Saravanan666/pypi-org huggingface dataset:
Package: hnxbeta
Hnxbeta is a development version of HyperNetX
intended for super users to test and give feedback.
Please install in a virtual environment and send comments
and bug reports tohypernetx@pnnl.gov.The HyperNetX library provides classes and methods for complex network data.
HyperNetX uses data structures designed to represent set systems containing
nested data and/or multi-way relationships. The library generalizes traditional
graph metrics to hypergraphs. It can be found athttps://github.com/pnnl/HyperNetXHnxbeta has C++ support available from the NWHypergraph library.
It is available viapip install nwhy.
This library is still in development and will be updated frequently on PyPI.
At present it is only available for OSX and Centos7.
To use, firstconda install tbbin your environment, note that pip does not
install the correct version of tbb at present.
Package: hoard
Hoard (CLI)This utility allows you to pull variables for a project from your [treasure]hoard.InstallationUse your favourite python package installer:pip install hoardConfigurationSet your hoard url and default environment in~/.hoardrc:[hoard]
url=<some_url>
env=devSet your project name in your project’s.hoard(ideally in your project’s top level directory):[hoard]
project=<project_name>UsageGet your auth token from the server backend:hoard loginList environments for a project, with overrides for project and env:hoard get [--project] [--env]Set one or more environment variables, with overrides for project and env:hoard set [--project] [--env] KEY=value [KEY=value,...]Delete one or more environment variables, with overrides for project and env:hoard rm [--project] [--env] KEY [KEY,...]Project specific commands, e.g. show the current project, list envs for current project, list all projects:hoard project [project] [--envs] [--all]Environment specific commands, e.g. show the current env, list all envs:hoard env [--all]Clear your local auth token:hoard logoutChangelog for Trove (CLI)1.0Initial release.
Package: hoarder
Django analytics kit for the data-obsessed.Hoarder in an event tracking API for Django that supports multiple analytics backends: KISSMetrics, Google Analytics, local MongoDB storage.Hoarder is for you if:You want to use multiple web analytics tools without duplicating code for each of themYou want to be able to swap analytics packages without changing your codeYou want to have a local copy of all your analytics dataInstallationRunpip install hoarderAdd‘hoarder’app toINSTALLED_APPSAdd‘hoarder.middleware.LoggingMiddleware’and‘hoarder.middleware.DeduplicationMiddleware’toMIDDLEWARE_CLASSESAdd the following to the beginning of head section in your base template:{% load hoarder_tags %}
{% tracking_code %}Specify the backends you want to use inHOARDER_BACKENDSsettings variableSupported backendshoarder.backends.LogBackend- just outputs all events to log for debug purposeshoarder.mongo.MongoBackend- stores all events in a local MongoDB databasehoarder.backends.KISSMetricsBackend- KISSMetrics integrationhoarder.ga.GABackend- Google Analytics integrationSettingsHOARDER_BACKENDS- list of enabled backendsHOARDER_MONGO_DATABASE- for Mongo backend, name of the database to useKISSMETRICS_API_KEY- for KISSMetrics backend, the API key from your KISSMetrics accountUsageRegistering an event in view:from hoarder import register_request_event
...
register_request_event(request, 'signed up', {'plan level' : 'Basic'})Registering an event outside of a view:from hoarder import register_request_event
...
register_user_event(user, 'billed', {'amount' : '49.99'})Labeling current visitor:from hoarder import label_visitor,
...
label_visitor(request, 'Nice person')
Package: hoa-utils
HOA utilsUtilities for the HOA format.InstallThe best way is to install the package from PyPI:pip install hoa-utilsAlternatively, you can install it from source (master branch):pip install git+https://github.com/whitemech/hoa-utils.gitWhat you'll findAPIs to create and manipulate HOA objectsCLI tools to about the HOA format.The implementation may not be very stable at the moment.Currently, the only supported CLI tool is:pyhoafparser: parse and validate a file in HOA format.DevelopmentIf you want to contribute, here's how to set up your development environment.InstallPoetryClone the repository:git clone https://github.com/whitemech/hoa-utils.git && cd hoa-utilsInstall the dependencies:poetry installTestsTo run tests:toxTo run only the code tests:tox -e py3.7To run only the code style checks:tox -e black-checktox -e isort-checktox -e flake8Intox.iniyou can find all the test environment supported.DocsTo build the docs:mkdocs buildTo view documentation in a browser:mkdocs serveand then go tohttp://localhost:8000AuthorsMarco FavoritoFrancesco FuggittiLicensehoa-utilsis released under the MIT License.Copyright 2020 WhiteMech
Package: hoba
