Saravanan666/pypi-org huggingface dataset:
Package: kraken
Descriptionkraken is a turn-key OCR system optimized for historical and non-Latin script
material.kraken’s main features are:Fully trainable layout analysis and character recognitionRight-to-Left,BiDi, and Top-to-Bottom
script supportALTO, PageXML, abbyyXML, and hOCR
outputWord bounding boxes and character cutsMulti-script recognition supportPublic repositoryof model filesVariable recognition network architectureInstallationkraken only runs onLinux or Mac OS X. Windows is not supported.The latest stable releases can be installed either fromPyPi:$ pip install krakenor throughconda:$ conda install -c conda-forge -c mittagessen krakenIf you want direct PDF and multi-image TIFF/JPEG2000 support it is necessary to
install thepdfextras package for PyPi:$ pip install kraken[pdf]or installpyvipsmanually with conda:$ conda install -c conda-forge pyvipsConda environment files are provided which for the seamless installation of the
main branch as well:$ git clone https://github.com/mittagessen/kraken.git
$ cd kraken
$ conda env create -f environment.ymlor:$ git clone https://github.com/mittagessen/kraken.git
$ cd kraken
$ conda env create -f environment_cuda.ymlfor CUDA acceleration with the appropriate hardware.Finally you’ll have to scrounge up a model to do the actual recognition of
characters. To download the default model for printed English text and place it
in the kraken directory for the current user:$ kraken get 10.5281/zenodo.2577813A list of libre models available in the central repository can be retrieved by
running:$ kraken listQuickstartRecognizing text on an image using the default parameters including the
prerequisite steps of binarization and page segmentation:$ kraken -i image.tif image.txt binarize segment ocrTo binarize a single image using the nlbin algorithm:$ kraken -i image.tif bw.png binarizeTo segment an image (binarized or not) with the new baseline segmenter:$ kraken -i image.tif lines.json segment -blTo segment and OCR an image using the default model(s):$ kraken -i image.tif image.txt segment -bl ocrAll subcommands and options are documented. Use thehelpoption to get more
information.DocumentationHave a look at thedocsRelated SoftwareThese days kraken is quite closely linked to theescriptoriumproject developed in the same eScripta research
group. eScriptorium provides a user-friendly interface for annotating data,
training models, and inference (but also much more). There is agitter channelthat is mostly intended for
coordinating technical development but is also a spot to find people with
experience on applying kraken on a wide variety of material.Fundingkraken is developed at theÉcole Pratique des Hautes Études,Université PSL.This project was partially funded through the RESILIENCE project, funded from
the European Union’s Horizon 2020 Framework Programme for Research and
Innovation.Ce travail a bénéficié d’une aide de l’État gérée par l’Agence Nationale de la
Recherche au titre du Programme d’Investissements d’Avenir portant la référence
ANR-21-ESRE-0005 (Biblissima+).
Package: krakenapi
Kraken APIPython interface library for Kraken API.DocumentationPackage documentation is available at this address:https://adocquin.github.io/kraken-api/Where to get itThe source code is currently hosted on GitHub at:https://github.com/adocquin/kraken-apiBinary installers for the latest released version are available at the Python Package Index (PyPI):pipinstallkrakenapiInstallation from sourcesIn the base directory execute:pipinstall.LicenseGPL-3.0How to contributeThanks for your interest in contributing to the project. You can contribute freely by creating an issue, fork or create
a pull request. Before issuing a pull request, make sure the changes did not break any existing functionality by
running unit tests in the base directory:pytest
Package: kraken-async-api
Kraken-async-apiA library for asynchronous communications with the Kraken cryptocurrency exchange.Quickstartimportasynciofromkraken_async_apiimportKraken,Config,Depthasyncdefprint_(data):print(data)asyncdefmain():# Only necessary if you wish to communicate with private endpointsconfig=Config(api_key="your api-key",api_sec="your api-sec")kraken_exchange=awaitKraken.connect(async_callback=print_,config=config)# ... your usage of the API here, for example:kraken_exchange.public.subscribe_to_book(["XXBTZGBP"],Depth.D25)if__name__=='__main__':asyncio.get_event_loop().run_until_complete(main())
Package: kraken-boilerplate
kraken_boilerplateLibrary of commonly used templatesTemplates are stored athttps://github.com/tactik8/boilerplatesHow to usefrom kraken_boilerplate import kraken_boilerplate as k

