Saravanan666/pypi-org huggingface dataset:
Package: cmdvars
cmdvarsRead environment variables defined in a shell script into Python.This library uses the shell to get variable values, and handles
multiline variables.UsageGiven a shell file: myvars.env:#!/bin/bashexportVAR1=1exportVAR2="This
is
a
multiline value"exportVAR3=3NOT_EXPORTED=4get_vars>>>importshellvars>>>shellvars.get_vars('myvars.env'){'VAR1':'1','VAR2':'This\nis\na\nmultiline value','VAR3':'3'}list_varsLists the variable names in the script.>>>importshellvars>>>shellvars.list_vars('myvars.env')['VAR1','VAR2','VAR3']This is equivalent to, but faster than>>>shellvars.get_vars('myvars.env').keys()
Package: cmdw
cmdwjust get info of length and width of terminal/console/cmdInstallingInstall and update usingpip_:.. code-block:: text$ pip install cmdcmdw supports Python 2 and newer, Python 3 and newer, and PyPy... _pip:https://pip.pypa.io/en/stable/quickstart/A Simple ExampleWhat does it look like? Here is an example of a cmdw:.. code-block:: python>>> import cmdw

>>> cmdw.getWidth()
>>> 164
>>> cmdw.getHeight()
>>> 26
>>> cmdw.getWidth() * "#"
>>> ############################################################################### 
....SupportPython 2.7 +, Python 3.xWindows, LinuxLinksLicense:BSD <https://github.com/licface/cmdw/blob/master/LICENSE.rst>_Code:https://github.com/licface/cmdwIssue tracker:https://github.com/licface/cmdw/issues
Package: cmdwatch
Command Watchercmdwatchis a CLI tool to watch the output of a given command until certain conditions given by the user are satisfied. The conditions can beThere is a change in outputWhen the time limit exceedsThe output of the command will be shown in the console as well.pip install cmdwatchUsage$cmdwatch-dDELAY[-oOUTPUT_FILE][-tTIMEOUT][-s]<cmd>

CommandWatcherTool

optionalarguments:-h,--helpshowthishelpmessageandexit-dDELAY,--delayDELAYHowlongtowaituntilnextexecution-oOUTPUT_FILE,--outputOUTPUT_FILEFilewheretheoutputshouldbestored-tTIMEOUT,--timeoutTIMEOUTForhowmanysecondshouldiwatch-s,--stopPassthisoptionifyouwanttostopcheckingwheneverthereisadifferenceinoutputIf you want to store the command outputs to a file then pass the --output/-o with the file nameExample:$cmdwatch-d2-oping_check.txtpinggoogle.comAbove usage will execute the "ping google.com" command every 2 seconds and stores the output into file ping_check.txtIf you want to stop the execution when there is a change in the output then pass --stop/-s optionExample:$cmdwatch-d2-oping_check.txt-spinggoogle.com
Package: cmeel
CMake Wheel: cmeelWheel build backend using CMake, to package anything with pip and distribute on PyPI.Following those relevant PEPs:PEP 427, The Wheel Binary Package Format 1.0PEP 517, A build-system independent format for source treesPEP 518, Specifying Minimum Build System Requirements for Python ProjectsPEP 600, Future ‘manylinux’ Platform Tags for Portable Linux Built DistributionsPEP 621, Storing project metadata in pyproject.tomlPEP 639, Improving License Clarity with Better Package Metadata,DRAFTPEP 660, Editable installs for pyproject.toml based builds (wheel based)Chathttps://matrix.to/#/#cmake-wheel:matrix.orgBasic ideaGlue between PEP 517 & 660 entry points and modern CMake standard project configuration / build / test / installThis Install in${PYTHON_SITELIB}/cmeel.prefix/:As there is a dot, it is not a valid python module name, so no risk of importing anything there by mistakePlay well with others, as everything is confined to${PYTHON_SITELIB}/cmeel.prefix${PYTHON_SITELIB}/cmeel.pthautomatically load${PYTHON_SITELIB}/cmeel.prefix/${PYTHON_SITELIB}, so python
