Saravanan666/pypi-org huggingface dataset:
Package: hyper2web
=========Hyper2Web=========Super Fast HTTP2 Framework for Progressive Web ApplicationInstallation############To install Hyper2Web, run this command in your terminal:.. code-block:: console$ # due to a known issue, please install Curio manually$ pip install git+https://github.com/dabeaz/curio.git$ pip install hyper2webThis is the preferred method to install Hyper2Web, as it will always install the most recent stable release.If you don't have `pip`_ installed, this `Python installation guide`_ can guideyou through the process... _pip: https://pip.pypa.io.. _Python installation guide: http://docs.python-guide.org/en/latest/starting/installation/Dependency##########Python3.6h2curioQuick Start###########Assuming you have a directory structure like::your project/--public/--index.html--index.js...--app.pyYour ``app.py`` looks like.. code-block:: pythonfrom hyper2web import appif __name__ == '__main__':# A basic callback style API is provided# Function name is up to youasync def post_echo(request, response):# Send the data received back to the clientawait response.send(request.stream.data)app = app.App(port=5000)app.post('name', post_echo)app.up()Then run this script.. code-block:: console$ python app.pyThat's it!If you just want to serve static files, it's just 2 lines!.. code-block:: pythonfrom hyper2web import appapp.App(port=5000).up()Docs####Documentation is hosted on hyper2web.readthedocs.io_... _hyper2web.readthedocs.io: http://hyper2web.readthedocs.ioExample#######See the example folders for examples.Test####.. code-block:: console$ python -m unittest discover testRun all tests under ``test/`` dir.Misc####Why did I create this framework?********************************April 23rd, 2017, Sunday, I woke up and felt bored and decided to create my own HTTP2 web framework.Since I had little or some prior web knowledge, this would be a super learning and fun project for me.=======History=======0.0.0 (2017-06-08)------------------* First release on PyPI.
Package: hyperactive-progress-board
Progress BoardAn addon for the Hyperactive package to visualize the progress of optimization runs.The Progress Board is a dashboard (opens in webbrowser) that provides visualization of live-updated data from Hyperactive. It integrates seamlessly with Hyperactive (v4) and opens up the optimization run with useful information. It also supports multiprocessing and multiple searches at the same time without any added complexity or work for the user.The Progress Board should be used for computationally expensive objective functions (like machine-/deep-learning models).The Progress Board is tested in Ubuntu, but Windows support maybe added in the future.Installationpip install hyperactive-progress-boardExamplefromsklearn.model_selectionimportcross_val_scorefromsklearn.treeimportDecisionTreeRegressorfromsklearn.datasetsimportfetch_california_housingfromhyperactiveimportHyperactivefromhyperactive_progress_boardimportProgressBoard# import progress boarddata=fetch_california_housing()X,y=data.data,data.targetprogress=ProgressBoard()# init progress board@progress.update# add decoratordefdtr_model(opt):dtr=DecisionTreeRegressor(min_samples_split=opt["min_samples_split"],)scores=cross_val_score(dtr,X,y,cv=5)returnscores.mean()search_space={"max_depth":list(range(2,50)),"min_samples_split":list(range(2,50)),"min_samples_leaf":list(range(1,50)),}progress.open()# open progress board before run beginshyper=Hyperactive()hyper.add_search(dtr_model,search_space,n_iter=1000)hyper.run()
Package: hyperbmp
Hyperbmp is a web tool for “hyperbitmap” files: grids of colors with hyperlinks.The hyperbitmap (.hbmp) format is a simple csv-based format:blue,blue,white,white,red,red
blue,blue,white,white,red,red
blue,blue,white>http://google.fr,white>http://google.fr,red,red
blue,blue,white>http://google.fr,white>http://google.fr,red,red
blue,blue,white,white,red,red
blue,blue,white,white,red,redEach grid entry in the CSV contains a valid HTML color and, optionally, a hyperlink.
If there is a hyperlink, the “>” character is used as a separator.The CSV can then be rendered as an HTML table, with each cell colored
accordingly, and hyperlinks rendered where they should appear.The hyperbmp software will render .hbmp files into HTML for browser display.The software also provides a simple editing environment for .hbmp files using
Javascript. It is built as a plugin toSvenwebthough a standalone version wouldn’t be hard to build either.When rendering a hyperbitmap in the browser, you can configure the height and width
of the grid elements using query string parameterspwandph. For example,/foo.hbmp?pw=10&ph=50will render foo.hbmp as a table where each TD has height=10 and width=10.Run the software using a paste.deploy configuration for svenweb, but replacepaste.app_factory = svenweb.factory:factorywithuse = egg:hyperbmpto enable the hyperbmp extensions for svenweb.  To tell the system to treat files
as hyperbitmaps, you can save files with the mimetype “text/csv+hbmp”. A mimetype
mapper is set up for the .hbmp extension, so if you visit an addform for a new file
that ends in .hbmp, the hyperbmp editing environment will be loaded. You can disable
it and drop into the plaintext editor by appending the querystring parameter ?raw.
