Saravanan666/pypi-org huggingface dataset:
Package: lEmoji
lEmojiLongstanding Emoji With Historical Version and GeneratorLEmoji provides latest and any other historical version's emoji array.fromlEmojiimportEMOJI_LISTfromlEmojiimportEMOJI_LIST_11_0# version 11.0LEmoji provides emoji generator to update new versions of emoji without upgrade this library.fromlEmoji.generatorimportGeneratorGenerator().generate()>>>Retrievinghttps://www.unicode.org/Public/emoji/...>>>Retrievinghttps://www.unicode.org/Public/emoji/1.0/...>>>Retrievinghttps://www.unicode.org/Public/emoji/2.0/......>>>Retrievinghttps://www.unicode.org/Public/emoji/13.0/...>>>Retrievinghttps://www.unicode.org/Public/emoji/13.1/...>>>Retrievinghttps://www.unicode.org/Public/emoji/1.0/emoji-data.txt...>>>Retrievinghttps://www.unicode.org/Public/emoji/2.0/emoji-data.txt...>>>Retrievinghttps://www.unicode.org/Public/emoji/2.0/emoji-sequences.txt......>>>Retrievinghttps://www.unicode.org/Public/emoji/13.1/emoji-zwj-sequences.txt...Join UsIf you have any interest to contribute this project,contact mewithout hesitation!Release History0.2.1.beta, Released on Dec 25, 2020Fix the bug of failed installing0.2.beta, Released on Oct 31, 2020As unicode.org modified the html code, we fix the bug that generator is failed to grab emoji data.We create this description file.0.1.beta, Released on Feb 22, 2020LEmoji is born.We grab emoji data from version 1.0 to version 13.0.We provide generator for off-pip updating.
Package: lemonade
Lemonade is a Python port of the LEMON Parser Generator written byD. Richard Hipp:http://www.hwaci.com/sw/lemon/Lemonade can be used in the traditional fashion to create a standaloneparser:lemonade gram.yThe above command generates "gram.py", which you can include in yourproject.Since Python is a dynamic language, Lemonade could also enable clientsoftware to generate a parser from a user-supplied .y file, and thenuse the generated parser on the fly.This is the beta release of Lemonade.  There is no documentation yet.You may find the original LEMON documentation helpful:http://www.hwaci.com/sw/lemon/lemon.htmlHowever, many of LEMON's "%" directives are irrelevant in Python;therefore, they have been eliminated in Lemonade.  Further, Lemonadedoes not allow code fragments ("{}") within the grammar file.Instead, the reduce actions are specified in a separate delegateclass.  See the 'examples' directory for an example.----Leif StrandAugust 28, 2012
Package: lemoncheesecake
lemoncheesecake: Test Storytellinglemoncheesecake is an end-to-end test framework for Python that brings trust around test results.
