Saravanan666/pypi-org huggingface dataset:
Package: lucd
Create Local Undetectable Chrome Driver (LUCD)This program will download and patch a Chrome driver to make it undetectable. So that you can use an undetectable Chrome driver for your Python Selenium code.Passed the antibot testFeaturesDownload the exact chrome driver based on your OS and installed chrome version.Remove browser control flagRemove signature in javascriptSet User-AgentStart maximum resolutionOpen Chrome Instance on debugging modeControl an existing Chrome instance.Unmute the sounds of the browser.Save/ load Chrome profiles.Run Chrome driver on headless mode.Installationpip install lucdorpip install git+https://github.com/SelmiAbderrahim/CreateUndetectableChromeDriver/blob/master/lucd/screenshots/antibot-tested.pngExamplefrom lucd.driver import Driver
driver = Driver()
chrome = driver.create()UsageCreate an undetectable Chrome driverfrom lucd.driver import Driver
driver = Driver()

# headless browser
driver.headless = True

# Mute the browser
driver.mute = True

# Set the profile path
driver.profile = r"C:\\path\\profile"

# Change useragent
driver.useragent = "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.134 Safari/537.36"

chrome = driver.create()Control/open an existing Chrome driverfrom lucd.driver import Remote
driver = Remote()

# Open Chrome on debugging mode and control it
chrome = driver.create()

# Control an existing Chrome driver
chrome = driver.create(control_existing_instance, port = 9222)TestsClone the projectgit clone https://github.com/SelmiAbderrahim/CreateUndetectableChromeDriver/blob/master/lucd/screenshots/antibot-tested.pngCreate virtual environmentpip install virtualenv
virtualenv env
source env/bin/activateInstall requirementspip install -r requirements.txtRun testspython -m pytest lucd/tests/
Package: lucene-querybuilder
synopsis:A Python DSL for Lucene queries.Easily create Lucene query strings without having to learn the language itself. The syntax is simple to use and allows creating larger queries from multiple smaller ones. A basic lesson on proper Lucene queries can be foundhere.Supports Python 2.6+.Getting Started>>> from lucenequerybuilder import QCreating QueriesA basic query can be given by passing in a string into Q’s constructor.>>> q = Q('a')>>> q = Q('The quick brown fox')The query builder will automatically detect whether a term (no whitespace) or a phrase (multiple terms together seaparated by whitespace) and properly bound them with quotation marks.All terms and phrases are expected to be unescaped, and will be escaped:>>> q = Q(r'The *quick* brown (fox)')

>>> str(q)

'"The \\*quick\\* brown \\(fox\\)"'Range QueriesRanges are also easy to put into a query. There are two types of range queries, inclusive range and exclusive range. These are passed into the query builder with keyword arguments.>>> q = Q(inrange=(1,5))>>> q = Q(exrange=['egg','hgg'])Ranges will work with any list-like object of length 2.Chaining QueriesYou can chain queries with&(AND),|(OR),& ~(AND NOT),+(MUST), and-(MUST NOT). AND, OR, and AND NOT require a query before and after it shows up. MUST and MUST NOT only work on the query directly afterwards. Some examples are below:>>> q = Q('a') & Q('b')

>>> q = Q('a') & ~Q('b')

>>> q = +Q('a') -Q('b')Nested QueriesQueries can be nested inside of each other to create new queries. This makes it easy to group queries together. Examples below:>>> q = Q(Q('a') & Q('b')) & ~Q('c')

>>> q = Q(Q(Q('a') | Q(inrange=[1,2])) +Q('c))FieldsFields can be added to queries by putting in a field as your first argument. Fields cannot have any whitespace and cannot be nested inside each other. The following examples are valid queries:>>> q = Q('name', 'Edward')

>>> q = Q('text', 'Mary had a little lamb')

>>> q = Q('age', inrange=[10, 9001])The following examples are invalid queries which will raise an error:>>> q = Q('name', Q('lastname', 'Purcell'))

