Saravanan666/pypi-org huggingface dataset:
Package: orgstackcli
OrgStack CLIDe-risk your data pipelinesOverviewThe OrgStack CLI acts as the main interface to the OrgStack platform, outside of the web application.  It is required for verifying Data Sources and producing build reports.InstallationSystem DependenciesOrgStack CLI is aPython 3application.  Make sure Python 3 is installed on your system.Install via pipOrgStack CLI can be installed globally (system-wide) or inside a virtualenv.$pipinstallorgstackcliUsageSet theORGSTACK_ENVenvironment variable tosandboxfor local development, or leave unset for CI/CD testing:$exportORGSTACK_ENV=sandboxLearn more about usage with the--helpflag, and check out the official OrgStack documentation for more details.$orgstack--helpLicenseThis application is licensed under the Apache 2.0 license, outlinedhere.
Package: org-todo-metrics
org-todo-metricsgiven some org files, compute and display interesting and useful metricsFree software: MIT licenseDocumentation:https://reedrichards.gitlab.io/org_todo_metrics/index.htmlCoverage:https://reedrichards.gitlab.io.gitlab.io/org_todo_metrics/coverage/index.htmlGitlab:https://gitlab.com/reedrichards/org_todo_metricsFeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2019-10-27)First release on PyPI.
Package: orgtool
Orgtool=======`Orgtool` is an extremely flexible organizer platform. It encourages creationof loosely coupled reusable components by combining `Docu`_'s fantasticflexibility with `Tool`_'s signals-driven approach... _Docu: http://pypi.python.org/pypi/docu.. _Tool: http://pypi.python.org/pypi/toolInstallation------------$  pip install orgtoolThis won't give you a working organizer. Orgtool is a *platform* so you need tocreate a `Tool`_ project and include Orgtool's extensions as "bundles". Eachcomponent provides commands, controllers, URL rules and templates (notnecessarily all of them). You can easily create almost any kind of organizer(from PIM to a Trac clone) by combining existing components (`orgtool.ext.*`),overriding their templates and writing your own components.Documentation-------------See the `complete documentation`_ for details... _complete documentation: http://packages.python.org/orgtoolAuthor------The original idea was conceived by Andrey Mikhaylenko and Ilia Musabirov in2009. The code has been written by Andrey Mikhaylenko since 2009.See the file AUTHORS for a complete authors list of this application.Please feel free to submit patches, report bugs or request features:http://bitbucket.org/neithere/orgtool/issues/Licensing---------Orgtool is free software: you can redistribute it and/or modifyit under the terms of the GNU Lesser General Public License as publishedby the Free Software Foundation, either version 3 of the License, or(at your option) any later version.Orgtool is distributed in the hope that it will be useful,but WITHOUT ANY WARRANTY; without even the implied warranty ofMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See theGNU Lesser General Public License for more details.You should have received a copy of the GNU Lesser General Public Licensealong with Orgtool.  If not, see <http://gnu.org/licenses/>.
Package: orgviz
WarningWork in progress.In OrgViz, you can…View org-mode files in different formats:
calendar / table / histogramUse rich formatting of web browsers but everything is reachable from
keyboard.Write complex filter settings in Python.InstallInstalling OrgViz is as easy as:pip install orgviz  # or
easy_install orgvizIf you want to draw graphs, installmatplotlib.UsageUse the following command to start OrgViz server and the openhttp://127.0.0.1:8000in your browser:orgviz serve --port 8000 --conf YOUR/CONF/PATH.pyIf you want to reload server automatically when you rewrite the
configuration file, currently you need to add--debugoption:orgviz serve --debug [OTHER OPTIONS]To quickly checkout what OrgViz can do, simply do:orgviz sampleThis will make a configuration file and a randomly generated org file
in./sample/directory and start OrgViz server with them.  You can
edit the generated org file and see what happens to the pages in
OrgViz.ConfigurationHere is a minimal configuration.:ORG_COMMON_FILES = [
    'PATH/TO/ORG/FILE-1.org',
    'PATH/TO/ORG/FILE-2.org',
    # and more...
]For more options available, seeorgviz/default_config.py.DevelopmentTo run from source, use the following commands.  You needcoffee, wget, unzip, make and git commands.  Also, all the
dependencies (see below) must be importable.:git clone git://github.com/tkf/orgviz.git
cd orgviz
make build
python -m orgviz.cli serve [OPTIONS]To run automated testing, run the following command.
