Saravanan666/pypi-org huggingface dataset:
Package: jackett-indexarr
jackett indexarrSets up radarr, sonarr, readarr & lidarr with the configured trackers in jackettJackett connection setupexport jackett_cookie="get the cookie from chrome session"
export jackett_endpoint="http://192.168.0.30:9117"
export jackett_api_key="dddddddddddddddddddddddddddddddddddddddddd"Define where sonarr, radarr & lidarr dbs areexport sonarr_db="/home/to/sonarr/sonarr.db"
export radarr_db="/home/to/radarr/radarr.db"
export lidarr_db="/home/to/lidarr/lidarr.db"Execute itpip install jackett-indexarr
jackett-indexarr
Package: jackfruit
JackfruitIntroductionThis library provides a simple way for creating telegram bots with deep level menu.ComponentsLibrary give users components, like:Menu (MenuView) - give user ability select menu item and navigate on menus;Text Input (TextDataInputView) - give user ability enter text data;Image Input (PhotoDataInputView) - give user ability send image to bot;Document Input (DocumentDataInputView) - give user ability send files to bot;Audio Input (AudioDataInputView) - give user ability send audio files to bot;Video Input (VideoDataInputView) - give user ability send video files to bot;Voice Input (VoiceDataInputView) - give user ability send voice messages to bot;Sticker Input (StickerDataInputView) - give user ability send sticker to bot;You can use classGenericDataViewfor show user screen, that blocking next navigation and force user to use command syntax.All components may be easy customized, for more details please see source code (it have commented).Usagefromosimportenvironfromtelegram.extimportUpdaterfromjackfruitimport*classMainMenu(MenuView):text='Hello from my bot!'menu_items=[[('Enter my name','EnterName'),('Select my age','SelectAge')],]classEnterName(TextDataInputView):text='Enter my name:'defprocess_data(self,state,update,context,data):return'MainMenu'classSelectAge(MenuView):text='Select my age:'menu_items=[[('Below 18','MainMenu'),('Above 18','MainMenu')]]updater=Updater(environ['TOKEN'],use_context=True)main_menu=MainMenu()enter_name=EnterName()select_age=SelectAge()Jackfruit(updater.dispatcher,main_menu,[('start','MainMenu')]).register(enter_name,select_age)updater.start_polling()updater.idle()
Package: jackhash
Japanese, ASCII, Chinese, Korean - Hash encodingEver felt sha256 hexdigests are way too long? We have unicode everywhere now, right? Why not use the full range of characters of unicode to encode the hash?
Well, there are some potential issues to take into consideration.Many characters in ASCII have special meaning to a machine, which potentially breaks highlighting. Emojis are especially troublesome due to interoperability - many editors, chat clients etc. don't display the same emoji in the same way, some even expand the emoji to a :text:, which defeats the whole purpose of compressed encoding.
However, the chinese, japanese and korean alphabets arehugein comparison, yet don't come with any of these downsides - editors, chat clients etc. all seem to display these characters the same way and there is no special meaning assigned to any of these characters by machines, so they are handled properly as one big string, easy to highlight and copy&paste.I curated all those different alphabets into one (japanese would only add 100 single characters to the chinese and korean alphabets and the license would be GPL3, so I left that one out actually) - coming up with a combined alphabet of 27642 characters, which allows to boil down the length of a sha256 digest down to just 18 characters which you can freely send via chat or put in Python 3 code files since they are unicode by default.LicensingBoth Chinese (https://github.com/tsroten/zhon/blob/develop/zhon/cedict/all.py) and Korean (https://github.com/arcsecw/wubi/blob/master/wubi/cw.py) alphabets are licensed under MIT
Package: jackknife
jackknifeJackknife resampling, parameter estimation and stability test.InstallationThejackknifegit repois available asPyPi packagepip install jackknifeUsageCheck theexamplesfolder for notebooks.CommandsCheck syntax:flake8 --ignore=F401Remove.pycfiles:find . -type f -name "*.pyc" | xargs rmRemove__pycache__folders:find . -type d -name "__pycache__" | xargs rm -rfUpload to PyPi with twine:python setup.py sdist && twine upload -r pypi dist/*SupportPleaseopen an issuefor support.ContributingPlease contribute usingGithub Flow. Create a branch, add commits, andopen a pull request.
