Saravanan666/pypi-org huggingface dataset:
Package: pyjack
pyjack is a debug/test/monkey-patching toolset that allows you to reversibly
replaceallreferences to a function or object in memory with a
proxy function or object. pyjack has two major functions:function “connect” can connect a ‘proxy’ function to almost
any python function/method.  This proxy function is called instead of the
original function.  However, the original function is passed to the proxy
function along with all args, kwargs so you can do things like:Modify the args, kwargs first, print a debug message, then call the original
functionNot call the function, rather just log it and print a debug messageetc. etc. – it’s all up to you.function “replace_all_refs” can be used to replace all
references to a object with references to another object. This replaces all
references in the _entire_ memory space.  You get one final reference to the
original reference, so it is possible to call this function again to restore
the memory state back to it’s original state.“connect” function>>> import pyjack
>>>
>>> def fakeimport(orgopen, *args, **kwargs):
...     print 'Trying to import %s' % args[0]
...     return 'MODULE_%s' % args[0]
...
>>> pyjack.connect(__import__, proxyfn=fakeimport)
<..._PyjackFuncBuiltin object at 0x...>
>>>
>>> import time
Trying to import time
>>> print time
MODULE_time
>>>
>>> __import__.restore()
>>>
>>> import time
>>> print time
<module 'time' (built-in)>“replace_all_refs” functionSetup an ‘item’ reference and put it in a few places:>>> item = (100, 'one hundred')
>>> data = {item: True, 'itemdata': item}
>>>
>>> class Foobar(object):
...     the_item = item
...
>>> def outer(datum):
...     def inner():
...         return ("Here is the datum:", datum,)
...
...     return inner
...
>>> inner = outer(item)
>>>
>>> print item
(100, 'one hundred')
>>> print data
{'itemdata': (100, 'one hundred'), (100, 'one hundred'): True}
>>> print Foobar.the_item
(100, 'one hundred')
>>> print inner()
('Here is the datum:', (100, 'one hundred'))Then replace them:>>> new = (101, 'one hundred and one')
>>> org_item = pyjack.replace_all_refs(item, new)
>>>
>>> print item
(101, 'one hundred and one')
>>> print data
{'itemdata': (101, 'one hundred and one'), (101, 'one hundred and one'): True}
>>> print Foobar.the_item
(101, 'one hundred and one')
>>> print inner()
('Here is the datum:', (101, 'one hundred and one'))But you still haveonefinal reference to the org data:>>> print org_item
(100, 'one hundred')So the process is reversible:>>> new = pyjack.replace_all_refs(new, org_item)
>>>
>>> print item
(100, 'one hundred')
>>> print data
{'itemdata': (100, 'one hundred'), (100, 'one hundred'): True}
>>> print Foobar.the_item
(100, 'one hundred')
>>> print inner()
('Here is the datum:', (100, 'one hundred'))Other ReferencesFor full documentation and several examples please visit:http://packages.python.org/pyjack/The git repo is here:https://github.com/cart0113/pyjack
Package: pyjacklib
pyjacklibPython bindings forlibjackusingctypes, which allow you to write JACK
client applications in Python.The library provides a low-level, almost unaltered mapping of thelibjackC API, plus a few additional convenience functions.The source code repository contains a fewexample scriptsto show its usage.Note:pyjacklibas a stand-alone project is in beta-stage and the API
may still change slightly before a 1.0 release. You have been warned!DependenciesTo use the library, your system needs to have the following installed at
run-time:TheJACKlibraryA Python 3 implementation, which supportsctypesTo build and install the library you need:setuptools(optional)pipBuilding and InstallingYou can download and installpyjacklibdirectly from PyPI usingpip:pip install pyjacklibOr you can download the latest source archive or clone the git repository
and run the following from inside the unpacked source directory resp. the root
of your checkout:python setup.py installYou can also build a wheel with:pip wheel .... and install it usingpip install.Licensepyjacklibis licensed under the GNU Public License Version v2, or
any later version.Please see the fileCOPYING.mdfor more information.AuthorsCreated byFilipe Coelho (falkTX)as part ofCadence.Turned into a stand-alone project and enhanced byChristopher Arndt.
