Saravanan666/pypi-org huggingface dataset:
Package: huscy.project-documents
huscy.project_documentsRequirementsPython 3.8+A supported version of DjangoTox tests on Django versions 3.2, 4.1 and 4.2.InstallationTo installhusy.project_documentssimply run:pip install huscy.project_documentsConfigurationWe need to hookhuscy.project_documentsinto our project.
This package depends onhuscy.projectsso we have to add this as well.
We also have to add further requirements for django_guardian, django_restframework and drf_nested_routers.Add packages into yourINSTALLED_APPSat settings module:INSTALLED_APPS=(...'guardian','rest_framework','rest_framework_nested','huscy.project_documents','huscy.projects',)Createhuscy.project_documentsdatabase tables by running:python manage.py migrateDevelopmentAfter checking out the repository you should runmake installto install all development and test requirements andmake migrateto create the database tables.
We assume you have a running postgres database with a userhuscyand a database also calledhuscy.
You can easily create them by runningsudo -u postgres createdb huscy
sudo -u postgres createuser -d huscy
sudo -u postgres psql -c "ALTER USER huscy WITH PASSWORD '123'"
sudo -u postgres psql -c "ALTER DATABASE huscy OWNER TO huscy;"
Package: huscy.project-ethics
huscy.project-ethicsRequirementsPython 3.8+A supported version of DjangoTox tests on Django versions 3.2, 4.1 and 4.2.InstallationTo installhusy.project-ethicssimply run:pip install huscy.project-ethicsConfigurationFirst of all, thehuscy.project_ethicsapplication has to be hooked into the project.Addhuscy.project_ethicsand further required apps toINSTALLED_APPSin settings module:INSTALLED_APPS=(...'guardian','rest_framework','huscy.project_ethics','huscy.projects',)Createhuscy.project-ethicsdatabase tables by running:python manage.py migrateDevelopmentAfter checking out the repository you should activate any virtual environment.
Install all development and test dependencies:make installCreate database tables:make migrateWe assume you're having a running postgres database with a userhuscyand a database also calledhuscy.
You can easily create them by runningsudo -u postgres createuser -d huscy
sudo -u postgres createdb huscy
sudo -u postgres psql -c "ALTER DATABASE huscy OWNER TO huscy;"
sudo -u postgres psql -c "ALTER USER huscy WITH PASSWORD '123';"
Package: huscy.projects
huscy.projectsRequirementsPython 3.8+A supported version of DjangoTox tests on Django versions 3.2, 4.1 and 4.2.InstallationTo installhusy.projectssimply run:pip install huscy.projectsAddhuscy.projectsand further required apps toINSTALLED_APPSin your settings module:INSTALLED_APPS=(...'guardian','rest_framework','huscy.projects',)Add Django Guardian ObjectPermissionBackend to AUTHENTICATION_BACKENDSAUTHENTICATION_BACKENDS=('django.contrib.auth.backends.ModelBackend','guardian.backends.ObjectPermissionBackend',)Hook the urls fromhuscy.projectsinto your urls.py:urlpatterns=[...path('/api/',include('huscy.projects.urls')),]Createhuscy.projectsdatabase tables by running:python manage.py migrateDevelopmentInstall PostgreSQL and create a database user calledhuscyand a database calledhuscy.sudo -u postgres createdb huscy
sudo -u postgres createuser -d huscy
sudo -u postgres psql -c "GRANT ALL PRIVILEGES ON DATABASE huscy TO huscy;"
sudo -u postgres psql -c "ALTER USER huscy WITH PASSWORD '123';"Checking out the repository start your virtual environment (if necessary).Install all development and test dependencies:make installCreate Database tables:make migrateRun tests to see if everything works fine:make test
Package: huscy.pseudonyms
huscy.pseudonymsRequirementsPython 3.8+A supported version of DjangoTox tests on Django versions 3.2, 4.1 and 4.2.InstallationTo installhusy.pseudonymssimply run:pip install huscy.pseudonymsConfigurationFirst of all, thehuscy.pseudonymsapplication has to be hooked into the project.Addhuscy.pseudonymsand further required apps toINSTALLED_APPSin settings module:INSTALLED_APPS=(...'huscy.pseudonyms','huscy.subjects',)Create database tables by running:python manage.py migrateDevelopmentAfter checking out the repository you should activate any virtual environment.
Install all development and test dependencies:make installCreate migration files and database tables:make migrateWe assume you're having a running postgres database with a userhuscyand a database also calledhuscy.
You can easily create them by runningsudo -u postgres createuser -d huscy
sudo -u postgres createdb huscy
sudo -u postgres psql -c ";ALTER DATABASE huscy OWNER TO huscy"
