Saravanan666/pypi-org huggingface dataset:
Package: horizon-hpe-storage-ui
Hewlett Packard Enterprise Storage DashboardFree software: Apache licenseOverviewThis plug-in extends the OpenStack Horizon Dashboard and provides useful features for OpenStack environments that use HPE 3PAR for backend storage.This plug-in adds an “HPE Storage” panel to the Admin dashboard, and provides diagnostic and discover tools to help administrators better manage their OpenStack Cinder environment and HPE 3PAR StoreServ backend storage arrays.Key features:Validate OpenStack Cinder configuration file (cinder.conf) entries to ensure they are properly specified.Validate required software packages and drivers are installed on Cinder and Nova nodes.Provide detailed Horizon views of all HPE Storage Arrays configured for Cinder backend storage.Provide a direct link between OpenStack volumes and their associated detail views in the HPE storage management console (HPE 3PAR SSMC).Query Nova nodes for volume paths and associated attached Cinder volumes.RequirementsThe following packages are required for this plug-in:OpenStack Barbican (https://pypi.python.org/pypi/python-barbicanclient)HPE Storage Diagnostic Tool (https://pypi.python.org/pypi/cinderdiags)Both of these packages will be installed automatically when this plug-in is installed.This plug-in is only intended for use on systems running OpenStack Horizon.Installation instructionsIn a Devstack environment, add the following to your Devstack local.conf file:enable_plugin barbican https://github.com/openstack/barbican.git
enable_plugin horizon-hpe-storage-ui https://github.com/hpe-storage/horizon-hpe-storage-ui.gitOr, to add to existing OpenStack deployment:cd horizon
cd ..
# create new package directory at same root path as Horizon
git clone https://github.com/hpe-storage/horizon-hpe-storage-ui.git
# install package
cd horizon-hpe-storage-ui
sudo pip install --upgrade .
# copy configuration file so that Horizon loads the plug-in
cp -a horizon_hpe_storage/enabled/* ../horizon/openstack_dashboard/local/enabled

# re-start apache server running Horizon
cd ../horizon
sudo service apache2 restartAfter reloading the Horizon dashboard in your browser, log-in as an “Admin” user. If the plug-in was successfully loaded, you should see a new “HPE Storage” panel listed at the bottom of the “Admin” section.Uninstalling the plug-inUninstall the python package and remove the config files:sudo pip uninstall horizon-hpe-storage-ui
rm horizon/openstack_dashboard/local/enabled/*_hpe_storage_admin_panel.*
Package: horizon-hwm-store
horizon-hwm-storeis a Python library to interact with Horizon service by saving and retrieving HWM.RequirementsPython 3.7+DocumentationSeehttps://horizon-hwm-store.readthedocs.io/Installationpipinstallhorizon-hwm-storeDevelopClone repoClone repo:gitclonehttps://github.com/MobileTeleSystems/horizon-hwm-store.git-bdevelopcdhorizon-hwm-storeSetup environmentCreate virtualenv and install dependencies:python-mvenvvenvsourcevenv/bin/activatepipinstall-Uwheelpipinstall-Upipsetuptoolspipinstall-U\-rrequirements.txt\-rrequirements-dev.txt\-rrequirements-docs.txt\-rrequirements-test.txtEnable pre-commit hooksInstall pre-commit hooks:pre-commitinstall--install-hooksTest pre-commit hooks run:pre-commitrunTestsStart all containers with dependencies:docker-composeup-dLoad environment variables with connection properties:source.env.localRun tests:./run_tests.shYou can pass additional arguments, they will be passed to pytest:./run_tests.sh-ksometest-lsx-vvvv--log-cli-level=INFOStop all containers and remove created volumes:docker-composedown-v
Package: horizon-openfoam
This repository provides a horizon dashboard for the OpenFOAM cloud
application. To use it, you must also install thebackend
application.Installing via pip to an existing OpenStack Horizon installationYou can install the horizon-openfoam dashboard via pip package manager:pip install horizon-openfoamEditopenstack_dashboard/local/local_settings.pyand add the
following parameters at the end:OFCLOUD_API_URL         = 'your_ofcloud_api_url'
S3_ACCESS_KEY_ID        = 'your_s3_access_key_id'
S3_SECRET_ACCESS_KEY    = 'your_s3_secret_access_key'
S3_HOST                 = 's3 host'
S3_PORT                 = 443TheOFCLOUD_API_URLis the root URL of theOpenFOAM
Backend.To enable the dashboard copy_6010_horizon-openfoam.pytoopenstack-dashboard/openstack_dashboard/local/enabled(usually under/usr/share)After installing restart your apache2 server where horizon is running.Ubuntu/debian:systemctl restart apache2.serviceCentOS:systemctl restart httpd.serviceInstalling locallyIn order to use the OpenFOAM Horizon dashboard, one must first clone the
OpenStack’s Horizon project and checkout the Liberty version:git clone https://github.com/openstack/horizon.git
git checkout stable/libertyInstall the required packages (we suggest to use virtualenv for this):cd horizon
pip install -r requirements.txtThen add theofclouddashboard submodulecd horizon/openstack_dashboard/dashboards/
git submodule add --name ofcloud https://github.com/mikelangelo-project/openfoam-ui.git ofcloudIn order to enable the dashboard, go tohorizon/openstack_dashboard/enabled. This directory contains several
files configuring the dashboards and panels. File ordering is important
in that it sets the structure of the Horizon dashboard.Create a file in this directory, for example_50_ofcloud.pyand copy
the following content:# The name of the dashboard to be added to HORIZON['dashboards']. Required.
DASHBOARD = 'ofcloud'