HobaYet another secrets management toolkit based onpasswordstoreRequirementsgitgnupgpasspython 3.6+pip 19.0.1+Installation$ pip install git+https://github.com/m-kus/hobaUsageAll hoba commands work only if there is ahoba.ymlfile inside the current directory. File format will be described below.Storing and sharing secretsPass is a great alternative to Hashicorp Vault and other enterprise secret storages, cause it's simple, safe, and portable. In my team we came to a pretty convenient scheme without loosing in security.All passwords encryption key, api keys, certificates, etc. are kept in a pass repo, which is gpg-encrypted and stored in git;Pass allows to implement simple access control policy for each tree node with inheritance;Each developer has to generate gpg key and add pubkey to the pass repo (keys are stored in .gpg-keys file);All developers have to import all keys from the repo and set maximum trust level;You can do this manually, but there is a command which does pretty much the same:$ hoba syncHoba can also spawn a shell with overridedPASSWORD_STORE_DIRenvironment variable:$ hoba shell
$ passDeploying secretsBy default hoba looks for adefaultsection inside the configuration file.$ hoba genYou can also specify target env:$ hoba gen devSample hoba configuration file:password-store:repo_url:http://github.com/example.gitrepo_dir:./.password-storeenvironments:dev:default:prod:targets:-type:env_fileoutput:./.secrets/{ENV}.envvariables:-DB_PASSWORD={ENV}/postgresql/passwordexcept:-dev-type:diroutput:./.secretsfiles:-ssl/example.com/cert_key:ssl/cert_key-ssl/example.com/dh_params:ssl/dh_paramsonly:-prod-type:keyringoutput:./.secrets/keyring_pass.cfgentries:-app@telegram:{ENV}/telegram/bot_api_keyDocker compose integration example:version:"3.1"services:nginx:environment:env_file:-./.secrets/dev.envsecrets:-cert_key-dh_params-source:keyringtarget:/root/.local/share/python_keyring/keyring_pass.cfgsecrets:cert_key:file:./.secrets/ssl/cert_keydh_params:file:./.secrets/ssl/dh_paramskeyring:file:./.secrets/keyring_pass.cfg
Package: hobart-svg
hobart-svgRender polygons, polylines, and mesh cross sections to SVG.FeaturesRender 2D and 3D polygons and polylines to SVG, with automatic computation
of the bounding rectangle.Render cross sections oflacecore-style polygonal meshes.Installationpipinstallhobart-svgUsagepython-mhobart_svg.clihorizontal-xs\--referencevitra_with_xs.dae\examples/vitra/vitra_without_materials.obj\15304560fromhobart_svgimportrender_longest_xsection_to_svgimportlacecoreimportnumpyasnpfrompolliwogimportPlaneimportvgmesh=lacecore.load_obj(filename="mesh.obj",triangulate=True)plane=Plane(point_on_plane=np.array([0.0,30.0,0.0]),unit_normal=vg.basis.y)render_longest_xsection_to_svg(mesh=mesh,plane=plane,filename="cross_section.svg")fromhobart_svgimportrender_longest_xsection_to_svgimportlacecorefrompolliwogimportPlanefromtri_againimportScenemesh=lacecore.load_obj(filename="examples/vitra/vitra_without_materials.obj",triangulate=True)plane=Plane(point_on_plane=np.array([-0.869231,60.8882,-20.1071]),unit_normal=vg.normalize(np.array([0.,0.1,-1.])))xs=render_longest_xsection_to_svg(mesh=mesh,plane=plane,filename="vitra_cross_section.svg")Scene().add_meshes(mesh).add_lines(xs).write("vitra_with_cross_section.dae")ContributeIssue Tracker:https://github.com/lace/hobart-svg/issuesSource Code:https://github.com/lace/hobart-svgPull requests welcome!SupportIf you are having issues, please let us know.LicenseThe project is licensed under the two-clause BSD license.
Package: hobase
HoBaseDataBase основанная на sqlitedictУстановкаpip install hobaseПодключениеfromhobaseimport*db=Database()Использованиеfromhobaseimport*# Инициализация датабазыa=Database(autocommit=True)# Создание переменной "324234" в "123"a.set({"324234":"123123"},UserID(123))print(a.get(UserID(123)))# Вывод# Дополнение ещё одной переменнойa.set({"1":"23123"},UserID(123))print(a.get(UserID(123)))# Удаление переменной и проверкаa.delete(id=UserID(123),obj="324234")print(a.get(id=UserID(123)))# Закрытие датабазы и проверка outputprint(a)a.close()print(a)
Package: hobbit-core
Hobbit-coreA flask project generator. Based on Flask + SQLAlchemy + marshmallow + webargs.https://hobbit-core.readthedocs.io/zh/latest/InstallationInstall and update using pip(Still using Python 2? It is time to upgrade.):pip install -U "hobbit-core[hobbit]"  # just install hobbit cmd
pip install -U "hobbit-core[hobbit,hobbit_core]"  # recommended when use virtualenvA Simple ExampleInit project:hobbit --echo new -n demo -d /tmp/demo -p 5000 -t rivendell
cd /tmp/demo
pipenv install -r requirements.txt --pre && pipenv install --dev pytest pytest-cov pytest-env ipython flake8 ipdb
pipenv shellRun server:(demo) ➜  demo FLASK_APP=app/run.py flask run
 * Serving Flask app "app/run.py"
 * Environment: production
 WARNING: This is a development server. Do not use it in a production deployment.
 Use a production WSGI server instead.
 * Debug mode: off
 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)Run test:(demo) ➜  demo py.test
===================================================== test session starts ======================================================
platform darwin -- Python 3.7.0, pytest-5.0.1, py-1.8.0, pluggy-0.12.0 -- /Users/Legolas/.virtualenvs/demo-OzheZQoG/bin/python3.7
cachedir: .pytest_cache
rootdir: /private/tmp/demo, inifile: pytest.ini
plugins: env-0.6.2, cov-2.7.1
collected 2 items

