Saravanan666/pypi-org huggingface dataset:
Package: hierts
hierTSHierachical Time Series(hierTS) is a lightweight package that offers hierarchical forecasting reconciliation techniques to Python users.For more details,read the docsor check out theexamples.ReferenceThe reconciliation methods that are currently in place are based on:Wickramasuriya, S. L., Athanasopoulos, G., & Hyndman, R. J. (2019). Optimal forecast reconciliation for hierarchical and grouped time series through trace minimization. Journal of the American Statistical Association, 114(526), 804-819.Ben Taieb, Souhaib, and Bonsoo Koo (2019). ‘Regularized Regression for Hierarchical Forecasting Without Unbiasedness Conditions’. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 1337–47. Anchorage AK USA: ACM, 2019.https://doi.org/10.1145/3292500.3330976.LicenseThis project is licensed under the terms of theApache 2.0 license.AcknowledgementsThis project was developed byAirlab Amsterdam.
Package: hievpy
HIEvPyHIEvPy is a python 3 wrapper around the API interface of theHIEv, a data capture
application used by theHawkesbury Institute for the EnvironmentatWestern
Sydney University.A short overview of the HIEvPy library, including installation instructions, is given below. Full
documentation, with examples, can be found on the project'sdocumentation pages.Pre-requisitesTo use HIEvPY you must have an active account (and subsequently a HIEv API token) on theHIEvapplication. To discuss registration please contact HIE's data manager,Gerry DevineInstallationHIEvPycan be installed viapip:$pipinstall--index-urlhttps://test.pypi.org/simple/hievpyNote: HIEvPy is currently hosted on Test PyPi. This will soon be moved to the official PyPi repositoryOnceHIEvPyhas been installed, you can import it into a python console or script using:importhievpyashp(using the optionalas hpas a shortcut)HIEvPy functionsGeneric functionssearch: Return a list of HIEv records matching a set of input search parameterssearch_download: Perform a hievpy search and automatically downloads the matching filesupload: Upload a file to HIEv with associated metadataupdate_metadata: Update metadata on a list of records returned by hievpy searchTOA5 functionstoa5_summary: Returns toa5 summary information (variable names, units and measurement types) for a given
individual search-returned record.search_loaf_toa5df: Performs a hievpy search and loads results into a pandas dataframe given the file recordsSee the project'sdocumentation pagesfor a full explanation of allHIEvPyfunctionsExamplesTheexamplesfolder contains a number of example scripts outlining usage of the differentHIEvPyfunctions.To run any of the example scripts you need to run hievpy.utils.make_credsfile() which creates a file github won't share calledcredentials.pyand populates it with your HIEv API tokenimport hievpy as hp
hp.utils.make_credsfile()LicenseCopyright (c) 2018 Gerry DevinePermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: hifibgc
HiFiBGCDetect Biosynthetic Gene Clusters (BGCs) in HiFi metagenomic data.InstallationCondaconda create -n hifibgc -c conda-forge -c bioconda -c amityadav -y hifibgcconda activate hifibgcUsageInstallhifibgc installAbove command need to be run only once. It installs a required database and a tool.Testhifibgc testChecks hifibgc on a small test data. On completion of above command, you should see something likeSnakemake finished successfullyon terminal and an output directoryhifibgc1.out.RunRun hifibgc with defaults:hifibgc run --input input.fastq# --input is requiredSpecify output directory and no of threads:hifibgc run --input input.fastq --output outdir --threads 16Specify bigscape_cutoff option:hifibgc run --input input.fastq --bigscape_cutoff 0.4Output05_final_output/ 
