Saravanan666/pypi-org huggingface dataset:
Package: hetio
Hetnets in PythonPackage relocationCritical:
This is the final release before the package namechangestohetnetpyfromhetio.
Future development will occur in thehetio/hetnetpyrepository.
PyPI releases will be available athttps://pypi.org/project/hetnetpy/.Users of v0.2.11 will see a warning when importinghetio.
These users should either switch to usinghetnetpyor downgrade tohetio<=0.2.10to avoid the warning.BackgroundHetnets: Hetnets, alsocalledheterogeneous information networks, are graphs with multiple node and edge types. Hetnets are both multipartite and multirelational. They provide a scalable, intuitive, and frictionless structure for data integration.Purpose: This package provides data structures for hetnets and algorithms foredge prediction. It only supports hetnets, which is its primary advantage compared to other network software. Node/edge attributes and edge directionality are supported.Impetus: Development originated with astudyto predict disease-associated genes and continues with a successivestudyto repurpose drugs.Caution: Documentation is currently spotty, testing coverage is moderate, and the API is not fully stable. Contributions are welcome. Please useGitHub Issuesfor feedback, questions, or troubleshooting.InstallationPlease use Python 3.4 or higher. To install the current PyPI version (recommended), run:pipinstallhetioFor the latest GitHub version, run:pipinstallgit+https://github.com/hetio/hetio.git#egg=hetioFor development, clone or download-and-extract the repository. Then runpip install --editable .from the repository's root directory. The--editableflag specifieseditablemode, so updating the source updates your installation.Once installed, tests can be executed by runningpy.test test/from the repository's root directory.DesignA Graph object stores a heterogeneous network and relies on the following classes:GraphMetaGraphEdgeMetaEdgeRelease instructionsThis section is only relevant for project maintainers.
Travis CI deployments are used to upload releases toPyPIandGitHub releases.
To create a new release, do the following:Bump the version in__init__.py.Add a release notes file inrelease-notes.
Format as a commit message that will be used as the GitHub release description.Run the following commands:TAG=v`pythonsetup.py--version`gitaddhetio/__init__.pyrelease-notes/$TAG.*
gitcommit--message"Prepare$TAGrelease"gitpush
gittag--annotate$TAG--filerelease-notes/$TAG.*
gitpushupstream$TAGRecommended: Edit the GitHub release to improve formatting and add a Zenodo badge.
Package: hetmatpy
hetmatpy: a Python 3 package for matrix operations of hetnetsThis codebase enables identifying the relevant network connections between a set of query nodes.
The method is designed to operate on hetnets (networks with multiple node or relationship types).This project is still under development.
Use with caution.EnvironmentInstall via pip from GitHub using:# install the latest release from PyPIpipinstallhetmatpy# install latest version on GitHubpipinstallgit+https://github.com/hetio/hetmatpy# for local development, run the following inside the development environment:pipinstall--editable.DevelopmentThis repo uses pre-commit checks:# run once per local repo before committingpre-commitinstallAcknowledgmentsThis work is supported through a research collaboration withPfizer Worldwide Research and Development.
This work is funded in part by the Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative through GrantsGBMF4552to Casey Greene andGBMF4560to Blair Sullivan.
Package: hetnetpy
Hetnets in PythonOverviewHetnetpy is a Python 3 package for creating, querying, and operating on hetnets.
This software provides convenient data structures for hetnets, as well as algorithms for edge prediction.
It is specifically tailored and streamlined for hetnets compared to other more generic network software.