# Get content from privacy template
content = k.get('privacy', record, 'EN-US')

# Get record template for a specific template
record = k.get_record('privacy')

# Get list of all files
record = k.get_files()

# Refresh templates from github
k.refresh()
Package: kraken-browser
Kraken BrowserOverviewRuns a chromium browser in the background.
Class Browser() retrieves a webpage along with images and screenshotsFeaturesAuto-proxy: rotates proxy automaticallyInputurl: url of the webpage to retrieveAttributesurl: url of the webpagehtml: html fo the webpage retrievedscreenshot: image object (dict) of the screenshot file (viewport)screenshot_full: image object (dict) of the screenshot file (full page)image_files: path of the image filesimages: array of image objects of the image filesimage object keys:schema:url url of the webpageschema:contenturl url of the imagetemp:data binary data of the imageHow to usefrom kraken_browser import Browserurl = 'https://www.test.combrowser = Browser(url)html = browser.html
Package: kraken-build
title: HomeThe Kraken build systemKraken is a build system, but not in the traditional sense. It's focus is on the orchestration of high-level tasks,
such as organization of your repository configuration, code generation, invoking other build systems, etc. It is not a
replacement for tools like Poetry, Cargo or CMake.RequirementsCPython 3.10+Getting startedCurrently, Kraken's OSS components are not very well documented and do not provide a convenient way to get started.
However, if you really want to try it, you can use the following steps:Installkraken-wrapper(e.g. withPipx) to get access to thekrakenwcommand-line tool.Create a.kraken.pyscript in your project's root directory.fromkraken.commonimportbuildscriptbuildscript(requirements=["kraken-build==0.32.3"])fromkraken.std.pythonimportmypy,black,isortmypy()black()isort()Runkrakenw lockto installkraken-buildfor your project inbuild/.kraken/venvand generate akraken.lockfile.Runkrakenw run lintto run the linters.Note that you can also use thekrakenCLI (instead ofkrakenw), however this will disregard thebuildscript()function, will not use the lock file and will use the version of Kraken that was installed globally.How-to'sUpgrade a project's lock fileTo upgrade a project's lock file, runkrakenw lock --upgrade. This will upgrade all dependencies to the latest
available version. If you want to upgrade based on updated constraints in.kraken.pywithout installing from scratch,
add the--incrementalflag or setKRAKENW_INCREMENTAL=1.DevelopmentThis repository usesSlapto manage the Python project. After installing Slap with Pipx, run the following to install Kraken for development:$ slap venv -c --python python3.10
$ slap install --link
# If you have the Slap shell magic installed, it will activate the Venv in your shell.
$ slap venv -aReleasesA release must be created by a maintainer that has write access to thedevelopbranch. The release process
is automated using Slap.$ slap release -tp <patch|minor|major|x.y.z>
$ slap publish
Package: kraken-cache
Kraken-cacheProvides a caching mechanism for kraken records.from kraken_cache.kraken_cache import Kraken_cacheHow to use:
Initialize cache at beginning. Load data from database with load method. Add data to be saved with set. Retrieve all of the data to be saved using export. Clear data to be saved (after a save to db) with clear_all.Initialize
k = Kraken_cache()Store data (to be writtened to db)
k.set(id, data)Load data (from db)
k.load(id, data)Retrieve data
k.get(id)Retrieve data that needs ot be saved to db
k.export()Reset all data (after save to db)
k.clear_all()
Package: krakenci-client
Kraken CI ClientThis is a client tool for accessing Kraken CI server,https://kraken.ci.About Kraken CIKraken CI is a modern, open-source, on-premise CI/CD system
that is highly scalable and focused on testing.More information can be found onhttps://kraken.ciGetting StartedQuick start guide is here:https://kraken.ci/docs/quick-startFull installation manual:https://kraken.ci/docs/installationAnd here is developers guide:https://kraken.ci/docs/dev-guideUsageGuides can be found here:https://kraken.ci/docs/guide-introDemo site is available here:https://lab.kraken.ci/RoadmapSee theopen issuesfor a list of proposed features (and known issues).ContributingContributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make aregreatly appreciated.Details onhttps://kraken.ci/docs/contrib-krakenLicenseDistributed under the Apache 2.0 License. SeeLICENSEfor more information.ContactMichal Nowikowski -godfryd@gmail.comProject Link:https://kraken.ci
Package: krakenci-server
Kraken CIAbout Kraken CIKraken CI is a modern, open-source, on-premise CI/CD system
that is highly scalable and focused on testing.More information can be found onhttps://kraken.ciGetting StartedQuick start guide is here:https://kraken.ci/docs/quick-startFull installation manual:https://kraken.ci/docs/installationAnd here is developers guide:https://kraken.ci/docs/dev-guideUsageGuides can be found here:https://kraken.ci/docs/guide-introDemo site is available here:https://lab.kraken.ci/RoadmapSee theopen issuesfor a list of proposed features (and known issues).ContributingContributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make aregreatly appreciated.Details onhttps://kraken.ci/docs/contrib-krakenLicenseDistributed under the Apache 2.0 License. SeeLICENSEfor more information.ContactMichal Nowikowski -godfryd@gmail.comProject Link:https://kraken.ci