    BGC_all_metadata.tsv  -->  summary file containing metadata for all BGCs 
    BGC_representative/ -->  directory containing representative BGCs (.gbk files) 
    BGC_all/ -->  directory containing all BGCs (.gbk files) 
    upsetplot_0.3.[pdf|jpg] -->  upsetplot comparing three assemblers (hifiasm-meta, metaflye and hicanu), and unmapped reads
Package: hifigan-vocoder
hifiganA wrapped hifi-gan vocoder for easy use.Source:https://github.com/jik876/hifi-ganInstallpipinstallhifigan-vocoderUsagefromhifigan_vocoderimporthifigan,get_sample_melmel=get_sample_mel()print(mel.shape)# torch.Size([1, 80, 2062])model=hifigan(dataset='uni',device='cpu')# dataset in ['uni', 'vctk']; device in ['cpu', 'cuda']; checkpoint will be downloaded from google driver.audio=model.infer(mel)print(mel.shape)# (527872,)
Package: hifipower
# hifipowerhigh fidelity equipment power controller daemonA daemon running on an Orange Pi or RPi, exposing a web API for switching the audio equipment on or off, using a relay connected with one of the GPIO pins.This software reads a configuration file (/etc/hifipowerd.conf) and gets the pin numbers for shutdown and reboot buttons, automatic mode sense and relay drive output. Then the web API is started, exposing three endpoints:address/hifi/power(GET) - get the current state as JSON,address/hifi/power/on(GET) - turns the power on,address/hifi/power/off(GET) - turns the power off.Future featuresUse PulseAudio or ALSA to detect lack of audio signal on the input (configurable), then if no audio is present for a preset time (e.g. 10 minutes), turn the equipment off automatically. Prevents idle power draw by e.g. vacuum tube amplifiers.
Package: hifir4py
Welcome to the Python3 interface of HIFIR package—hifir4py. The Python
interface is implemented with Cython.Detailed documentation ofhifir4pycan be found athttps://hifirworks.github.io/hifir4py.InstallationOne can simply usepipto installhifir4py, i.e.,pip3 install hifir4py --userInstallation from SourceIt is also possible to install from the source. First, down load the most
recent stable releasegit clone -b release https://github.com/hifirworks/hifir4py.gitYou can update to the most recent version viagit pullsincegit cloneor lastgit pull. In addition, you can download the archives athttps://github.com/hifirworks/hifir4py/releases.You need to configure linking against LAPACK by setting the environment
variableHIFIR_LAPACK_LIBwhose default is-llapack. If you
have a specific library path to LAPACK, you then need to set the environment
variableHIFIR_LAPACK_LIB_PATH.To sum up, the following environment variables can be configuredHIFIR_LAPACK_LIB, default is-llapackHIFIR_LAPACK_LIB_PATH, default is emptypip3 install . --userInstallation with customized LAPACK/BLASSometimes, it’s helpful to have optimized LAPACK package. The following command
shows how to link MKL (on Ubuntu).HIFIR_LAPACK_LIB="-lmkl_intel_lp64 -lmkl_sequential -lmkl_core" HIFIR_LAPACK_LIB_PATH=/opt/intel/mkl/lib/intel64 pip3 install . --userCopyrights & Licenseshifir4pyis developed and maintained by the NumGeom Research Group atStony Brook University.This software suite is released under a dual-license model. For academic users,
individual users, or open-source software developers, you can use HIFIR under
theAGPLv3+license free of
charge for research and evaluation purpose. For commercial users, separate
commercial licenses are available through the Stony Brook University.