Package: pyjackson
PyJackson is a serialization library based on type hintingExampleJust type hint__init__and you are ready to go:import pyjackson


class MyPayload:
    def __init__(self, string_field: str, int_field: int):
        self.string_field = string_field
        self.int_field = int_field


pyjackson.serialize(MyPayload('value', 10))  # {'string_field': 'value', 'int_field': 10}

pyjackson.deserialize({'string_field': 'value', 'int_field': 10}, MyPayload)  # MyPayload('value', 10)More features and exampleshereand in examples dir.Installationpip install pyjacksonDocumentationhttps://pyjackson.readthedocs.io/DevelopmentTo run all tests run:toxLicenceFree software: Apache Software License 2.0Changelog0.0.28 (2021-06-02)Support for python 3.90.0.27 (2020-12-05)Fix decorated class module name0.0.26 (2020-07-07)Experimental pydantic support0.0.25 (2020-03-23)Support for int and float keys in dicts0.0.24 (2020-02-22)Support for python 3.80.0.23 (2019-12-16)Fixed bug in subtype resolving0.0.21 (2019-11-25)Fixed default type name0.0.19 (2019-11-25)Allow subtype reregistration flag0.0.18 (2019-11-22)Added support for full class path in type field (with importing logic)0.0.17 (2019-11-21)Added Any support for serde skipping0.0.16 (2019-11-15)Raise on subtype resolve error and fix for camel case forward ref resolving0.0.15 (2019-11-11)Set class docstring and qualname of hierarchy root to be valid0.0.14 (2019-11-05)Added decorator for camel case field renaming0.0.13 (2019-11-03)Added decorator for field renaming0.0.12 (2019-10-28)Fixed is_serializable for Field0.0.11 (2019-10-28)Fixed is_serializable for Signature0.0.10 (2019-10-16)Set class name and module of hierarchy root to be valid0.0.9 (2019-10-09)Removed empty Serialzier __init__ method and fix for staticmethod in serializer0.0.8 (2019-10-07)Changed is_collection to not include dict type0.0.7 (2019-10-04)Added datetime.datetime serializer0.0.6 (2019-10-02)Added Tuple[X, Y] and Tuple[X, …] support0.0.5 (2019-09-30)Fixed comparison of serializers0.0.4 (2019-09-17)Added some examples and minor fixes0.0.3 (2019-09-17)First release on PyPI.
Package: pyjade
PyJade is a high performance port of Jade-lang for python, that converts any .jade source to the each Template-language (Django, Jinja2, Mako or Tornado).UTILITIESTo simply output the conversion to your console:pyjade [-c django|jinja|mako|tornado] input.jade [output.html]INSTALLATIONFirst, you must do:pip install pyjadeOr:python setup.py installNow simplyname your templates with a `.jade` extensionand this jade compiler
will do the rest.  Any templates with other extensions will not be compiled
with the pyjade compiler.DjangoInsettings.py, add aloadertoTEMPLATESlike so:TEMPLATES=[{'BACKEND':'django.template.backends.django.DjangoTemplates','DIRS':[],'OPTIONS':{'context_processors':['django.template.context_processors.debug','django.template.context_processors.request','django.contrib.auth.context_processors.auth','django.contrib.messages.context_processors.messages','django.core.context_processors.request'],'loaders':[# PyJade part:   ##############################('pyjade.ext.django.Loader',('django.template.loaders.filesystem.Loader','django.template.loaders.app_directories.Loader',))],'builtins':['pyjade.ext.django.templatetags'],# Remove this line for Django 1.8},},]Jinja2Just addpyjade.ext.jinja.PyJadeExtensionas extensionjinja_env=Environment(extensions=['pyjade.ext.jinja.PyJadeExtension'])MakoJust addpyjade.ext.mako.preprocessoras preprocessorfrompyjade.ext.makoimportpreprocessorasmako_preprocessormako.template.Template(haml_source,preprocessor=mako_preprocessor)FlaskJust addpyjade.ext.jinja.PyJadeExtensionas