It allows test developers to be very explicit about what their tests really do with logging, matchers, file attachments, etc..Here is a test example:importjsonimportrequestsimportlemoncheesecake.apiaslccfromlemoncheesecake.matchingimport*URL="https://api.github.com/orgs/lemoncheesecake"@lcc.suite("Github tests")classgithub:@lcc.test("Test Organization end-point")deforganization(self):lcc.set_step("Get lemoncheesecake organization information")lcc.log_info("GET%s"%URL)resp=requests.get(URL)require_that("HTTP code",resp.status_code,is_(200))data=resp.json()lcc.log_info("Response\n%s"%json.dumps(data,indent=4))lcc.set_step("Check API response")check_that_in(data,"type",is_("Organization"),"id",is_integer(),"description",is_not_none(),"login",is_(present()),"created_at",match_pattern("^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}Z$"),"has_organization_projects",is_true(),"followers",is_(greater_than_or_equal_to(0)),"following",is_(greater_than_or_equal_to(0)),"repos_url",ends_with("/repos"),"issues_url",ends_with("/issues"),"events_url",ends_with("/events"),"hooks_url",ends_with("/hooks"),"members_url",ends_with("/members{/member}"),"public_members_url",ends_with("/public_members{/member}"))And here are the corresponding test results:NB: in real test code, you’d better uselemoncheesecake-requestswhen doing HTTP / REST API
testing.FeaturesAdvanced test hierarchies using suites, tests and nested suitesTest description and metadata: tags, properties (key=value associations) and linksSupport for test filteringMultiple reporting flavors built-in: HTML, JSON, XML, JUnit, ReportPortal, Slack notificationsBDD support usingbehaveTest parallelizationRich CLI toolboxlemoncheesecake is compatible with Python 3.8-3.12.Installationlemoncheesecake can be installed through pip:$pipinstalllemoncheesecakeFor more details about installing lemoncheesecake with the non-default reporting backends, seehere.DocumentationThe documentation is available onhttp://docs.lemoncheesecake.io.The lemoncheesecake ecosystemlemoncheesecake-requestsprovides logging
and response checking features forrequestsand HTTP / REST API / Web Services testinglemoncheesecake-seleniumis a package
that helps you develop Web UI tests withseleniumContactBugs and improvement ideas are welcomed in tickets. A Google Groups forum is also available for discussions about
lemoncheesecake:https://groups.google.com/forum/#!forum/lemoncheesecake.
Package: lemoncheesecake-requests
lemoncheesecake-requests provides logging facilities torequestsfor
tests written with thelemoncheesecaketest framework.In this example, we implement a very basic test on a Github API endpoint:# suites/github.pyimportlemoncheesecake.apiaslccfromlemoncheesecake.matchingimport*fromlemoncheesecake_requestsimportSession,is_2xx@lcc.test()defget_org():session=Session(base_url="https://api.github.com")resp=session.get("/orgs/lemoncheesecake").\require_status_code(is_2xx()).\check_json({"id":is_integer(),"name":equal_to("lemoncheesecake")})We run the test:$lccrun=================================== github ====================================
 OK  1 # github.get_org

Statistics :
 * Duration: 0.214s
 * Tests: 1
 * Successes: 1 (100%)
 * Failures: 0And here is the report details :InstallationInstall through pip:$pipinstalllemoncheesecake-requestslemoncheesecake-requests is compatible with Python 3.7-3.10.Featuresrequest/response data logging into lemoncheesecakeresponse status code checking using lemoncheesecake matching mechanismDocumentationThe documentation is available onhttps://lemoncheesecake-requests.readthedocs.io.ContactBug reports and improvement ideas are welcomed in tickets.
A Google Groups forum is also available for discussions about lemoncheesecake:https://groups.google.com/forum/#!forum/lemoncheesecake.
Package: lemoncheesecake-selenium
lemoncheesecake-selenium provides logging facilities to theSelenium Python libraryfor
tests written with thelemoncheesecaketest framework.Here is a simple example of a search onhttps://www.python.org:# suites/python_org_search.pyimportlemoncheesecake.apiaslccfromlemoncheesecake.matchingimport*fromlemoncheesecake_seleniumimportSelector,save_screenshot,is_in_pagefromseleniumimportwebdriverfromselenium.webdriver.common.keysimportKeys@lcc.test()defpython_org_search():driver=webdriver.Firefox()driver.implicitly_wait(10)driver.get("http://www.python.org")selector=Selector(driver)check_that("title",driver.title,contains_string("Python"))search_field=selector.by_name("q")search_field.clear()search_field.set_text("pycon")search_field.set_text(Keys.RETURN)selector.by_xpath("//h3[text()='Results']").check_element(is_in_page())save_screenshot(driver)driver.close()We run the test:$lcc.pyrun============================== python_org_search ==============================
 OK  1 # python_org_search.python_org_search

Statistics :
 * Duration: 10s
 * Tests: 1
 * Successes: 1 (100%)
 * Failures: 0

HTML report : file:///tmp/python_org_search/report/report.htmlAnd here are the report details :InstallationInstall through pip:$pipinstalllemoncheesecake-seleniumlemoncheesecake-selenium is compatible with Python 3.7-3.10 and Selenium 4.x.You will also need toinstall a WebDriverto control your web browser.Featuresclicking, setting text, selecting element in a SELECT, etc..checking DOM nodesscreenshotsDocumentationThe documentation is available onhttps://lemoncheesecake-selenium.readthedocs.io.ContactBug reports and improvement ideas are welcomed in tickets.