packages work out of the boxExisting${PYTHON_SITELIB}/cmeel.prefixare automatically added to$CMAKE_PREFIX_PATH, so we can build CMake
packages whose dependencies are provided by other packages installed with cmeelStuff in${PYTHON_SITELIB}/cmeel.prefix/binis exposed viacmeel.run:cmeel_run, or copied if start with a shebangBasic pyproject.toml exampleextract fromhttps://github.com/cmake-wheel/cmeel-example/blob/main/pyproject.toml:[project]name="cmeel-example"version="0.4.12"description="This is an example project, to show how to use cmeel"requires-python=">= 3.7"license="BSD-2-Clause"authors=[{name="Guilhem Saurel",email="guilhem.saurel@laas.fr"}][project.urls]homepage="https://github.com/cmake-wheel/cmeel-example"repository="https://github.com/cmake-wheel/cmeel-example.git"changelog="https://github.com/cmake-wheel/cmeel-example/blob/main/CHANGELOG.md"[build-system]requires=["cmeel[build]"]build-backend="cmeel"Complete specification is available at:https://packaging.python.org/en/latest/specifications/declaring-project-metadataInstallIf you want to use the helpers provided by cmeel, toeg. test building a project in a manylinux container withcmeel docker, the best way to install cmeel is to use pipx:pipx install cmeelOtherwise, if you just want to use the build backend, there is no need to install anything: your frontent (eg.pip)
should do this for you
Package: cmeel-casadi-kin-dyn
casadi_kin_dynPackage for generation of symbolic (SX) expressions of robot kinematics and dynamics. Based on URDF and Pinocchio.What has changed?In comparison to the originalcasadi_kin_dynrepository, such changes were made:Migration tocmeel-based packagingUsepre-committo prettify repositoryAddedtorque,potentialEnergy,kineticEnergyregressorsAddedjacobian time derivativemappingAddedjacobian of CoMmappingv1.6.7Added ability to setroot_jointtoFreeFlyerjointv1.6.8root_jointis now transformed to enum that can be freely extended with Pinocchio JointModel types.v1.6.9One can now fixfloatingjoints in the model by passing a list of[x, y, z, qvx, qvy, qvz, qs].importcasadi_kin_dyn.casadi_kin_dynascas_kin_dynkindyn=cas_kin_dyn.CasadiKinDyn(urdf,root_joint=cas_kin_dyn.CasadiKinDyn.JointType.OMIT,fixed_joints={"floating_base_joint":np.array([0,0,0,0,0,0,1])},)v1.6.10Derivatives of centroidal dynamics are exposed frompinocchio::computeCentroidalDynamicsDerivatives1.6.11Added collision handler which bindsdistanceandjacobianfunctions with the use ofhpp-fcllibrary.
Package: cmeel-example
Example project C++ for cmeelThis is an example project, to show how to usecmeel, and to provide tests for itTest thisInstallationBinary wheels are published on PyPI for many Linux and mac OS flavors and architectures, so you'll probably be able to
install from binaries withpython -m pip install cmeel-example(don't forget to use an up-to-datepipwithpython -m pip install -U pip).If pip can't find binaries for your platform, it will download the.tar.gzsource and build it for you.If you really want to explicitely build it yourself:python -m pip install git+https://github.com/cmake-wheel/cmeel-example.gitUsageFrom shell:cmeel-add 3 4From python:importcmeel_examplecmeel_example.cmeel_add(3,4)
Package: cmeel-mim-solvers
mim_solversImplementation of numerical solvers used in the Machines in Motion Laboratory.
In particular, the Sequential Quadratic Programming (SQP) solver described inthis papersolves nonlinear constrained OCPs efficiently.All solvers are implemented by usingCrocoddyl(v2.0) as the base software.