sudo -u postgres psql -c "ALTER USER huscy WITH PASSWORD '123';"
Package: huscy.subjects
huscy.subjectsRequirementsPython 3.8+A supported version of DjangoTox tests on Django versions 3.2, 4.1 and 4.2.InstallationTo installhusy.subjectssimply run:pip install huscy.subjectsAddhuscy.subjectsand further required apps toINSTALLED_APPSin yoursettings.py:INSTALLED_APPS=(...'django_countries','guardian','phonenumber_field','rest_framework','huscy.subjects',)Hook the urls fromhuscy.subjectsinto yoururls.py:urlpatterns=[...path('api/',include('huscy.subjects.urls')),]Createhuscy.subjectsdatabase tables by running:python manage.py migrateConfigurationThere are some settings to configure the service. These settings have be added tosettings.py.NameDefault valueDescriptionHUSCY_SUBJECTS_AGE_OF_MAJORITY18Specifies the age of majority.HUSCY_SUBJECTS_SUBJECT_VIEWSET_MAX_RESULT_COUNT500Specifies the maximum number of subjects returned by the queryset in the SubjectViewSet.DevelopmentInstall PostgreSQL and create a database user calledhuscyand a database calledhuscy.sudo -u postgres createdb huscy
sudo -u postgres createuser -d huscy
sudo -u postgres psql -c "GRANT ALL PRIVILEGES ON DATABASE huscy TO huscy;"
sudo -u postgres psql -c "ALTER USER huscy WITH PASSWORD '123';"Check out the repository and start your virtual environment (if necessary).Install dependencies:make installCreate database tables:make migrateRun tests to see if everything works fine:make test
Package: huscy.users
huscy.usersRequirementsPython 3.8+A supported version of DjangoTox tests on Django versions 3.2, 4.1 and 4.2.InstallationTo installhusy.userssimply run:pip install huscy.usersConfigurationThehuscy.usersapplication has to be hooked into the project.Addhuscy.userstoINSTALLED_APPSin settings module:INSTALLED_APPS=(...'huscy.users',)DevelopmentAfter checking out the repository you should activate any virtual environment.
Install all development and test dependencies:make installCreate database tables:python manage.py migrateWe assume you're having a running postgres database with a userhuscyand a database also calledhuscy.
You can easily create them by runningsudo -u postgres createdb huscy
sudo -u postgres createuser -d huscy
sudo -u postgres psql -c "ALTER USER huscy WITH PASSWORD '123';"
sudo -u postgres psql -c "ALTER DATABASE huscy OWNER TO huscy;"
Package: hushbugger
`hushbugger` is an alternative to a debugger. Instead of helping you find bugs and remove them, it will do its best to make bugs invisible.# ExampleImagine you have the following code (as featured in the [Hypothesis docs](https://hypothesis.readthedocs.io/en/latest/quickstart.html)):```pydef encode(input_string):count = 1prev = ''lst = []for character in input_string:if character != prev:if prev:entry = (prev, count)lst.append(entry)count = 1prev = characterelse:count += 1else:entry = (character, count)lst.append(entry)return lst```It has a fatal flaw: it crashes if you give it an empty string:```>>> encode('')Traceback (most recent call last):...UnboundLocalError: local variable 'character' referenced before assignment```To hide the bug, simply apply the `hush` decorator:```pyfrom hushbugger import hush@hushdef encode(input_string):count = 1prev = ''lst = []for character in input_string:if character != prev:if prev:entry = (prev, count)lst.append(entry)count = 1prev = characterelse:count += 1else:entry = (character, count)lst.append(entry)return lst```Now it works!```>>> encode('')[]```# How it worksIf the function raises an exception, its bytecode is disassembled and inspected to look for return statements. If a constant value is returned (e.g. `return True`), that value is used. If a variable is returned (e.g. `return x`), and that variable had a value at the time of the exception, that value is used.If no usable return statements are found, a `Dummy` object is returned. It responds to almost any operation you throw at it (calling it, adding it, iterating over it, etcetera), so hopefully it gets discarded before visibly breaking anything. Its `repr` is also disguised, as if it belonged to a random module.```py@hushdef double(x):return 2 * x``````>>> double([1, 2, 3])[1, 2, 3, 1, 2, 3]>>> ret = double({})>>> ret<errno.Coalescer object at 0x7f96708cb438>>>> len(list(ret.invert()))51```# Installing```pip install hushbugger```
Package: hushh-vibe-catalog
hushh-vibe-catalogSupport clients for the hushh vibe-catalog file formatThere is documentationavailableInstallation$>pipinstallhushh-vibe-catalogLatest Version Schemanamespace hushh.hcf;