Seehttps://het.io/softwarefor additional software packages designed specifically for hetnets.Package relocationNote that this package was previously namedhetio, available at the following repositories:https://github.com/hetio/hetnetpy(current)https://github.com/hetio/hetio(former)https://github.com/dhimmel/hetio(former)In July 2019, the package wasrenamedtohetnetpyto more clearly represent its functionality and disambiguate it from other products.BackgroundHetnets: Hetnets, alsocalledheterogeneous information networks, are graphs with multiple node and edge types. Hetnets are both multipartite and multirelational. They provide a scalable, intuitive, and frictionless structure for data integration.Purpose: This package provides data structures for hetnets and algorithms foredge prediction. It only supports hetnets, which is its primary advantage compared to other network software. Node/edge attributes and edge directionality are supported.Impetus: Development originated with astudyto predict disease-associated genes and continues with a successivestudyto repurpose drugs.Caution: Documentation is currently spotty, testing coverage is moderate, and the API is not fully stable. Contributions are welcome. Please useGitHub Issuesfor feedback, questions, or troubleshooting.InstallationPlease use Python 3.4 or higher. To install the current PyPI version (recommended), run:pipinstallhetnetpyFor the latest GitHub version, run:pipinstallgit+https://github.com/hetio/hetnetpy.git#egg=hetnetpyFor development, clone or download-and-extract the repository. Then runpip install --editable .from the repository's root directory. The--editableflag specifieseditablemode, so updating the source updates your installation.Once installed, tests can be executed by runningpy.test test/from the repository's root directory.DesignA Graph object stores a heterogeneous network and relies on the following classes:GraphMetaGraphEdgeMetaEdgeDevelopmentThis repo uses pre-commit:# run once per local repo before committingpre-commitinstallThis following is only relevant for maintainers.
Create a new release athttps://github.com/hetio/hetnetpy/releases/new.
GitHub Actions will build the distribution and upload it to PyPI.
The version information inferred from the Git tag usingsetuptools_scm.LicenseThis repository is dual licensed, available under either or both of the following licenses:BSD-2-Clause Plus Patent License atLICENSE-BSD.mdCC0 1.0 Universal Public Domain Dedication atLICENSE-CC0.md
Package: hetrob
HetRob - Coordination of Heterogeneous Robotic TeamsA python package for the optimization of mission plans for heterogeneous, cooperating robotic teams using genetic
algorithms.Free software: MIT licenseDocumentation:https://hetrob.readthedocs.io.InstallationThe package is best installed using the Python package manager PIP.$pip3install--userhetrobBasic UsageFor a more detailed description of the usage refer to theDocumentation.CreditsCookiecutter: A python boilerplate project templating CLI toolcookiecutter-pypackage: A cookiecutter template, which provides the basic boilerplate for creating the folder
structure of a publishable python packagedeap: Short for “distributed evolutionary algorithms with python”History0.1.0 (2020-06-30)First release on PyPI.0.2.0 (2020-10-02)Added all the stuff from the implementation phase of the bachelor thesisDocumentationAdded very basic information about the optimization of a base VRP with a simple GAAdded a chapter for advanced topicsAdded a chapter for a command line interface0.3.0 (2020-11-23)Changed the documentation theme to “read the docs”Added the “getting started page” to the documentationAdded the example “basic_vrp.py”Added the example “hsvrsp.py”
Package: hetsar
HETSAR: Python package to estimate spatial autoregressive models with heterogeneous coefficientshetsar fits spatial autoregressive panel data models with heterogeneous coefficients.
The estimation is performed via quasi maximum-likelihood.