# If set to True, this dashboard will not be added to the settings.
DISABLED = False

# A list of applications to be added to INSTALLED_APPS.
ADD_INSTALLED_APPS = [
    'openstack_dashboard.dashboards.ofcloud',
]Finally, edit the local settings file
(horizon/openstack_dashboard/local/local_settings.py) and put the
following settings (replace with values appropriate to your system
setup):OFCLOUD_API_URL         = 'ofcloud-backend-url'
S3_ACCESS_KEY_ID        = 'your-s3-key'
S3_SECRET_ACCESS_KEY    = 'your-s3-secrect-key'
S3_HOST                 = 's3-host'
S3_PORT                 = s3-portTheOFCLOUD_API_URLis the root URL of theOpenFOAM
Backend.RunningStart the OpenStack Horizon application, login and look for the OpenFOAM
Cloud dashboard.cd horizon
python manage.py runserver 0.0.0.0:8000AcknowledgementsThis project has been conducted within the RIAMIKELANGELO
project(no. 645402), started in
January 2015, and co-funded by the European Commission under the
H2020-ICT- 07-2014: Advanced Cloud Infrastructures and Services
programme.
Package: horizon_overrides_plugin
Simple Horizon plugin which solves plugin overrides hell !ProblemHorizon supports only one overrides.py file. But if you have more than one plugin with overrides.py maybe you want include all overrides.py files.RequirePython 2.6 +Openstack Dashboard Icehouse +Installation notespipinstallhorizon-overrides-pluginINSTALLED_APPS+=('horizon_overrides',)HORIZON_CONFIG['customization_module']='horizon_overrides.overrides'Usageall overrides.py files will be included in defeault stateyou can specify OVERRIDES = [‘my_plugin’,’my_second_plugin.overrides’, ‘another_plugin.will_be_overrides’] in settings.py which restrict includesOVERRIDES=['my_plugin','my_second_plugin.overrides','another_plugin.will_be_overrides']NOTE: all plugins must be in the INSTALLED_APPS tupleFull example configINSTALLED_APPS=("horizon_overrides","horizon_telemetry","horizon_monitoring","horizon_billing",)HORIZON_CONFIG['customization_module']='horizon_overrides.overrides'OVERRIDES=("horizon_telemetry.overrides","horizon_monitoring","horizon_billing.another_name_for_override_file",)Read morehttp://docs.openstack.org/developer/horizon/topics/tutorial.html
Package: horizons
horizonsA python client for theJPL HORIZONS System.This is an ugly regex fueled API. JPL has a much cleanerSSD/CNEOS API Servicethat overlaps with HORIZONS in some places. HORIZONS' orbital element data on "Major Bodies" (i.e. planets, moons, and some others) are not available yet in this other collection of APIs. This project only aims to cover those features.Only getting position and velocity vectors of major bodies is supported. This project could be extended to pull from other features of HORIZONS, like retrieving orbital elements.UsagefromhorizonsimportHorizonswithHorizons()ash:bodies=h.get_major_bodies()# equivalent to 'MB' in HORIZONSprint(bodies)# [#   ...,#   horizons.BodyResult(#     id='301',#     name='Moon',#     designation='',#     other='Luna'#   ),#   ...# ]moon_vectors=h.get_vectors('301',center='399')print(moon_vectors)# horizons.VectorsResult(#   epoch_jd_tdb=2458642.5,#   calendar_date_tdb='A.D. 2019-Jun-08 00:00:00.0000',#   pos_km=(#     -268370.0664760619,#     252047.1714898835,#     16377.37006983293#   ),#   vel_kmps=(#     -0.7239795957732902,#     -0.7759062564667508,#     0.08457449888090685#   )# )