Package: kraken-class-entity
Entity class apiGeneric class library to interact with kraken db through api.The library handles type and key conversion to ensure compliance.FeaturesAutomatic schema type correction (imageobject --> schema:ImageObject)Automatic record_id assignation if missingAutomatic variable name (key) correction (familyname --> schema:familyName)Automatic value type correction (www.test.com-->https://www.test.com/)How to use:entity: single entity recordentities: collection of entity recordsEntityInitializeentity = Entity()entity.record_type = 'schema:Person'entity.record_id = 'abc'Get/store dataname = entity.get('givenName')entity.set('givenName', name)Get/store record / jsonentity.record = recordrecord = entity.recordentity.json = json_stringjson_string = entity.jsonGet and store data to databaseSet once for all subsequent entitiesentity.api_url = 'url_to_use'Get from dbentity.get_api()entity.get_api_async()Post to dbentity.post_api()entity.post_api_async()EntitiesInitializeentities = Entities()entities.record_type = 'schema:Person'entities.record_id = 'abc'Load / dump dataWill convert records to entityrecords = entity.dump()entity.load(records)Attributesentity.ref_id: dict reference to record ({'@type': 'record_type', '@id': 'record_id'})Get/store record / jsonentities.record = recordrecord = entities.recordentities.json = json_stringjson_string = entities.jsonGet and store data to databaseSet once for all subsequent entitiesentities.api_url = 'url_to_use'Get from dbentities.get_api()entities.get_api_async()Post to dbentities.post_api()entities.post_api_async()
Package: krakenclient
krakenclient: Python API client for Kraken (built on krakenex)Installationpip3installkrakenclientUsageimportkrakenclient.kraken_client_apiaskrakenclient# How to access order book dataxrp_order_book=krakenclient.get_order_book(pair='XRPUSD')print(xrp_order_book)# How to perform account operationskrakenclient.set_keys(public='your_public_key',private='your_private_key')# Set your api keys to perform account operationstrade_balance=krakenclient.get_trade_balance(asset='XRPUSD')print(trade_balance)# Need help?krakenclient.i_need_help()DependenciesPython 3krakenex: 2.1.0DisclaimerWe are not affiliated with Kraken and this is a third-party implementation.
Package: kraken-common
kraken-commonThekraken-commonpackage is the shared utility namespace for the Kraken build system and
the Kraken wrapper CLI. It contains various generic utilities, as well as the tools for loading
the metadata of a Kraken project.Aside from general utilities that are used by one, the other or both, this package also implements the
shared logic for executing Kraken Python and BuildDSL build scripts and retrieving its metadata.Script runnersThe following types of Kraken script runners are currently available via thekraken.commonpackage:PythonScriptRunner: Matches akraken.pyor.kraken.pyfile and runs it as a pure Python script.BuildDslScriptRunner: Matches akraken.buildor.kraken.buildfile and runs it as abuilddslscript, with thebuildscript()function being available by default.Buildscript metadataA Kraken project contains at least one.kraken.pyfile (build script) and maybe a.kraken.lockfile (lock file). The build script at the root of a project may contain hints for the Kraken wrapper
CLI to be able to correctly bootstrap an environment that contains the Kraken build system.PythonBuildDSLfromkraken.commonimportbuildscriptbuildscript(requirements=["kraken-std ^0.4.16"],)buildscript{requires"kraken-std ^0.4.16"}The way that this works is that thebuildscript()function raises an exception that aborts the execution
of the build script before the rest of the script is executed, and the exception contains the metadata.
When the build script is executed by the Kraken build system instead, the function does nothing.The API to capture the data passed to a call to thebuildscript()function is as follows:fromkraken.commonimportBuildscriptMetadatawithBuildscriptMetadata.capture()asmetadata_future:...metadata=metadata_future.result()
Package: kraken_connector
kraken-connectorWS and HTTP clients for Kraken exchange APIGithub repository:https://github.com/tlg7c5/kraken-connector/Documentationhttps://tlg7c5.github.io/kraken-connector/Getting started with your projectFirst, create a repository on GitHub with the same name as this project, and then run the following commands:gitinit-bmain
gitadd.
gitcommit-m"init commit"gitremoteaddorigingit@github.com:tlg7c5/kraken-connector.git
gitpush-uoriginmainFinally, install the environment and the pre-commit hooks withmakeinstallYou are now ready to start development on your project!
The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.To finalize the set-up for publishing to PyPi or Artifactory, seehere.
For activating the automatic documentation with MkDocs, seehere.
To enable the code coverage reports, seehere.Releasing a new versionCreate an API Token onPypi.Add the API Token to your projects secrets with the namePYPI_TOKENby visitingthis page.Create anew releaseon Github.Create a new tag in the form*.*.*.For more details, seehere.Repository initiated withfpgmaas/cookiecutter-poetry.
Package: kraken-datatype
kraken datatypeOverviewLibrary to extract, validate and normalize datatypes.datatypes:emailurldomaindatecountryaddresstelephoneboolcurrencydomainfunctions:validate: returns True false if validatenormalize: returns normalized value or Noneguess: return best guess or None of datatypeHow to use:import kraken_datatype as dt 

