Saravanan666/pypi-org huggingface dataset:
Package: in-dbt-core
dbtenables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.Understanding dbtAnalysts using dbt can transform their data by simply writing select statements, while dbt handles turning these statements into tables and views in a data warehouse.These select statements, or "models", form a dbt project. Models frequently build on top of one another – dbt makes it easy tomanage relationshipsbetween models, andvisualize these relationships, as well as assure the quality of your transformations throughtesting.Getting startedInstall dbtRead theintroductionandviewpointJoin the dbt CommunityBe part of the conversation in thedbt Community SlackRead more on thedbt Community DiscourseReporting bugs and contributing codeWant to report a bug or request a feature? Let us know onSlack, or openan issueWant to help us build dbt? Check out theContributing GuideCode of ConductEveryone interacting in the dbt project's codebases, issue trackers, chat rooms, and mailing lists is expected to follow thedbt Code of Conduct.
Package: indcomp
indcompis a package for performing indirect treatment comparisons (ITCs).indcomp currently supports the Matching-Adjusted Indirect Comparison (MAIC) approach, implemented as perNICE's guidance.View theindcomp documentation.Install# PyPI
pip install indcompDependenciesNumPySciPypandasmatplotlibUsage - Matching-Adjusted Indirect Comparison (MAIC)For this example, we use simulated data as perNICE's worked example (DSU Technical Support Document - Appendix D).The objective is to weight individual patient-level data (IPD) for a hypothetical randomised control trial (RCT) comparing treatmentsAandB, to match on specified characteristics described in aggregated data for a hypothetical RCT comparing treatmentsAandC. In this example, we weight theABtrial such that the age matches the mean and standard deviation of theACtrial.This example illustrates a common real-world scenario in whichBandCare interventions for a disease, andAis a placebo. Typically, MAIC is used to fairly evaluate IPD for a potential new treatment (B) against that of an existing treatment (C) for which only aggregate data is available (the published results for theACtrial).TheABtrial comprises 500 individual patient records.fromindcompimportMAICfromindcomp.datasetsimportload_NICE_DSU18# load simulated Individual Patient Data (IPD) for trial AB# load simulated Aggregated Data (AgD) for trial ACdf_AB_IPD,df_AC_AgD=load_NICE_DSU18()print(f"Number of AB patients:{len(df_AB_IPD)}")print(df_AB_IPD.sample(5))> Number of AB patients: 500>       ID  age  gender trt  y> 113  114   73    Male   A  1> 371  122   45  Female   B  1> 77    78   48    Male   A  1> 441  192   49    Male   B  0> 120  121   68    Male   A  1TheACtrial is aggregate data for 300 patients.# 300 AC patientsprint(df_AC_AgD.round(2))>    age.mean  age.sd  N.male  prop.male  y.A.sum  y.A.bar  N.A  y.C.sum  y.C.bar  N.C> 0     50.27    3.12      68       0.23      125     0.83  150       21     0.14  150We instantiate and configure aMAICinstance to weight theABdata to yield the same mean and standard deviation age as theACtrial. These characteristics are quite different for the starting, unweighted data.# adjust df_AB_IPD['age'] to have same mean as df_AC_AgD['age.mean'] and# adjust df_AB_IPD['age'] to have same std as df_AC_AgD['age.sd']maic=MAIC(df_index=df_AB_IPD,df_target=df_AC_AgD,match={"age.mean":("mean","age"),"age.sd":("std","age","age.mean")})# compare unweighted populations, before performing matching adjustmentmaic.compare_populations()After calculating the weights, we examine the effective sample size (ESS) and plot the distribution of weights. Our sample size decreases from the original 500 to an effective sample size of 178.56.# calculate and examine weights and Effective Sample Sizemaic.calc_weights()print(f"Effective Sample Size:{maic.ESS_:.2f}")# original sample size: 500 patientsmaic.plot_weights()> Effective Sample Size: 178.56After applying the weights, the mean and standard deviation age of theABtrial now matches that of theACtrial.# compare weighted populations, after performing matching adjustmentmaic.compare_populations(weighted=True)
Package: indecode
Code and Decode stringInstall and importFor install indecode : pip install indecodeFor import indecode : import indecodeFunctionsThis module contain four functions :generate_key() - return stringcode(text to code in str, key return by the “generate_key()” function) - return stringdecode(text return by the “code()” function, key return by the “generate_key()” function) - return stringget_key_with_img(complete path of the image) - return string, can replace the “generate_key()” fonctionErrorsThe indecode module can trigger the following errors :TypeError : one of the arguments is not a stringCodeError : one of the caracters in the text argument is not encodableDecodeError : one of the caracters in the text argument is not decodableKeyElementError : one of the caracters in the key argument must not be in the keyKeyLengthError : the key is not of the expected length.ImageNotFoundError : ‘/home/pi/Documents/indecode/img.jpg’ not found.