>>> q = Q('bad', Q('range', inrange=[10, 9001]))Fuzzy QueriesA fuzzy term query can be accomplished using the fuzzy keyword:>>> q = Q('name', fuzzy=('edd', .2))

>>> str(q)

'name:(edd~0.200)'The first element in the fuzzy tuple is the term, and the second is the similarity ratio- a float, str, or decimal between 0 and 1.If you drop the second element, and just provide a str, the string will signify to use Lucene’s default ratio - 0.5:>>> q = Q('name', fuzzy='edd')

>>> str(q)

'name:(edd~)'Wildcard QueriesTo keep wildcard queries from having ‘?’ and ‘*’ from being escaped, simple include the wildcard flag:>>> str(Q('c?t', wildcard=True))

'c?t'which will match ‘cat’ or ‘cot’.Boosting & Wildcard QueriesThese queries are not yet supported, but will be soon. Feel free to add support yourself and request a pull!
Package: luchtmeetnet
AirQualityThis is a Python Package for Air Quality in Dutch Provinces from the site luchtmeetnet.Explanation LKI
The air quality index card (LKI) is the sum of the most important air pollutants.Dutch:
De luchtkwaliteitsindex-kaart (LKI) is een optelsom van de belangrijkste luchtverontreinigende stoffen.The app will search for your closes station that measures your air quality.InstallationLuchtmeetnet requires Python 3.6+ to runpip install luchtmeetnetTO-DOSeveral confitions
More measurements of different substance
Package: lucia
luciaINSTALLATION|DOCUMENTATION|LICENSEAn audio game engine written in pythonGoals:The goal of lucia is to change the audio game creation method from the now old and no longer maintained bgt, to python.
Lucia should not act as a starting game, but as a base, that a high quality game can be build upon.
In addition lucia should be cross platform, At Least on windows and mac.Code / dependencies that doesn't meet these requirements cannot be a part of lucia.InstallationThere's the to default ways to install lucia.
Through pippip install luciaOr the manual waygit clone https://github.com/LuciaSoftware/lucia.git
cd lucia
python setup.py installBuilding / Running:Running tests:To run the tests run the following command:python setup.py testGenerating documentation:To generate Lucia's documentation, you first need to install pydoc-markdownpip install pydoc-markdownafter go into the "docs" folder:cd docsAnd run:pydocmd buildAlternatively, you can also view a local demo of the docs by executing the following command:pydocmd serveContributingEveryone is welcome to help improve Lucia. starthereLicense:Copyright (C) 2019  LuciaSoftware and it's contributors.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, version 3 of the License.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License
along with this program.  If not, seehttps://github.com/LuciaSoftware/lucia/blob/master/LICENSE.
Package: lucid3
lucid3: Loop and uCrystals identification version 3Authors: Olof Svensson and Sogetilucid3 is a computer vision Python library that detects
crystallography samples holders.mxCuBE relies lucid3 to provide automatic centring.Dependencies:python >= 3.5opencv >= 2.4DevelopmentInstall from sourcepython-mpipinstall-e.[dev]Run testspytestLaunch lucid3 from the command linelucid3 -h
usage: lucid3 [-h] [--vertical] [--display] [--create_result_file] [--result_directory RESULT_DIRECTORY] [--debug] snapshot_file_path

Application for finding loop in diffractometer snapshot of sample

required arguments:
  snapshot_file_path    Path to snapshot jpg/png file

optional arguments:
  --vertical            Vertical rotation axis
  --display             Display snapshot with result
  --create_result_file  Create an image file with result
  --result_directory RESULT_DIRECTORY
                        Directory to where store result file (default cwd)
  --debug               Display snapshot with all intermediate steps and with result
Package: lucid-H
under testingUnder construction! still adding more functions!