Consequently, Crocoddyl users can use our efficient solvers while constructing their OCPs using the same API they are used to.
The default solvers of Crocoddyl are also re-implemented for benchmarking purposes (namely DDP and FDDP) but with modified termination criteria and line-search.Examples on how to use the solvers can be found in theexamplesdirectory.DependenciesPinocchio(rigid-body dynamics computations)Crocoddyl(optimal control library)ProxSuite(quadratic programming) [OPTIONAL]InstallationUsing condaconda install mim-solvers --channel conda-forgeUsing CMakegit clone --recursive https://github.com/machines-in-motion/mim_solvers.gitcd mim_solvers && mkdir build && cd buildcmake .. [-DCMAKE_BUILD_TYPE=Release] [-DCMAKE_INSTALL_PREFIX=...]make [-j6] && make installContributorsArmand Jordana(NYU): main developer and manager of the projectSébastien Kleff(NYU): main developer and manager of the projectAvadesh Meduri(NYU): main developer and manager of the projectLudovic Righetti(NYU): project instructorJustin Carpentier(INRIA): project instructorNicolas Mansard(LAAS-CNRS): project instructorYann de Mont-Marin(INRIA): Conda integration and support
Package: cmeel-urdfdom
urdfdomThe URDF (U-Robot Description Format) library provides core data structures and a simple XML parsers for populating the class data structures from an URDF file.For now, the details of the URDF specifications reside onhttp://ros.org/wiki/urdfUsing with ROSIf you choose to check this repository out for use with ROS, be aware that the necessarypackage.xmlis not
included in this repo but instead is added in during the ROS release process. To emulate this, pull the appropriate
file into this repository using the following format. Be sure to replace the ALLCAPS words with the appropriate terms:wget https://raw.github.com/ros-gbp/urdfdom-release/debian/ROS_DISTRO/UBUNTU_DISTRO/urdfdom/package.xmlFor example:wget https://raw.github.com/ros-gbp/urdfdom-release/debian/hydro/precise/urdfdom/package.xmlInstalling from Source with ROS DebiansWarning: this will break ABI compatibility with future /opt/ros updates through the debian package manager. This is a hack, use at your own risk.If you want to install urdfdom from source, but not install all of ROS from source, you can follow these loose guidelines.
This is not best practice for installing, but works.
This version is for ROS Hydro but should be easily customized for future version of ROS:sudo mv /opt/ros/hydro/include/urdf_parser/ /opt/ros/hydro/include/_urdf_parser/
sudo mv /opt/ros/hydro/lib/liburdfdom_model.so /opt/ros/hydro/lib/_liburdfdom_model.so
sudo mv /opt/ros/hydro/lib/liburdfdom_model_state.so /opt/ros/hydro/lib/_liburdfdom_model_state.so
sudo mv /opt/ros/hydro/lib/liburdfdom_sensor.so /opt/ros/hydro/lib/_liburdfdom_sensor.so
sudo mv /opt/ros/hydro/lib/liburdfdom_world.so /opt/ros/hydro/lib/_liburdfdom_world.so
sudo mv /opt/ros/hydro/lib/pkgconfig/urdfdom.pc /opt/ros/hydro/lib/pkgconfig/_urdfdom.pc
sudo mv /opt/ros/hydro/share/urdfdom/cmake/urdfdom-config.cmake /opt/ros/hydro/share/urdfdom/cmake/_urdfdom-config.cmake

cd ~/ros/urdfdom # where the git repo was checked out
mkdir -p build
cd build
cmake ../ -DCMAKE_INSTALL_PREFIX=/opt/ros/hydro
make -j8
sudo make install

# now rebuild your catkin workspace
cd ~/ros/ws_catkin
catkin_make
Package: cmemcache_hash
cmemcache_hashenablespython-memcachedto use the very same hashing
algorithm that thecmemcachemodule uses.This is useful when you’re mixingcmemcacheandpython-memcachedor
other libraries that use thecmemcache-style hashing algorithm, like
PostgreSQL’spgmemcachemodule.SetupSimply install the module and import it, and it is enabled:import cmemcache_hashIf you feel like deactivating, use:cmemcache_hash.deactivate()Or reactivating it:cmemcache_hash.activate()LicenseThe BSD three-clause license. See attachedLICENSEfile.IRC#sendapatchonchat.freenode.net.