table Product {
  id: string;
  description: string;
  url: string;
}

table Vibe {
  id: string;
  description: string;
  product_idx: [int];
}

table Category {
  id: string;
  description: string;
  url: string;
  product_idx: [int];
}

enum VibeMode : byte { ProductText = 0, ProductImage, Text, Image, Category}

table FlatEmbeddingBatch {
    id: string;
    shape:[int];
    type: VibeMode;
    flat_tensor:[float];
}

table ProductVibes {
  id: string;
  products: [Product];
  categories: [Category];
  vibes: [Vibe];
  flat_batches: [FlatEmbeddingBatch];
}

table Catalog {
  id : string;
  version: string;
  description: string;
  product_vibes: ProductVibes;
}

root_type Catalog;
Package: hush-push
# hush-push## Installation`pip install --user hush-push`## Usage```usage: hush [-h] [--version] [--execute] [--overwrite] [--verbose][--remote-endpoint REMOTE_ENDPOINT]Hello worldoptional arguments:-h, --help            show this help message and exit--version             show the current version--execute, -e         create the specified configuration parameters--overwrite, -o       force put the configuration parameters even if theyalready exist--verbose, -v         enable verbose logging--remote-endpoint REMOTE_ENDPOINT, -r REMOTE_ENDPOINTspecify remote endpoint```## Pre-requisitesYou need to specify which configuration file to use by setting the environment variable `AWS_CONFIG_FILE` to the absolute path of your configuration file.## Directory structureThe directory structure need to be organized in folders at the root of your project. The first folder name should be equal to the profile name specified in the configuration file to use for the call. If your config looks like this:```ini[profile accProfile]role_arn = arn:aws:iam::000000000000:role/ROLEregion = eu-west-1source_profile = default```You must put your configuration parameters in the following structure under the directory `secrets/`:```<project-root>:secrets/accProfile/parameterName```If the `parameterName` is a folder structure, the configuration parameter name will be a concatenated version of those. If the folder structure looks like this:```<project-root>:secrets/accProfile/eu-west-1/staging/remoteEndpoint```the parameter name will look like this: `/eu-west-1/staging/remoteEndpoint` with the value of the parameter set to the content of the file `remoteEndpoint`## DevelopmentTo build the dist: `python3 setup.py sdist bdist_wheel` and answer "no" to the question if it's a production release. To upload the created dist run `python3 -m twine upload --repository-url https://test.pypi.org/legacy/ dist/*` and sign in with your username and password.
Package: husky-simplex
Husky_SimplexText processing packageData preprocessing is the first and most essential stage in developing a machine learning
model as it affects the overall accuracy and efficiency of the outcome. Ordinary text data
contains non-contextual words, noise, misspelled words, symbols, punctuations, and
unnecessary syntactic connotations. To circumvent these hindrances, we need to clean
raw text data into data that is acceptable for statistical and computational analysis.The purpose of the package is to provide a one-stop platform for most of the necessary
text preprocessing techniques. These steps are used to augment the computational
significance of text data for Natural Language Processing tasks.Package FunctionsTokenization - Converting string input to a list of words.Word counter - Counting the total number of words in the input.Stopword removal - Removing non-contextual words that are only used for the
grammatical structure.Punctuation removal - Removing punctuations.Symbol removal - Removing symbols.Stemming - Removing tense connotations.Bag of words - Quantifying words.Count vectorization - Vectorization of text based on term frequency.TF-IDF vectorization - Vectorization of text based on term frequency in relation to
document frequencyInstallationpip install husky_simplexorgit clone https://github.com/Sudhendra/Husky_Simplex.gitcd Husky_Simplexpip install - r requirements.txt
Package: huskytools