A Google Groups forum is also available for discussions about lemoncheesecake:https://groups.google.com/forum/#!forum/lemoncheesecake.
Package: lemondb
LemonDBLemonDB is a simple and lightweight document oriented database written in pure Python 3 tried on version:3.9&3.8. It should work on versions <= 3.7. This class handle all operation including storing document on a file.Example:fromlemondbimportLemonDBdb=LemonDB('test.db')db.insert_many([{'name':'Zenqi'},{'name':'John Doe'},{'name':'Elizabeth Doe'}])# Search from database using `find` or `search`foriindb.find('Doe').where(lambdax:x['name'].startswith('John')):print(i)#: {'name': 'John Doe'}#: You can use the query or dictfromlemondbimportQueryquery=Query()print(db.find_one(query.name=='Zenqi')))#: {'name': 'Zenqi'}print(db.find_one({'name':'Zenqi'}))#: {'name': 'Zenqi'}📌 New Features in 1.x Series!Differenttypesare now supported!Searching / filtering were improved.Have you ever wanted to serialize a datetime object? and other type object that standard JSON could'nt serialized?
Well lemondb now support those. Search & filtering were improved. LemonDB now using cursors. Don't believe me? Try this outfromlemondbimportLemonDBfromdatetimeimportdatetime# Adding datetime objectdb=LemonDB('test.json')db.insert({'name':'John Doe','elapsed-time':datetime.now()})# Searching now accept dict queriesdb.find_one({'name':'John Doe'})
Package: lemon-explainer
LEMONis a technique to explain why predictions of machine learning models are made. It does so by providing feature contribution: a score for each feature that indicates how much it contributed to the final prediction. More precisely, it shows the sensitivity of the feature: a small change in an important feature's value results in a relatively large change in prediction. It is similar to the popularLIMEexplanation technique, but is more faithful to the reference model, especially for larger datasets.Website ↗Academic paper ↗InstallationTo install use pip:$ pip install lemon-explainerExampleA minimal working example is shown below:importnumpyasnpimportpandasaspdfromsklearn.datasetsimportload_irisfromsklearn.ensembleimportRandomForestClassifierfromlemonimportLemonExplainer# Load datasetdata=load_iris(as_frame=True)X=data.datay=pd.Series(np.array(data.target_names)[data.target])# Train complex modelclf=RandomForestClassifier()clf.fit(X,y)# Explain instanceexplainer=LemonExplainer(X,radius_max=0.5)instance=X.iloc[-1,:]explanation=explainer.explain_instance(instance,clf.predict_proba)[0]explanation.show_in_notebook()DevelopmentFor a development installation (requires npm or yarn),$ git clone https://github.com/iamDecode/lemon.git
$ cd lemonYou may want to (create and) activate a virtual environment:$ python3 -m venv venv
$ source venv/bin/activateInstall requirements:$ pip install -r requirements.txtAnd run the tests with:$ pytest .Approximate distance kernel LIMEIf you prefer to use a Gaussian distance kernel as used in LIME, we can approximate this behavior with:fromlemonimportLemonExplainer,gaussian_kernelfromscipy.specialimportgammainccinvDIMENSIONS=X.shape[1]KERNEL_SIZE=np.sqrt(DIMENSIONS)*.75# kernel size as used in LIME# Obtain a distance kernel very close to LIME's gaussian kernel, see the paper for details.p=0.999radius=KERNEL_SIZE*np.sqrt(2*gammainccinv(DIMENSIONS/2,(1-p)))kernel=lambdax:gaussian_kernel(x,KERNEL_SIZE)explainer=LemonExplainer(X,distance_kernel=kernel,radius_max=radius)This behavior is as close as possible to LIME, but still yields more faithful explanations due to LEMON's improved sampling technique. Read the paper for more details about this approach.CitationIf you want to refer to our explanation technique, please cite our paper using the following BibTeX entry:@inproceedings{collaris2023lemon,title={{LEMON}: Alternative Sampling for More Faithful Explanation Through Local Surrogate Models},author={Collaris, Dennis and Gajane, Pratik and Jorritsma, Joost and van Wijk, Jarke J and Pechenizkiy, Mykola},booktitle={Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis (IDA 2023)},pages={77--90},year={2023},organization={Springer}}LicenseThis project is licensed under the BSD 2-Clause License - see theLICENSEfile for details.