Package: horizon-sensu-dashboard
Horizon Monitoring DashboardSensu dashboard as Horizon plugin.Allows list events from multi Sensu APIs aka Uchiwa datacenters.Known Error Database as optional service provide store for your errors and workarounds.Monitoring, issues and solutions in one dashboard.OverviewInstallation notesRequirementsConfiguration SensuConfiguration KEDBRead moreOverviewThis plugin provideMonitoringdashboard with these panelsCurrent EventsEvent StahesService ChecksAggregationsMonitored ClientsMonitoring Statusoptionaly with configured KEDB is there two additional panelsKnown ErrorsWorkaroundsInstallation notesRequirementsOpenstack HorizonSensu API >= 0.16.0KEDB is optionalpipinstallhorizon-sensu-dashboardConfiguration Sensuadd ‘horizon_monitoring’ toINSTALLED_APPStupleadd ‘monitoring’ to ‘dashboards’ key inHORIZON_CONFIGand config for your Sensu APISENSU_HOST='localhost'SENSU_PORT=4567for more Sensu APIs write thisSENSU_API={'DC1':{'host':'10.10.10.10'},'DC2':{'host':'10.10.10.11','port':9999,'icon':'fa fa-cloud'},}for custom check filter you could write thisdefcheck_filter(check):return":".join(check['name'].split("_")[1:-1])SENSU_CHECK_FILTER=check_filterthis filter is applied on check in event view, default returns check name.Configuration KEDBif you are using serviceKEDBput this into yoursettings.py:KEDB_HOST='localhost'KEDB_PORT=6754Read morehttp://docs.openstack.org/developer/horizon/topics/tutorial.htmlhttp://sensuapp.org/docs/0.16/apihttp://docs.openstack.org/developer/horizon/_modules/horizon/tables/base.htmlhttp://docs.openstack.org/developer/horizon/ref/tables.htmlhttp://nagios.sourceforge.net/docs/3_0/flapping.htmlhttps://github.com/ehazlett/sensu-py/https://github.com/tcpcloud/kedb.git
Package: horizont
horizont implements a number of topic models. Conventions fromscikit-learnare
followed.The following models are implemented using Gibbs sampling.Latent Dirichlet allocation (Blei et al., 2003; Pritchard et al., 2000)(Coming soon) Logistic normal topic model(Coming soon) Dynamic topic model (Blei and Lafferty, 2006)Getting startedhorizont.LDAimplements latent Dirichlet allocation (LDA) using Gibbs
sampling. The interface follows conventions inscikit-learn.>>>importnumpyasnp>>>fromhorizontimportLDA>>>X=np.array([[1,1],[2,1],[3,1],[4,1],[5,8],[6,1]])>>>model=LDA(n_topics=2,random_state=0,n_iter=100)>>>doc_topic=model.fit_transform(X)# estimate of document-topic distributions>>>model.components_# estimate of topic-word distributionsRequirementsPython 2.7 or Python 3.3+ is required. The following packages are also required:numpyscipyscikit-learnfutures (Python 2.7 only)GSLis required for random number
generation inside the Pólya-Gamma random variate generator. On Debian-based