Package: hyperbolic
hyperbolicThis is a Python 3 library for generating hyperbolic geometry and drawing it withdrawsvg.  Currently the Poincaré disk and half-plane models are supported.Installhyperbolic is available on PyPI:$ python3 -m pip install hyperbolicExamplesSee the Jupyter notebooks inexamples:Euclidean geometryPoincaré disk and planeTiling the Poincaré disk and planeTiling of isosceles trianglesUsing this library, along with the drawsvg library, you can create art like this hyperbolic weave:This weave is built from a tiling ofisosceles triangles:
Package: hyperborea
HyperboreaAboutHyperborea is an intermediate library between the Asphodel Python Library and high level applications.Hyperborea provides process isolation, streaming, disk recording and uploading functionality.The Asphodel communication protocol was developed by Suprock Technologies (http://www.suprocktech.com)LicenseHyperborea is licensed under the ISC license.The ISC license is a streamlined version of the BSD license, and permits usage in both open source and propretary projects.
Package: hyper-bump-it
Hyper Bump ItA command line tool for updating the version in project files needed for the next release.hyper-bump-it's features include:Updating the version to a new fully specified valueIncreasing the version based on a specific version partOptional Git integrations:Commit changesCreate a new branch or tagPush changes to a remote repositoryCustomizable search and replacement patternsMatch based on the current version or arbitrary datesSafe by default, but can be overridden:Request confirmation before editing filesExplicit configuration need to push changesWon't run if the current branch is not the defaultWon't run if there are unstaged changesTOML configuration file (can be part ofpyproject.toml)ExamplesThis first exampleUpdates to an explicit new versionUpdates multiple files that had lines matching the search patternCommits those changes to a newly created branchhyper-bump-it to 2.3.4
Execution Plan:
Create branch bump_version_to_2.3.4
Switch to branch bump_version_to_2.3.4
Update version in configuration file
Update files
────────────────────────────── example/foo.txt ──────────────────────────────
--- example/foo.txt
+++ example/foo.txt
@@ -1,3 +1,3 @@
 hello
---1.2.3--abc
+--2.3.4--abc
 world

 Lorem ipsum dolor sit amet, consectetur adipisci elit, sed eiusmod.
---1.2.3--edf
+--2.3.4--edf
 Ut enim ad minim veniam, quis nostrum exercitationem ullam corporis.

────────────────────────────── example/bar.txt ──────────────────────────────
--- example/bar.txt
+++ example/bar.txt
@@ -1,3 +1,3 @@
 hello
-more --1.2.3-- text
+more --2.3.4-- text
 world

Commit changes: Bump version: 1.2.3 → 2.3.4
Switch to branch main

Do you want to perform these actions? [y/n] (n): y
Creating branch bump_version_to_2.3.4
Switching to branch bump_version_to_2.3.4
Updating version in configuration file
Updating files
Updating example/foo.txt
Updating example/bar.txt
Committing changes: Bump version: 1.2.3 → 2.3.4
Switching to branch mainThis second exampleUpdates to the next minor versionUpdates multiple files that had lines matching the search patternCommits those changes, tags the new commit, and pushes the changes to the remote repository$ hyper-bump-it by minor
Execution Plan:
Update version in configuration file
Update files
────────────────────────────── example/foo.txt ──────────────────────────────
--- example/foo.txt
+++ example/foo.txt
@@ -1,7 +1,7 @@
 hello
---1.2.3--abc
+--1.3.0--abc
 world
 
 Lorem ipsum dolor sit amet, consectetur adipisci elit, sed eiusmod.
---1.2.3--edf
+--1.3.0--edf
 Ut enim ad minim veniam, quis nostrum exercitationem ullam corporis.