Abouthuskytools provides tools for interacting with theHuskyLens AI camera.FeaturesLow-level API for interacting with the HuskyLens camera. It's meant as a replacement
for theofficial HuskyLens Python API. It's not a drop-in replacement but all
the functionality, except for I2C-support, is there.A command line interface for quick testing and debugging.[NOT IMPLEMENTED YET]Helper classes for working with the HuskyLens camera, e.g. a class for working
with faces. [NOT IMPLEMENTED YET]Installationhuskytools is available on PyPI, so you can install it with pip:pipinstallhuskytoolsAlternatively, you can install the latest development version of huskytools by
cloning the repository and install it with pip:gitclonehttps://github.com/Andreasdahlberg/husky-tools.gitcdhusky-tools
pipinstall.UsageAPIThis example shows how to connect to the HuskyLens.fromhuskytoolsimporthuskylenswithhuskylens.Interface("/dev/ttyUSB0")aslens:iflens.knock():print("HuskyLens connected")else:print("HuskyLens not found")This example shows how to get all detected faces from the HuskyLens.fromhuskytoolsimporthuskylenswithhuskylens.Interface("/dev/ttyUSB0")aslens:iflens.knock():lens.set_algorithm(huskylens.RecognitionAlgorithm.FACE_RECOGNITION)forblockinlens.get_blocks():print("Block ID:{}, X:{}, Y:{}".format(block.id,block.x,block.y))Command line interfaceNOT IMPLEMENTED YETHelper classesNOT IMPLEMENTED YETContributingContributions are welcome. Please open an issue or a pull request on GitHub.SupportIf you have any questions or problems, please open an issue on GitHub and i will be happy to help.
Package: husl
[![Build Status](https://travis-ci.org/husl-colors/husl-python.svg?branch=master)](http://travis-ci.org/husl-colors/husl-python)
[![Package Version](https://img.shields.io/pypi/v/husl.svg)](https://pypi.python.org/pypi/husl/)A Python implementation of [HUSL](http://www.husl-colors.org) (revision 3).## Installationpip install husl## Usagehusl_to_hex(hue, saturation, lightness)hueis a float between 0 and 360,saturationandlightnessare floats between 0 and 100. This function returns the resulting color as a hex string.husl_to_rgb(hue, saturation, lightness)Like above, but returns a list of 3 floats between 0 and 1, for each RGB channel.hex_to_husl(hex)Takes a hex string and returns the HUSL color as a list of floats as defined above.rgb_to_husl(red, green, blue)Like above, butred,greenandblueare passed as floats between 0 and 1.For HUSLp (the pastel variant), usehuslp_to_hex,huslp_to_rgb,hex_to_huslpandrgb_to_huslp.## TestingRunpython setup.py test.## AuthorsRobert McGinley ([mcginleyr1](http://github.com/mcginleyr1))Alexei Boronine ([boronine](http://github.com/boronine))
Package: huSoftM
# huSoftMhuSoftM is a toolkit for acessing the “SoftM Suite” ERP system in Python. See the module documentation for a
general introduction into the workings of huSoftM. Major subsystems:odbc_bridge Erlang Language http-to-odbc converter beeing the basis for all SoftM access in this library.softmtables - read write access to single table rows including locking.[kunden](http://github.com/hudora/huSoftM/blob/master/html/kunden.html) - customer information following
the [AddressProtocol](http://github.com/hudora/huTools/blob/master/doc/standards/address_protocol.markdown).[tools](http://github.com/hudora/huSoftM/blob/master/html/tools.html) - nice helper functions[connection](http://github.com/hudora/huSoftM/blob/master/html/connection.html) - SQL read acess to tables
including automatic mapping and conversion.[bestaende](http://github.com/hudora/huSoftM/blob/master/html/bestaende.html) - Zugriff auf (Lager-)
Bestandsdaten.See [SoftMtabellen](http://cybernetics.hudora.biz/projects/wiki/SoftMtabellen) for a representation of our
knowlege concerning the Tables in SoftM.# DownloadsGet it at [https://github.com/hudora/huSoftM][7][7]:https://github.com/hudora/huSoftM# ChangesSeehttp://github.com/hudora/huSoftM/blob/master/CHANGES
Package: huspy
huspyGit hooks for python.Huspy is inspired byHusky.The code is transfered from Husky's typscript to python.Usagepip install huspy