Package: jackmesh
jackmeshManage your Jack audio server connections with ease usingjackmesh, a lightweight Python utility that leverages plain TOML configuration files.FeaturesDump current Jack connections in TOML format.Load Jack connections from TOML files. Default fallback to loading from~/.jack_connections.tomlif no file specified.InstallationpipinstalljackmeshUsageDump Current Jack ConnectionsTo dump current jack connections to stdout in TOML format:jackmesh-dYou can also redirect this output to a file:jackmesh-d>my_connections.tomlLoad Jack ConnectionsLoad jack connections using:jackmesh-lpath/to/your/file.tomlIf no file is specified,jackmeshwill by default look for~/.jack_connections.toml:jackmesh-lThe assumption is that the TOML file provides the complete connection configuration and no other connections shall exist. Before applying the config file all existing connections will be removed.Configurationjackmeshuses TOML format for its configuration files. An example of the configuration file:[Pianoteq]out_1=["system:playback_FL",]out_2=["system:playback_FR",]["Built-in Audio Pro"]capture_AUX0=["REAPER:in1",]capture_AUX1=["REAPER:in2",][REAPER]out1=["Built-in Audio Pro:playback_AUX0",]out2=["Built-in Audio Pro:playback_AUX1",]ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.See alsojackmesh: A Tool for Managing Jack Audio Server ConnectionsLicenseGNU GPL v3
Package: jack-netbridge
jack_netbridgejack_netbridgeis a Python tool to send and receive Jack audio and MIDI as multicast network streams. This is useful for transmitting audio or MIDI over a network with minimal latency using the JACK audio system.Installationpip install jack-netbridgeUsageusage:jack_netbridge[-h][-cCONFIG]jack_netbridge:send/receiveJackaudioandMIDIasmulticaststreams

options:-h,--helpShowthishelpmessageandexit.-cCONFIG,--configCONFIGPathtotheconfigurationfile.Configuration file exampleBy defaultjack_netbridgewill look for the~/.jack_netbridge.tomlfile to read configuration. Each section in the TOML file describes a client and a port with arbitrary names, separated by:.Configuration example:["audio_recv_L:out"]
type = "AudioReceiver"
multicast_group = "239.0.0.1"
multicast_port = 4023
multicast_ttl = 2
interface_name = "eth1"

["audio_recv_R:out"]
type = "AudioReceiver"
multicast_group = "239.0.0.1"
multicast_port = 4024
multicast_ttl = 2
interface_name = "eth1"

["midi_recv_R:in"]
type = "MidiTransmitter"
multicast_group = "239.0.0.1"
multicast_port = 4025
multicast_ttl = 2
interface_name = "eth1"TroubleshootingGarbled audio: make sure that both sample rate and buffer size are identical for both receiver and transmitter.No data sent or received: check if the current multicast group is sent / received on the right interface, e. g by checkingip routeoutput.ContributionWe welcome contributions to improve this project. Please submit issues and pull requests on the GitHub page.LicenseThis project is licensed under the MIT License. See theLICENSEfile for details.Feedback and IssuesIf you encounter any issues or would like to give feedback, please open an issue on the GitHub repository.See also:jack-netbridge: Send Your JACK Audio/MIDI as Multicast Network Streams
Package: jackofspades-lib-lab-lotr
Lord of the Rings SDKThis is a sample SDK as a take home assessment for liblabInstallpip install jackofspades_lib_lab_lotrExample uses:fromlotr_sdkimportBook,Movie# Get all booksbooks=Book.get()# Get a certain bookid="5cf5805fb53e011a64671582"book=Book.get(id)# Get all moviesmovies=Movie.get()# Get a certain movieid="5cd95395de30eff6ebccde56"movie=Movie.get(id)# Get all quotes from a moviemovie=Movie.get(id)quotes=movie.quotes# And so on...Testing:Install pytestpython -m pip install pytestrunbash test.shor runpython -m pytest testsfrom the projects root directory