Package: indecro
IntroIndecro is a simple framework for job schedulingAll parts are designed to be replaceable.Main ideas are:Task creator doesn't need to know how tasks are implemented or executedPersistence may be implementedYou can choose how jobs will be parallelized and whether they will be parallelized at allNot only time-based scheduling rules! Magic filters and bool-based rules is availableCurrently project is in the design stage and any APIs are to be changedHow to install:Install using pippipinstallindecroHow to use:Create schedulerfromindecroimportSchedulerfromindecro.executorimportExecutorfromindecro.storage.memory_storageimportMemoryStoragescheduler=Scheduler(executor=Executor(),storage=MemoryStorage())Schedule job using decorator-based shortcut (custom job name can be provided for compatibility)fromdatetimeimporttimedeltafromindecro.rulesimportRunOnce# Rule, theft control time when scheduled task would be executed@scheduler.job(rule=RunOnce(after=timedelta(seconds=10)))asyncdefsome_job():print('Executing some job..')Schedule job using direct functionasyncdefsome_another_job():print('Executing some another job..')scheduler.add_job(some_another_job,rule=RunOnce(after=timedelta(seconds=20)))Run scheduler:awaitscheduler.run()More examples of using framework you can find in examples directorycdexamples
ls
Package: indeed_contactForm
indeed_contactForm will store messages sent with it in your database,make them avaliable in the admin interface and send you an email withthe messages content.For this to work you need to configure your django project to be able tosend emails.simply use indeed_contactForm in a view like this:from indeed_contactForm.views import contact as contactFormdef contact(request):return contactForm(request, 'contact.html')if you need to make some variables in the template avaliable, you cansimply pass contact() a dict like you would pass it to render_to_response.def contact(request):return contactForm(request, 'contact.html', {'myVar':42})contact.html can contain a normal form, for example:{% extends "whatever/base.html" %}{% block content %}{% if form.errors %}<p style="color: red;">Please correct the error{{ form.errors|pluralize }} below.</p>{% endif %}<form action="" method="post">{% csrf_token %}<table>{{ form.as_table }}</table><input type="submit" value="Absenden"></form>{% endblock %}
Package: indeedjobsearch
[]indeedjobsearch Botwhat is Indeed Job Search Bot ?Indeed job search bot is a bot that finds you 150 + jobs in less than 5 secondsThe output can be saved as either CSV or Excel FileRefer to examples shown BelowDependenciespipinstallpandas
pipinstallbs4
pipinstallrequestsInstallationpipinstallindeedjobsearchUsagetry:fromindeedjobsearch.indeedjobsearchimportIndeedJobSearchprint("All modules loaded .... ")exceptExceptionase:print("Failed to load Module ")# create a object of classjobsearch=IndeedJobSearch(title='Python',location="Bridgeport , CT")# call method getJobs()data=jobsearch.getJobs()# Return Pandas Dataframeprint(data)# Save all the Jobs in Excel Filejobsearch.saveExcel()we will add more features to this. if you have any issue running this kindly send a email to the authorAuthorsSoumil Nitin ShahBachelor in Electronic Engineering |
Masters in Electrical Engineering |
Master in Computer Engineering |Website :https://soumilshah.herokuapp.comGithub:https://github.com/soumilshah1995Linkedin:https://www.linkedin.com/in/shah-soumil/Blog:https://soumilshah1995.blogspot.com/Youtube :https://www.youtube.com/channel/UC_eOodxvwS_H7x2uLQa-svw?view_as=subscriberFacebook Page :https://www.facebook.com/soumilshah1995/Email :shahsoumil519@gmail.comLicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for details