result = dt.validate('email', 'name@test.com')
print(result)

result = dt.normalize('email', 'name@test.com')
print(result)

result = dt.guess('name@test.com')
print(result)
Package: kraken-db-api
Python library to access kraken-db via apiHow to use:import kraken_db_api as dbdb.set_db_url('url of the db server')Post
db.post(observation)Get
observations = db.get(record_type, record_id, key, value)Get schemas
schemas = db.get_schemas()Search
search_params = {
'record_type': 'person',
'record_id': 'id',
'order_by': 'created_date',
'order_direction': 'desc',
'limit': 20,
'offset': 20
}
observations = db.search(search_params)
Package: kraken-db-sqlite
Library to schema_orgHow to usefrom kraken_db import kraken_db as dbdb.init()Data dictionaryObservationid = Column(String)
observation_id = Column(String, primary_key=True)
ref_id = Column(String)
datasource = Column(String)
agent = Column(String)
instrument = Column(String)
object = Column(String)
result = Column(String)
start_time = Column(DateTime)
end_time = Column(DateTime)
valid = Column(Boolean)

record_type = Column(String)
record_id = Column(String)
key = Column(String)
value = Column(String)
credibility = Column(Float)
created_date = Column(DateTime)
Package: kraken-entity-client
Kraken Entity ClientOverviewClass to interact with kraken db as entityHow to usefrom kraken_entity_client.kraken_entity_client import Kraken_entity_client as KSet api url(only have to do it once, will be reused as env variable for other instances)k1 = K()
k1.set_api_url('https://krakenengine.tactik8.repl.co/api')Get recordk1 = K()
k1.record_type = 'schema:test'
k1.record_id = 'id_of_record'
k1.get()
record = k1.recordPost recordk1 = K()
k1.record = record
k1.post()
Package: krakenexapi
A Kraken Exchange API adapter.Free software: MIT licenseInstallationpip install krakenexapiYou can also install the in-development version with:pip install https://github.com/Querela/python-krakenexapi/archive/master.zipDocumentationhttps://python-krakenexapi.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelogWIP0.0.1 (2020-12-27)Add raw kraken Exchange API.Add basic Kraken Exchange API - public methods.Add custom exceptions.Add basic response classes for better accessing of entries, fix stringified floats.Add call rate limiting (crl).Add tests for crl, more in work.Add private user data API endpoints.Add basic documentation.First official pre-release.0.0.0 (2020-12-25)First release on PyPI.
Package: kraken-extract-from-html
Extract from htmlWhat it doesExtracts the following from html:urlsemailsimagestablesstructured data (schema.org)texttitlefeedsHow to useUsing the apiSend a url (get)Send the url as a query parameter 'url'.
Will retrieve the content and return extracted data.
If 'contentUrl' provided, will use the content from 'contentUrl' but use 'url' as attributesSend a WebContent object (post)The content will be extracted from either the 'text' field or it will retrieve the content from the url in 'archivedAt'.{
    "@type": "webContent",
    "url": [
        "https://storage.googleapis.com/kraken-cdn/641fcdaa9664421b3ac4db2b6b494397bf0dc8d65a559e9c2238de77d09e740e.html"
    ],
    "archivedAt": [
        "https://storage.googleapis.com/kraken-cdn/641fcdaa9664421b3ac4db2b6b494397bf0dc8d65a559e9c2238de77d09e740e.html"
    ],
    "about": {
        "@type": "webPage",
        "url": "https://www.petro-canada.ca/en/business/rack-prices"
    }
}Using the libraryProvided url of the page and html content, returns list of records with extractions.from kraken_extract_from_html import kraken_extract_from_html as krecords = k.get(url, html)
Package: kraken-flake8-extensions