Package: jackpolynomials
jackpolynomialsJack polynomials with Python.>>>fromgmpy2importmpq>>>fromsympy.combinatorics.partitionsimportIntegerPartition>>>fromjackpy.jackimportJackPol>>>>>>poly=JackPol(3,IntegerPartition([2,1]),alpha=mpq(3,2))>>>print(poly)Poly(7/2*x_0**2*x_1+7/2*x_0**2*x_2+7/2*x_0*x_1**2+6*x_0*x_1*x_2+7/2*x_0*x_2**2+7/2*x_1**2*x_2+7/2*x_1*x_2**2,x_0,x_1,x_2,domain='QQ')
Package: jack-select
This application displays an icon in the system tray (also known as
notification area) of your desktop, which shows the status of theJACKaudio
server and when you click on it, a menu pops up, which lets you quickly select
from the JACK configuration presets you created withQjackCtl. When you
select a preset, its JACK engine and driver configuration settings are loaded
via DBus into JACK and then the server is restarted. This allows you to switch
between different audio setups with just two mouse clicks.jack-selectworks with the DBus-version of JACK only. It is written in
Python 3 using thePyGObjectbindings for GTK 3. Python 2 is not supported.It is available from the source code repository on GitHub:https://github.com/SpotlightKid/jack-selectReleases can be downloaded from the Python Package Index:https://pypi.org/project/jack-selectjack-selectis also available as an Arch Linux package from the Arch User
Repository:https://aur.archlinux.org/packages/jack-select/
Package: jack-server
ControlJACKaudio server with Python.
Can be used as replacement forjackdfor more robust configuration, for example, when usingjackpackage.Installationpip install jack_serverAlso you need to havejackserverlibrary on your machine, it comes withJACK2. I had problems with apt-package on Ubuntu (jackd2), if you do too, compile jack yourself.Usage🎛jack_server.ServerOn server creation youcanspecify some parameters:importjack_serverserver=jack_server.Server(name="myfancyserver",sync=True,realtime=False,driver="coreaudio",device="BuiltInSpeakerDevice",rate=48000,period=1024,# nperiods=2  # Work only with `alsa` driver)server.start()input()They are actually an equivalent ofjackdflags:-n,--nametoname,-S,--synctosync,-R,--realtime,-r,--no-realtimetorealtime,-dtodriver,And driver arguments:-d,--devicetodevice,-r,--ratetorate,-p,--periodtoperiod,start(self) -> NoneOpenandstartthe server. All state controlling methods are idempotent.stop(self) -> NoneStop and close server.driver: jack_server.DriverSelected driver.name: strActual server name. It is property that calls C code, so you can actually set the name.sync: boolWhether JACK runs in sync mode. Useful when you`re trying to send and receive multichannel audio.realtime: boolWhether JACK should start in realtime mode.params: dict[str, jack_server.Parameter]Server parameters mapped by name.💼jack_server.DriverDriver (JACK backend), can be safely changed before server is started. Not supposed to be created by user code.name: strDriver name, read-only.device: strSelected device.rate: jack_server.SampleRateSampling rate.period: intBuffer size.nperiods: intNumber of periods. 2 is right for motherboard, PCI, PCI-X, etc.; 3 for USB (source).Can be helpful when tailoring performance on jittery systems.params: dict[str, jack_server.Parameter]Driver parameters mapped by name.📻jack_server.SampleRateValid sampling rate,44100or48000.🔻jack_server.ParameterNot supposed to be created by user code.name: strRead-only verbose name of parameter.value: int | str | bytes | boolValue of the parameter, can be changed.❗️jack_server.set_info_function(callback: Callable[[str], None] | None) -> NoneSet info output handler. By default JACK does is itself, i. e. output is being printed in stdout.‼️jack_server.set_error_function(callback: Callable[[str], None] | None) -> NoneSet error output handler. By default JACK does is itself, i. e. output is being printed in stderr.