For inqueries regarding commercial licenses, please contact
Prof. Xiangmin Jiao atxiangmin.jiao@stonybrook.edu.How to Citehifir4pyIf you use HIFIR (includinghifir4py) in your research for nonsingular
systems, please cite the following paper.@article{chen2021hilucsi,author={Chen, Qiao and Ghai, Aditi and Jiao, Xiangmin},title={{HILUCSI}: Simple, robust, and fast multilevel {ILU} for
               large-scale saddle-point problems from {PDE}s},journal={Numer. Linear Algebra Appl.},year={2021},doi={10.1002/nla.2400}}If you use our work in solving ill-conditioned and singular systems, we
recommend you to cite the following papers.@article{jiao2020approximate,author={Xiangmin Jiao and Qiao Chen},journal={arxiv},title={Approximate generalized inverses with iterative refinement
              for $\epsilon$-accurate preconditioning of singular systems},year={2020},note={arXiv:2009.01673}}@article{chen2021hifir,author={Chen, Qiao and Jiao, Xiangmin},title={{HIFIR}: Hybrid incomplete factorization with iterative
               refinement for preconditioning ill-conditioned and singular
               Systems},journal={arxiv},year={2021},note={arXiv:2106.09877}}ContactsQiao (Chiao) Chen, <qiao.chen@stonybrook.edu>, <benechiao@gmail.com>Xiangmin Jiao, <xiangmin.jiao@stonybrook.edu>
Package: hiflow
HiFlowHiFlow是一个配置驱动的基于模块的工作流控制库。本库在2020年的下半年初具雏形，先后在多个AI部署项目中得到了使用。实践证明这样一个可配置工作流引擎可以让算法研发人员只关注于算法模块本身的实现，从而大大加速了项目的研发进度。虽然如此，在此之前该库还没有跟业务代码进行分离，整体实现上面耦合程度较高，我觉得有必要将该库从业务代码中抽离出来，以方便和加速后续项目的研发落地。在这一目标驱动下，我抽空重写了该库，并优化了底层逻辑设计，希望能为更多项目的部署贡献一份力量！更多信息请移步文档。
Package: higdon
This simple program generates a.icscalendar file from a Hal
Higdon training plan, tailored to a race day that you specify.UsageSpecify the URL of the plan you wish to use, and the target race day.
For example, to make a calendar for the 2015Eugene Marathon, using
theNovice 2plan:$NOVICE2=https://www.halhigdon.com/training-programs/marathon-training/novice-2-marathon/$higdon$NOVICE2"May 10, 2015"This generates a file,novice-2-marathon.2015-05-10.ics,
for loading into your favorite calendar app.InstallationUsingpip:$pip3installhigdonDevelopment version:$pip3install-egit+https://github.com/baldwint/higdon.git#egg=higdonOr, if you wish to install dependencies yourself, just downloadhigdon.pyand run that directly.
Package: highball
Highball!Python Web Framework built for learning purposeIt's a WSGI framework and can be used with any WSGI application server such as Gunicorn.InstallationpipinstallhighballHow to use itBasic usage:fromhighball.apiimportAPIapp=API()@app.route("/home")defhome(request,response):response.text="Hello from the HOME page"@app.route("/hello/{name}")defgreeting(request,response,name):response.text=f"Hello,{name}"@app.route("/book")classBooksResource:defget(self,req,resp):resp.text="Books Page"defpost(self,req,resp):resp.text="Endpoint to create a book"@app.route("/template")deftemplate_handler(req,resp):resp.body=app.template("index.html",context={"name":"highball","title":"Best Framework"}).encode()Unit TestsThe recommended way of writing unit tests is withpytest. There are two built in fixtures
that you may want to use when writing unit tests with highball. The first one isappwhich is an instance of the mainAPIclass:deftest_route_overlap_throws_exception(app):@app.route("/")defhome(req,resp):resp.text="Welcome Home."withpytest.raises(AssertionError):@app.route("/")defhome2(req,resp):resp.text="Welcome Home2."The other one isclientthat you can use to send HTTP requests to your handlers. It is based on the famousrequestsand it should feel very familiar:deftest_parameterized_route(app,client):@app.route("/{name}")defhello(req,resp,name):resp.text=f"hey{name}"assertclient.get("http://testserver/matthew").text=="hey matthew"TemplatesThe default folder for templates istemplates. You can change it when initializing the mainAPI()class:app=API(templates_dir="templates_dir_name")Then you can use HTML files in that folder like so in a handler:@app.route("/show/template")defhandler_with_template(req,resp):resp.html=app.template("example.html",context={"title":"Awesome Framework","body":"welcome to the future!"