────────────────────────────── example/bar.txt ──────────────────────────────
--- example/bar.txt
+++ example/bar.txt
@@ -1,3 +1,3 @@
 hello
-more --1.2.3-- text
+more --1.3.0-- text
 world

Commit changes: Bump version: 1.2.3 → 1.3.0
Tag commit: v1.3.0
Push commit to origin with tag v1.3.0

Do you want to perform these actions? [y/n] (n): y
Updating version in configuration file
Updating files
Updating example/foo.txt
Updating example/bar.txt
Committing changes: Bump version: 1.2.3 → 1.3.0
Tagging commit: v1.3.0
Pushing commit to origin with tag v1.3.0
Package: hypercli
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       |___/|_|               v 1.0.1hyperclihypercliis a Python package that provides an elegant solution for interacting with command line tools. It offers a menu-based command line interface (CLI) that allows users to navigate through different options and execute functions based on their choices.FeaturesGenerate menu-driven CLI programs with ease using decoratorsCustomize the menus, options, and visual styles according to your requirementsSupports nested menus and navigation between menusInstallationYou can installhypercliusing pip. Open your terminal and run the following command:pip install hypercliUsageTo usehypercli, import thehyperclimodule from thehyperclipackage and create an instance of thehypercliclass. You can then define your menus, options, and functions to be executed. Finally, call therun()method to start the CLI interface.Here's an example of how to usehypercli:# import hyperclifromhypercliimporthypercli# create an instance of hyperclicli=hypercli()# configure the instancecli.config["banner_text"]="HYPERCLI"cli.config["intro_title"]="Intro"cli.config["intro_content"]="Generate enhanced menu-driven CLI programs with ease!"cli.config["show_menu_table_header"]=True# add navigation options to the menucli.link("Main Menu","Mathematics Menu")cli.link("Main Menu","String Menu")@cli.entry(menu="Main Menu",option="Greeter")defgreet():name=input("Enter your name: ")print(f"Hello,{name}!")@cli.entry(menu="Mathematics Menu",option="Add two numbers")defadd(num1=1,num2=1):a=int(input(f"Enter first number (default{num1}): ")ornum1)b=int(input(f"Enter second number (default{num2}): ")ornum2)print(f"{a}+{b}={a+b}")@cli.entry(menu="Mathematics Menu",option="Subtract two numbers")defsub(num1=1,num2=1):a=int(input(f"Enter first number (default{num1}): ")ornum1)b=int(input(f"Enter second number (default{num2}): ")ornum2)print(f"{a}-{b}={a-b}")@cli.entry(menu="String Menu",option="Reverse a string")defreverse():string=input("Enter a string: ")print(string[::-1])@cli.entry(menu="String Menu",option="Show length of a string")defstr_length():string=input("Enter a string: ")print(f"Length of string is{len(string)}")# run the clicli.run()LicenseThis project is licensed under the MIT License. See theMITfile for more information.
Package: hyperclip
hyperclipThis Python 3.5+ package implements volume computation of hypercubes clipped by hyperplanes.
All methods implemented here have been proposed by Yunhi Cho and Seonhwa Kim (2020) in the articleVolume of Hypercubes Clipped by Hyperplanes and Combinatorial Identities. An arxiv paper is availablehere.
The documentation is available onRead the Doc.InstallationHyperclip is available throughPyPI, and may be installed usingpip:pip install hyperclipIntroductionThe package is essentially composed by two classes :hyperclip.Hyperplaneandhyperclip.Hyperclip.hyperclip.Hyperplaneallows users to create a n-dimensional hyperplane defined asa.x + r \geq 0. It is possible to directly setaandror to providendistinct points which belongs to the hyperplane, i.ea.x + r = 0.hyperclip.Hyperclipallows users to create an hyperclip object. It aims to compute the volume ofA.X+R \leq 0forXinside the uniform hypercube[0,1]^n. It is possible to directly setAandRor to set a list ofhyperclip.Hyperplaneobjects.Example codeHere's an example showing the usage ofhyperclip.Hyperclipfor a 2-dimensional case.
The result provided by Hyperclip is compared to a MonteCarlo volume estimation.importnumpyasnpimporthyperclipfrommatplotlibimportpyplotaspltn=2m=3np.random.seed(29)hyperplanes=[hyperclip.Hyperplane().set_by_points(np.random.random((n,n)))fori_minrange(m)]np.random.seed(None)X=np.random.random((10**6,n))id_pos_side=np.ones(X.shape[0])forhypinhyperplanes:id_pos_side=np.all((id_pos_side,hyp.side(X)),axis=0)fig,axs=plt.subplots()axs.set_aspect('equal','box')plt.scatter(X[id_pos_side,0],X[id_pos_side,1],s=2,color='gray')forhypinhyperplanes:sol=hyp.compute_n_solutions()x_a,y_a,x_b,y_b=sol.flata=(y_b-y_a)/(x_b-x_a)b=y_a-x_a*ay_0=by_1=a*1+bplt.plot([0,1],[y_0,y_1])hc=hyperclip.Hyperclip().set_hyperplanes(hyperplanes)vol=hc.volume()plt.text(0.25,0.2,"10**6 MonteCarlo : "+str(round(id_pos_side.mean(),4)))plt.text(0.25,0.1,"Hyperclip : "+str(round(vol,4)))plt.xlim([0,1])plt.ylim([0,1])plt.show()ContactPlease, send me an email atfrancois-remi.mazy@inria.fr.