See Aquaro, Bailey and Pesaran (J. Appl. Econometrics, 2021) for technical details.The hetsar package was written in 2021 by Ida Johnsson. It is distributed under the 3-Clause BSD license.See the source for this project here:https://github.com/ida-j/hetsar.InstallationPrerequisitesInstall dependencies:$ pip install -r requirements.txtInstall from pip:$ pip install hetsarInstall from source:$ git clone https://github.com/ida-j/hetsar.git
$ cd hetsar
$ python setup.py build_ext --inplace
$ python setup.py install
Package: hetzner-control
hetzner-controlhetzner-controlits CLI tool, which lets you easily manage servers onthe Hetzner platformTable of contentsMotivationUsageInstallation guideWant to contribute?LicenseMotivationI wanted to create a console application that would interact
with the REST API of the cloud service for convenient server management
and the platform in general.I also wanted to improve my skills in application
design and API work while I'm studying software engineering in university.Usage$htz[OPTIONS]COMMAND[ARGS]...Options:--install-completion: Install completion for the current shell.--show-completion: Show completion for the current shell, to copy it or customize the installation.--help: Show documentation message for available commands/flagsCommands:info: Information about available data centers, servers, pricesserver: Operations with serversversion: Show app versionFor a more detailed description of the command, see wiki pageInstallation guideFirst, install environment variable, i.e. in .bashrc$exportHETZNER_API_TOKEN="YOUR_HETZNER_TOKEN_HERE"Installation optionYou can install hetzner-control from pip$pip3installhetzner-controlOr you can clone the repository and build the wheel/sdist module with poetry (you can preinstall poetry):$gitclonehttps://github.com/Hanabiraa/hetzner-control.git
$cdhetzner-control
$poetryinstall
$poetrybuildWant to contribute?Clone repo and create a new branch:$gitcheckouthttps://github.com/Hanabiraa/hetzner-control-bname_for_new_branchMake changes and testSubmit Pull Request with comprehensive description of changesLicenseMIT License
Package: hetznerdns
HetznerDNSAn API and CLI tools for Hetzner DNS. It is work in progress, the functionality is added as required.Hetzner DNS DocsAPI DocsAccess EndpointInstallationpip install hetznerdnsUsageTo use the CLI client, you need to generate access token in theHetzner DNS web frontend. CLI client configuration is done via environment variables.export HETZNER_DNS_TOKEN=tokenAt the moment, it is possible to get/create/delete zones and records, for example:$ hetznerdns-cli zone get --name ermilov.org
{'id': 'tfJ9nMJckFAV7LBghxWTNB', 'name': 'ermilov.org', 'ttl': 86400, 'registrar': '', 'legacy_dns_host': '', 'legacy_ns': ['oxygen.ns.hetzner.com.', 'helium.ns.hetzner.de.', 'hydrogen.ns.hetzner.com.'], 'ns': ['hydrogen.ns.hetzner.com', 'oxygen.ns.hetzner.com', 'helium.ns.hetzner.de'], 'created': '2021-01-22 13:26:21.526 +0000 UTC', 'verified': '', 'modified': '2021-01-22 13:26:22.479 +0000 UTC', 'project': '', 'owner': '', 'permission': '', 'zone_type': {'id': '', 'name': '', 'description': '', 'prices': None}, 'status': 'verified', 'paused': False, 'is_secondary_dns': False, 'txt_verification': {'name': '', 'token': ''}, 'records_count': 4}

$ hetznerdns-cli zone create --name test-test-example.com
$ hetznerdns-cli zone get --name test-test-example.com
{'id': '5DFHAbGXmHX8ojKh6Prs8H', 'name': 'test-test-example.com', 'ttl': 3600, 'registrar': '', 'legacy_dns_host': '', 'legacy_ns': [], 'ns': ['hydrogen.ns.hetzner.com', 'oxygen.ns.hetzner.com', 'helium.ns.hetzner.de'], 'created': '2021-02-05 12:57:21.941 +0000 UTC', 'verified': '', 'modified': '2021-02-05 12:57:21.941 +0000 UTC', 'project': '', 'owner': '', 'permission': '', 'zone_type': {'id': '', 'name': '', 'description': '', 'prices': None}, 'status': 'verified', 'paused': False, 'is_secondary_dns': False, 'txt_verification': {'name': '', 'token': ''}, 'records_count': 0}

$ hetznerdns-cli zone delete --name test-test-example.com
$ hetznerdns-cli record create --name www --type A --value 127.0.0.1 --zone-name ermilov.org
{'record': {'id': '1ed054dbcc1b6445f10e5a86a6f9539b', 'type': 'A', 'name': 'www', 'value': '127.0.0.1', 'ttl': 3600, 'zone_id': 'tfJ9nMJckFAV7LBghxWTNB', 'created': '2021-02-05 12:58:39.63 +0000 UTC', 'modified': '2021-02-05 12:58:39.63 +0000 UTC'}}

$ hetznerdns-cli record get --name www --zone-name ermilov.org
{'id': '1ed054dbcc1b6445f10e5a86a6f9539b', 'type': 'A', 'name': 'www', 'value': '127.0.0.1', 'ttl': 3600, 'zone_id': 'tfJ9nMJckFAV7LBghxWTNB', 'created': '2021-02-05 12:58:39.63 +0000 UTC', 'modified': '2021-02-05 12:58:39.63 +0000 UTC'}

$ hetznerdns-cli record delete --name www --zone-name ermilov.orgDevelopment# Create virtual environment for python3
# Then inside the environment execute
git clone https://github.com/earthquakesan/hetznerdns-py && cd hetznerdns-py
pip install -e .