sytems, GSL may be installed with the commandsudoapt-getinstalllibgsl0-dev.  horizont looks for GSL headers and libraries in/usr/includeand/usr/lib/respectively.Cython is needed if compiling from source.Important linksDocumentation:http://pythonhosted.org/horizontSource code:https://github.com/ariddell/horizont/Issue tracker:https://github.com/ariddell/horizont/issuesLicensehorizont is licensed under Version 3.0 of the GNU General Public License. See
LICENSE file for a text of the license or visithttp://www.gnu.org/copyleft/gpl.html.
Package: horkos
HorkosA library for validating data at the edges of data systems.Installpip install horkosDocumentationDetailed documentation can be found onRead the Docs.UsageFirst define the data schema:# http-requests-schema.yamlname:"http_requests"description:>-This is the http request event data set, it is all about http requests wereceive. It's important to include as much information about itas is reasonable. The hardest thing about data is understanding it afterthe fact.fields:path:type:stringdescription:>-The path of the url that was hit. This will be everything after thehost portion of the url.params:type:stringnullable:truechecks:-jsondescription:>-The parameters of the http request. If the method is a `GET` these comefrom the url otherwise they are the JSON from the request body.method:type:stringchecks:-name:choiceargs:options:-DELETE-GET-HEAD-OPTIONS-PATCH-POST-PUTdescription:>-The http method of the request. Must be one of:`DELETE`, `GET`, `HEAD`, `OPTIONS`, `PATCH`, `POST`, or `PUT`.response_code:type:integerdescription:The http response code of the requesttimestamp:type:stringchecks:-iso_timestampdescription:The time at which the http request was received.To use this schema to validate records:importhorkosschema=horkos.load_schema('http-requests-schema.yaml')schema.process({'path':'/foo/bar'})# RecordValidationError: Casting errors - params is required, method is required, ...schema.process({'path':'/foo/bar','params':'{"foo": "bar"}','method':'BAD','response_code':'200','timestamp':'2020-06-15T12:34:56',})# RecordValidationError: Check errors - "BAD" in method did not pass choice check, ...schema.process({'path':'/foo/bar','params':'{"foo": "bar"}','method':'GET','response_code':'200','timestamp':'2020-06-15T12:34:56',})# {..., 'response_code': 200, ...}CLIIt's also possible to usehorkosvia cli to validatecsvandjsonfiles.path,params,method,response_code,timestamp
/foo/bar,,GET,200,2020-06-15T12:34:56
/fizbuz,{"param":"value"},POST,200,2020-12-15T12:34:56
/fizbuz,,ERROR,500,2020-12-15T12:34:56
/fizbuz,,GET,BAD,2020-12-15T12:34:56To validate the csv run:$ horkos check -s http-requests-schema.yaml data.csv
[Row 2]: Check errors - value of "ERROR" for method did not pass choice check
[Row 3]: Casting errors - value of "BAD" for response_code could not be cast to integer
2 errors found
Package: horkos-doc
Horkos DocA command-line tool for generating HTML documentation fromhorkosschemasInstallpip3 install horkos-docUsage> horkos-doc --help
usage: horkos-doc [-h] [--config CONFIG] [--author AUTHOR]
                  [--home-page HOME_PAGE] [--output OUTPUT]
                  [input]