tests/test_option.py::TestOption::test_options PASSED
tests/test_ping.py::TestAPIExample::test_ping_api PASSED

---------- coverage: platform darwin, python 3.7.0-final-0 -----------
Name                         Stmts   Miss  Cover   Missing
----------------------------------------------------------
app/__init__.py                  0      0   100%
app/configs/__init__.py          0      0   100%
app/configs/default.py           6      0   100%
app/configs/development.py       1      1     0%   1
app/configs/production.py        2      2     0%   1-3
app/configs/testing.py           8      0   100%
app/core/__init__.py             0      0   100%
app/exts.py                      8      0   100%
app/models/__init__.py           2      0   100%
app/models/consts.py             1      0   100%
app/run.py                      35      1    97%   49
app/schemas/__init__.py          2      0   100%
app/services/__init__.py         2      0   100%
app/services/option.py           6      0   100%
app/tasks/__init__.py            1      1     0%   1
app/utils/__init__.py            0      0   100%
app/views/__init__.py            2      0   100%
app/views/option.py              5      0   100%
app/views/ping.py                7      0   100%
tests/__init__.py               17      1    94%   29
tests/conftest.py               11      0   100%
tests/test_option.py             5      0   100%
tests/test_ping.py               5      0   100%
----------------------------------------------------------
TOTAL                          126      6    95%


=================================================== 2 passed in 0.24 seconds ===================================================Othershobbit --help
Package: hobo
Python package for working with HOBO data logger data.Specifically, this has been tested with CSV exports from Onset HOBO U23-001
data loggers. It may or may not handle data from other HOBO loggers, though
HoboWare likely produces a compatible CSV format for other similar hardware.License: As a work of the United States Government, this project is in the
public domain within the United States.2016-02-24  David A. Riggs, Physical Science Tech, Lava Beds National Monument
Package: hobohm
[DEPRECATED] hobohm[DEPRECATED] Note:hobohmhas been merged intogreedysubwhich should be used instead.greedysubimplements a better algorithm (typically giving larger subsets).Thehobohmprogram aims to select a non-redundant subset of DNA- or protein-sequences, such that all pairwise sequence identities
are below a given threshold.The program takes as input (1) a text-file containing a list of pairwise similarities between sequences (name1 name2 similarity), and (2) a cutoff for deciding when two sequences are too similar (i.e., when they are "neighbors").The output (written to file) is a list of names that should be kept in the subset. No retained items are neighbors, and the algorithm aims to pick the maximally sized such set, given the cutoff. (Note that this is a hard problem, and this heuristic is not optimal. See  notes on computational intractibility of the problem and performance of heuristics in thegreedysub README).The "Hobohm" algorithm was originally created with the purpose of selecting homology-reduced sets of protein data from larger datasets. "Homology-reduced" here means that the resulting data set should contain no pairs of sequences with high sequence identity:"Selection of representative protein data sets", Protein Sci. 1992. 1(3):409-17.This command-line program implements algorithm 2 from that paper, and can be applied to any type of data for which pairwise similarities (or distances) can be defined.AvailabilityThehobohmsource code is available on GitHub:https://github.com/agormp/hobohm. The executable can be installed from PyPI:https://pypi.org/project/hobohm/Installationpython3 -m pip install hobohmUpgrading to latest version:python3 -m pip install --upgrade hobohmDependencieshobohmrelies on thepandas package, which is automatically included when using pip to install.Usageusage: hobohm [-h] [--val VALUETYPE] [-c CUTOFF] [-k KEEPFILE] INFILE OUTFILE