pip install -r requirements-dev.txt
make test
Package: hetzner-fireaccess-cleaner
hetzner-fireaccess-cleanerThis CLI is to be used with clearing automated access to a Hetzner firewallGetting startedpip install hetzner-fireaccess-cleanerHow does it work?This script is made to be run by an automation, like crontab.
It's looking for the stringauto-expire-[]where we have a timestamp to when the listed rule should expire in UNIX time.Example: auto-expire-[1647127315]Remote access for USER - auto-expire-[1647127315]It uses the default hcloud CLI config file.https://github.com/hetznercloud/cliHow you implement and use this is up to you.Usagehetzner-fireaccess-cleanerclean[FIREWALLNAME]For more info about available flags, checkout out the helphetzner-fireaccess-cleaner -h.ExamplesClean the firewallfirewall-1hetzner-fireaccess-cleanercleanfirewall-1Using a different context than the current activehetzner-fireaccess-cleaner--contextaccess-projectcleanremote-firewallDEMO$hetzner-fireaccess-cleanercleanremote-firewall
Nocontextprovided,usingdefault
Rulemarkedforremoval:Arulewhichisexporedauto-expire-[1647127315]Removingrules
FinishedContributionsContributions are welcome.DisclaimerThis has not yet been tested a lot and only on a small hetzner account, use with caution.
Package: hetzner-fix-report
hetzner-fix-reportFixes Hetzner CSV reports by cleaning the CSV and merging project name from PDF.InstallationPreliminary librariesDebian, Ubuntu, etcsudo apt-get install build-essential libpoppler-cpp-dev pkg-config python-devFedora, Red Hat, etcsudo yum install gcc-c++ pkgconfig poppler-cpp-devel python-devel redhat-rpm-configArch, etcsudo pacman -S popplerPython packageThis project is hosted onPyPIand can therefore be installed easily through pip:pip install hetzner_fix_reportDependending on your setup you may need to add--userafter the install.UsageSingle reportUse the command line interface to combine acsvandpdffile:hetzner-fix-report Hetzner_2020-01-05_RXXXXXXXXXX.csv Hetzner_2020-01-05_RXXXXXXXXXX.pdfOr shorten it using brace expansion:hetzner-fix-report Hetzner_2020-01-05_RXXXXXXXXXX.{csv,pdf}If you want to save the enriched csv output, use either the-oparameter as explained in the program's help or redirect output to a file using>.Batchwise processingWhen in a directory that holds multiplecsvandpdffiles the following shell script should call the tool and save its output within a newly created subdirectory:mkdir -p fix
for csv in *.csv; do pdf=${csv%%.*}.pdf; hetzner-fix-report -o "fix/$csv" "$csv" "$pdf"; doneOriginal & enriched formatHetzner's original CSV reports have the problem of being unprecise and not machine readable.
This is especially noticeable in the long multiline comment column that may is mostly human readable.
Currently the PDF report contains additional information about the entry's (server/backup) associated project.
Since this information is not contained within the CSV reports I wanted to fix this.