Package: indeed-mongodb-scrapper
indeed_mongodb_scrapperIndeed Scrapper storing the data on MongoDB databaseInstallationUsing Pip$pipinstallindeed-mongodb-scrapperManual$gitclonehttps://github.com/YacineAll/indeed_mongodb_scrapper.git$cdindeed_mongodb_scrapper$pythonsetup.pyinstallUsage$indeed_mongodb_scrapper
Package: indego
Indego Bike Share Python LibraryAboutI have tried to make a re-usable Python library for the Philadelphia Indego Bike Share API! I'm not very familiar with Python, but tried to learn by creating this.I wrote this similarly tomy existing Indego PHP library.Check outthe City of Philadelphia GitHubif you think this library is interesting!InstallationInstallation of this library should be as simple as running:pip install indegoCompatibilityPlease note that this library is only compatible with Python 3+. Python 2 is not supported.ExampleWhen combined with the providedIndegoclass, the following code will generate the example output:from indego import Indego

# Instantiate the Indego class
indego = Indego()

# Retrieve and print "university" stations
uni_stations = indego.get_stations('university')
print(uni_stations)

# Show how many stations were returned above
uni_count = len(uni_stations)
print(uni_count, 'stations returned')Output:$ python3 university_example.py
{3008: {'addressStreet': '1076 Berks Street', 'addressCity': 'Philadelphia', 'addressState': 'PA', 'addressZipCode': '19122', 'bikesAvailable': 3, 'closeTime': '03:55:00', 'docksAvailable': 16, 'eventEnd': None, 'eventStart': None, 'isEventBased': False, 'isVirtual': False, 'isVisible': False, 'kioskId': 3008, 'kioskPublicStatus': 'Active', 'kioskStatus': 'FullService', 'name': 'Temple University Station', 'notes': None, 'openTime': '04:00:00', 'publicText': '', 'timeZone': 'Eastern Standard Time', 'totalDocks': 19, 'trikesAvailable': 0, 'kioskConnectionStatus': 'Active', 'kioskType': 1, 'latitude': 39.98078, 'longitude': -75.15055, 'hasGeofence': False, 'classicBikesAvailable': 3, 'smartBikesAvailable': 0, 'electricBikesAvailable': 0, 'isArchived': False}, 3020: {'addressStreet': '3051 South St.', 'addressCity': 'Philadelphia', 'addressState': 'PA', 'addressZipCode': '19147', 'bikesAvailable': 11, 'closeTime': '03:55:00', 'docksAvailable': 24, 'eventEnd': None, 'eventStart': None, 'isEventBased': False, 'isVirtual': False, 'isVisible': False, 'kioskId': 3020, 'kioskPublicStatus': 'Active', 'kioskStatus': 'FullService', 'name': 'University City Station', 'notes': None, 'openTime': '04:00:00', 'publicText': '', 'timeZone': 'Eastern Standard Time', 'totalDocks': 35, 'trikesAvailable': 0, 'kioskConnectionStatus': 'Active', 'kioskType': 1, 'latitude': 39.94922, 'longitude': -75.19036, 'hasGeofence': False, 'classicBikesAvailable': 11, 'smartBikesAvailable': 0, 'electricBikesAvailable': 0, 'isArchived': False}}
2 stations returnedProviding an argument/filter toget_stations()to limit the selection of stations only limits the results within theIndegoclass. The API end-point itself always returns all stations.Unfortunately, there does not appear to be a signifcant amount of documentation for the API being used nor does there seem to be any parameters available to limit the stations being retrieved from the API.Callingget_stations()without any arguments will return a list of all (currently, 132) stations.More InformationThe actual Philadelphia Indego Bike Share API, a GeoJSON fileOpenDataPhilly description of the APIInteresting article visualizing Indego usage