Package: cmem-cmemc
cmemccmemc is the official command line client foreccenca Corporate Memory.InstallationIn order to install the cmemc, run:pipx install cmem-cmemcOf course you can install cmemc also with pip, but we recommendpipxfor normal desktop usage.Configuration and Usagecmemc is intended for System Administrators and Linked Data Expert, who wants to automate and remote control activities on eccenca Corporate Memory.The cmemc manual including basic usage pattern, configuration as well as a command reference is available at:https://eccenca.com/go/cmemccmemc only works with Python 3 and refuses to work with Python 2.x.
In addition to that, cmemc will warn you in case an untested Python environment is used.
Package: cmem-cmempy
cmempycmempy is a Python API wrapper foreccenca Corporate Memory.InstallationTo install the Python library run:pip install cmem-cmempyYou may consider installing the package only for the current user:pip install cmem-cmempy --userConfiguration and Usagecmempy is intended for Linked Data Experts to interface with the eccenca Corporate Memory backend components DataIntegration and DataPlatform.The cmempy manual including basic usage patterns and configuration is available at:https://eccenca.com/go/cmempycmempy is tests with python 3.9 and 3.11.
Package: cmem-plugin-irdi
cmem-plugin-irdiCreate uniqueECLASSIRDIsThis is a plugin foreccencaCorporate Memory.You can install it with thecmemccommand line
clients like this:cmemc admin workspace python install cmem-plugin-irdiPlugin UsageAll fields of the IRDI are configurable, minusItem Code, which is created by the pluginCreated IRDIs are unique per configurationSpecify a graph that stores the state ofItem CodesInput and output paths are configurableif no input path is configured, values are read from the URIs of the input (Transformation Input)
Package: cmem-plugin-kafka
cmem-plugin-kafkaSend and receive messages from Apache Kafka.This is a plugin foreccencaCorporate Memory.You can install it with thecmemccommand line
clients like this:cmemc admin workspace python install cmem-plugin-kafkaPlugin supported message formatXML dataset formatAn example XML document is shown below. This document will be sent as two messages
to the configured topic. Each message is created as a proper XML document.<?xml version="1.0" encoding="utf-8"?><KafkaMessages><Message><PurchaseOrderOrderDate="1996-04-06"><ShipTocountry="string"><name>string</name><street>string</street><city>string</city><state>string</state><zip>9200</zip></ShipTo><BillTocountry="string"><name>string</name><street>string</street><city>string</city><state>string</state><zip>2381</zip></BillTo></PurchaseOrder></Message><Messagekey="1234"><SingleTagHere>...</SingleTagHere></Message></KafkaMessages>Producer plugin generates 2 messages with below content<?xml version="1.0" encoding="utf-8"?><PurchaseOrderOrderDate="1996-04-06"><ShipTocountry="string"><name>string</name><street>string</street><city>string</city><state>string</state><zip>9200</zip></ShipTo><BillTocountry="string"><name>string</name><street>string</street><city>string</city><state>string</state><zip>2381</zip></BillTo></PurchaseOrder><?xml version="1.0" encoding="utf-8"?><SingleTagHere>...</SingleTagHere>JSON Dataset formatAn example JSON document is shown below. This document will be sent as two messages