The enriched format has the following keys and examplary values:KeyExampleNewid2520725✔namemy-server✔projectMy Project✔typecx31quantity1usage_hours42✔price8.9price_netto4.9price_max2.49✔day_from2020-06-01day_to2020-06-30is_backupFalse✔is_serverTrue✔is_cephFalse✔
Package: hetzner-set-dns-txt-record
hetzner_set_dns_txt_recordpython script that can be used to change hetzner DNS TXT entries (intended to be used with a manual auth hook in certbot)Installationpip3 install hetzner_set_dns_txt_recordStandalone UsageSet record to a value:hetzner_set_dns_txt.py --record=<which TXT record to set, e.g. _acme-challenge> --value=<your-value> --user=<your-hetzner-user> --password=<your-hetzner-password> --domain="<the complete domain you want to set the TXT record for>" --basedomain=<the top level base domain> --verboseDelete TXT recordhetzner_set_dns_txt.py --record=<which TXT record to delete, e.g. _acme-challenge> --delete --user=<your-hetzner-user> --password=<your-hetzner-password> --domain="<the complete domain you want to set the TXT record for>" --basedomain=<the top level base domain> --verboseAcknowledgementsThe method to manipulate the DNS entries in the Hetzner robot is fromhetzner-letsencrypt-wildcard-auto-renewand
was improved upon to fit into a more general DNS TXT utility for Hetzner.
Package: heureka-overene
Heureka 'Overené zákazníkmi' Python moduleHeureka Overené zákazníkmi(ShopCertification) service API implementation for PythonUsageImport classheureka_overene.ShopCertificationusingyour API keyfor login.Basic usage of ShopCertificationfromheureka_overeneimportShopCertification,HeurekaService# Slovak shop initializationshop_certification=ShopCertification(api_key='Your API key',email='Your email',service=HeurekaService.SK)# Czech shop initializationshop_certification=ShopCertification(api_key='Your API key',email='Your email',service=HeurekaService.CZ)# log ordercertification.log_order()Set the customer order ID (only integers are allowed):certification.order_id=12345Add products id from the customer order. (Use IDs which you use in ITEM_ID field of theHeureka XML feed)certification.add_product_id('PROD-124')
Package: heurisp
Heurisp(What is it)A repository ofPython2implementedHeuristics forSampling-basedPath (Motion) Planner(HSP).Currently, it includes these heuristics:Orientation-Aware Space Exploration (OSE, referred to [^1]). It is one of the state-of-the-art heuristics according to [^2].How to useOrientation-Aware Space Exploration(Details included intest/test.py)fromheurispimportOrientationSpaceExplorerasOSExplorer# see test directory for details to set arguments.explorer=OSExplorer()explorer.initialize(start,goal,grid_map,grid_res,grid_ori)explorer.exploring()How to installPyPI$pip2installheurispFrom source$gitclonehttps://github.com/liespace/pyHSP.git
$cdpyHSP
$pythonsetup.pysdist# install$pipinstallheurisp-fdist/*--no-cache-dir# or upload yours# $ twine upload dist/*Reference[^1]: Chen, Chao, Markus Rickert, and Alois Knoll. "Path planning with orientation-aware space exploration guided heuristic search for autonomous parking and maneuvering." 2015 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2015.[^2]: Banzhaf, Holger, et al. "Learning to predict ego-vehicle poses for sampling-based nonholonomic motion planning." IEEE Robotics and Automation Letters 4.2 (2019): 1053-1060.