Package: indegreeparser
pyresparserA modified pyresparse resume parser that extracts years of experience more accuratelyBuilt with â‌¤ï¸ژ byAhmed ElKodshFeaturesExtract nameExtract emailExtract mobile numbersExtract skillsExtract total experience (more accurately)Extract college nameExtract degreeExtract designationExtract company namesInstallationYou can install this package usingpipinstallindegreeparserFor NLP operations we use spacy and nltk. Install them using below commands:# spaCypython-mspacydownloaden_core_web_sm# nltkpython-mnltk.downloaderwords
python-mnltk.downloaderstopwordsDocumentationOfficial documentation is available at:https://www.omkarpathak.in/pyresparser/Supported File FormatsPDF and DOCx files are supported on all Operating SystemsIf you want to extract DOC files you can installtextractfor your OS (Linux, MacOS)Note: You just have to install textract (and nothing else) and doc files will get parsed easilyUsageImport it in your Python projectfromindegreeparserimportResumeParserdata=ResumeParser('/path/to/resume/file').get_extracted_data()CLIFor running the resume extractor you can also use thecliprovidedusage:pyresparser[-h][-fFILE][-dDIRECTORY][-rREMOTEFILE][-reCUSTOM_REGEX][-sfSKILLSFILE][-eEXPORT_FORMAT]optionalarguments:-h,--helpshowthishelpmessageandexit-fFILE,--fileFILEresumefiletobeextracted-dDIRECTORY,--directoryDIRECTORYdirectorycontainingalltheresumestobeextracted-rREMOTEFILE,--remotefileREMOTEFILEremotepathforresumefiletobeextracted-reCUSTOM_REGEX,--custom-regexCUSTOM_REGEXcustomregexforparsingmobilenumbers-sfSKILLSFILE,--skillsfileSKILLSFILEcustomskillsCSVfileagainstwhichskillsaresearchedfor-eEXPORT_FORMAT,--export-formatEXPORT_FORMATtheinformationexportformat(json)Notes:If you are running the app on windows, then you can only extract .docs and .pdf filesResultThe module would return a list of dictionary objects with result as follows:[
  {
    'college_name': ['Marathwada Mitra Mandalâ€™s College of Engineering'],
    'company_names': None,
    'degree': ['B.E. IN COMPUTER ENGINEERING'],
    'designation': ['Manager',
                    'TECHNICAL CONTENT WRITER',
                    'DATA ENGINEER'],
    'email': 'omkarpathak27@gmail.com',
    'mobile_number': '8087996634',
    'name': 'Omkar Pathak',
    'no_of_pages': 3,
    'skills': ['Operating systems',
              'Linux',
              'Github',
              'Testing',
              'Content',
              'Automation',
              'Python',
              'Css',
              'Website',
              'Django',
              'Opencv',
              'Programming',
              'C',
              ...],
    'total_experience': 1.83
  }
]
Package: indentation
Text indentation functions.UsageIndenting to a specific level:>>> import indentation
>>> indentation.set( "hello", 1 )
'    hello'

>>> indentation.set( "    hello", 0 )
'hello'Indenting to a specific level (and keeping relative lines in place):>>> import indentation
>>> print( indentation.set("hello\n    world", 1) )
    hello
        world
Package: indentedlogs
indentedlogsAdds indentation to the log messages according to their location in the call stack.Documentation:https://gergelyk.github.io/python-indentedlogsRepository:https://github.com/gergelyk/python-indentedlogsPackage:https://pypi.python.org/pypi/indentedlogsAuthor:grzegorz.krason@gmail.comLicense:MITRequirementsThis package requires CPython 3.8 or compatible. If you have other version already installed, you can switch usingpyenv. It must be installed as described in themanual.pyenvinstall3.8.2