Package: jack-web
jack_webThis script starts a webserver and serves an interface to patch jack connectionsinstallation$ pip install jack_webusagestart the server$ jack_webthe webinterface can be accessed on this pagehttp://localhost:2323/editing html & cssfirst: find the directory in which your package is installed$ pip show jack_web | grep Locationappendjack_web/templates/index.htmlin my case/home/ljurk/.local/lib/python3.8/site-packages/jack_web/templates/index.html
Package: jackyleeutils
# Personal Utilities## Test if you install successfullyimport jackylee.test as jl
jl.test()## Algorithm### Sortimport jackylee.algorithm.sort as jst
jst.quick_sort([6,10,13,5,8,3,2,11])### Union and findimport jackylee.algorithm.unionfind as juf## Leecodeimport jackyutils.leecode as *
Package: jacky-tools
Problem StatementData scientists code up a lot of pipelines that can often take a long time due to long pre-processing sequences or massive
amounts of time required. And if errors occur, then the pipeline needs to be re-run. This means we usually want to be notified
as early as possible if errors occurred.So what is pipelinenotifier?Pipeline notifier will send messages to your Slack/Discord/Keybase channel once you set up a webhook. Support can be added for
more channels if desired. Feel free to ping me atjacky.wong@vctr.ai. It will send error messages so you can tell what is wrong
the moment it happens.Data Science BotsAs data scientists, you are running a lot of code over a large amount of time. This often means that that you want to be notified about things via mobile while you have applications running in the background.I ended up re-writing this code across a number of organisations.from pipelinenotifier import KeyBaseNotifier

with KeyBaseBot(, "<webhook_url>") as bot:
    # Insert training loop/reader here.
    score = 0.5
    bot.send_message(f"Scored {score}.")If there is an error, it will send the error message to your channel.
Package: jacobi
Fast numerical derivatives for analytic functions with arbitrary round-off error and error propagation.Click here for full documentation.FeaturesRobustly compute the generalised Jacobi matrix for an arbitrary real analytic mapping ℝⁿ → ℝⁱ¹ × … × ℝⁱⁿDerivative is either computed to specified accuracy (to save computing time) or until maximum precision of function is reachedAlgorithm based on John D’Errico’sDERIVEST: works even with functions that have large round-off errorUp to 1000x faster thannumdifftoolsat equivalent precisionReturns error estimates for derivativesSupports arbitrary auxiliary function argumentsPerform statistical error propagation based on numerically computed jacobianLightweight package, only depends on numpyPlanned featuresCompute the Hessian matrix numerically with the same algorithmFurther generalize the calculation to support function arguments with shape (N, K), in that case compute the Jacobi matrix for each of the K vectors of length NExamplesfrommatplotlibimportpyplotaspltimportnumpyasnpfromjacobiimportjacobi# function of one variable with auxiliary argument; returns a vectordeff(x):returnnp.sin(x)/xx=np.linspace(-10,10,200)fx=f(x)# f(x) is a simple vectorized function, jacobian is diagonalfdx,fdxe=jacobi(f,x,diagonal=True)# fdxe is uncertainty estimate for derivativeplt.plot(x,fx,color="k",label="$f(x) = sin(x) / x$")plt.plot(x,fdx,label="$f'(x)$ computed with jacobi")scale=14plt.fill_between(x,fdx-fdxe*10**scale,fdx+fdxe*10**scale,label=f"$f'(x)$ error estimate$\\times\\, 10^{{{scale}}}$",facecolor="C0",alpha=0.5,)plt.legend()fromjacobiimportpropagateimportnumpyasnpfromscipy.specialimportgamma# arbitrarily complex function that calls compiled libraries, numba-jitted code, etc.deffn(x):r=np.empty(3)r[0]=1.5*np.exp(-x[0]**2)r[1]=gamma(x[1]**3.1)r[2]=np.polyval([1,2,3],x[0])returnr# x and r have different lengths# fn accepts a parameter vector x, which has an associated covariance matrix xcovx=[1.0,2.0]xcov=[[1.1,0.1],[0.1,2.3]]y,ycov=propagate(fn,x,xcov)# y=f(x) and ycov = J xcov J^TComparison to numdifftoolsSpeedJacobi makes better use of vectorized computation than numdifftools and converges rapidly if the derivative is trivial. This leads to a dramatic speedup in some cases.Smaller run-time is better (and ratio > 1).PrecisionThe machine precision is indicated by the dashed line. Jacobi is comparable in accuracy to numdifftools. The error estimate has the right order of magnitude but slightly underestimates the true deviation. This does not matter for most applications.