this is Hemant's work intended to help other developers to develope 

It is easy to use.Examples of How To Usefrom HemantDhanwar import EmailServices as eses.disk_usage('D:/','D:/')es.email_with_attachhment('HemantDhanwar@lucidmotors.com', 'D:\H_Work_SPACE\key.txt', 'HemantDhanwar@lucidmotors.com,kirankumarj@lucidmotors.com,shravankumar@lucidmotors.com', 'D:\')disk_usage(path, output_path, SAVE = True)email_with_attachhment(username, path2key, mail_to, path)path is where i saved my csv data
Package: lucidmode
Currently a Beta-Versionlucidmodeis an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning models. It has built in machine learning methods optimized for visual interpretation of some of the most relevant calculations.DocumentationOficial Website:https://www.lucidmode.orgDocumentation:https://lucidmode.readthedocs.ioPython Package Index (PyPI) repository:https://pypi.org/project/lucidmode/Github repository:https://github.com/lucidmode/lucidmodeInstallationWith package manager(coming soon)Install by using pip package manager:pip install lucidmodeCloning repositoryClone entire github projectgit@github.com:lucidmode/lucidmode.gitand then install dependenciespip install -r requirements.txtModelsArtificial Neural NetworkFeedforward Multilayer perceptron with backpropagation.fit: Fit model to datapredict: Prediction according to modelInitialization, Activations, Cost functions, regularization, optimizationWeights Initialization: With 4 types of criterias (zeros, xavier, common, he)Activation Functions: sigmoid, tanh, ReLUCost Functions: Sum of Squared Error, Binary Cross-Entropy, Multi-Class Cross-EntropyRegularization: L1, L2, ElasticNet for weights in cost function and in gradient updatingOptimization: Weights optimization with Gradient Descent (GD, SGD, Batch) with learning rateExecution: Callback (metric threshold), History (Cost and metrics)Hyperparameter Optimization: Random Grid Search with MemoryComplementaryMetrics: Accuracy, Confusion Matrix (Binary and Multiclass), Confusion Tensor (Multiclass OvR)Visualizations: Cost evolutionPublic Datasets: MNIST, Fashion MNISTSpecial Datasets: OHLCV + Symbolic Features of Cryptocurrencies (ETH, BTC)Important LinksRelease notes:https://github.com/lucidmode/lucidmode/releasesIssues:https://github.com/lucidmode/lucidmode/issuesExample Notebooks:https://github.com/lucidmode/lucidmode/tree/main/notebooksDocumentation:https://lucidmode.readthedocs.ioPython Package Index (PyPI) repository:https://pypi.org/project/lucidmode/AuthorJ.Francisco Munnoz -IFFranciscoME- Is an Associate Professor in the Mathematics and Physics Department, atITESOUniversity.Current ContributorsLicenseGNU General Public License v3.0Permissions of this strong copyleft license are conditioned on making available
complete source code of licensed works and modifications, which include larger
works using a licensed work, under the same license. Copyright and license notices
must be preserved. Contributors provide an express grant of patent rights.Contact: For more information in reggards of this repo, please contact francisco.me@iteso.mx
Package: lucidmotors
python-lucidmotorsUnofficial Python bindings to the Lucid Motors API. No affiliation with Lucid
Motors.To install dependencies, assuming you have Python development tools already, run:pip install -r requirements.txtTry fiddling withexamples/vehicle_info.py. With no arguments it will prompt
for your Lucid username and password, then print out your user profile and
vehicle information.To generate a test case from your data, visittestmycode.cc. This will log in using your Lucid
account, remove identifying information from the API response, and let you
submit the anonymized data for review.If you're feeling adventurous, try playing withexamples/test_all_actions.pywhich
will run through every action we have figured out out thus far. A "stress test" of
sorts.
Package: lucidsonicdreams
Lucid Sonic DreamsLucid Sonic Dreams syncs GAN-generated visuals to music. By default, it usesNVLabs StyleGAN2, with pre-trained models lifted fromJustin Pinkney's consolidated repository. Custom weights and other GAN architectures can be used as well.Sample output can be found onYouTubeandInstagram.InstallationThis implementation has been teston on Python 3.6 and 3.7. As per NVLabs' TensorFlow implementation of StyleGAN2, TensorFlow 1.15 is required. TensorFlow 2.x is not supported.To install, simply run:pip install lucidsonicdreamsUsageYou may refer to theLucid Sonic Dreams Tutorial Notebookfor full parameter descriptions and sample code templates. A basic visualization snippet is also found below.Basic Visualizationfrom lucidsonicdreams import LucidSonicDream