})Static FilesJust like templates, the default folder for static files isstaticand you can override it:app=API(static_dir="static_dir_name")Then you can use the files inside this folder in HTML files:<!DOCTYPE html><htmllang="en"><head><metacharset="UTF-8"><title>{{title}}</title><linkhref="/static/main.css"rel="stylesheet"type="text/css"></head><body><h1>{{body}}</h1><p>This is a paragraph</p></body></html>MiddlewareYou can create custom middleware classes by inheriting from thehighball.middleware.Middlewareclass and overriding its two methods
that are called before and after each request:fromhighball.apiimportAPIfromhighball.middlewareimportMiddlewareapp=API()classSimpleCustomMiddleware(Middleware):defprocess_request(self,req):print("Before dispatch",req.url)defprocess_response(self,req,res):print("After dispatch",req.url)app.add_middleware(SimpleCustomMiddleware)
Package: highchartexport
highchartexportConvert highchart configuration into an image file using export server of HighCharts, which ishttp://export.highcharts.com/InstallationYou can use pip commandpip install highchartexportExampleIn terminalhighchartexport --json "{\"chart\":{\"type\":\"area\"},\"series\":[{\"data\":[1,2,3,4,5,6],\"name\":\"areaplot\"}]}" --out area_chart.pnghighchartexport --json "{\"chart\":{\"type\":\"area\"},\"series\":[{\"data\":[1,2,3,4,5,6],\"name\":\"areaplot\"}]}" --out area_chart.png --width 2000 --scale 2Pass highchart json fileFor PNG image filehighchartexport --in hc_config.json --out area_chart.png --width 2000 --scale 2 --type pngFor SVG filehighchartexport --in hc_config.json --out area_chart.svg --width 2000 --scale 2 --type svgFor SVG file with StockCharthighchartexport --in hc_config.json --out area_chart.svg --chart StockChart --width 2000 --scale 2 --type svgFor PDF file with Map Charthighchartexport --in hc_config.json --out area_chart.svg --chart Map --width 2000 --scale 2 --type pdfImport in your Python programimporthighchartexportashc_exportconfig={"chart":{"type":'bubble',"plotBorderWidth":1,"zoomType":'xy'},"title":{"text":'Highcharts bubbles save in pdf file'},"series":[{"data":[[19,81,63],[98,5,89],[51,50,73],],"marker":{"fillColor":{"radialGradient":{"cx":0.4,"cy":0.3,"r":0.7},"stops":[[0,'rgba(255,255,255,0.5)'],[1,'rgba(200, 200, 200, 0.8)']]}}}]}# use default width and scale valuehc_export.save_as_pdf(config=config,filename="bubble.pdf")# you can pass width and scale valuehc_export.save_as_pdf(config=config,filename="bubble.pdf",width=1000,scale=4)
Package: highcompress
HighCompress + PythonPython package for the compressing images through Highcompress API. Highcompress compresses your images intelligently and efficiently. Get your Highcompress key fromhere!How to installpip install highcompressHow to useimport highcompress as hc

hc.key="Your_API_Key"

//Pass the path of image
hc.from_file("Image path")

hc.from_file("Image path","path to save compressed image")More Features coming soon like releasing setting levels etc.
Package: highdicom
High DICOMA library that provides high-level DICOM abstractions for the Python programming language to facilitate the creation and handling of DICOM objects for image-derived information, including image annotations, and image analysis results.