Package: jacobs-jinja-too
Jacob's Jinja TooA simple wrapper around Jinja2 templating with a collection of custom filters.Jinja2is a templating language for Python.Only tested with Python3.7.The main purpose for this project is for depencency management as this diagram shows:[Top Level Project] --> [jacobs-jinja-too] : uses
[Top Level Project] --> [Another Project]  : depends
[Another Project] --> [jacobs-jinja-too]   : usesInstallationpip3installjacobs-jinja-tooExample UsagefromjacobsjinjatooimportTemplatorasjj2t=jj2.MarkdownTemplator()t.add_template_dir('templates/')params={"name":"My Name"}t.render_template('foo.jinja2',output_name='foo.txt',**params)LicenseGPLv2There is no copyright claim or ownership of any content created by jacobs-jinja-too.
Package: jacobs-json-doc
jacobs-json-docA JSON/YAML loader for Python3.PyYAMLorruamel.yamldo a good job at parsing YAML or JSON into a Python object. This package wraps ruamel.yaml to provide a little bit of extra functionality.Line NumbersIf you're trying to do use parts of a JSON/YAML document, and you find that the structure of the document didn't conform to a schema or expectations, then you might want to display an error saying something like "On line 123, the value of foo was missing."  This package allows easier access to the YAML/JSON line numbers by accessing the.lineproperty.Dollar ReferencesJSON Schema, OpenAPI, AsyncAPI, and others have a concept of references like this:{"$ref": "other.json#/path/to/definition"}.The idea here is that instead of the JSON object with the$refyou should be able to get a JSON structure from somewhere else.  In this example, you should find a document calledother.jsonand pull out a structure at/path/to/definition.LoaderAloader object(inherits fromjacobsjsondoc.loader.LoaderBaseClass) is able to get the JSON/YAML source.  The loader can be different if you are loading from a database, filesystem, http, etc.Reference ModesGiven a loader, jacobs-json-doc can deal with dollar references.  There are two modes for how it can deal with references:UseDocReferenceobjects.  Anywhere in the document tree where there is a$refreference, aDocReferenceobject is created.Automatic resolution.  Anywhere in the document tree where there is a$refreference, the reference is automatically resolved and the$refs are replaced with the structures that they were referencing.ExamplesThetest_document.pyfile is a good source for examples.A very brief example is:fromjacobsjsondoc.documentimportcreate_documentmy_document="/path/to/example.yaml"doc=create_document(uri=my_document)print(doc['a']['b'])print(doc['a']['b'].line)If you are loading a single bit of data, without any$refreferences, you can do it like this:importjacobsjsondoctext_data='{"hello":"world"}'doc=jacobsjsondoc.parse(text_data)LicenseGPLv2
Package: jacobs-json-schema
jacobs-json-schemaThis package is yet another JSON Schema validator.  I wrote it because I needed something small to run in Python 3.5.Most data validation features are supported without any dependencies (see "Conformance").DocumentationIs available atRead the Docs.UsageBefore using this library, the schema dna data must already be parsed into a Python data structure.  This can be as simple as usingjson.loads().fromjacobsjsonschema.draft7importValidatorschema={"type":"string"}validator=Validator(schema)data="Hello world"validator.validate(data)# Will throw if there are any validation errorsLazy error reporting is also supported.  This means that as much of the data as possible is evaluated, and errors are collected instead of raising an exception.schema={"type":"string"}validator=Validator(schema,lazy_error_reporting=True)data="Hello world"ifvalidator.validate(data):print("Validated")else:forerrorinvalidator.get_errors():print(error)ConformanceThere are two ways of running the validator:Passing a JSON-deserialized Python dictionary as the schema.  There are no additional external dependencies needed.  Straightforward$refreferences (no usage of$id) within the same schema are supported.Parse the schema using utility from thejacobs-json-docpython package, and pass the wrapped schema to the validator.  Several external dependencies are required.  Full$idand$reffunctionality is supported.Where "Mostly" is specified, it passes all tests excluding those fromref.json,id.json,defintions.json,refRemote.jsonandunknownKeyword.json.SpecificationStandaloneusing jacobs-json-docPython Version3.5+3.7+Draft-04MostlyPassedDraft-06MostlyPassedDraft-07MostlyPassedDraft-2019-09UntestedUntestedDraft-2020-12UntestedUntestedLicenseMIT License.  If you modify the source, please publish your modifications.