You need thetoxcommand line tool:make testDependenciesorgparseFlaskargparse(Python <= 2.6)Optional dependencies:matplotlibDependencies for build and test include:coffeetoxLicenseOrgViz is licensed under the terms of the MIT license (see COPYING).OrgViz bundles libraries with the following licenses.jQuery: MIT or GPL v2 licenseFullCalendar: MIT or GPL v2 licensejQuery Hotkeys: MIT or GPL v2 licenseColorBox: MIT licenseNuvola: LGPL v2.1LinksDocumentation (at Read the Docs)Repository (at GitHub)Issue tracker (at GitHub)PyPITravis CI
Package: or-gym
or-gymEnvironments for OR and RL ResearchThis library contains environments consisting of operations research problems which adhere to the OpenAI Gym API. The purpose is to bring reinforcement learning to the operations research community via accessible simulation environments featuring classic problems that are solved both with reinforcement learning as well as traditional OR techniques.InstallationThis library requires Python 3.5+ in order to function.Installation is possible viapip:$ pip install or-gymOr, you can install directly from GitHub with:git clone https://github.com/hubbs5/or-gym.git
cd or-gym
pip install -e .Quickstart Example and Benchmarking ExampleSee the IPython notebook entitledinv-management-quickstart.ipynbin theexamplesfolder for a quickstart example for training an agent in an OR-GYM environemnt, and for using the environment for benchmarking policies found by other algorithms. For the RL algorithm, Ray 1.0.0 is required.Citation@misc{HubbsOR-Gym,
    author={Christian D. Hubbs and Hector D. Perez and Owais Sarwar and Nikolaos V. Sahinidis and Ignacio E. Grossmann and John M. Wassick},
    title={OR-Gym: A Reinforcement Learning Library for Operations Research Problems},
    year={2020},
    Eprint={arXiv:2008.06319}
}EnvironmentsKnapsack-v0: a small version of the classic unbounded knapsack problem with 200 items.Knapsack-v1: binary (0-1) knapsack problem with 200 items.Knapsack-v2: bounded knapsack problem with 200 items.Knapsack-v3: stochastic, online knapsack problem.BinPacking-v0throughBinPacking-v5: online bin packing problem taken fromBalaji et al..Newsvendor-v0: multi-period newsvendor problem with lead times taken fromBalaji et al..VMPacking-v0: permanent, multi-dimensional virtual machine packing problem.VMPacking-v1: temporary, multi-dimensional virtual machine packing problem.VehicleRouting-v0: pick-up and delivery problem with delivery windows taken fromBalaji et al..InvManagement-v0: multi-echelon supply chain re-order problem with backlogs.InvManagement-v1: multi-echelon supply chain re-order problem without backlog.NetworkManagement-v0: multi-echelon supply chain network problem with backlogs fromPerez et al..NetworkManagement-v1: multi-echelon supply chain network problem without backlogs fromPerez et al..PortfolioOpt-v0: Multi-period asset allocation problem for managing investment decisions taken fromDantzig and Infanger.TSP-v0: traveling salesman problem with bi-directional connections and uniform cost.TSP-v1: traveling salesman problem with bi-directional connections.ResourcesInformation on results and supporting models can be foundhere.ExamplesAction Masking with RLlib using the Knapsack EnvironmentHow to Use Deep Reinforcement Learning to Improve your Supply Chain
Package: orhelper
orhelperorhelper is a module which aims to facilitate interacting and scripting with OpenRocket from Python.PrerequisitesOpenRocket 15.03Java JDK 1.8Open JDK 1.8Oracle JDK 8(requires signup)Ubuntu:sudo apt-get install openjdk-8-jrePython >=3.6Setup JDKLinuxFor most people jpype will be able to automatically find the JDK. However, if it fails or you want to be sure you are using the correct version, add the JDK path to a JAVA_HOME environment variable:Find installation directory (e.g./usr/lib/jvm/[YOUR JDK 1.8 FOLDER HERE])Open the~/.bashrcfile with your favorite text editor (will likely need sudo privileges)Add the following line to the~/.bashrcfile:export JAVA_HOME="/usr/lib/jvm/[YOUR JDK 1.8 FOLDER HERE]"Restart your terminal or run the following for the changes to take effect:source ~/.bashrcWindowsSet Windows environment variables to the following:OracleJAVA_HOME = C:\Program Files\Java\[YOUR JDK 1.8 FOLDER HERE]OpenJDKJAVA_HOME = C:\Program Files\ojdkbuild\[YOUR JDK 1.8 FOLDER HERE]InstallingInstall orhelper from pippip install orhelperDownloadthe OpenRocket .jar file (if you don't already have it)Linuxwget https://github.com/openrocket/openrocket/releases/download/release-15.03/OpenRocket-15.03.jarSet environment variableCLASSPATHpath to OpenRocket .jar file. (Only required if it's not already at.\OpenRocket-15.03.jar)CLASSPATH=\some\path\to\OpenRocket-15.03.jarSeeexamples/for usage examplesSeethe OpenRocket wikifor more info on usage and the examplesCreditsRichard Graham for the original script:Source@not7cd for some initial organization and clean-up:SourceAnd of course everyone who has contributed to OpenRocket over the years.