L = LucidSonicDream(song = 'song.mp3',
                    style = 'abstract photos')

L.hallucinate(file_name = 'song.mp4')
Package: lucidtech-las
Python SDK for Lucidtech AI Services APIDocumentationLink to docsInstallation$pipinstalllucidtech-lasUsageSign up for freehereand download API credentials to use this SDK.
Read more about authenticating to the APIhereQuick startimportjsonfromlasimportClientclient=Client()models=client.list_models()['models']# List all models availablemodel_id=models[0]['modelId']# Get ID of first model in listdocument=client.create_document('path/to/document.pdf')prediction=client.create_prediction(document['documentId'],model_id=model_id)print(json.dumps(prediction,indent=2))ContributingPrerequisites$pipinstall-rrequirements.txt
$pipinstall-rrequirements.ci.txtRun tests$makeprism-start
$python-mpytestCreate docs$tox-edocs.docsout
Package: lucidtech-las-cli
Command Line Interface for Lucidtech AI ServicesInstallation$pipinstalllucidtech-las-cliDocumentationLink to docsUsageAll methods support the--helpflag which will provide information on the purpose of the method,
and what arguments could be added.$lasdocumentscreate--help
$lasmodelslist--help
$lasworkflowsupdate--helpContributingPrerequisites$pipinstall-rrequirements.txt
$pipinstall-rrequirements.ci.txtRun tests$makeprism-start
$python-mpytest
Package: lucidwallet
LucidwalletA Frontend for FluxwalletFeaturesFull graphical wallet in your terminalBrowser support coming soonCan work over ssh with full copy paste (even headless)Flux native wallet (other chains coming soon)Optionally encrypt keysSend / receive transactionsSign messages (login to home.runonflux.io)Create wallet / import from mnemonicUses Websocket to subscribe for latest blocks etcQuickstart (Python 3.10+)Install:pipinstalllucidwalletOnce installed run from a terminal:Run:lucidwalletORif you're having trouble with your Python path:python3-mlucidwalletORif you want a portable, albiet slower way to run:dockerrun--namelucidwallet-itmegachips/lucidwallet:latestThen on subsequent runs:dockerstartlucidwallet-iaInstallationRequires Python 3.10 or greater. If you don't have Python 3.10 - use the docker imagemacOSPrerequisites:gmpbrewinstallgmpInstall:python3-mpipinstalllucidwalletA note on macOS terminal, it is recommended that you useITerm2, native terminal works, however you need to modify some settings. Seehereif you plan on usingTerminal.appUbuntu 22.04 (comes standard with Python 3.10)Prerequisites:libgmp-devsudoapt-getupdate&&apt-getinstallpython3-piplibgmp3-devInstall:python3-mpipinstalllucidwalletSource your profile to pick up new bin folder (or restart terminal)source~/.profileWindowsTested on a Windows Server 2022 VM.Prerequisites:A decent terminal. Powershell 7 works, but it's not pretty.tabby.shhas been tested and works well.Once Python is installed, install with pip. Make sure your paths are up to date.python3-mpipinstalllucidwalletNote, there is nofastecdsanatively on Windows. So some cryptographic functions are slower. You can install thefastecdsa-anypackage however you will need a working gmp and C++ build tools for Python installed.OR - Just use docker.DockerUsage notes:The perfered method to run in docker is to NOT use mounts and reuse the same container.Performance takes a bit of a hit on docker (especially on macOS) You can try virtiofs for faster mounts. (If you are bind mounting a database) SeehereHowever, docker lucidwallet is the easiest to install.Preferred method:dockerrun--namelucidwallet-itmegachips/lucidwallet:latestThen on subsequent runs:dockerstartlucidwallet-iaIf you want to use a local db dir, mount it like this:dockerrun-v$(pwd)/database/:/database--rm-itmegachips/lucidwallet:latestThis will create adatabasefolder in your current directory, and the container will store database files there.
Package: lucier