Package: jacot
This module provides the auto-conversion filter
supports well-known Japanese Encodings(CP932/EUC-JP).Installvia github$ git clone https://github.com/saitoha/jacot.git
$ cd jacot
$ python setup.py installor via pip$ pip install jacotUsage$ jacot [options] [command | -]Options:-h, --help                  show this help message and exit
--version                   show version
-t TERM, --term=TERM        override TERM environment variable
-l LANG, --lang=LANG        override LANG environment variable
-o ENC, --outenc=ENC        set output encoding
--disable-input-conversion  disable input auto conversion
--disable-output-conversion disable output auto conversion
-s, --enable-skk            use SKK input methodDependenceHayaki Saito’s TFF, Terminal Filter Frameworkhttps://github.com/saitoha/tffHayaki Saito’s Sentimental-SKKhttps://github.com/saitoha/sentimental-skkSentimental-SKK package includes the large SKK dictionary,
SKK-JISYO.L (Masahiko Sato et al./SKK Development Team).http://openlab.jp/skk/skk/dic/SKK-JISYO.LReferencesLuit - locale and ISO 2022 support for Unicode terminalshttp://www.pps.univ-paris-diderot.fr/~jch/software/luit/cocot - COde COnverter on Ttyhttp://vmi.jp/software/cygwin/cocot.htmlcygwin ck terminal emulatorhttp://www.geocities.jp/meir000/ck/Unicode Text Editor MinEdhttp://towo.net/mined/libfephttps://github.com/ueno/libfepDaredevil SKK (DDSKK)http://openlab.ring.gr.jp/skk/ddskk-ja.html
Package: jacotei-api
# jacotei-api-sdk-python3## Exemplos ##Publicacao de 1000 ofertas```Python#!/usr/bin/python3import jsonfrom jacotei_api_v1 import *from jacotei_api_v1.api import *from jacotei_api_v1.model import *from jacotei_api_v1.client import ApiClient;apiClient = client.ApiClient({'client_id':'xxxxx','access_token':'xxxx'},'https://webapisb.jacotei.com.br/publisher/v1')offers_api = OffersApi.OffersApi(apiClient)offer_request = OfferRequest.OfferRequest()offer_request.offers = []for i in range(0,  1000):offer = Offer.Offer()offer.sku = ioffer.available = True;offer.title = 'Produto '+str(i)offer.link = 'http://aasdfaf.com/asdflasdf'offer.images = ['http://aasdfaf.com/asdflasdf.jpg']offer.categories = ['Categoria','Subcategoria','Sub subcategoria']price = OfferPrice.OfferPrice()price.price = 1.99price.installment = 1price.installment_value = 1.99offer.prices  = [price]offer_request.offers .append(offer)try:offers_result = offers_api.update_offers_using_post(offers = offer_request)print (vars(offers_result))except BaseException as e:print(e.msg)```