positional arguments:
  input                 A directory of schema files from which to build the
                        html documentation. This is not required if a value is
                        set within the given config file.

optional arguments:
  -h, --help            show this help message and exit
  --config CONFIG, -c CONFIG
                        The path to a configuration file for horkos-doc. This
                        file can be used to override the built-in default for
                        command-line arguments. By default this is
                        `.horkos-doc`.
  --author AUTHOR, -a AUTHOR
                        The author of the documentation. This is used to
                        create copyright statements within the generated
                        documentation.
  --home-page HOME_PAGE, --hp HOME_PAGE
                        The name to use for the home page of the generated
                        documentation. By default this is "Horkos Doc".
  --output OUTPUT, -o OUTPUT
                        The directory in which to store built html. By default
                        this is ./buildIf all the schema files are in./schemasto build the docs run:horkos-doc ./schemasConfigurationAll options available on the command-line can also be set in an optional
configuration file. By default this file is expected to be.horkos-doc.[default]
input = ./schemas
output = ./docs
author = Mr. Foobar
home_page = The Docs!
Package: hornbill4p
python client for hornbilltest in python3.6# use case:## classify```pythonimport hornbill4phost = 'algorithm3'port = 50051client = hornbill4p.HornbillRpcClient(host, port)res = client.classify("是个宝宝儿", ["ADTWT"])print(res)``````bash> ADTWT$1```## batch_classify```pythonimport hornbill4phost = 'algorithm3'port = 50051client = hornbill4p.HornbillRpcClient(host, port)res = client.batch_classify(["是个宝宝儿", "是个宝宝儿"], ["ADTWT"])for i in res:print(i)``````bash> ADTWT$1> ADTWT$1```# install```bashgit clone https://git.datatub.com/hornbill/hornbill4p.git``````bashpip install -r requirements.txtpython setup.py install```
Package: hornet
hornetWARNINGThis library is currently under development and is not functional.The hornet library aims to provide a relatively simple interface for working
with stacking nested configurations from multiple sources.  These sources may be
JSON files, YAML files, specially formatted environment variables, databases, or
anything else that you can dream up.Basic UsageTODOFeaturesTODODocumentationTODOInstallationThe recommended way to install is usingpiporconda:pip install hornet
conda install hornetOr it can be installed from source usingsetuptools:python setup.py installBugs and issuesIf you find a bug, let me know athttps://github.com/bheklilr/hornet/issues.  Or
if you feel really motivated, write the fix and submit a pull request.LicenseI’m using MIT because that’s what I’m most familiar with, but really I don’t
care who uses this software or for what reason.  I make no claim to its accuracy
or reliability, use at your own risk.  This is just a side project for me, so
don’t expect too much.  If you need it under a different license, just shoot me
an email and I’ll work with you on how to make that happen.
Package: horn-py
Horn: A Flask scaffolding toolInstallation$pipinstallhorn-pyUsageUsage:
  horn new <target> [--app=<app> --proj=<proj> --pypi=<pypi> --bare]
  horn new <target> <from> [<checkout>] [--json=<json>] [-f=PATH | --file=PATH]
  horn gen api <module> <table> <fields>...
  horn gen model <module> <table> <fields>...
  horn gen schema <module> (<fields>... | --model=<model> | <fields>...  --model=<model>)
  horn -h | --help
  horn --version

Options:
  --app=<app>               App name [default: app].
  --proj=<proj>             Project name.
  --pypi=<pypi>             Pypi domain.
  --bare                    Bare project.

  --json=<json>             Json string [default: {}].
  -f=PATH, --file=PATH      Json file PATH.

  --model=<model>           Schema baseed on model.

  -h, --help                Show this screen.
  --version                 Show version.

Examples:
  horn new tmp/foo_bar --app foobar --proj FooBar
  horn new tmp/foo_bar https://github.com/bigfang/drf-starter.git --json '{"app":"someapp"}'
  horn gen api Post posts title:string:uniq content:text:nonull author:ref:users
  horn gen model Post posts title:string:uniq:index content:string:nonull author:ref:users:nonull
  horn gen schema Post title:string content:string author:nest:user