Package: heuristiciohbsp
heuristiciohbspHeuristic Methods for Minimizing Cut Bars and Using Leftovers from the One-dimensional Cutting Process - IOH-BSP Heuristic.Getting StartedDependenciesYou need Python 3.8 or later to useheuristiciohbsp. You can find it atpython.org.InstallationClone this repo to your local machine using:git clone https://github.com/omatheuspimenta/heuristiciohbsp.gitorpip install heuristiciohbspFeaturesIn this heuristic, the losses of the cutting process are concentrated on the smallest number of bars possible, using a greedy structure, in order to become losses (unusable) into leftovers (usable).Examplefromheuristiciohbspimportbspn=7L=30l=[7,9,11,14,19,21,26]d=[2,3,2,2,2,1,1]left=loss=bar=0x=[]left,loss,bar,x=bsp.ioh(L=L,n=n,l=l,d=d)Input and ParametersL:Size of bar to be cutting.(int)n:Number of Items to be cutting.(int)l:Lenght of items to be cutting.(list)d:Demand of items to be cutting.(list)smallitem:Size of small item. Default is the smallest item to be cutting.(int)Outputleft:Leftover from the cutting process.(int)loss:Loss from the cutting process.(int)bar:Bar number used in the cutting process.(int)x:Cutting pattern.(list)ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.CitationIf you use this software in your work, please cite our paper. (soon)LicenseMIT
Package: heuristic-optimization
Status: Experimental / alpha – do not use yetThis library currently implementsparticle swarm optimizationand offers base classes to quickly implement other (meta-)heuristic
optimization algorithms for continuous domains (as opposed to discrete /
combinatorial optimization).Scope and AudienceHeuristic optimization algorithms (sometimes calledmetaheuristics)
aim to find approximate global optima on problems that are intractable for
exact algorithms. They make no guarantees regarding the optimality of the
result (in particular, they arenotapproximation algorithms).On the upside, these heuristics make few – if any – assumptions about theobjective function:
It can be non-differentiable or even discontinuous and may have multiple local
and global minima.However, this library originated from a specific use case and thus makes some
assumptions (which may also evolve in the future).
E.g.,we assume that objective function evaluations are “costly”
(measured in seconds rather than milliseconds, so that an algorithm’s
implementation itself is certainly not a performance bottleneck),we only handle “soft” constraints usingpenalties,we may take liberties when converting real-valued inputs to floating-point
or rational representations (due to numeric properties of our problems).Now, even if this still sounds like a good fit for your project, at this point
you should probably consider using a more mature alternative or indeed rolling
your own solution tailored to your precise problem.Installationpip install heuristic_optimizationUsageSeeexamples/.CreditsBothtisimst/pyswarmandljvmiranda921/pyswarmsimplement
particle swarm optimization in Python and served as inspiration (but did not
quite fit the use case).
Package: heuristicsearch
Heuristic SearchesThis module contains functions to perform a* search and ao* search algorithmsInstallationRun the following command to install:pipinstallheuristicsearchUseagefromheuristicsearch.a_star_searchimportAStarfromheuristicsearch.ao_starimportAOStar# object creation Astar(adjacency_list -> dictionary, heuristic_values -> dicitonary)# call the apply_a_star method to find the shortest pathadjacency_list={'A':[('B',1),('C',3),('D',7)],'B':[('D',5)],'C':[('D',12)]}heuristics={'A':1,'B':1,'C':1,'D':1}graph1=AStar(adjacency_list,heuristics)graph1.apply_a_star(start='A',stop='B')# similar approach for AOStar# object creation AOStar(adjacency_list -> dictionary, heuristic_values -> dicitonary, startNode)# call apply_AOStar method
Package: heuristictree
heuristictreeHeuristic Methods for Minimizing Cut Bars and Using Leftovers from the One-dimensional Cutting Process - TREE Heuristic.Getting StartedDependenciesYou need Python 3.8 or later to useheuristictree. You can find it atpython.org.InstallationClone this repo to your local machine using:git clone https://github.com/omatheuspimenta/heuristictree.gitorpip install heuristictreeFeaturesIn this heuristic, the losses of the cutting process are concentrated on the smallest number of bars possible, using a tree structure, in order to become losses (unusable) into leftovers (usable).Examplefromheuristictreeimporttreeashtn=7L=30l=[7,9,11,14,19,21,26]d=[2,3,2,2,2,1,1]left=loss=bar=0x=[]left,loss,bar,x=ht.tree(L=L,n=n,l=l,d=d)Input and ParametersL:Size of bar to be cutting.(int)l:Lenght of items to be cutting.(list)d:Demand of items to be cutting.(list)smallitem:Size of small item. Default is the smallest item to be cutting.(int)Outputleft:Leftover from the cutting process.(int)loss:Loss from the cutting process.(int)bar:Bar number used in the cutting process.(int)x:Cutting pattern.(list)ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.CitationIf you use this software in your work, please cite our paper. (soon)LicenseMIT