Sequence MIDI messages using aFlask-style interface. Very much a work-in-progress.Installationpip install lucierUsagefromlucierimportSequencer,MidiController,utilss=Sequencer()@s.register([MidiController(0)])asyncdeflow_melody(ctrl,tick):ifutils.every_n_ticks(50,tick):awaitctrl.play_note(60,60,.5)@s.register([MidiController(1)])asyncdefhigh_melody(ctrl,tick):ifutils.every_n_ticks(50,tick,offset=25):awaitctrl.play_note(72,60,.5)s.play()
Package: lucifer
LuciferLucifer is a Python package for creating nice and colourful progress bars using the map() and apply() method as well as for loops.EtymologyOld EnglishLucifer"Satan," also "morning star, Venus in the morning sky before sunrise,"
also an epithet or name of Diana, from Latin Lucifer "morning star," noun use of adjective,
literally "light-bringing," from lux (genitive lucis) "light" (from PIE root *leuk- "light, brightness") +
ferre "to carry, bear," from PIE root *bher- (1) "to carry," also "to bear children." Venus in the
evening sky was Hesperus.ProgressBarTo use a progress bar you need to initiate a ProgressBar object with the maximum progress amount (total) and call the show method of the object with the amount to update the progress bar.fromluciferimportProgressBarfromtimeimportsleepbar=ProgressBar(total=100)foriinrange(100):sleep(0.05)bar.show(amount=i+1)You can also add your own text to the progress bar.fromluciferimportProgressBarfromtimeimportsleepbar=ProgressBar(total=100)foriinrange(100):sleep(0.05)bar.show(amount=i+1,text=f'working on{i}')mapYou can also use the ProgressBar's map method instead of Python's map method. The output is an iterable. As soon as you turn the iterable object into a list the progress bar will be displayed.fromluciferimportProgressBarfromtimeimportsleeplist1=list(range(100))defwait_and_double(x,wait_time):sleep(wait_time)returnx*2# this will not make the progress bar appeariterable2=ProgressBar.map(function=lambdax:wait_and_double(x=x,wait_time=0.05),iterable=list1)# this will make the progress bar appearlist2=list(iterable2)applyProgressBar also works with Panda's DataFrame and Series objects.fromluciferimportProgressBarfromtimeimportsleepfrompandasimportDataFramedata=DataFrame({'name':['Arminius','Boudica','Alaric','Attila','Genseric'],'ethnicity':['German','Celt','Goth','Hun','Vandal']})data['name_and_ethnicity']=ProgressBar.apply(data=data,function=lambdax:x['name']+' the '+x['ethnicity'])data['name_lower']=ProgressBar.apply(series=data['name'],function=lambdax:x.lower())iterateYou can also use ProgressBar to for iterating over iterable objects, especiallyforloops.fromluciferimportiterateforiiniterate(range(100)):# do somethingpass
Package: lucina
LucinaFrom markdown to Jupyter notebook.https://pypi.org/project/lucina/Create a Jupyter notebook with Python & Markdown fragments from mardkwon files.InstallationInstall Lucina by runningpip install lucina.UsageRunninglucinaon fileinput.md.lucina-odocs/output.ipynbdocs/input.mdIt outputs fileoutput.ipynbthat looks like:DevelopmentEnvironmentUsepip install -e '.[dev]'to installlucinawith development dependencies (tests & lint).ContributingCode of the project is managed onhttps://github.com/entwanne/lucina/git repository.Building & deploying a new versionYou need to installtwinepackage (pip install twine) to be able to deploy a version of the library.You can usepython setup.py sdistto build the current version of the package.Then you can deploy this version to PyPI by runningtwine upload dist/*.
Package: luckdog
luckdog  新版本已经出来了luckdog是类似于postman的接口访问工具。#######################################################################Last update time: 2020-04-20
By： 8034.com#######################################################################更新日志：
2022-04-02  增加断言######################################################################### 打包 检查
python setup.py check 
## 打包 生成
python setup.py sdist
## 上传
twine upload -u uu -p DD dist/*
## 使用
pip install luckdog 
## 更新
pip install --upgrade luckdog
## 卸载
pip uninstall -y luckdog#######################################################################MANIFEST.ininclude pat1 pat2 ...   #include all files matching any of the listed patterns