Notes:
  Model attrs:  uniq => unique=True, nonull => nullable=False,
                index => index=True, default:val => default=val
  Schema attrs: dump => dump_only, load => load_only, exclude => exclude,
                required => required=True, none => allow_none=True
Package: horology
HorologyConveniently measures the time of your loops, contexts and functions.Installationhorology versioncompatible python1.43.10-3.121.33.8-3.111.23.6-3.91.13.6-3.8Horology can be installed with PIP. It has no dependencies.pip install horologyUsageThe following 3 tools will let you measure practically any part of your Python code.Timing an iterable (list, tuple, generator, etc)Quick examplefromhorologyimportTimedanimals=['cat','dog','crocodile']forxinTimed(animals):feed(x)Result:iteration    1: 12.0 s
iteration    2: 8.00 s
iteration    3: 100 s

total 3 iterations in 120 s
min/median/max: 8.00/12.0/100 s
average (std): 40.0 (52.0) sCustomizationYou can specify where (if at all) you want each iteration and summary to be printed, eg.:forxinTimed(animals,unit='ms',iteration_print_fn=logger.debug,summary_print_fn=logger.info):feed(x)Timing a function with a@timeddecoratorQuick examplefromhorologyimporttimed@timeddeffoo():...Result:>>> foo()
foo: 7.12 msCustomizationChose time unit and name:@timed(unit='s',name='Processing took ')defbar():...Result:>>> bar()
Processing took 0.185 sTiming part of code with aTimingcontextQuick exampleJust wrap your code using awithstatementfromhorologyimportTimingwithTiming(name='Important calculations: '):...Result:Important calculations: 12.4 sCustomizationYou can suppress default printing and directly use measured time (also within context)withTiming(print_fn=None)ast:...make_use_of(t.interval)Time unitsTime units are by default automatically adjusted, for example you will seefoo: 7.12 msrather thanfoo: 0.007 s. If you don't like it, you can
override this by setting theunitargument with one of these names:['ns', 'us', 'ms', 's', 'min', 'h', 'd'].ContributionsContributions are welcomed, seecontribution guide.InternalsHorology internally measures time withperf_counterwhich provides thehighest available resolution,seedocs.
Package: horoscope
=====horoscope=====A Python module to fetch and parse data from Ganeshaspeaks.Installation============Install using pip:pip install horoscopeUsage=====from horoscope import Horoscopeyour_horoscope = Horoscope.get_todays_horoscope ('Libra')#do stuff with the parsed datayour_horoscope['date']your_horoscope['sunsign']your_horoscope['horscope']Features========Currently implemented---------------------* Today's Horscope* Weekly Horoscope* Monthly Horoscope* Yearly HoroscopeTodo----* Personality Profile* Facts About a Sunsign* Practical Side of a Sunsign* Astrological Perspective of a Sunsign* More information about a sunsign
Package: horpy
HPyHPy is a script created for educational purposes. It plots graphs of the radial and angular part of the wave function of the hydrogen atom, a topic covered in early quantum chemistry courses.
Enjoy!!Installation$ pip install horpy 
or
$ pip3 install horpyExamplesIn the first example, it is the radial part of the wave function of the hydrogen atom. The quantum numbers n and l are 2 and 0, respectively.In the second example, it is the angular part of the wave function of the hydrogen atom. The quantum numbers l and m are 3 and 0, respectively.
Package: horriblesubs-batch-downloader
Often times I find that HorribleSubs does not upload a single torrent
containing all episodes of an anime, or as they call them,batches.This scraper will search all their shows given a search word (via
command line or after prompt during program execution), and download all
episodes of the desired show in the highest resolution available.Demo
videohttps://www.youtube.com/watch?v=0FqFxD7GCI8&feature=youtu.beFeaturesre-uses previous list of shows scraped from the site that gets saved
in a text file if not expiredasks user which show they wanted if there is more than one match
foundRequirementsPython 3.5+xdg-openif using UnixSoftware that can download content from a magnet link (e.g.:transmission,tixati,BitTorrent, etc.)Installpip install-Uhorriblesubs-batch-downloaderorclone this repocd horriblesubs_batch_downloaderpython setup.py installUsageHere’s some examples. There’d actually be prompts for the user to go through
for each one to select the desired show.hsbd "one piece"
hsbd jojo
hsbd naruto
hsbd --helpNote: it will save the shows in the current working directory ($PWD) and
attempt to load cached info from the HS site so it’s better to cd to a directory
like Downloads first.