pyenvlocal3.8.2InstallationpipinstallindentedlogsExamplespythonexamples/demo0.py
pythonexamples/demo1.py
pythonexamples/demo2.pyDevelopment# Preparing environmentpipinstall--userpoetry# unless already installedpoetryinstall# Auto-formattingpoetryrundocformatter-riindentedlogstests
poetryrunisort-rcindentedlogstests
poetryrunyapf-r-iindentedlogstests# Checking coding stylepoetryrunflake8indentedlogstests# Checking composition and qualitypoetryrunmypyindentedlogstests
poetryrunpylintindentedlogstests
poetryrunbanditindentedlogstests
poetryrunradonccindentedlogstests
poetryrunradonmiindentedlogstests# Testing with coveragepoetryrunpytest--covindentedlogs--covtests# Rendering documentationpoetryrunmkdocsserve# Building packagepoetrybuild# Releasingpoetryversionminor# increment selected componentgitcommit-am"bump version"gitpush
gittag${$(poetryversion)[2]}gitpush--tags
poetrybuild
poetrypublish
poetryrunmkdocsbuild
poetryrunmkdocsgh-deploy-bgh-pagesDonationsIf you find this software useful and you would like to repay author's efforts you are welcome to use following button:
Package: indented-logs
Decorators to log function calls with parameter and timingUsageDecorators to track down function call with indent. This tool is very handly for debugging, since the out is much cleaner than using pythonStack Frames.
Both logging function and indent characters are configurableDecorate a function:fromindented_logsimportlog_call@log_call()defmethod1(arg1,arg2):returnarg1+arg2method1(3,4)Output:...CALL:method1(3,4)...'method1'RETURN:7...'method1'FINISHEDin0.000003secsMultiple functions:fromindented_logsimportlog_call@log_call()defget_data():get_parameters()query_db(conn="sample_conn_str")@log_call()defget_parameters():pass@log_call()defquery_db(conn):returncovert_data("1","2")@log_call()defcovert_data(a,b):return(int(a),int(b))get_data()Output:...CALL:get_data()......CALL:get_parameters()......get_parametersRETURN:None......get_parametersFINISHEDin0.000004secs......CALL:query_db(,conn=sample_conn_str).........CALL:covert_data(1,2).........covert_dataRETURN:(1,2).........covert_dataFINISHEDin0.000005secs......query_dbRETURN:(1,2)......query_dbFINISHEDin0.000870secs...get_dataRETURN:None...get_dataFINISHEDin0.002771secsDecorate class:
Usinglog_call_clsfromindented_logsimportlog_call_cls@log_call_cls(indent="***",log_time=False,logger_func=log_with_capture)classMyClass:defmethod1(self,arg1,arg2):self.method2(arg1)defmethod2(self,arg1):passobj=MyClass()obj.method1("aaaaa","bbbbbbb")Ouput:***CALL:method1(aaaaa,bbbbbbb)******CALL:method2(aaaaa)******method2RETURN:None******method2FINISHEDin0.000005secs***method1RETURN:None***method1FINISHEDin0.000916secsCustomize indent characters:fromindented_logsimportlog_call@log_call(indent='___')defmethod1(arg1,arg2):returnarg1+arg2method1(3,4)Turn off logtime:fromindented_logsimportlog_call@log_call(indent='___',log_time=False)defmethod1(arg1,arg2):returnarg1+arg2method1(3,4)Output:___CALL:method1(3,4)___'method1'RETURN:7___'method1'FINISHEDin0.000006secDevelopmentConda environmentCreate conda environmentconda env create -f environment.ymlIf any dependency is added, remember to update conda environment fileconda env export --from-history > environment.ymlTestsRun using pytest:pytest -s --cov=srcBuild and publishIncrease the version number in setup.py, run:python -m build .Publish to test Pypi:python -m twine upload --repository testpypi dist/* --skip-existingPublish to Pypi:python -m twine upload --repository pypi dist/* --skip-existing
Package: indenti