exclude pat1 pat2 ...   #exclude all files matching any of the listed patterns

recursive-include dir pat1 pat2 ...  #include all files under dir matching any of the listed patterns

recursive-exclude dir pat1 pat2 ... #exclude all files under dir matching any of the listed patterns

global-include pat1 pat2 ...    #include all files anywhere in the source tree 
matching — & any of the listed patterns

global-exclude pat1 pat2 ...    #exclude all files anywhere in the source tree matching — & any of the listed patterns

prune dir   #exclude all files under dir

graft dir   #include all files under dir
Package: luckleesample
A sample Python projectA sample project that exists as an aid to thePython Packaging User
Guide'sTutorial on Packaging and Distributing
Projects.This project does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.The source for this project is available here.Most of the configuration for a Python project is done in thesetup.pyfile,
an example of which is included in this project. You should edit this file
accordingly to adapt this sample project to your needs.This is the README file for the project.The file should use UTF-8 encoding and can be written usingreStructuredTextormarkdownwith the appropriatekey set. It will be used to generate the project webpage on PyPI and will be
displayed as the project homepage on common code-hosting services, and should be
written for that purpose.Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not a
good idea, although a simple “What's New” section for the most recent version
may be appropriate.
Package: luckstring
luckdog是类似于内置函数split的方法，扩展支持了分割符号忽略大小写特征的分割。使用说明：1） 安装：pip install luckstring2） 执行from luckstring import luckstring
string = "`product_group_id` VARCHAR(64) NULL DEFAULT NULL comment '产品组的ID'"
luckstring.split(string, "COMMENT")注： 为方便后期操作方便可以 把上面的 运行命令放到bat或shell文件中，下次直接双击运行#######################################################################Last update time: 2022-04-01By： 9034.com#######################################################################更新日志：
2022-04-01  v1.0.0  初始化#######################################################################打包步骤## 打包 检查
python setup.py check 
## 打包 生成
python setup.py sdist
## 上传
twine upload dist/*
## 使用
pip install luckstring
## 更新
pip install --upgrade luckstring
## 卸载
pip uninstall -y luckstring#######################################################################MANIFEST.in 配置教程include pat1 pat2 ...   #include all files matching any of the listed patterns

exclude pat1 pat2 ...   #exclude all files matching any of the listed patterns

recursive-include dir pat1 pat2 ...  #include all files under dir matching any of the listed patterns

recursive-exclude dir pat1 pat2 ... #exclude all files under dir matching any of the listed patterns

global-include pat1 pat2 ...    #include all files anywhere in the source tree 
matching — & any of the listed patterns

global-exclude pat1 pat2 ...    #exclude all files anywhere in the source tree matching — & any of the listed patterns

prune dir   #exclude all files under dir

graft dir   #include all files under dir