extension to the environment of the appapp.jinja_env.add_extension('pyjade.ext.jinja.PyJadeExtension')PyramidAdjust your “your_project/__init__.py” and add the following line somewhere to in the main() functionconfig.include('pyjade.ext.pyramid')Tornado TemplatesAppend this after importing tornado.templatefromtornadoimporttemplatefrompyjade.ext.tornadoimportpatch_tornadopatch_tornado()(...)SyntaxExactly the same as the Jade Node.js module (except of cases, which are not implemented)https://github.com/visionmedia/jade/blob/master/README.mdExampleThis code!!! 5html(lang="en")headtitle=pageTitlescript(type='text/javascript')if(foo) {bar()}bodyh1.titleJade - node template engine#containerifyouAreUsingJadepYou are amazingelsepGet on it!Converts to<!DOCTYPE html><htmllang="en"><head><title>{{pageTitle}}</title><scripttype='text/javascript'>if(foo){bar()}</script></head><body><h1class="title">Jade - node template engine</h1><divid="container">{%if youAreUsingJade%}<p>You are amazing</p>{%else%}<p>Get on it!</p>{%endif%}</div></body></html>Register filtersIf you want to register a function as a filter, you only have to
decorate the function withpyjade.register_filter("filter_name")importpyjade@pyjade.register_filter('capitalize')defcapitalize(text,ast):returntext.capitalize()TESTINGYou must havenosepackage installed.
You can do the tests with:./test.shTODOs and BUGSSee:http://github.com/syrusakbary/pyjade/issues
Package: pyjade-coffin
JadeandJinja2template support for Django usingPyJade’s Jinja2 extension
withCoffin.PyJade’s Django template loader lacks mixin functionality due to the fact
Django has no macro support. This package uses Coffin with PyJade’s Jinja2
extension to overcome this. It also provides a few fixes/tweaks to make jade’s
behavior in Django more closely match the native JavaScript jade engine.What this package does:Registers PyJade’s Jinja2 extension with coffin so.jadefiles are rendered
though Jinja2 which gives us mixin support.Add relative path include support by subclassingcoffinEnvironmentand
overriding thejoin_pathmethod. This matches jade’s native JavaScript
engine’s behavior.Sets Jinja2’s autoescape tofalsewhich allows HTML escaping to be handled
in Jade templates.InstallationInstall PackageInstall with pip:pip install pyjade-coffinSetup DjangoAddcoffinandpyjade-coffintoINSTALLED_APPSinsettings.py:INSTALLED_APPS = (
...
    'coffin',
    'pyjade_coffin',
...
)UsageShortcut Render FunctionsTo render a jade/jinja2 template you can use the render functions in thepyjade_coffin.shortcutsmodule provides:render_to_responserenderrender_to_stringThese functions work just likedjango.shortcuts’ render functions except
they render Jade and Jinja2 templates.NOTE:Jade templates are detected by their file extension so only*.jadefiles get processed by PyJade.Here is an example view:from django.template import RequestContext
from pyjade_coffin.shortcuts import render_to_response


def test_jade(request):
    c = RequestContext(request, {
        'test': ['this', 'is', 'test', 'data'],
        'check': "<em>Autoescape Test</em>",
    })

    return render_to_response('test_page.jade', c)
Package: py-jaeger-tracing
PyJaegerTracingPyJaegerTracing: Ultimate tool for distribution tracing in PythonInstallationpipinstallpy-jaeger-tracingFeaturesMultiprocessing supportContext / Decorator based tracingInjecting / Extracting tracer spanLogger integrationRequests integration using patchingBoto3 integration using patchingTornado integrationAll in Onedocker run -d --name jaeger \
  -e COLLECTOR_ZIPKIN_HTTP_PORT=9411 \
  -p 5775:5775/udp \
  -p 6831:6831/udp \
  -p 6832:6832/udp \
  -p 5778:5778 \
  -p 16686:16686 \
  -p 14268:14268 \