Package: lemon-framework
LemonVersion: 1.3.4Welcome to LemonThis project is open source so do what ever you want with it.Watch for more info:https://www.youtube.com/watch?v=PYr8js5QY1MInfoThis project is a web framework written in python. You can write a web app with python in this new web framework.Lemon has not been tested on windows or mac, so if there is any issues please report them in the issues area.Lemon is not for production.How to usePlease read documentation to get started. The lemon docs are at:docs/LemonDocumentation.mdHow to installWindowspip install lemon-frameworkLinux and Macpip3 install lemon-frameworkDocumentationDocumentation is located in docs/ContributeRead theCONTRIBUTE.mdfileScreenshots and ImagesWhat needs doingMake multipart-form/data faster when uploading large fileserror handling more reliableneeds a debug mode for easier debuggingmore security features
Package: lemonpy
Welcome to LemonpyThis is a meta packages for my research about geometric approaches to solving kinematics projects and machine learning related topics. Visit my blog atlemonfold.io.Install withpoetryinstall-E"dbc mgng"Where the extras install the following packagesdbc:design-by-contract–A design-by-contract Librarymgng:lemonpy-mgng–An implementation of the merge growing neural gas algorithm
Package: lemonpy-mgng
Welcome to mgngAn experimental implementation of the Merge Growing Neural Gas algorithm.
The project turned into an exercise for using state-of-the-art python tools.
This project has been created with mycookiecutter for science projectsThe Growing Neural Gas and Merge Growing Neural Gas AlgorithmsGrowing Neural Gas (NGN)is atopology preserving (see this blog for a demonstration)orthis explaination) extension to theNeural gas (NG)approach is usefull for learning when an underlying topology is not known (as in the case of theSelf-organizing maps (SOM)algorithm). When it comes to time series data (such as trajectories), an extension to the neural gas algorithm has been approached (Merge Neural Gas (MNG)) and a combination with the GNG leads to theMerge growing neural gas (MNGN)approach. It adds a context memory to the neurons of the NGN and is useful forrecognisingtemporal sequences and with a single weighting parameter, can be reduced to a regular NGN for which an implementationis available.This packages implements the MGNG algorithm as a vanillanumpyimplementation (which can be executed on the GPU withCupy). The package uses modern python tools such aspoetry,attrs(a focus has been laid on those two for this release), and sphinx and mypy/pylint/black for documentation and coding standards.See the notebooks in the repective subfolder of the project root and thedocumentation.Installation and developmentFirst make sure to install Python (^3.7) the dependency management
toolPoetrythen create an isolated virtual
environment and install the dependencies:poetryinstallPer terminal session,  the following command should be executed
to activate the virtual environment.poetryshellTo generate the documentation run:cddoc/
makeapi# optional, only when the code base changesmakehtmlTo run unit tests, run:pytest--log-level=WARNING# Specify a selected testpytest--log-level=DEBUG-k"TestExample"pytest--log-level=DEBUGtests/test_example.py::TestExample::test_exampleTo work withVisualStudio Code:cp.vscode/template.settings.json.vscode/settings.json
whichpython# copy the path without the executableand add the path to the virtual environment to in the"python.pythonPath"setting.cp.vscode/template.settings.json.vscode/settings.json
whichpython# copy the path without the executableand add the path to the virtual environment to in the"python.pythonPath"setting.