About Indenti==================Indenti is a Python package with tools that make string building,writing indented text, and generating markup easier and prettier.Indenti contains the following modules:-  IndentWriter-  XmlWriter-  StringBuilderInstallation------------Installation is simple. With python3-pip, do the following:$ sudo pip install -e .About IndentWriter==================IndentWriter is a module that simplifies the task of indenting output.It keeps track of indent levels and provides a pythonic way ofincrementing and decrementing the indent level using the optional 'with'syntax. By default, IndentWriter writes to sys.stdout, but can be toldto write to any other File object at construction.Example Usage, IndentWriter(using 'with'):::from indenti import IndentWriteriw = IndentWriter()iw('def hello():')with iw:iw('print "Hello!"')Example Usage, IndentWriter(without 'with'):::from indenti import IndentWriteriw = IndentWriter()iw('def hello():')iw.indent()iw('print "Hello!"')Example Usage, IndentStringBuilder:::from indenti import IndentStringBuildersb = IndentStringBuilder()sb('def hello():')with sb:sb('print "Hello!"')print str(sb)About XmlFactory================Via XmlFactory, any node name can be specified as an attribute, whichreturns a functor to create a new node.Example Usage, XmlWriter(A CherryPy HTML Servlet):::import cherrypyfrom indenti import XmlFactoryclass HelloWorld:def index(self):xf = XmlFactory()xml = xf.html(xf.head(xf.title("Hello, world!")),xf.body(xf.h1("Hello, CherryPy!", style='color: red; font-size: 20px')))return str(xml)index.exposed = TrueNOTE:~~~~~The word 'class' is a python keyword, so we can't use it as a keywordargument to create an attribute name. In this case, we pass adictionary, which is interpreted as a map of attributes for the node.You can always do this instead of using keyword arguments, if this isyour preference.Example Usage, XmlWriter(Using attributes/nodes that conflict withpython keywords):::import cherrypyfrom indenti import XmlFactoryclass HelloWorld:def index(self):xf = XmlFactory()xml = xf.html(xf.head(xf.title("Hello, world!")),xf.body(xf.h1("Hello, CherryPy!", {'class': 'header')))return str(xml)index.exposed = TrueChange Log----------Version 1.4: April 22nd, 2017~~~~~~~~~~~~~~~~~~~~~~~~~~~~~- Make XmlFactory callable, allowing tags with dashes, e.g. xf('my-dash-tag')()Version 1.2: November 1st, 2016~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~- Make parents respect the NOINDENT status of their children in HTML mode.Version 1.1: October 18th, 2016~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~- Added support for unindented blocks in HTML mode (for textarea)- Fixed escaping of XML attributes
Package: indentify
python-starterA straightforward starter template for Python packages.Includes things like:All necessary files and paths in.gitignoresetup.cfgconfigurationLocal development usingrequirements.txtandrequirements-dev.txtTools likemypy,blackandpytestset up out of the boxSetupClone this repo and delete.gitRenamesrc/sample_packagefolder to your package nameRename the package import intests/sample_test.pyEdit the marked fields insetup.cfg, and remove commentsEditLICENSESetup and activate avirtualenvRunpip install -r requirements-dev.txtThat's it! See if it worked by runningmycommandandpython -m <package name>TestingRunpytestType CheckingRunmypy .Create and upload a package to PyPIMake sure to bump the version insetup.cfg.Then run the following commands:rm-rfbuilddist
pythonsetup.pysdistbdist_wheelThen upload it to PyPI usingtwine:twineuploaddist/*