  -p 9411:9411 \
  jaegertracing/all-in-one:1.13
Package: pyjags
PyJAGS: The Python Interface to JAGSPyJAGS provides a Python interface to JAGS, a program for analysis of Bayesian
hierarchical models using Markov Chain Monte Carlo (MCMC) simulation.PyJAGS adds the following features on top of JAGS:Multicore support for parallel simulation of multiple Markov chains (See Jupyter NotebookAdvanced FunctionalitySaving sample MCMC chains to and restoring from HDF5 filesFunctionality to merge samples along iterations or across chains so that sampling can be resumed in consecutive chunks until convergence criteria are satisfiedConnectivity to the Bayesian analysis and visualization package ArvizLicense: GPLv2Supported PlatformsPyJAGS works on MacOS and Linux. Windows is not currently supported.InstallationA working JAGS installation is required.pip install pyjagsUseful LinksPackage on the Python Package Indexhttps://pypi.python.org/pypi/pyjagsProject page on githubhttps://github.com/michaelnowotny/pyjagsJAGS manual and exampleshttp://sourceforge.net/projects/mcmc-jags/files/AcknowledgementsJAGS was created by Martyn PlummerPyJAGS was originally created by Tomasz MiaskoAs of May 2020, PyJAGS is developed by Michael Nowotny
Package: pyjags-arviz
pyjags_arvizMakes MCMC samples from PyJAGS usable in ArviZTable of ContentsInstallationGetting StartedInstallationInstall via PIP:pip install pyjags_arvizorpip3 install pyjags_arvizif not using Anaconda.To get the latest version, clone the repository from github,
open a terminal/command prompt, navigate to the root folder and install viapip install .orpip3 install .if not using Anaconda.UsageImport the function convert_pyjags_samples_dict_to_arviz_inference_data viafrom pyjags_arviz import convert_pyjags_samples_dict_to_arviz_inference_dataHaving sampled the from the posterior distribution using PyJAGS viasamples \
    = jags_model.sample(...)one can writeidata = convert_pyjags_samples_dict_to_arviz_inference_data(samples)to convert the dictionary returned from PyJAGS to an ArviZ InferenceData object.This object can be used in ArviZ to generate trace plots and compute diagnostics.Trace plot:az.plot_trace(idata);Effective sample size:az.ess(idata)Gelman and Rubin statistic:az.rhat(idata)Autocorrelation plot:az.plot_autocorr(idata);
Package: pyjak
PyjakA Python library for reading and writing binary sources. The standard library
packagestructhas many caveats and is not very user friendly. We wrap it for
you and present a slick api with sane exception handling.InstallationThe easiest way to install is through pip:pip3 install pyjakExamplesHeres how you would serialize a common integer:frompyjakimportdump_int32_bytes=dump_int32(1)print(_bytes)Result: (On little endian systems)b'\x01\x00\x00\x00'And to turn it back into an integer:frompyjakimportparse_int32_int=parse_int32(b'\x01\x00\x00\x00')print(_int)Result: (On little endian systems)1Unsigned integersAll integer functions have unsigned versions as well. Lets say you want to fit
the number 4000000000 into a 4 byte integer. You would need the
unsigned version:frompyjakimportdump_uint32_bytes=dump_uint32(4000000000)print(_bytes)Result: (On little endian systems)b'\x00(k\xee'And to turn it back into an integer:frompyjakimportparse_uint32_int=parse_uint32(b'\x00(k\xee')print(_int)Result: (On little endian systems)4000000000Byte orderAs you may have noticed, we didn't need to specify the byte order
(or endianness) of the byte array. This is because all functions in
pyjak defaults to the native byte order of your system.But you can also specify which byte order you want by using theByteOrderenumeration (except when calling int8 or uint8 functions).