Package: hypercluster
HyperclusterA package for clustering optimization with sklearn.Requirements:pandasnumpyscipymatplotlibseabornscikit-learnhdbscanOptional:
snakemakeInstallWith pip:pip install hyperclusteror with conda:conda install hypercluster
# or
conda install -c conda-forge -c bioconda hyperclusterIf you are having problems installing with conda, try changing your channel priority. Priority of conda-forge > bioconda > defaults is recommended.
To check channel priority:conda config --get channelsIt should look like:--add channels 'defaults'   # lowest priority
--add channels 'bioconda'
--add channels 'conda-forge'   # highest priorityIf it doesn't look like that, try:conda config --add channels bioconda
conda config --add channels conda-forgeDocshttps://hypercluster.readthedocs.io/en/latest/index.htmlIt will also be useful to check out sklearn's page onclusteringandevaluation metricsExampleshttps://github.com/liliblu/hypercluster/tree/dev/examplesQuickstart with SnakeMakeDefaultconfig.ymlandhypercluster.smkare in the snakemake repo above.Edit theconfig.ymlfile or arguments.snakemake-shypercluster.smk--configfileconfig.yml--configinput_data_files=test_datainput_data_folder=.Example editing with python:importyamlwithopen('config.yml','r')asfh:config=yaml.load(fh)input_data_prefix='test_data'config['input_data_folder']=os.path.abspath('.')config['input_data_files']=[input_data_prefix]config['read_csv_kwargs']={input_data_prefix:{'index_col':[0]}}withopen('config.yml','w')asfh:yaml.dump(config,stream=fh)Then call snakemake.snakemake-shypercluster.smkOr submit the snakemake scheduler as an sbatch job e.g. with BigPurple Slurm:moduleaddslurm
sbatchsnakemake_submit.shExamples forsnakemake_submit.shandcluster.jsonis in the scRNA-seq example.Quickstart with pythonimportpandasaspdfromsklearn.datasetsimportmake_blobsimporthyperclusterdata,labels=make_blobs()data=pd.DataFrame(data)labels=pd.Series(labels,index=data.index,name='labels')# With a single clustering algorithmclusterer=hypercluster.AutoClusterer()clusterer.fit(data).evaluate(methods=hypercluster.constants.need_ground_truth+hypercluster.constants.inherent_metrics,gold_standard=labels)clusterer.visualize_evaluations()# With a range of algorithmsclusterer=hypercluster.MultiAutoClusterer()clusterer.fit(data).evaluate(methods=hypercluster.constants.need_ground_truth+hypercluster.constants.inherent_metrics,gold_standard=labels)clusterer.visualize_evaluations()
Package: hyperco-client
Installationpip install hyperco-clientIntroductionWith this client you can interact with the Hyper.co API withou needing to prepare the requests yourself.
It provides a clean and easy way to build client calls.The client will raise an exception if the Hyper.co API returns an error response.Examplefromhyper.clientimportClientfromhyper.linksimportCreateLinkParamsapi_key="YOUR_HYPER_API_KEY"client=Client(api_key=api_key)# ---- Get all business licenses  ---------------------- #licenses=client.list_licenses(page=2,limit=10)print(licenses)# ------------------------------------------------------ ## ---- Create a new product link  ---------------------- #params=CreateLinkParams(product_id="product_id",password="link_password",trial_period_days=7,group_buy_guild="0000000000000000",enable_bot_protection=True,max_usages=50,start_date=datetime.fromtimestamp(1683577538),initial_fee_amount=10)link=client.create_link(params=params)print(link)# ------------------------------------------------------ ## ---- Authorize a license  ---------------------------- #valid_license=client.authorize(license_key="license_key")print(valid_license)# ------------------------------------------------------ #
Package: hyper-compose
Hyper-ComposeCommand line utility which installs docker-compose application into the hyper.sh cloudAs Hyper is (loosly) based on the docker-api, we can re-use docker-compose and docker-py, but hack out the network part to use the authentication stuff from hyperPOCThis project is more a PoC. Some features of docker-compose are not workingNetworking configurationcontainer re-creation (they need to be removed, and the created again)IP affectation (you will need to use original hyper command line in order to affect public IP addresses to your containers)Future plansThe official hyper-compose functionality from hyper crew will come later with better integration to the hyper system.