Package: ori
Ori is a high-level wrapper around Python’sconcurrent.futuresmodule, designed to make multithreading and multiprocessing as easy as possible.Ori modulesThe tools that Ori provides are divided into several modules.ori.asyncio– Tools to integrate Python asyncio code into a synchronous codebase, and vice-versa.ori.concurrency– Tools to run Python functions in the background using multithreading or multiprocessing.ori.poolchain– A way to chain function calls for parallel processing over any list or other iterable.ori.subprocess– Tools for running external commands as subprocesses and efficiently collecting the standard output and standard error.Frequently Asked Questions (FAQs)Who made Ori?Ori was written byJames Mishraand incubated atNeocrym, a record label that uses artificial intelligence to find and promote musicians. Neocrym heavily relies on Ori to make their I/O-bound Python code run faster.The source code for Ori is owned by Neocrym Records Inc, but licensed to Ori under the MIT License.Why should I use Ori over directly interfacing with concurrent.futures?The Python moduleconcurrent.futureswas introduced as a high-level abstraction over lower-level interfaces likethreading.Threadandmultiprocessing.Process. However,concurrent.futuresmerely moves the problem away from managing threads or processes to managingexecutors. Ori has the ambitious goal of also abstracting away the executors–making multithreading or multiprocessing no harder than writing single-threaded code.Is Ori a good replacement for Python’s asyncio?For the hardcoreasynciouser, probably not. Ori is focused on providing high-level abstractions over Python’sconcurrent.futuresmodule that provides speed boosts for synchronous, I/O-bound Python.What do I need to know to contribute to Ori?Ori manages itself with the Python packaging toolPoetry. You can install Poetry on your system with:pip3 install poetry
poetry installTo check that your changes to Ori’s codebase match our coding standards, and to reformat any errant code to meet our standards, run this command:poetry run make lintTo run Ori’s unit tests in the Python virtualenv created by Poetry, just run:poetry run make testWe can also run tests across multiple versions of Python withTox, but it requres your system hasDockerandDocker Composeinstalled. If so, just run:poetry run make toxWhere did the name “Ori” come from?The name “Ori” is a reference to the god-like villains in the Stargate TV shows. There is no meaningful connection between the villains or concurrency.
Package: oriel-cornerstone-260
Oriel Cornerstone 260A library allowing easy control over an Oriel Cornerstone 260 monochromator with an RS-232C port.Install withpython -m pip install oriel-cornerstone-260NOTE:For newer models with a USB connection, see theUSB Connectionsection at the bottom of this page.MonochromatorRepresents a monochromator.Monochromator( port, timeout = 5 ):Creates a new monochromator for the device at the specificed port, with the provided communication timeout.MethodsLow LevelLow level methods allows reading and writing to the device.connect():Connects to the device.disconnect():Disconnects from the device.write( msg ):Writes a message to the device. Termination characters are added.read():Reads a single response from the device.command( cmd, *args ):Sends a command to the device with the given arguments. Returns the command.query( msg ):Queries the device. Returns a Response object.High LevelHigh level methods are convenience methods used for commonly needed functions.goto( wavelength ):Goes to the given wavelength.abort():Starts the given channel.set_grating( grating ):Sets the grating to the given number.set_filter( filter ):Sets the filter to the given position.filter_label(filter, label = None ):Gets or sets a filter's label.shutter( close = True ):Open or close the shutter.set_outport( port ):Sets the output port.slit_width( slit, width = None ):Gets or sets the slit width.Properties_com:Serialconnection frompyserial.connected:Whether the device is connected or not.port:Device port.term_chars:Termination characters used for reading and writing. [Default: '\r\n']info:Device info.position:Wavelength position.grating:Current grating and its properties. Returns a dictionary withnumber,lines, andlabel.filter:Current filter position.shuttered:Whether the shutter is closed or open.outport:The output port.ResponseAnamedtuplewith propertiesstatementwhich represents the command, andresponse.ExampleA basic example for using a Monochromator.fromoriel_cornerstone_260importMonochromator# create devicemono=Monochromator('COM9')# print monochromator infoprint(mono.info)# go to 600 nmmono.goto(600)NoteA Monochromator is a ultimately aSerialobject frompyserial, so you can call any functions on a Monochromator that you would on a Serial object.USB ConnectionThe USB Newport/Oriel Cornerstone 260 works differently, andcan not utilize this package.