The available orders are:frompyjakimportByteOrderByteOrder.LITTLEByteOrder.BIGByteOrder.NATIVEprint(ByteOrder.NATIVE==ByteOrder.LITTLE)Result: (On little endian systems)TrueYou can specify what byte order the serialized output should have:frompyjakimportdump_int32,ByteOrder_bytes=dump_int32(1,ByteOrder.BIG)print(_bytes)Result:b'\x00\x00\x00\x01'Or when parsing:frompyjakimportparse_int32,ByteOrder_int=parse_int32(b'\x00\x00\x00\x01',ByteOrder.BIG)print(_int)Result:1BooleansYou can also serialize booleans. Booleans are assumed to represented as an
unsigned 1 byte integer, where 0 means False and any other value means True.Supported data typesint8 (Signed 1 byte integer)uint8 (Unsigned 1 byte integer)int16 (Signed 2 byte integer)uint16 (Unsigned 2 byte integer)int32 (Signed 4 byte integer)uint32 (Unsigned 4 byte integer)int64 (Signed 8 byte integer)uint64 (Unsigned 8 byte integer)float32 (4 byte single precision float)float64 (8 byte double precision float)bool (unsigned 1 byte integer)Supported versionsPython 3.4Python 3.5Python 3.6Python 3.7IssuesReport issues using theissue trackeron the github repo.Changelogv0.1.0Initial release.AuthorsMax Byrde (miniwa)LicenseMIT (see LICENSE)
Package: pyjamaas
pyjamaasPython Juju and MaaS toolkit.Featurespyjamaassimplifies interaction with MaaS and Juju when working with a large number of heterogenous machines. It heavily utilizes the MaaS tags mechanism.Features:pyjamaas tags: Easily create, delete and update multiple tags for multiple machinespyjamaas clone: Easily clone configuration to multiple machines, using tagspyjamaas machine: Utility commands for retrieving machine informationAlso seeexamplesInstallation$pipinstallpyjamaasConfigurationpyjamaasneeds MaaS credentials. You can use environment variables:$exportMAAS_API_URL=https://maas.server.name:5240/MAAS/api/2.0
$exportMAAS_API_KEY=AAAAAAAAAAAAAA:BBBBBBBBBBBBBBB:CCCCCCCCCCCCCCCOr create apyjamaas.conffile (seesample):[maas]api_url=https://maas.server.name:5240/MAAS/api/2.0api_key=AAAAAAAAAAAAAA:BBBBBBBBBBBBBBB:CCCCCCCCCCCCCCC$pyjamaas<command>--config-filepyjamaas.confpyjamaaswill automatically look for config files in a few standard directories, e.g./etc/pyjamaas.conf,/etc/pyjamaas/pyjamaas.conf,~/.pyjamaas/pyjamaas.conf).Print loaded configuration withpyjamaas config. If a required option is missing, an error message is printed:$pyjamaasconfig
valuerequiredforoptionapi_keyingroup[maas]UsageFor a list of available commands:$pyjamaas--helpMostpyjamaascommands have the formatpyjamaas <command> <args> --match <filter>. The<filter>can be used to select machines based onsystem_id,hostname, ortags. The examples below should be clear enough:# Match a single machine using hostname$pyjamaasmachinelist--match'{hostname: host1}'# Match multiple machines by hostname$pyjamaasmachinelist--match'{hostname: [host1, host2]}'# Match multiple machines by system id$pyjamaasmachinelist--match'{system_id: [system1, system2]}'# Match machines using tags (multiple tags imply AND)$pyjamaasmachinelist--match'{tags: [tag1, tag2]}'Auto completionEnable auto-completion with:$.<(pyjamaascomplete)
Package: py-jama-client
py_jama_clientA python Jama Connect REST API client libraryAcknowledgmentsThis client library is heavily inspired by, and even based on the client library created by the Jama teampy-jama-rest-client. However, due to inactivity I have taken it upon myself to create a distinct package for those who have a need for a more comprehensive client -- specifically for the use of embedded resources.Jama SoftwareJama Software is the definitive system of record and action for product development. The company’s modern requirements and test management solution helps enterprises accelerate development time, mitigate risk, slash complexity and verify regulatory compliance. More than 600 product-centric organizations, including NASA, Boeing and Caterpillar use Jama to modernize their process for bringing complex products to market. The venture-backed company is headquartered in Portland, Oregon. For more information, visit jamasoftware.com.Please visit dev.jamasoftware.com for additional resources and join the discussion in our community community.jamasoftware.com.RequirementsPython 3.11 or greaterInstallationpipinstallpy-jama-clientUsageBasicfrompy_jama_rest_client.clientimportJamaClient# import clientfrompy_jama_rest_client.apis.abstract_items_apiimportAbstractItemsAPI# import APIclient=JamaClient(host="example.jamacloud.com",credentials=("my_username","my_password"),)# create client instanceabstract_items_api=AbstractItemsAPI(client)# pass client instance to APIabstract_items=abstract_items_api.get_abstract_items()# use API methods to fetch resourcesprint(abstract_items.data)With Linksfrompy_jama_rest_client.clientimportJamaClient# import clientfrompy_jama_rest_client.apis.items_apiimportItemsAPI# import APIclient=JamaClient(host="example.jamacloud.com",credentials=("my_username","my_password"),)# create client instanceitems_api=ItemsAPI(client)# pass client instance to APIitems=items_api.get_items(project_id=82,params={'include':('data.itemType','data.childItemType',)},# NOTE: 'params' must be a key-word argument)# use API methods to fetch resources, include itemTypes, and childItemTypes in responseprint(items.data,items.linked)Additional NotesPlease be aware that this package is a work-in-progress, and some API methods may be missing from the source code. Please open an issue, or submit a pull-request (see CONTRIBUTING.md for more).