# In a git repository, this command will generate `./.huspy` directory, which is the git hooks directory.
huspy install

# This command will add a pre-commit hook.
huspy set ./huspy/pre-commit python test.py

# This command will uninstall the git hooks.
huspy uninstall
Package: husqvarna-getl
GETLAn elegant way to ETL'ing.View theGETL documentationInstallationInstall GETL by running:pipinstallhusqvarna-getlUpcoming featuresLift definition validationContributeIssue Tracker:https://github.com/husqvarnagroup/GETL/issuesSource Code:https://github.com/husqvarnagroup/GETLSupportIf you are having issues, please create an issue on ourgithub.LicenseMIT License
Package: husrev
This tool has been forked from atGitHubPython 3 and the latest SQLAlchemy version).This is a tool that reads the structure of an existing database and generatesthe appropriate SQLAlchemy model classes, using the declarative style ifpossible.FeaturesSupports SQLAlchemyProduces declarative code that almost looks like it was hand writtenProducesPEP 8compliant codeAccurately determines relationships, including many-to-many, one-to-oneAutomatically detects joined table inheritanceExcellent test coverageIt creates each SQLAlchemy class file separately under the"models"folder.Usage instructionsInstallationTo install, do:pip install husrevor, failing that:easy_install husrevExample usageAt the minimum, you have to give husrev a database URL.The URL is passed directly to SQLAlchemy'screate_engine() method so please refer toSQLAlchemy's documentationhttp://docs.sqlalchemy.org/en/latest/core/engines.htmlfor instructions on how to construct a proper URL.Examples:husrev postgresql:///some_local_db --noinflecthusrev mysql+oursql://user:password@localhost/dbnamehusrev sqlite:///database.dbTo see the full list of options:husrev --helpModel class naming logicThe table name (which is assumed to be in English) is converted to singularform using the "inflect" library. Then, every underscore is removed whiletransforming the next letter to upper case. For example,sales_invoicesbecomesSalesInvoice.Use--noinflectdisable inflect transform.Relationship detection logicRelationships are detected based on existing foreign key constraints asfollows:many-to-one: a foreign key constraint exists on the tableone-to-one: same asmany-to-one, but a unique constraint exists onthe column(s) involvedmany-to-many: an association table is found to exist between two tablesA table is considered an association table if it satisfies all of thefollowing conditions:#. has exactly two foreign key constraints#. all its columns are involved in said constraintsRelationship naming logicRelationships are typically named based on the opposite class name.For example, if anEmployeeclass has a column namedemployerwhichhas a foreign key toCompany.id, the relationship is namedcompany.A special case for single column many-to-one and one-to-one relationships,however, is if the column is named likeemployer_id. Then therelationship is namedemployerdue to that_idsuffix.If more than one relationship would be created with the same name, thelatter ones are appended numeric suffixes, starting from 1.Source codeThe source can be browsed atGitHubReporting bugsAbug trackeris provided by GitHub.
Package: husteblume
pyHusteblumeInstallationInstall the dependencies using pip:pip install -r requirements.txtUsagepython3 main.pyExample{'user-agent': 'okhttp/4.4.0'}
<husteblume.api.Stations object at 0x105b713d0>
'DEHANN'
<User: appId=6C17808F>
{'authorization': 'Basic NkMxNzgwOEY6bmxZTGtkVnNpWm5SR2tzTWpwa01aeFFoY2o=',
 'user-agent': 'okhttp/4.4.0'}
<husteblume.api.Forecast object at 0x104d84eb0>
{'ALNU': [0, 0, 0],
 'AMBR': [0, 0, 0],
 'ARTE': [1, 1, 1],
 'BETU': [0, 0, 0],
 'CORY': [0, 0, 0],
 'FRAX': [0, 0, 0],
 'POAC': [2, 2, 2],
 'SECA': [0, 0, 0]}
Package: hutch-python
hutch-pythonis the launcher and config reader for LCLS interactive IPython
sessions. The documentation is hosted athttps://pcdshub.github.io/hutch-python.RequirementsThis module is intended to be run using the latest pcds release in thepcds-envspackage.This module requires Python 3.6+ and the following utilities:ipython, for improved interactive sessionspcdsdaqfor using the daq in scanspcdsdevicesfor our Device abstraction layerselogfor posting to the LCLS experiment elogshappito enable device loading from a happi databasepsdm_qs_clias an optional happi dependency for loading from the experiment
questionnairelightpathorganizes devices to provide a summarized state of the beamline as a wholepyyaml, for reading config filescoloredlogs, for colored loggingpyfigletfor hutch banners (think bigxpppythonon startup)cookiecutterfor starting new hutch reposTo connect to the LCLS DAQ, your environment must have access topydaqfor connecting to and running the daqpycdbfor changing daq object configurationspyamifor viewing data from the daqThese are not available outside of the slac intranet, and in some cases
must be sync’d with the active DAQ versions, independent of all other
packages.To automatically select the current experiment, you must run with access to
the LCLS NFS directories.