It currently provides tools for creating and decoding the following DICOM information object definitions (IODs):AnnotationsParametric Map imagesSegmentation imagesStructured Report documentsSecondary Capture imagesKey Object Selection documentsLegacy Converted Enhanced CT/PET/MR images (e.g., for single frame to multi-frame conversion)Softcopy Presentation State instances (including Grayscale, Color, and Pseudo-Color)DocumentationPlease refer to the online documentation athighdicom.readthedocs.io, which includes installation instructions, a user guide with examples, a developer guide, and complete documentation of the application programming interface of thehighdicompackage.CitationFor more information about the motivation of the library and the design of highdicom's API, please see the following article:Highdicom: A Python library for standardized encoding of image annotations and machine learning model outputs in pathology and radiologyC.P. Bridge, C. Gorman, S. Pieper, S.W. Doyle, J.K. Lennerz, J. Kalpathy-Cramer, D.A. Clunie, A.Y. Fedorov, and M.D. HerrmannIf you use highdicom in your research, please cite the above article.SupportThe developers gratefully acknowledge their support:TheAlliance for Digital PathologyTheMGH & BWH Center for Clinical Data ScienceQuantitative Image Informatics for Cancer Research (QIICR)RadiomicsTheNCI Imaging Data Commons
Package: higher-criticism-test
HCtest -- Higher Criticism TestHigher Criticism (HC) test statistics for testing the global significance of many independent hypotheses. As an input,
the test receives a list of P-values and returns the HC test statistics. See (Donoho & Jin 2004)Example:from scipy.stats import norm
from hctest import HCtest

n = 1000 #number of samples

X = norm.rvs(size=n)
pvals = norm.sf(X)

hc = HCtest(pvals)
hc_val, p_th = hc.HCstar(gamma = 0.25)

print("Higher-Criticism statistic = ", hc_val)
Package: higher-lower
higher-lowerFunctions for finding numbers using higher/lowerInstallationInstall this library usingpip:$ pip install higher-lowerhigher_lower(min_value, max_value, callback)Thehigher_lower()function searches for a value betweenmin_valueandmax_value, callingcallback()for each candidate value to see if the target is higher or lower.min_value- the lowest possible valuemax_value- the highest possible valuecallback(candidate)- a callback function that takes a single integer argument and returnsActualIs.MATCH,ActualIs.HIGHERorActualIs.LOWERFor example:fromhigher_lowerimportActualIsdefcallback(candidate):ifcandidate==7:returnActualIs.MATCHelifcandidate>7:returnActualIs.LOWERelse:returnActualIs.HIGHERGiven the above callback function, a search can be made for the number between 0 and 100 like so:fromhigher_lowerimporthigher_lowernumber=higher_lower(0,100,callback)# number is now 7DevelopmentTo contribute to this library, first checkout the code. Then create a new virtual environment:cd higher-lower
python -mvenv venv
source venv/bin/activateOr if you are usingpipenv:pipenv shellNow install the dependencies and tests:pip install -e '.[test]'To run the tests:pytest
Package: highfive
HighFive is a simple distributed processing framework designed so you and your friends can donate CPU time to each other to run large, interesting computations. It’s easy to spin up a HighFive master and connect as many remote workers as you want to it!Don’t want to lock down all your computers for hours while you wait for results? Since HighFive was designed for cooperative work, the workers can
disconnect at any time without harming the main process! Then, they can reconnect to the same process later and get back to work!HighFive is written in Python 3, and uses asyncio for managing connections. Because it uses async/await syntax, it is currently only supported by Python 3.5 and up.