Package: lemonrunner
LemonrunnerRun this forever and stream the results.The entry point is the Lemonrunner-class, which exposes the run-method. Run
takes an id, a function, and optional key-word arguments for args, kwargs,
timeout, times and interval.Any function passed to run will be run either forever, or N times, if the times arument is given. Returns, yielded values or exceptions are all retrieved from the monitor-method.The monitor function of the Lemonrunner-class is a generator which yields each message from each function as they come in.ExamplefromtimeimportsleepfromlemonrunnerimportLemonrunnerdeffoo():raiseValueErrordefbar():sleep(3)return5defbaaz():yield'abc'runner=Lemonrunner()runner.run('foo',foo,interval=1)runner.run('bar',bar,interval=1,timeout=2)runner.run('baaz',baaz,times=2)forid,message_type,timestamp,return_valueinrunner.monitor():print(id,message_type,timestamp,return_value)
Package: lemons
lemonsis a package that makes things easy.Why lemons?Originally intending to call this packageezpz, it was soon discovered that the name had already been taken. Heartbroken, and with no other ideas for what to call this package, it felt like the world had ended. The feeling of dread and loss was devastating - debilitating, even.Nonetheless, when life give you lemons, you squeeze them! Aha, an epiphany: why not go back to the root of it all, the title of one of my earliest programs:EZPZ Lemon Squeezy? A simple yet elegant title was there all along, yearning to represent this package and all it stood for; the darkness vanished as quickly as it came, and the namelemonswas born.What is it?Lemonstries to make GUI building easier by eliminating a lot of repetitive and error-prone code. Please keep in mind that the package is still in its infancy, so its functionality is currently quite limited.he tkinter framework, as many know, is not the most user-friendly GUI-builder out there.lemonshopes to help ease that pain a little. For example, creating a scrollable notebook tab, which previously took dozens of lines of code per tab, can now be done in just one.How to get itDependenciesCurrently,lemonsprimarily uses the standard Python library and therefore does not require any additional packages to be installed on your machine. However, if you want to use image functionality from the gui module, thenpillowis necessary.Pip installationThe latest stable version of the package is uploaded to PyPI.To install, open a command prompt and type, or copy and paste:pip install lemonsTo upgrade to the latest version:pip install --upgrade lemonsTo uninstall the package:pip uninstall lemonsAuthorsJake Brehm-Initial Work-Email|Github|LinkedIn
Package: lemonsqueezer
LemonSqueezeris a python wrapper for lemonbar that makes it easy to make
beautiful, informative status bars usingless powerthan most other status
bars. This is achieved by only updating the bar when new output is available,
without polling commands for output, (such as polybar or a custom lemonbar
script would do).InstallationArch Linux`sh git clonehttps://aur.archlinux.org/python-lemonsqueezer.gitcdpython-lemonsqueezermakepkg-si`General`sh sudo pip installpython-lemonsqueezer`BasicsLemonsqueezer defines its output in terms ofModules. These are python
objects which define how and when to render output on the bar. The baseBarModuleclass has little to no behaviour attached to it and so, to create
useful modules, a couple of helper subclasses are available (SeeCommandWatcherModuleorPeriodicModulein the docs). There are also a few
premade modules for things such as battery or a clock.Creating custom modulesNew modules are created by subclassing the baseBarModuleclass and
overriding thesetupandget_outputmethods.Lemonsqueezer uses asyncio to achieve its efficiency. Bothsetupandget_outputare coroutine methods. When the bar starts,setupis awaited
first. When it returns, its output is placed on the bar at the appropriate
location (as specified by the BarModule constructor). After that,get_outputis awaited repeatedly, setting the module text whenever it
returns. Note that ifget_outputreturns None, then the bar is not updated
at all.Helper subclassesPeriodicModuleRun a command every few seconds and set the output based on its outputThis is the closest to how other bars usually get output, and it’s probably
the most inefficient method to create a module. However you can still have
a small improvement over a traditional bar manager since you are able to
return None if there are no changes to the output.CommandMonitorModuleUse this type of module when you want to have the module update whenever a
command produces some output. A lot of the built-in modules are defined using this.