It will be directly integrated into the “hyper” command line utility, and will be implemented mostly server side, to provide better coordination, and status monitoring.Install from pippip install hyper-composeHow to developSetup virtualenv in order to install all dependencies:virtualenv sandbox
. ./sandbox/bin/activate
pip install -U pip
pip install -e .Now you havehyper-composein your path, and you can use it like docker compose:cd path/to/composeyml
hyper-compose up
hyper-compose stop
hyper-compose rmNote that you still need to use hyper command line in order to associate floating IP to your containers
Package: hyperconf
HyperConfigOverviewHyperConfig is a Python library for creating schema-based configuration.
It allows zero code configuration definition where both the structure and the
configuration values are validated using YAML based schema definition files.Advantages:less code: define the structure in YAML, validate and load configs using a one-liner.shared schemas: define once, use in multiple projects.extensibility: add configuration types and validation rules without coding.InstallationpipinstallhyperconfigUsageDefine your schema in a definition file,ships.yaml:# Spaceship Configuration Schemaship_type:type:strvalidator:hval.isalpha()required:trueshipcolor:type:strvalidator:hval.lower() in ['red', 'blue', 'green', 'yellow', 'gray']required:trueenginepower:type:intvalidator:100 <= hval <= 1000required:trueshieldlevel:type:floatvalidator:0.0 <= hval <= 1.0required:trueship:captain:strcrew:type:intvalidator:hval > 0class:shiptypecolor:shipcolorshields:shieldlevelengines:enginepowerThen use the schema to create configuration values,gameconfig.yaml:use:shipsncc1701=ship:captain:James T. Kirkcrew:203class:constitutioncolor:grayshields:1.0engines:900and load it:>>>fromhyperconfigimportHyperConf>>>config=HyperConf.load("gameconfig.yaml")>>>print(config.ncc1701.captain)Please check the documentation athttps://hyperconf.readthedocs.io/en/latest/index.htmlLicenseThis project is licensed under the MIT License - see the LICENSE file for details.
Package: hypercore-crypto
hypercore-cryptoCryptography primitives for HypercoreInstall$pipinstallhypercore-cryptoExamplefromhypercore_cryptoimportdata,key_pairfrompysodiumimportcrypto_sign_PUBLICKEYBYTESpublic_key,secret_key=key_pair()assertlen(public_key)==crypto_sign_PUBLICKEYBYTESprint(data(b"hello world").hex())
Package: hypercurrent-django
HyperCurrent Middleware for Python DjangoDjango middleware to dispatch metering metadata for HTTP API calls to HyperCurrent.Installationpipinstallhypercurrent_metering
pipinstallhypercurrent_djangoUsageIn yoursettings.pyfile in your Django project directory,
please add the following to the middleware array:'hypercurrentdjango.middleware.HyperCurrentMiddleware'ConfigurationHYPERCURRENT_API_KEY(required),string,
yourHyperCurrent API Integration KeyHYPERCURRENT_APPLICATION_HEADER(optional),string, the HTTP header to determine the API consumer.
The default is "clientId".HYPERCURRENT_METADATA_HEADER(optional),string, An optional response header to extract metering metadata from.HYPERCURRENT_API_URL(optional),string, the HyperCurrent API URL.
You should only need to change this if using a
non-US based HyperCurrent instance (ie, EMEA or customer compute.)
Package: hyperdash
Hyperdashis a machine learning monitoring library capable of running alongside Tensorflow, Scikit-Learn, and other modeling libraries. It was developed with a focus on enabling fast knowledge gain.Use Hyperdash if you’re looking for cloud-based model monitoring that:Is fast and easy-to-use with scripts and Jupyter.Tracks your hyperparameters across different model experiments.Graphs performance metrics (loss, reward, etc.) in real-time.Can be viewed remotely on theWeb,iOS, andAndroidwithout self-hosting (e.g. Tensorboard).Saves your experiment’s print output (standard out / error) as a local log file.Notifies you when a long-running experiment has finished.Hyperdash is compatible with:Python 2.7 - 3.6
Package: hyperDataS
HyperDShyperDataS (HyperDataStorage) is a library written in Python that provides a compressed data storage and retrieval system for large data. It uses the ZipFile format and provides a Pythonic interface to manipulate and access the data. The library is designed to be easy to use and provides advanced features such as compressing python objectsRequirementsPython 3InstallationpipinstallhyperDataSUsageUnfortunately hyperDataS doesn't have documentation but you can check the examples directory for understanding it