Package: highghlow-pythonweb
PythonWEBA Flask wrapper for easy RESTful api developmentQuickstartimportpythonwebapp=pythonweb.Server()classExampleException(Exception):codename="ERR_EXAMPLE"verbose="This is an example exception. The specified exception params would be here:{0}and here:{1}"code=501@app.api("/api/example",form=False)# form=true means that you can use this api route as a form handlerdefexample_endpoint(param1:int,param2:bool):# Type annotations are not used by the serverifparam2:raiseExampleException(param1,param2,"Param")# 501 {"error":"ERR_EXAMPLE", "message":[param1, param2, "Param"], "verbose":"This is an example..."}return{"some_json":param1+1}
Package: highiq
This software conducts radar and lidar doppler spectra processing using the GPU. Complex autocorrelation
functions are converted to Doppler spectra and moments using CuPy, a NumPy-like interface for CUDA. A
CUDA-compatible GPU is required.Free software: 3-clause BSD licenseIn order to use HighIQ, you must install the version of CuPy for your
specific version of CUDA. In order to do so, follow the link below:https://docs.cupy.dev/en/stable/install.html
Package: highlevel-python
highlevel-pythonhighlevel-pythonis an API wrapper for highlevel, written in Python.This library uses Oauth2 for authentication.Installingpip install highlevel-pythonUsagefromhighlevel.clientimportClientclient=Client(client_id,client_secret,redirect_uri=redirect_uri)To obtain and set an access token, follow this instructions:Get authorization URLurl=client.authorization_url(state=None)# This call generates the url necessary to display the pop-up window to perform oauth authentication# param state(code) is required for direct request for oauth, for local test isn't necessaryGet access token using codetoken=client.get_access_token(code)# "code" is the same response code after login with oauth with the above url.Refresh access token using refresh_tokentoken=client.refresh_access_token(refresh_token)# "refresh_token" is the token refresh in response after login with oauth with the above url.Postman CollectionYou can find a Postman Collection with API routes and responses in:https://interstellar-desert-735390.postman.co/workspace/My-Workspace~0f763140-1ebb-48f5-8410-120620bf6c0c/collection/30746140-04303b39-b1da-42de-aee2-5ac4ffbda658?action=share&creator=30746140&active-environment=30746140-00ac4392-b9f1-4d92-86d7-710ce7a58ca6
Package: highlighter
highlighterEasy to use PEP 508 markers.  These are the strings in requirements after a
semicolon, such asenum34; python_version < '3.5'means the packageenum34but only on some versions of python.frompackaging.markersimportMarkerfrompackaging.requirementsimportRequirementfromhighlighterimportEnvironmentMarkersreq=Requirement("enum34; python_version < '3.5'")env=EnvironmentMarkers.for_python("3.7.5","win32")env.match(req.marker)# False# Lower-level interface, you can use Marker directlym=Marker("python_version < '3.5'")env.match(m)# False# What about extras?req=Requirement("somepackage[foo,bar]")m=Marker("extra == 'foo'")env.match(m,extras=req.extras)# TrueEgg-info ExtrasThis also includes a function that can convert a requires.txt (as found in
egg-info dirs, the only kind we have in sdists) into an equivalent list of
requirements.txt lines using PEP 508 markers.fromhighlighter.sdistimportconvert_sdist_requiresconvert_sdist_requires("""\[socks]PySocks!=1.5.7,>=1.5.6[socks:sys_platform == "win32" and python_version == "2.7"]win_inet_pton""")=="""\PySocks!=1.5.7,>=1.5.6; extra == 'socks'win_inet_pton; (sys_platform == "win32" and python_version == "2.7") and extra == 'socks'"""Licensehighlighter is copyrightTim Hatch, and licensed under
the MIT license.  I am providing code in this repository to you under an open
source license.  This is my personal repository; the license you receive to
my code is from me and not from my employer. See theLICENSEfile for details.
Package: highlight-io
highlight-io Python SDKThis directory contains the source code for the Highlight Python SDK.E2EThee2edirectory contains supported Python frameworks integrated with our SDK for local development and testing.
Do not use the snippets verbatim as they are configured for local development and will not work in production without changes.InstallInstallpoetrypoetry install --all-extrasRun e2e appsDjangocd e2e/highlight_djangopoetry run python manage.py runserverFlaskcd e2e/highlight_flaskpoetry run flask runFastapiStart Redis:cd docker./start_infra(in order to start Redis)Using Boto/Boto3 endpoints:Update the have the following environment variables (edit Run Confirguration in PyCharm)E2E_AWS_ACCESS_KEY(from IAM account)E2E_AWS_SECRET_KEY(from IAM account)SQS_QUEUE_URL(from SQS queue information)Running the main app:cd e2e/highlight_fastapipoetry run uvicorn main:appRunning Celery worker:cd e2e/highlight_fastapipoetry run celery -A e2e.highlight_fastapi.work worker --loglevel=INFOLogurucd e2e/highlight_logurupoetry run python main.pyRun testspoetry run pytestLintpoetry run black  .