Select non-redundant subset of DNA or protein-sequences, such that all pairwise
sequence identities are below threshold.

positional arguments:
  INFILE           input file containing similarity or distance for each pair of
                   items: name1 name2 value
  OUTFILE          output file contatining neighborless subset of items (one name per
                   line)

options:
  -h, --help       show this help message and exit
  --val VALUETYPE  specify whether values in INFILE are distances (--val dist) or
                   similarities (--val sim)
  -c CUTOFF        cutoff value for deciding which pairs are neighbors
  -k KEEPFILE      (optional) file with names of items that must be kept (one name per
                   line)
Package: hoboreader
hoboreaderPython package for reading Onset Hobo sensor csv filesAny problems?Please raise an Issue on GitHubTo install:pip install hoboreaderQuick demo:The following code reads a Hobo csv file and converts it to a pandas DataFrame:fromhoboreaderimportHoboReaderh=HoboReader('sample_hobo_data.csv')df=h.get_dataframe()The DataFrame looks like this:User GuideImporting the HoboReader class:fromhoboreaderimportHoboReaderCreating an instance of HoboReader and reading in a Hobo data csv file:Either:h=HoboReader()h.read_csv('sample_hobo_data.csv')or:h=HoboReader('sample_hobo_data.csv')Working with attributesAs the csv file is read in, a number of attributes are populated. These are:h.reader# a Python csv.reader objecth.header_row# a list of the header row of the csv fileh.header_list# a list of dictionaries with the header row informationh.hobo_timezone_str# a string of the timezone as expressed in the header rowh.timezone# a Python datetime.timezone instanceh.data_rows# a list of each row of the timeseries measured datah.data_columns# a list of each column of the timeseries measured datah.datetimes# a list of the timestamps converted to Python datetime.datetime instancesSee theattributes_demo.ipynbJupyter Notebook in the 'demo' section for more on these attributes.Creating a Pandas DataFrameA Pandas DataFrame can be created using:df=h.get_dataframe()See thedataframe_demo.ipynbJupyter Notebook in the 'demo' section for how to work with this dataframe.Creating rdf dataThe Hobo data can be converted to rdf data using:g=h.get_rdf()See therdf_demo.ipynbJupyter Notebook in the 'demo' section for how to work with the rdf data.Getting the sensor serial numberA function which return the sensor serial number:sn=h.get_sensor_serial_number()
Package: hocapontas
hocapontas is a small library built to provide an easy to use API when
developing ‘life-assisting’ applications in Python. Example areas where
hocapontas might be useful is when developing a CLI application for
managing your budget or a slackbot for planning and reminding your of
coming events. Just simple things, but simpler.An Early StageAs of this early stage in development, hocapontas doesn’t look like
much. It currently features a small task scheduler where task items
are made up of dictionaries to be easily passed on and manipulated in
which ever environment one desires.For storing data persistantly, a plain text file is used and contains
just the task items, no users or other metadata exists yet. Future
versions will include adapter APIs for communication between proper
databases.TODODatabase AdapterSupport for MongoDBSupport for multiple usersReminder Module (upcoming events, nag about incomplete tasks, etc.)Budget Planning ModuleLicenseGNU GPLv3
Package: ho-cho
Ho-ChoInstallMac# Install MeCabbrewinstallmecabmecab-ipadic# Install mecab-ipadic-neologdgitclone--depth1https://github.com/neologd/mecab-ipadic-neologd.git\&&cdmecab-ipadic-neologd\&&bin/install-mecab-ipadic-neologd-n-a-y&&cd..

pipinstallho-choUbuntu# Install MeCab and mecab-ipadic-neologdapt-getupdate&&apt-getinstall-ymecablibmecab-devmecab-ipadicmecab-ipadic-utf8# Install mecab-ipadic-neologdgitclone--depth1https://github.com/neologd/mecab-ipadic-neologd.git\&&cdmecab-ipadic-neologd\&&bin/install-mecab-ipadic-neologd-n-a-y&&cd..