to the configured topic. Each message is created as a proper JSON document.[{"message":{"key":"818432-942813-832642-453478","headers":{"type":"ADD"},"content":{"location":["Leipzig"],"obstacle":{"name":"Iron Bars","order":"1"}}}},{"message":{"key":"887428-119918-570674-866526","headers":{"type":"REMOVE"},"content":{"comments":"We can pass any json payload here."}}}]Producer plugin generates 2 messages with below content{"location":["Leipzig"],"obstacle":{"name":"Iron Bars","order":"1"}}{"comments":"We can pass any json payload here."}Entities formatRandom values plugin entities will generate below format JSON document.{"schema":{"type_uri":"https://example.org/vocab/RandomValueRow"},"entity":{"uri":"urn:uuid:3c68d8e7-bf17-4045-a9eb-c9c9813f717f","values":{"<https://example.org/vocab/RandomValuePath0>":["a8o4Ocsb6RZClFRUZU3b2w"],"<https://example.org/vocab/RandomValuePath1>":["RTICRU7JcTUVn94decelPg"],"<https://example.org/vocab/RandomValuePath2>":["A9r-969NjAlX0DNWftxKoA"],"<https://example.org/vocab/RandomValuePath3>":["FygWRy1UJ4-IzIim1qukJA"],"<https://example.org/vocab/RandomValuePath4>":["AJcbn-LJEs-Dif96xu2eww"]}}}
Package: cmem-plugin-pyshacl
cmem-plugin-pyshaclThis is a plugin foreccencaCorporate Memoryplugin performingSHACLvalidation withpySHACL.Installationcmemc admin workspace python install cmem-plugin-pyshaclOptionsData graph URIThe URI of the graph to be validated. The graph URI is selected from a list of graphs of types:di:Datasetdsm:ThesaurusProjectowl:Ontologyshui:ShapeCatalogvoid:DatasetSHACL graph URIThe URI of the graph containing the SHACL shapes to be validated against. The graph URI is selected from a list of graphs of typeshui:ShapeCatalog.Generate validation graphIf enabled, the validation graph is posted to the CMEM instance with the graph URI specified with thevalidation graph URIoption. Default value:false.Validation graph URIIf thegenerate validation graphoption is enabled the validation graph is posted to the CMEM instance with this graph URI.Output entitiesIf enabled, the plugin outputs the validation results and can be connected to, for instance, a CSV dataset to produce a results table. Default value:false.Clear validation graphIf enabled, the validation graph is cleared before workflow execution. Default value:true.Advanced OptionsResolve owl:importsIf enabled, the graph tree defined withowl:importsin the data graph is resolved. Default value:true.Blank node skolemizationIf enabled, blank nodes in the validation graph are skolemized into URIs. Default value:true.Add labelsIf enabled,rdfs:labeltriples are added to the validation graph for instances ofsh:ValidationReportandsh:ValidationResult. Default value:true.Add labels from data and SHACL graphsIf enabled along with theadd labelsoption,rdfs:labeltriples are added for the focus nodes, values and SHACL shapes in the validation graph. The labels are taken from the specified data and SHACL graphs. Default value:false.Add shui:conforms flag to focus node resourcesIf enabled,shui:conforms falsetriples are added to the focus nodes in the validation graph. Default value:false.Meta-SHACLIf enabled, the SHACL shapes graph is validated against the SHACL-SHACL shapes graph before validating the data graph. Default value:false.Ontology graph URIThe URI of a graph containing extra ontological information. RDFS and OWL definitions from this are used to inoculate the data graph. The graph URI is selected from a list of graphs of typeowl:Ontology.InferenceIf enabled, OWL inferencing expansion of the data graph is performed before validation. Options areRDFS,OWLRL,Both,None. Default value:None.AdvancedEnable SHACL Advanced Features. Default value:false.Parameter InputIn order to set options via the input the following parameter names can be used:OptionNameData graph URIdata_graph_uriSHACL graph URIshacl_graph_uriGenerate validation graphgenerate_graphValidation graph URIvalidation_graph_uriOutput entitiesoutput_entitiesClear validation graphclear_validation_graphResolve owl:importsowl_importsBlank node skolemizationskolemizeAdd labelsadd_labelsAdd labels from data and SHACL graphsinclude_graphs_labelsAdd shui:conforms flag to focus node resourcesadd_shui_conformsMeta-SHACLmeta_shaclOntology graph URIontology_graph_uriInferenceinferenceAdvancedadvanced
Package: cmerg
