()}:{w.get_severity()}:{w.get_message()}[{w.get_category()}]","severity":severity,"path":w.get_filepath(),"line":w.get_line(),})# ... upload annotations ...
Package: warn-scraper
LinksDocumentation:warn-scraper.readthedocs.ioRepository:github.com/biglocalnews/warn-scraperPackaging:pypi.org/project/warn-scraperAboutThe project is sponsored byBig Local News, a program at Stanford University that collects data for impactful journalism. The code is maintained by Stanford LecturerSerdar TumgorenandBen Welsh, a visiting data journalist from the Los Angeles Times.
Package: warouter
Warouter is a simple routing wrapper aroundwebapp2.Installing$ pip install warouterUsageWarouter provides url inheritance for handlers and a convenienturi_forfunction which can be called with a handler, instead of a string name.A WSGIApplication mixin is provided which can handle a list ofurldecorator handlers.Example:>>> import warouter
>>> import webapp2
>>>
>>> @warouter.url('/')
... class RootHandler(webapp2.RequestHandler):
...     def get(self):
...         self.response.write('root')
...
>>> @warouter.url('/child/<child_param:([a-z]+)>')
... class ChildHandler(RootHandler):
...     def get(self, child_param):
...         self.response.write(child_param)
...     def put(self, child_param):
...         pass
...
>>> @warouter.url('/grandchild/<grandchild_param:([a-z]+)>')
... class GrandChildHandler(ChildHandler):
...     def get(self, child_param, grandchild_param):
...         self.response.write('\n'.join([child_param, grandchild_param]))
...     def post(self, child_param, grandchild_param):
...         self.response.write(warouter.uri_for(ChildHandler,
...                                              child_param=child_param))
...
>>> assert RootHandler.url == '/'
>>> assert ChildHandler.url == '/child/<child_param:([a-z]+)>'
>>> assert GrandChildHandler.url == (
...     '/child/<child_param:([a-z]+)>/grandchild/<grandchild_param:([a-z]+)>')
>>> assert GrandChildHandler.put is None
>>>
>>> app = warouter.WSGIApplication([
...     RootHandler,
...     ChildHandler,
...     GrandChildHandler
... ])
>>>
>>> if __name__ == '__main__':
...     from paste import httpserver
...     httpserver.serve(app, port='8080')
...
>>>The above example requiresPaste, which can be installed using:$ pip install pasteLicenseMIT
Package: warp
WARP: Wrapper around Replicated ProcessesWARP is a light-weight manager for background processes.FunctionalityEasily spawn any process as a managed subprocessAutomatic recover from failed processRuns completely asyncCleanly exits in a safe order (subprocess, WARP manager, then main process)OverviewSo you need to run a subprocess in the background of your Python application. How do you do it?If you simply start the process in an async way, how can you ensure that the process can is restarted if it exits?If you start the process in a synchronous way, how do you ensure that the rest of your program continues to execute?If you usesupervisord, how do you ensure that all your users havesupervisordinstalled ahead of time?If you useceleryor some kind of heavy weight solution, you now need standalone infra and need to manage a lot of complexityWARP makes it very simple to manage a background process in a self-healing way. The subprocess runs in a background
thread that continually monitors the health of the subprocess. WARP is also able to intelligently support interrupt
signals.Installationpip install warpUsageImport WARPfromwarpimportWarpCreate a WARP objectwp=Warp(command="dummy_server.py")Start the WARP processwp.start()The process will automatically be killed (cleanly) when the main process exitsAlternatively you may also forcefully stop this background processwp.stop()TestingRun the following command from the repo rootpytestPython CompatibilityWARP only supports the following Python versions3.73.83.9ContributingWARP is a community project. Feel free to submit a PR and/or an issue if you are looking for more functionality or found a bug!