Package: lemonsync
lemonsync 0.1.19Released: 27-May-2015LemonSyncwill listen for changes in the folder you configure, and
automatically push updates to your store “editing” theme. This is helpful if you
want to add your theme under version control, or prefer to work locally
rather than in the LemonStand UI.PlatformsLemonSync supports the following platforms.Mac OS XWindows 7/8Linux 2.6, 3.xInstallationFullinstallationnotes are available in thewiki.ConfigurationSee thewikifor an example config file andconfigurationexamples.UsageSee thewikifor examples on how toget startedand other notes onusage.TODOMake it easy for multiple developers to work on the same theme.Add option to create theme from the command line.
Package: lemontest
🍋test /ˈlɛmən tɛst/ Noun.
 1. A test which appears to test a feature, but in fact does not test that feature at all.
 [us. I reviewed that pull request and found one 🍋test that doesn't test right.]What?A unittest runner for detecting 🍋tests.Why?Good development practice dictates that new features should be accompanied with new tests. Good tests can identify regressions and accidental removal of features.A 🍋test, is a test which appears to test a feature, but in fact does not test that feature at all. 🍋tests can be considered worse than not having a test at all, because they give the false assumption that your new feature is tested. If a regression occurs, 🍋tests won’t let you know. The detection of 🍋tests can identify situations when the feature does not meet your requirements. Detecting 🍋tests helps ensure code quality and feature delivery.This library identifies 🍋tests. This is done by examining two git branches: the feature, and the merge destination. The algorithm separates business logic from testing code, and then uses Git to revert business logic to it’s previous state (the same as the merge destination). A test suite is then run on the reverted business logic with the new tests. Any tests that are successful are marked as 🍋tests.Testing for 🍋tests is a form of mutation testing. The mutation operation in this case is reverting the business logic to it’s previous state before the feature was written.Quickstartpipinstalllemontestmanage.pytest--testrunner=lemontest.djangorunner.DjangoLemonTestRunner--to-branch=master--from-branch=feature/123It must be a git repository.Lemontest needs a git repository to be able to revert business logic.Travis CITravis conveniently provides environment variables we can use.pipinstalllemontestmanage.pytest--testrunner=lemontest.djangorunner.DjangoLemonTestRunner--to-branch=$TRAVIS_BRANCH--from-branch=$TRAVIS_PULL_REQUEST_SHAAlgorithmGet source files that have changed (git diff)Identify test source files (use unittest discovery and intersect with step 1)Identify business logic files (set difference between step 1 and step2)Use git to revert business logic code (git checkout)Run tests that have changedRaise an exception for each test that succeeds
Package: lemon-tools
lemon-tools (Python Package Builder)This package is a meta-package that provides python libs for projects and mainlylemon-make-packagescript.lemon-make-packagecreates a python package templateIntalllemon_toolspipintalllemon_toolsCreate ayour_pkg_namepackageUselemon-make-packageto create a new python package:$lemon-make-package-nnew_pkg_name-d"New project package"=>Newpythonpackagenew_pkg_namecreated$cdnew_pkg_name/$gitinit;gitadd*;gitcommit-am'initial commit'$gittag-a0.42-m0.42$makecleanCheck if__version__is set:$cd/tmp$python-c'import new_pkg_name; print (new_pkg_name.__version__)'0.42$Check ifnew_pkg_namescript works:$(venv)user@machine:/tmp$new_pkg_name-runnew_pkg_name/data/data.csv.gzLoaded==>out.csvMADEshapeis(999,142)(venv)user@machine:/tmp$wc-lout.csv1000out.csv(venv)user@machine:/tmp$