cmergPython parser for CarMaker ERG files with Pandas dataframe export.Use and ExamplesMoslty these are notes for myself but hopefully someone else finds them useful.InstallationThis packageis published on PyPIunder the namecmerg.Windows>python-mpipinstall-Upip
>python-mpipinstallcmergLinux$python3-mpipinstall-Upip
$python3-mpipinstallcmergExamplesImport the package folder.import cmergCreate ERG file object. (Using example file from repo)log1 = cmerg.ERG('test-data/Test-Dataset-1_175937.erg')List of the signals in the file.log1.signalsSave the vehicle speed signal to a variable.speed = log1.get('Vhcl.v')Plot signal.speed.plot()Add signal to dataframe.# New easy call to return a pandas dataframe.df=log1.to_pd()# Simple example of adding ERG data to pandas.# TODO: Make 'toPd()' callimportcmergimportpandasaspdimportnumpyasnplog1=cmerg.ERG('data-file.erg')speed=log1.get('Vhcl.v')t=np.array(speed.timestamps)spd=np.array(speed.samples)df=pd.DataFrame({'time':t,'speed':spd})
Package: cmeson
cmeson is a text-based user interface for themesonbuild system and offers a convenient, graphical way to configure build options instead of having to memorize and type them out in the terminal. Due to incompatibility of its TUI library, cmeson only supports Linux, MacOS and other Unix-like systems. Consequently, if you want to use this application on Windows, you can do so through WSL or Cygwin. The name and functionality of this application are derived from a similar application forcmakeccmake.InstallationFrom PyPI:pip3 install --user cmesonFrom source:git clone https://github.com/proskur1n/cmeson
cd cmeson
pip3 install --user .Usagecmeson builddir
cmeson [OPTIONS] builddir [sourcedir] [TRAILING]

OPTIONS
	-h, --help               Show help message and exit
	--backend BACKEND        Select backend to query build options forsourcediris a directory containingmeson.buildfile andbuilddiris the build directory for the project.sourcediris only needed for projects for whichmeson setuphas not been run yet and defaults to the current working directory if not specified.The--backendoption determines the list of options in the backend section and defaults to ninja. If you specify a backend using this option, you must not change the backend in TUI as this will result in an error from meson. See the meson documentation for a complete list of supported backends.If any trailing options are given, they are passed as-is to meson and are not interpreted by this application. Normally you do not need to specify any trailing options as most of them can be configured directly through TUI.LicenseMIT License (see LICENSE for more information)
Package: cmf
Modelling water and solute fluxescmf is a programming library to create hydrological models, which are highly modular and connectible to other
models developed using amultiple hypotheses backgroundand is based on thefinite volume methodAlthough written in C++, its primary usage is to be compiled
as an extension to other programming languages, using SWIG. Researchers can build individual models,
targeting their scientific question by using the library objects like water storages, boundary conditions,
fluxes and solvers. cmf uses the finite volume method to set up a wide range of models of water flow through
your study area. Resulting models can range fromlumped conceptual modelstofully distributed darcian modelsand everything in between.cmfis published as free software under GPLv3. (c) 2007-2017 by Philipp Kraft and the
Institute of Landscape Ecology and Resources Management, Justus-Liebig Universität Gießen.DocumentationCan be found here:https://philippkraft.github.io/cmfDevelopmentYou can join the development or report bugs at Github:PublicationsThe basic publication of cmf is:Kraft, P., Vaché, K.B., Frede, H.-G. Breuer, L. 2011. A hydrological programming language extension for integrated
catchment models, Environmental Modelling & Software,doi: 10.1016/j.envsoft.2010.12.009Published applications