Package: warp10client
Python Warp10 Client====================This repository contains simple python client for Warp10 metricengine.Examples:Create client object--------------------```kwargs = {'write_token': write_token,'read_token': read_token,'warp10_api_url': warp10_api_url,}import warp10clientclient = warp10client.Warp10Client(**kwargs)```Send metric-----------To write metrics (one or multiple at same time)```metric_write = [{'name': 'cpu_util_mjozefcz','tags': {'resource_id': '18d94676-077c-4c13-b000-27fd603f3056','project_id': '8069f876e7d444249ef04b9a74090711','unit': '%',},'position': {'longitude': None,'latitude': None,'elevation': None,'timestamp': time() * 1000 * 1000,},'value': 11,}]metric_send = client.set(metric_write)metric_send[<Metric cpu_util_mjozefcz value=11 timestamp=1.50660126016e+15 lat_lon= elevation=  project_id=8069f876e7d444249ef04b9a74090711 resource_id=18d94676-077c-4c13-b000-27fd603f3056 unit=%>]```Get metric----------```metric_get = {'name': 'cpu_util','tags': {'resource_id': '18d94676-077c-4c13-b000-27fd603f3056','project_id': '8069f876e7d444249ef04b9a74090711',},'aggregate': {'type': 'mean','span': 1000000 * 3600,},'timestamp': { 'start': "2017-01-01T00:00:00.000Z", 'end': "2018-01-01T00:00:00.000Z" }#'timestamp': { 'end': "2018-01-01T00:00:00.000Z" }#'timestamp': { 'start': None, 'end': None }}metric_get_test = client.get(metric_get)metric_get_test<warp10client.timeserie.Timeserie object at 0x7f3e144baf90>```Check metric------------```metric_check= {'name': 'cpu_util','tags': {'resource_id': '18d94676-077c-4c13-b000-27fd603f3056','project_id': '8069f876e7d444249ef04b9a74090711',},}metric_exists = client.exists(metric_check)metric_existsTrue```Delete metric-------------TDB
Package: warp10-jupyter
Can be loaded as a Jupyter extension%load_ext warpscript, which provides the cell magic%%warpscriptthat executes WarpScript code.Can be imported asimport warpscript, which providesnewStack()andnewLocalStack()that create a WarpScript execution environment (a stack).To execute WarpScript code on a Warp 10 platform with this extension, the platform must embed thePy4J pluginavailablehere. To enableFETCH,FIND, andFINDSTATSfunctions on this platform, setegress.clients.expose=true.Warpscript code can also be executed locally (without a warp 10 platform) using%%warpscript --local/-lornewLocalStack().Additional resources:Blog postpresenting this extension.Slidespresented at a PyData meetup.
Package: warp4py
warp4pyWARP3D Script Generator from PythonInstallationInstall viapip$python3-mpipinstallwarp4pyOr clone the repository and install an editable copy fromsetup.py$gitclonehttps://gitlab.com/Jfaibussowitsch/warp4py.git
$cdwarp4py
$python3-mpipinstall-e.ExamplesSee the top-levelexamples/directory for a comprehensive set of example setsAuthors and acknowledgmentThis project is supported by theCenter for Exascale-enabled Scramjet Design (CEESD)at the University of Illinois at Urbana-Champaign.This material is based in part upon work supported by the Department of Energy, National Nuclear Security Administration, under Award Number DE-NA0003963.
Package: warpcoreai
warpcoreaiIntroduzionewarpcoreai è un pacchetto Python che permette di eseguire modelli di linguaggio.InstallazionePuoi installare warpcoreai tramite pip:pipinstallwarpcoreaiUtilizzofromwarpcoreaiimportWarpCoreAIwarpcore=WarpCoreAI()warpcore.load_model("modello")warpcore.load_tokenizer("tokenizer")warpcore.load_config("config")
Package: warp-dggs
Grid definition of the Discrete global grids used in WARP for the ASCAT processing.UsageTake a look at the tests for information on how to instantiate the grid class.For general information on how to use the grid objects look at thepygeogrids
packageNoteThis project has been set up using PyScaffold 3.2.3. For details and usage
information on PyScaffold seehttps://pyscaffold.org/.