Package: pyjamalib
PyJama - Python for Joint Angle Measurement and AcquisitionPyJama is open access project that was developed during my master's work atEdmond and Lily Safra International Institute of NeuroscienceofSantos Dumont Insitute. PyJama is a user friendly python library for analyzing human kinematics data. Aimed at analyzing data from IMU's, MIMU's, data from optical devices and in the future tracking data from deeplearning models. The PyJama library was designed based on theJAMA device.ContentsInstallationExamplesContributingDevelopment TeamPublicationsCreditsInstallationThe latest stable release is available on PyPI, and you can install it by sayingpip install pyjamalibAnaconda users can install usingconda-forge:conda install -c conda-forge pyjamalibTo build PyJama from source, saypython setup.py build.
Then, to install PyJama, saypython setup.py install.
If all went well, you should be able to execute the demo scripts underexamples(OS X users should follow the installation guide given below).Alternatively, you can download or clone the repository and usepipto handle dependencies:unzip pyjamalib.zip
pip install -e pyjamaliborgit clone https://github.com/tuliofalmeida/pyjama
pip install -e pyjamalibBy callingpip listyou should seepyjamalibnow as an installed package:pyjamalib (0.x.x, /path/to/pyjamalib)ExamplesExample of using the library using data extracted using JAMA.Example of using the library using data extracted using Vicon and Xsens.ContributingFor minor fixes of code and documentation, please go ahead and submit a pull request.  A gentle introduction to the process can be foundhere.Check out the list of issues that are easy to fix. Working on them is a great way to move the project forward.Larger changes (rewriting parts of existing code from scratch, adding new functions to the core, adding new libraries) should generally be discussed by opening an issue first. PRs with such changes require testing and approval.Feature branches with lots of small commits (especially titled "oops", "fix typo", "forgot to add file", etc.) should be squashed before opening a pull request. At the same time, please refrain from putting multiple unrelated changes into a single pull request.Development Team:Tulio Almeida -GitHub-Google ScholarAbner Cardoso -GitHub-Google ScholarAndrÃ© Dantas -GitHub-Google ScholarPublicationsThe publications related to this project are still in the process of being published. If you publish any paper using JAMA please contact us to updatehere!CreditsDaniele ComottiGitHub used as a basis for filtersSebastian MadgwickReference for the manipulations of quaternionsCenter for Vision, Speech & Signal Processing - University of Surrey. For making available theTotal Capture datasetused to develop the library example. Reference paper:Trumble et. al., 2017
Package: pyjamas-rfglab
PyJAMASPyJAMASisJustAMoreAwesomeSiesta.Documentation and installation instructionsYou can find the officialPyJAMASdocumentation, with detailed
installation instructions,here.Citing PyJAMASIf you usePyJAMAS, please cite:Fernandez-Gonzalez R, Balaghi N, Wang K, Hawkins R, Rothenberg K, McFaul C, Schimmer C, Ly M, do Carmo A, Scepanovic G,
Erdemci-Tandogan G, Castle V.PyJAMAS: open-source, multimodal segmentation and analysis of microscopy images. *
Bioinformatics*. 2021 Aug 13:btab589. doi: 10.1093/bioinformatics/btab589.SponsorsWe are grateful for the generous support from the following agencies and institutions, which contribute to the
development and maintenance ofPyJAMAS: