Saravanan666/pypi-org huggingface dataset:
Package: uiza
Python Client for Uiza platformIntroductionThe Uiza API is organized around RESTful standard. Our API has predictable, resource-oriented URLs, and uses HTTP response codes to indicate API errors. JSON is returned by all API responses, including errors, although our API libraries convert responses to appropriate language-specific objects.DocumentationSee the.Uiza API docs v4.InstallationSupported Python VersionsPython 2.7.x. Python 2.7 support will be removed on January 1, 2020.Python 3.xTested with Python 2.7.11, 3.4, 3.6.8Install uiza package via pipSuggestion install this library using pip withvirtualenv. Because with virtualenv, it is possible to install this library without:Needing system install permission.Clashing with the installed system dependencies.On Mac/Linuxpipinstallvirtualenv
virtualenv<your-env>source<your-env>/bin/activate
<your-env>/bin/pipinstalluizaOn Windowspipinstallvirtualenv
virtualenv<your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exeinstalluizaUsageThe first, needing create Uiza connection usingapp_idandauthorization:importuizauiza.authorization="your-authorization"uiza.app_id="your-app-id"After connection created, this is example search Entity:importuizafromuiza.api_resources.entityimportEntityfromuiza.exceptionsimportServerExceptionuiza.authorization="your-authorization"uiza.app_id="your-app-id"try:entity_data,_=Entity().search(keyword='Sample')exceptServerExceptionase:raiseeexceptExceptionase:raisee...Next steps, reading theClient Library Documentationto see other available methods on the client.EntityCategoryStorageLive StreamingCallbackUserUnittestThe first, you need install dependencies:pipinstall-rrequirements.txtRun unittest:python-munittestdiscovertestsCoverage code:coveragerun-munittestdiscovertests
coveragereportContributingBug reports and pull requests are welcome on GitHub athttps://github.com/uizaio/api-wrapper-python.LicenseThe package is available as open source under the terms of theMIT License.
Package: ujotypes
This Python extension allows you to use the ujotypes-c library in Python.
Use of ujotypes in Python is primairly through a class wrapper. Additionally
you can access the native C-API functions if you have to.Supported Python veriosn: 3.7.x up to 3.12.xWindows x64 and Linux x64 binary wheels available on PyPiSourcecodeDocumentationInstalling the extensionTheujotypesextension is available on
the Python Package Index (PyPi). The extension is available as a binary wheel
for Linux x64 systems that aremanylinuxcompatible and on Windows x64 systems.To install it without having to build it yourself open a command line and
run:pipinstallujotypesBuilding the extensionBuilding the extensions requires a local compiler. When building on Windows
you need to match the compiler of the Python version you want to build the
extension for. Acomprehensive listingis available in the pythondev documentation.Also theujotypes-cproject needs to be cloned and built locally.The standard build process for the ujotypes-py Python extension
expects to find the directory of the ujotypes-c project to be next to the
ujotypes-py directory. Should your clone of the ujotypes-c project be in a
different location you will have to adjust the paths in thesetup.pyfile.To build and install open a command line and run:pythonsetup.pybuildpipinstall.Running Unit TestsThe ujotype-py project comes with a set of unittests.
To run tests from the package root dir call:python-munittestdiscovertest-vCode QualityWe value code quality and ask you to check your code with pylint and flake8
before making a merge request.pylintRunning pylint for the python code in this project the following commands are
used:pylint--rcfile=.pylintrc./ujotypes/pylint--rcfile=.pylintrc--disable=duplicate-code./test/flake8You can run flake 8 with:flake8
Package: ujq
UJQUniversal Job Queue or UJQ in short is a Redis based Simple MultiPlatform Job management library. This Library is light weight and build for working with microservices. Currently we have Node and Python implementation of Library. C# and Java are in pipeline.BenifitsJobs can be created and processed by different application or servicesAuto trigger when job is createdJob Completion and error indicationsPythonCLICK HEREfor Node.js PackageInstalling UJQYou can use PIP to installpip install ujqConnecting to RedisUse the following to connect to redisfromujqimportujqimportjsonUJQ=ujq(host="127.0.0.1",port=6379)UJQ.connect()Create a new JobThe following Code will create a new Jobid=UJQ.createJob('Test_100',{"test":"test45y76475"})print(id)On creation of New JobThe Below Code will work on the job and returns a statusdefcallback(message,complete):print(json.dumps(message))complete({'status':True,"DummyData":"blablabla"},False)UJQ.onCreated('Test_100',callback)In case of error, the false tag can be set as true... Invoking the complete callback will complete the job and will be moved from queue...On completion of Jobresult=UJQ.onCompleted(id)print(result)The above code will complete the job.Run JobA new method is created for UJQ version 2 and above to run which combines both createJob and onCompletedresult=UJQ.runJob('Test_100',{"test":"test45y76475"})print(result)Express with UJQA simple implementation of Express in Node.js with UJQ in Python as shownCreate aServer.jswith the below codeconstexpress=require("express")constUJQ=require("ujq")constujq=newUJQ({port:"6379",host:"127.0.0.1"})constapp=express()constport=3000ujq.connect().then(()=>{app.get('/',(req,res)=>{ujq.createJob("test_q2",{test:"sample Data"})//Set On Complete.then((result)=>ujq.onCompleted(result.id))//Send Result.then((result)=>res.send(result))})}).catch((e)=>console.log(e))app.listen(port,()=>console.log(`Example app listening at http://localhost:${port}`))Now CreateWorker.pywith the below Codefromujqimportujqimportjsondefcallback(message,complete):print(json.dumps(message))complete({'status':True,"DummyData":"blablabla"},False)UJQ.onCreated('Test_100',callback)Run both the files andEnjoy:BNew onError methodThis method will handle errors during disconnect of redis in betweenUJQ.onError(lambdax:run())
Package: ujs-jsonsyntax
Part of theUsing JSON Schemaproject.The ‘hello world’ of JSON processing, check the syntax of a JSON file.For command line/script use, a console message is displayed and the process
exits with 0 for success, 1 for failure.Command Line / Script UseUsage: jsonsyntax filename
- filename name of file to check (path optional)To run the syntax checker (command line or script) against the fileexample.jsonuse,jsonsyntaxexample.jsonLibrary Function UseTo use the syntax checker as a library function, call thesyntaxCheckfunction in a try/except block. For example,fromjsonsyntaximportcheckSyntaxtry:checkSyntax("example.json")print("Valid JSON file")exceptase:print("Error: "+e.message);InstallInstallation using pip for Python 2 (2.7) or Python 3.pipinstallujs-jsonsyntaxLicenseMIT
Package: ujs-jsonvalidate
Part of theUsing JSON Schemaproject.jsonvalidateis a command line and library utility allowing JSON content
to be validated using JSON Schema content from local or remote sources, and
use of custom schema storage and URI access.The utility uses thejsonschemalibrary for the schema validation processing
(GitHub repo).For command line/script use, a console message is displayed and the process
exits with 0 for success, 1 for failure.Command Line / Script UseTo run the validation (command line or script), use thevalidatecommand with a file name (path optional). For example, to check the fileexample.jsonagainst the schemaexample_schema.json, use,validateexample.jsonexample_schema.jsonLibrary Function Usevalidate(dataFile, schemaFile, refFiles, jsdbFile, callback)Arguments:dataFileStringFile name of JSON data file (path optional)schemaFileStringFile name of JSON Schema file (path optional)refFilesString[]Array of file names for $ref files (path optional)jsdbFileStringFile name for JSDB file (path optional)Returns:code, data, message-codeis the validation result-datais the validated JSON content from dataFile-messageis text message associated with thecodeFor example,fromjsonvalidateimportvalidate,VALIDdataFile="example.json"schemaFile="example_schema.json"refFiles=["ref1_schema.json","ref2_schema.json"]jsdbFile=Nonecode,data,message=validate(dataFile,schemaFile,refFiles,jsdbFile)ifcode==VALID:print("Valid JSON content");else:print("Error: "+str(message))InstallationThe program can be installed usingpip, with the command,pipinstallujs-jsonvalidateLicenseMIT
Package: ujson-bedframe
UltraJSON is an ultra fast JSON encoder and decoder written in pure C with bindings for Python 2.5+ and 3.For a more painless day to day C/C++ JSON decoder experience please checkoutujson4c, based on UltraJSON.Please checkout the rest of the projects in the Ultra series:http://github.com/esnme/ultramemcachehttp://github.com/esnme/ultramysqlTo install it just run Pip as usual:$ pip install ujsonUsageMay be used as a drop in replacement for most other JSON parsers for Python:>>> import ujson
>>> ujson.dumps([{"key": "value"}, 81, True])
'[{"key":"value"},81,true]'
>>> ujson.loads("""[{"key": "value"}, 81, true]""")
[{u'key': u'value'}, 81, True]Encoder optionsencode_html_charsUsed to enable special encoding of “unsafe” HTML characters into safer Unicode sequences. Default is false:>>> ujson.dumps("<script>John&Doe", encode_html_chars=True)
'"\\u003cscript\\u003eJohn\\u0026Doe"'ensure_asciiLimits output to ASCII and escapes all extended characters above 127. Default is true. If your end format supports UTF-8 setting this option to false is highly recommended to save space:>>> ujson.dumps(u"\xe5\xe4\xf6")
'"\\u00e5\\u00e4\\u00f6"'
>>> ujson.dumps(u"\xe5\xe4\xf6", ensure_ascii=False)
'"\xc3\xa5\xc3\xa4\xc3\xb6"'double_precisionControls how many decimals to encode for double or decimal values. Default is 9:>>> ujson.dumps(math.pi)
'3.1415926536'
>>> ujson.dumps(math.pi, double_precision=1)
'3.1'
>>> ujson.dumps(math.pi, double_precision=0)
'3'
>>> ujson.dumps(math.pi, double_precision=4)
'3.1416'Decoders optionsprecise_floatSet to enable usage of higher precision (strtod) function when decoding string to double values. Default is to use fast but less precise builtin functionality:>>> ujson.loads("4.56")
4.5600000000000005
>>> ujson.loads("4.56", precise_float=True)
4.5599999999999996BenchmarksUltraJSONcalls/sec compared to three other popular JSON parsers with performance gain specified below each.Test machine:Linux version 2.6.32-131.0.15.el6.x86_64Versions:ujson: 1.21simplejson: 2.6.2cjson: 1.05yajl: 0.3.5Python: Python 2.6.6 (r266:84292, Jul 20 2011, 10:22:43)ujsonsimplejsoncjsonyajlArray with 256 utf-8 stringsEncode4090,74899,3983,863189,864,5548,781,28Decode863,29586,15201,61352,481,474,282,45Medium complex objectEncode9750,371377,151512,063341,917,086,452,92Decode5576,754247,163587,832850,131,311,551,96Array with 256 stringsEncode17998,0112954,468715,0215924,351,392,071,13Decode14540,7119696,1314908,469547,140,740,981,52Array with 256 doublesEncode2185,201466,871956,993421,101,491,120,64Decode16062,018990,509743,408331,741,791,651,93Array with 256 True valuesEncode69767,6025202,5641145,9964330,762,771,701,08Decode91416,0256439,9754918,0942786,021,621,662,14Array with 256 dict{string, int} pairsEncode11307,541830,452720,907725,566,184,161,46Decode8695,947572,896076,715231,321,151,431,66Dict with 256 arrays with 256 dictEncode37,764,8810,4927,627,743,601,37Decode17,7015,5611,2512,001,141,571,47
Package: ujsonDB
ujsonDB is lightweight, fast, and simple database based on Python’s own
json module. And it’s BSD licensed!ujsonDB is Fun>>> import ujsondb

>>> db = jsondb.load('test.db', False)

>>> db.set('key', 'value')

>>> db.get('key')
'value'

>>> db.dump()
TrueAnd Easy to Install$ pip install ujsondbLinkswebsitedocumentation
Package: ujson_delta
This is a forked version of json-delta which uses ujson instead of the
standard library json package. This should speed things up a bit. Also
includes changes to make more PEP-8 compliant. This is built for
Python 3+ since you should be using that now;)From the original version:
json-delta v1.1.3: A diff/patch pair and library for JSON data
structures. (http://json_delta.readthedocs.org/)JSON-delta is a multi-language software suite for computing deltas
between JSON-serialized data structures, and applying those deltas as
patches.  It enables separate programs at either end of a
communications channel (e.g. client and server over HTTP, or two
processes talking to one another using bidirectional IPC) to
manipulate a data structure while minimizing communications overhead.This is the python implementation.  It requires Python version 2.7 or
newer (including Python 3).  It can be installed in the standard way:$ python setup.py install(potentially needing superuser privileges).  This will install a
single module named json_delta, and scripts named json_diff,
json_patch and json_cat.HTML documentation for all four of these can be found in the doc/
directory, along with manpages for the scripts.Donations to support the continuing development of JSON-delta will be
gratefully received via gratipay (https://gratipay.com/phijaro),
PayPal (himself@phil-roberts.name) or
Bitcoin: (1HPJHRpVSm1Y4zrgppd2c6LysjxeabbQN4).
Package: ujsondiff
ujsondiff========Diff JSON and JSON-like structures in Python.Installationpip install ujsondiffQuickstart>>> import ujsondiff as jd
>>> from ujsondiff import diff

>>> diff({'a': 1, 'b': 2}, {'b': 3, 'c': 4})
{'c': 4, 'b': 3, delete: ['a']}

>>> diff(['a', 'b', 'c'], ['a', 'b', 'c', 'd'])
{insert: [(3, 'd')]}

>>> diff(['a', 'b', 'c'], ['a', 'c'])
{delete: [1]}

# Typical diff looks like what you'd expect...
>>> diff({'a': [0, {'b': 4}, 1]}, {'a': [0, {'b': 5}, 1]})
{'a': {1: {'b': 5}}}

# ...but similarity is taken into account
>>> diff({'a': [0, {'b': 4}, 1]}, {'a': [0, {'c': 5}, 1]})
{'a': {insert: [(1, {'c': 5})], delete: [1]}}

# Support for various diff syntaxes
>>> diff({'a': 1, 'b': 2}, {'b': 3, 'c': 4}, syntax='explicit')
{insert: {'c': 4}, update: {'b': 3}, delete: ['a']}

>>> diff({'a': 1, 'b': 2}, {'b': 3, 'c': 4}, syntax='symmetric')
{insert: {'c': 4}, 'b': [2, 3], delete: {'a': 1}}

# Special handling of sets
>>> diff({'a', 'b', 'c'}, {'a', 'c', 'd'})
{discard: set(['b']), add: set(['d'])}

# Load and dump JSON
>>> print diff('["a", "b", "c"]', '["a", "c", "d"]', load=True, dump=True)
{"$delete": [1], "$insert": [[2, "d"]]}

# NOTE: Default keys in the result are objects, not strings!
>>> d = diff({'a': 1, 'delete': 2}, {'b': 3, 'delete': 4})
>>> d
{'delete': 4, 'b': 3, delete: ['a']}
>>> d[jd.delete]
['a']
>>> d['delete']
4
# Alternatively, you can use marshal=True to get back strings with a leading $
>>> diff({'a': 1, 'delete': 2}, {'b': 3, 'delete': 4}, marshal=True)
{'delete': 4, 'b': 3, '$delete': ['a']}
Package: ujsonpath
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[![PyPI version](https://badge.fury.io/py/ujsonpath.svg)](https://badge.fury.io/py/ujsonpath)
[![Requirements Status](https://requires.io/github/LuizArmesto/ujsonpath/requirements.svg?branch=master)](https://requires.io/github/LuizArmesto/ujsonpath/requirements/?branch=master)
Package: ujson-segfix
UltraJSON is an ultra fast JSON encoder and decoder written in pure C with bindings for Python 3.5+.To install it just run pip as usual:$pipinstallujsonWARNING - READ THIS NOWThis version of ujson is specifically intended to fix a segmentation fault in ujson untilthisPR is merged (and backported to 3.2)UsageMay be used as a drop in replacement for most other JSON parsers for Python:>>>importujson>>>ujson.dumps([{"key":"value"},81,True])'[{"key":"value"},81,true]'>>>ujson.loads("""[{"key": "value"}, 81, true]""")[{u'key':u'value'},81,True]Encoder optionsencode_html_charsUsed to enable special encoding of “unsafe” HTML characters into safer Unicode sequences. Default isFalse:>>>ujson.dumps("<script>John&Doe",encode_html_chars=True)'"\\u003cscript\\u003eJohn\\u0026Doe"'ensure_asciiLimits output to ASCII and escapes all extended characters above 127. Default is true. If your end format supports UTF-8 setting this option to false is highly recommended to save space:>>>ujson.dumps(u"\xe5\xe4\xf6")'"\\u00e5\\u00e4\\u00f6"'>>>ujson.dumps(u"\xe5\xe4\xf6",ensure_ascii=False)'"\xc3\xa5\xc3\xa4\xc3\xb6"'escape_forward_slashesControls whether forward slashes (/) are escaped. Default isTrue:>>>ujson.dumps("http://esn.me")'"http:\/\/esn.me"'>>>ujson.dumps("http://esn.me",escape_forward_slashes=False)'"http://esn.me"'indentControls whether indention (“pretty output”) is enabled. Default is0(disabled):>>>ujson.dumps({"foo":"bar"})'{"foo":"bar"}'>>>ujson.dumps({"foo":"bar"},indent=4){"foo":"bar"}BenchmarksUltraJSONcalls/sec compared to other popular JSON parsers with performance gain specified below each.Test machine:Linux 5.0.0-1032-azure x86_64 #34-Ubuntu SMP Mon Feb 10 19:37:25 UTC 2020Versions:CPython 3.8.2 (default, Feb 28 2020, 14:28:43) [GCC 7.4.0]nujson    : 1.35.2orjson    : 2.6.1simplejson: 3.17.0ujson     : 2.0.2ujsonnujsonorjsonsimplejsonjsonArray with 256 doublesencode22,0824,28276,9755,3285,436decode24,12734,34929,05914,17413,822Array with 256 UTF-8 stringsencode3,5572,52824,3003,0612,068decode2,0302,490931406358Array with 256 stringsencode39,04131,76976,40316,61516,910decode25,18524,28734,43732,38827,999Medium complex objectencode10,38211,42732,9953,9595,275decode9,7859,79611,5155,8987,200Array with 256 True valuesencode114,341101,039344,25662,38272,872decode149,367151,615181,123114,597130,392Array with 256 dict{string, int} pairsencode13,71514,42051,9423,2716,584decode12,67011,78812,1766,7438,278Dict with 256 arrays with 256 dict{string, int} pairsencode50542161023decode3232302023Dict with 256 arrays with 256 dict{string, int} pairs, outputting sorted keysencode4641824Complex objectencode533582408431decode466454154164
Package: ujs-safefile
Part of theUsing JSON Schemaproject.Robust storage using text files is enhanced with support for automated recovery
should an update fail.This library provides support for reading and writing files in a recoverable
mode, allowing automated recovery when the program restarts. Normal file
read / write is also supported, enabling a common interface for both files
using automated recovery capabilities and those not using them.APIreadFileRead a file synchronously from a file system.readFile(filename)arguments:filenamestringName of file to read (path optional)raisesSafeFileErrorreturnsstringData readdata=readFile(filename)writeFileWrite a file synchronously to a file system.writeFile(filename, data)arguments:filenamestringName of file to write (path optional)datastringData to write to the fileraisesSafeFileErrorwriteFile(filename,data)safeReadFileRead a file synchronously from a file system, inspecting the file system state
and performing recovery processing if needed.safeReadFile(filename)Arguments:filenamestringName of file to read (path optional)raisesSafeFileErrorreturnsstringData readdata=safeReadFile(filename)safeWriteFileWrite data to a file synchronously, using a recoverable set of steps. Should