pipinstallho-choWindowcoming soon ...Usage1. cleaningテキストのクリーニングhocho/cleaning.py2. tokenizing単語の分割hocho/tokenizer/impl/mecab_tokenizer.py3. normalization単語の正規化文字種の統一数字の置き換え辞書を用いた単語の統一hocho/normalization.py4. stopwordsストップワードの除去辞書による方法出現頻度による方法有名なストップワードを用いた除去方法hocho/stopwords.pyDevelopmentHow to developgitpulloriginmain

gitcheckout-bfeature/xxxx

gitadd.
gitcommit-m"xxx"gitpushoriginfeature/xxxRun testpytest-vtestsSet uppipinstall-e.Publish to TestPyPI# Install dependenciespipinstallsetuptoolswheeltwine# Buildpythonsetup.pysdistbdist_wheel# Publish to TestPyPItwineupload--repository-urlhttps://test.pypi.org/legacy/dist/*Publish to PyPI# Install dependenciespipinstallsetuptoolswheeltwine# Buildpythonsetup.pysdistbdist_wheel# Publish to PyPItwineuploaddist/*
Package: hockepy
____  ____    ____      ______  ___  ____   _________  ______    ____  ____
|_   ||   _| .'    `.  .' ___  ||_  ||_  _| |_   ___  ||_   __ \ |_  _||_  _|
  | |__| |  /  .--.  \/ .'   \_|  | |_/ /     | |_  \_|  | |__) |  \ \  / /
  |  __  |  | |    | || |         |  __'.     |  _|  _   |  ___/    \ \/ /
 _| |  | |_ \  `--'  /\ `.___.'\ _| |  \ \_  _| |___/ | _| |_       _|  |_
|____||____| `.____.'  `._____.'|____||____||_________||_____|     |______|(pronounced like hockey-py so probably something like/ˈhɑː.kipaɪ/)Important:Please keep in mind thathockepyis under active development
and any part can be changed anytime.Installationpip install hockepyCLI utilityThe main purpose ofhockepyis to provide a command line utility for geeky
hockey fans. The easiest way to discover the features currently implemented is
to display help:$ hockepy -h
usage: hocke.py [-h] [-D] [-v] {today,schedule} ...

positional arguments:
  {today,schedule}

optional arguments:
  -h, --help        show this help message and exit
  -D, --debug       turn debug output on
  -v, --verbose     turn verbose output onSubcommands also support-hoption:$ hockepy schedule -h
usage: hocke.py schedule [-h] [--home-first] [--utc]
                           [first_date] [last_date]

positional arguments:
  first_date    first date to get schedule for
  last_date     last date to get schedule for

optional arguments:
  -h, --help    show this help message and exit
  --home-first  print the home team first
  --utc         print times in UTC instead of local timeBear in mind that the actual help may differ as this listing won't necessarily
be updated with any feature addition/change.ConfigurationYou can highlight your favorite team using a configuration file called.hockepy.conf(an example is included in the repository):highlight_teams = [
    "Boston Bruins",
    "Pittsburgh Penguins",
]The file can be placed in the current working directory, your home directory or
in a directory specified by HOCKEPY_CONF_DIR (hockepy checks in that order).NHL APIAnother goal is to offer a Python interface to a subset of NHL API. Other
leagues may or may not be added as well but the main plan is to support NHL for
now.NHL API is available athttps://statsapi.web.nhl.com/api/v1/. I am not aware
of any available documentation so it's been discovering and trial-and-error for
me so far. If you know about any documentation, let me know.Please note that any usage of the API (and therefore usage ofhockepyas
well) is likely subject toNHL Terms of Service.
Package: hocker
HOCkeRPython package for combining hOCR files and images into searchable PDFsTable of ContentsWhat is hoCKeR?How to installHow to UseCreditsWhat is hOCkeR?HOCkeR is a Python package for combining hOCR files and images into searchable PDFs. The package lays the text on top of the image, and then creates a PDF with the text and image. The code used is fromHOCRConverterby jbrinley. The code was designed for Python 2, therefore does not work with newer version of python, so I created this package as an update to the original code.How to installTo install the package, run the following command within a python environment:pipinstallhockerIf any errors occur whilst installing, try using the .whl file insteadlinked hereHow to use hOCkeRBelow is an example of how to use hOCkeR to combine an png and a .hocr file into a PDFimporthockerashkrimage_path='path/to/image.png'hocr_path='path/to/image.hocr'# Specify the element in the hocr file to use as the texthocr=hkr.HOCRCombiner('ocrx_word')# For tesseract outputs, it is 'ocrx_word'# Specify the hocr and image pathhocr.locate_image(image_path)hocr.locate_hocr(hocr_path)# Output the PDFhocr.to_pdf('path/to/output.pdf')Credits & linkshOCKeRby Lucas WarwickHOCRConverterby jbrinley