kraken-flake8-extensionsThis Flake8 plugin implements lints specific for the code base of the Kraken build system.CodeDescriptionKRE001Annotations onkraken.core.property.Objectsubclasses (such as tasks) must use backwards compatible type hints because they are evaluated at runtime. Use collection types from thetypingmodule instead.KRE002Use of built-in type subscripts (3.9+) or type unions (3.10+) requiresfrom __future__ import annotationsfor backwards compatibility.
Package: krakenforwarder
krakenforwarderThis Python program listens to trades from Crypto-exchange platform Kraken (https://www.kraken.com) and forwards them on a TCP port so you can plug in anything, like a live algorithmic trader or a live analysis tool.Installationpip3 install krakenforwarderUsageLaunch the forwarder in sub-process, then listenimporttimefrommultiprocessingimportProcessfromkrakenforwarder.forwarderimportKrakenForwarderfromkrakenforwarder.listenerimportlistenfromkrakenforwarder.utilimport*cfg_forwarders=[{F_PULL_PERIOD:5,# in secondsF_ASSET_PAIR:'XXBTZEUR',# see https://support.kraken.com/hc/en-us/articles/360000920306-Ticker-pairsF_TYPE:V_SPOT,F_ZMQ_PUBLISH_PORT:5555},{F_PULL_PERIOD:5,# in secondsF_ASSET_PAIR:'XETHZEUR',# see https://support.kraken.com/hc/en-us/articles/360000920306-Ticker-pairsF_TYPE:V_SPOT,F_ZMQ_PUBLISH_PORT:5556},]cfg_listener={F_KEY_ZMQ_HOSTNAME:'localhost',F_ZMQ_PUBLISH_PORT:[cfg[F_ZMQ_PUBLISH_PORT]forcfgincfg_forwarders]}proc_forwarders=[]forcfgincfg_forwarders:kraken_forwarder=KrakenForwarder(cfg)forward_process=Process(target=kraken_forwarder.forward)proc_forwarders.append(forward_process)forprocinproc_forwarders:proc.start()time.sleep(1)formsginlisten(cfg_listener):print(msg)forprocinproc_forwarders:proc.join()This prints trades in console:{"pair": "XXBTZEUR", "Trade": ["9388.90000", "0.01604115", 1568346002.9574, "b", "m", ""]}
{"pair": "XXBTZEUR", "Trade": ["9390.00000", "0.03569491", 1568346002.9981, "b", "m", ""]}
{"pair": "XXBTZEUR", "Trade": ["9390.00000", "0.01000000", 1568346003.0047, "b", "m", ""]}
{"pair": "XXBTZEUR", "Trade": ["9392.90000", "0.03477392", 1568346003.0213, "b", "m", ""]}
OVER
...
{"pair": "XXBTZEUR", "Trade": ["9384.50000", "0.00500000", 1568346015.5326, "s", "m", ""]}
OVER
{"pair": "XETHZEUR", "Trade": ["162.98000", "0.24458271", 1568346014.6035, "s", "m", ""]}
{"pair": "XETHZEUR", "Trade": ["162.98000", "0.00063427", 1568346014.6274, "s", "m", ""]}
{"pair": "XETHZEUR", "Trade": ["162.98000", "0.00000165", 1568346014.6296, "s", "m", ""]}
OVERTo call forward contracts, instead usefromkrakenforwarder.utilimport*cfg_forwarders=[{F_PULL_PERIOD:5,# in secondsF_ASSET_PAIR:'pi_xbtusd',F_TYPE:V_FUTURES,# see https://support.kraken.com/hc/en-us/articles/360022839531-Tickers for possible choicesF_ZMQ_PUBLISH_PORT:5557},]
Package: kraken-html
kraken_htmlHow to usefrom kraken_html import kraken_html as mQuick startRecordsConverts a record into a HTML record, where url are transformed as a links for exampleHTML record formatfrom kraken_html import kraken_html as m

record = {...}
html_record = m.html_record.html_record(record)HTML record listfrom kraken_html import kraken_html as m

records = [{...}, {...}]
records_list = m.html_record.to_list(records)HTML record formfrom kraken_html import kraken_html as m

record = {...}
record_form = m.html_record.to_json(record)PagesPages are full website pages that includes navigation, heaters and footers.from kraken_html import kraken_html as m

page_content = 'some content...'
webpage = m.pages.blank(page_content)SectionsSections are components of pages, building blocks to build full pagesHeroImage with key benefitrecord = {
    "headline": "Headline 1",
    "text": "Some text"
}

theme = 'dark'
page_content = m.section.hero(record, theme)
webpage = m.pages.blank(page_content)