the write processing fail to complete, auto-recovery can perform the steps
required to bring the file content back to a stable state.safeWriteFile(filename, data)Arguments:filenamestringName of file to write (path optional)datastringData to write to the fileraisesSafeFileErrorsafeWriteFile(filename,data)safeGetStateGet the current state of the set of files representing the current file
system contents. Returns one of,SAFE_NORMAL, normal state, base and backup files only presentSAFE_RECOVERABLE, partial write condition that is automatically recoverable
the next time a read, write or recover function is calledSAFE_INTERVENE, last write failed before the data being written reached
a recoverable state. Manual intervention is required if recovery of the last
write is required, otherwise auto-recovery will recover to the prior stable
state.safeGetState(filename)Arguments:filenamestringName of file to check (path optional)returnsintegerState value (SAFE_NORMAL, SAFE_RECOVERABLE or
SAFE_INTERVENE) or a file error (INVALID_NAME, DOES_NOT_EXIST or
IS_NOT_A_FILE)state=safeGetState(filename)safeRecoverInitiate the auto-recovery process. This follows the same steps assafeReadFilefollows, but can be called independently.safeRecover(filename)Arguments:filenamestringName of file to recover (path optional)raisesSafeFileErrorsafeRecover(file)SafeFileErrorSafeFileError(code, message)Arguments:codeintegerError code (from list below)messagestringText message associated with codeConstants for the error codes,NO_ERRORINVALID_NAMEDOES_NOT_EXISTIS_NOT_A_FILEREAD_ERRORWRITE_ERRORSAFE_NORMALSAFE_RECOVERABLESAFE_INTERVENEInstallationThe program can be installed usingpip, with the command,pipinstallujs-safefileLicenseMIT
Package: ukat
UKRIN Kidney Analysis Toolbox (ukat)ukatis a vendor agnostic framework for the analysis of quantitative renal MRI data.TheUKRIN-MAPS projectaims to standardise the acquisition and analysis of renal MRI data to enable multi-site,
multi-vendor studies.
Although many MRI vendors produce quantitative maps on the scanner, their methods are closed source and as such,
potentially cause variability in multi-vendor studies.ukatprovides an open-source and robust analysis platform that can be used to process data from multiple vendors.The focus of this package is analysis of data from the standardised UKRIN protocol, however the methods are intentionally
left generic to enable analysis of data collected using different protocols or on different areas of the body.More information can be found inthis ISMRM abstract.InstallingukatThere are a few different ways you can installukatbased on what you want to do with it"I just want to process my data with this package"Make sure you're running Python >=3.8Installukatwithpip install ukat"I want to modify this code to do something a bit different but don't want my modifications to go back intoukat"Clone this repository withgit clone https://github.com/UKRIN-MAPS/ukat.gitChange to theukatroot directory (the one containing a file namedsetup.py).Run the following command in your terminal:pip install -e .Now if you make any changes to theukatcode, they'll permeate into any analysis you perform where you've importedukat."I want to contribute toukatand write code that ends up back on this repository for others to use"Great!Forkthe repository to your GitHub account. Then,clonethe repository to your local machine. After doing this, you should see:$ git remote -v
origin   https://github.com/<YOUR-GITHUB-USERNAME>/ukat.git (fetch)
origin   https://github.com/<YOUR-GITHUB-USERNAME>/ukat.git (push)Now,configuregit to sync your fork with the originalukatrepository:$ git remote add upstream https://github.com/UKRIN-MAPS/ukat.gitNow the upstream repository should be set:$ git remote -v
origin     https://github.com/<YOUR-GITHUB-USERNAME>/ukat.git (fetch)
origin     https://github.com/<YOUR-GITHUB-USERNAME>/ukat.git (push)
upstream   https://github.com/UKRIN-MAPS/ukat.git (fetch)
upstream   https://github.com/UKRIN-MAPS/ukat.git (push)Now you can suggest changes (e.g. suggest new code) to be added to the repository viapullrequests. Don't forget to keep your forkin syncwith the upstream repository (i.e. theukatrepository in the UKRIN-MAPS organisation).If you are new to git/GitHub you may find the following cheat sheets handy (web,pdf).You'll probably also want to follow the instructions in the section above so you can useukatfor your normal analysis.If you run into any problems or find any issues with the installation process please raise anissue.Contributing guidelinesPlease read ourcontributing guidelines (work-in-progress).