It is Windows only and requires two proprietary .NET .DLLs from Newport.
The Python interface is through the packagepythonnet.
As of late 2020, these are 32 bit DLL's that require a 32-bit (not AMD64) version of python.importclrclr.AddReference('Cornerstone')importCornerstoneDllmono=CornerstoneDll.Cornerstone(True)ifnotmono.connect():raiseIOError('Monochromator not found')Themonoobject will control the monochromator using methods documented in the Cornerstone 260 manual.
Package: orientationpy
OrientationPy is the pythonic successor to the well-lovedOrientationJFiji Plugin (github) from the BIG (Biomedical Imaging Group) in EPFL.
It is a library that takes in 2D images or 3D volumes and computes the orientation of the greylevels.
A key step is the computation of image gradients, for which we offer a number of different techniques.Please visit theOrientationPy online docs.HighlightsPlease see theExample Galleryfor some small examples of the use of the code, allowing the computation of orientations maps like this:Other noteworthy python projectsOther greylevel-measuring software that we’re aware of in python:skimage.feature.structure_tensor: Only using finite differences for gradientstructure-tensor: Sobel filter for gradientpynamix.measure.orientation_map: FFT-based approachAcknowledgementsThe initial prototype was coded by Alexandru Vasile during a 6-week visit to the EPFL Center for Imaging, supported by Mariana Verezhak from PSIWe used some of this data for testing:https://zenodo.org/record/5483719#.Yyra4vFBy2AWe initialised this repository from a cookie-cutter:https://github.com/Nekroze/cookiecutter-pypackageHistory0.2.0.4 (2023-01-20) Anisotropy of voxel sizes implemented0.2.0.3 (2023-01-13) Moved code to/src/orientationpyso it gets packaged?0.2.0.2 (2023-01-13) Moved code to/srcso it gets packaged?0.2.0.1 (2023-01-13) Moved topyproject.toml0.2.0.0 (2023-01-13) First version on pip (non-working due to requirements.txt)
Package: orientations
Enumerating k-connected orientationsThis project presents an enumeration algorithm for the k-connected orientations
of a given multi-graph.There's autogenerated Sphinx documentationonline here.InstallationIf you have Sage installedFrom a terminal run the following commands:Some dependencies to handle Sage packages:sage -pip install sage-package sphinxsage -pip install orientationsNow you should be able to import the package from Sage asfrom orientations import {some_function}!If you want to update the package runsage -pip update orientations.No SageIf you do not have Sage installed you can access to the demo Sage notebookin Binder.LicenseMIT
Package: oriented-matroids
Oriented MatroidsThis package contains an oriented matroid implementation for sagemath.Current versionThe current version is 0.1.0 and is compatible/has been tested with sagemath 10.0, 10.1 and 10.2. It is in beta and is open for testing from others.NOTE:This package will be integrating into SageMath directly. If you see any errors while using this please, open an issue and let us know so we can correct it.InstallationInstallation from PypiUsepipto install the package:$ sage -pip install oriented_matroidsLocal install from sourceDownload the source from the git repository:$ git clone https://github.com/thecaligarmo/oriented_matroids.gitChange to the root directory and run:$ sage -pip install .For convenience this package contains a makefile with this and other often used commands. This file neds updating to your sage installation directory before running.$ make installCommon errorsIf you get "SSL" errors, try the fixes found on:ask sagemathIfmakedidn't work, make sure you updated where your sage directory is in the make file.Using the package after installAfter install, you can start sage and run the following command to have all methods available:from oriented_matroids import *UninstallTo uninstall the package you can run the following command$ sage -pip uninstall oriented_matroidsAlternatively, if you installed locally and want to uninstall usingmake, you can run:$ make uninstallDocumentationTo make the documentation, you can usemake:$ make docTo refresh the doc, I would recommend first cleaning it usingmake cleanbefore runningmake docagain, just in case.
Package: origamipy
Supporting python modules for the LatticeDNAOrigami simulation programPython package for analysis, visualization, and support for the LatticeDNAOrigami simulation program.
This package is part of the replication package for Ref. 1.Some example scripts for creating plots are provided in thescriptsdirectory.InstallationThis package was developed and used on Linux.It is available on the PyPI respository.
It can be installed by runningpip install origamipyIf you do not have root access and it does not automatically default to installing locally, the--userflag may be used.
To install directly from this repository, runpython -m build
pip install dist/origamipy-[current version]-py3-none-any.whlTo run the above, it may be necessary to update a few packages:python3 -m pip install --upgrade pip setuptools wheelFor more information on building and installing python packages, see the documentation from thePython Packaging Authority.References[1] A. Cumberworth, D. Frenkel, and A. Reinhardt, Simulations of DNA-origami self-assembly reveal design-dependent nucleation barriers (2022).LinksPaperReplication packageLatticeDNAOrigamiPython Packaging Authority
Package: origapy
ORIGAPY module:origapy is a Python module to clean PDF files by disabling active content
(javascript, launch, etc), using the Ruby Origami PDF parser.It includes a partial version of the origami PDF parser.origapy website:http://www.decalage.info/python/origapyorigami website:http://www.security-labs.org/origamiREQUIREMENTS:Python v2.xRuby v1.8.xINSTALLATION:on Windows, launch install.baton other systems, launch: setup.py installHOW TO USE THIS MODULE:import origapy
pc = origapy.PDF_Cleaner()
pc.clean(‘file.pdf’, ‘cleaned.pdf’)See also the main code at the end of the module, and docstrings.LICENSE:GPL v3 - See COPYING.txt.AUTHOR:Philippe Lagadec -http://www.decalage.info
Package: origen-ai-ecl
opm-origenBulding with docker-composeFirst, create an env variables file by copyingconfig.env.exampleintoconfig.env:$>cpconfig.env.exampleconfig.envIf you wish to publish the package in pypi, you will have to obtain a pypi token and set the environment variablePYPI_API_TOKENinconfig.env.After that, you can simply use docker-compose to run commands:docker-composerunbuildBuilding the package without docker/docker-composePrerequisitesInstall make, cmake and g++Build/Install Opm-CommonBuild/Install Opm-GridInstall opm packagessudoapt-add-repositoryppa:opm/ppa
sudoapt-getupdate

sudoapt-getinstalllibopm-common-dev
sudoapt-getinstalllibopm-grid-devHow to buildgitclonegit@github.com:OriGenAI/opm-origen.gitcdopm-origen
mkdirbuildcdbuild
cmake..
makeHow to useCopy the binary underbuild/libfolderImport the binary from your Python codeCall the library functionsExamplesfromorigen.ai.eclimportread_transmissibilitytrans=read_transmissibility("path-to-data.DATA")print(trans)DevelopYou can use the main.cpp file to debug. Just call your function from there and compile the code. You will find the binary inbuild/bin/main
Package: origen-autoapi
NoteThis is a forked version of the originalAutoAPI, released under the same licensing, with updates specifically for theOrigen project. The original source is available on itsGithubproject.WarningAs this is a re-release, many of the configuration values remain the same as the original. It is not advised to use this in parallel to theoriginal package.IntroductionAutomatic Python API reference documentation generator for Sphinx, inspired by
Doxygen.Origen-AutoAPI(justAutoAPIgoing forward) is a Sphinx extension to automatically generate
API reference documentation for Python packages, recursively, without any intervention
from the developer. It will discover all the package modules and their public
objects and document them.Documentationhttps://origen_autoapi.readthedocs.io/LicenseCopyright (C) 2015-2020 KuraLabs S.R.L

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied.  See the License for the
specific language governing permissions and limitations
under the License.