Saravanan666/pypi-org huggingface dataset:
Package: litchi-wp
litchi_wp 3.0.0Python package to handle litchi csv waypointsExamples:Create Waypoint in your codefromlitchi_wp.waypointimportWaypointfromlitchi_wp.enumsimportActionType,AltitudeModewp=Waypoint(lat=-21.360244,lon=-64.85657,alt=100)# minimal waypoint setupwp.set_altitude(value=100,mode=AltitudeMode.AGL)# set altitude above groundwp.set_speed_ms(value=0.1)# stop movement (0 sets cruise speed, so this is the best we can get)wp.set_action(action_type=ActionType.TILT_CAMERA,param=-90)# action 1: tilt gimbal for nadir shotwp.set_action(action_type=ActionType.STAY_FOR,param=1000)# action 2: wait 1 second to stabilizewp.set_action(action_type=ActionType.TAKE_PHOTO)# action 3: take the photooutput=wp.get_header()# first line for the waypoint file needs to be the headeroutput+=wp.to_line()# adds the waypoint to the outputprint(output)# check the resultlatitude,longitude,altitude(m),heading(deg),curvesize(m),rotationdir,gimbalmode,gimbalpitchangle,actiontype1,actionparam1,actiontype2,actionparam2,actiontype3,actionparam3,actiontype4,actionparam4,actiontype5,actionparam5,actiontype6,actionparam6,actiontype7,actionparam7,actiontype8,actionparam8,actiontype9,actionparam9,actiontype10,actionparam10,actiontype11,actionparam11,actiontype12,actionparam12,actiontype13,actionparam13,actiontype14,actionparam14,actiontype15,actionparam15,altitudemode,speed(m/s),poi_latitude,poi_longitude,poi_altitude(m),poi_altitudemode,photo_timeinterval,photo_distinterval
-21.360244,-64.85657,100,180,0,0,0,0,5,-90,0,1000,1,0,-1,0,-1,0,-1,0,-1,0,-1,0,-1,0,-1,0,-1,0,-1,0,-1,0,-1,0,-1,0,1,0.1,0,0,0,0,-1.0,-1.0Create Waypoints from litchi csv filefromlitchi_wp.waypointimportWaypointfilename='/home/user/file.csv'waypoints=Waypoint.from_file(filename)"""Now waypoints contains a list of all the waypoint objects created from parsing the file"""See the docs for all the options:WaypointActionAltitudeEnumsGimbalPhotoPoi
Package: litds
litdsDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nlitds--fileenv.ymlInstallpipinstall-e.# install from pypipipinstalllitdsnbdev# activate conda environment$condaactivatelitds# make sure the litds package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the litds package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/litds.gitor fromconda$condainstall-cdsm-72litdsor frompypi$pipinstalllitdsDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find
package manager specific guidelines oncondaandpypirespectively.Brief Datasets Demodd=DiamondsDataset()dd.getone()(tensor([[ 0.0491,  0.0015],
         [ 0.1555,  0.3419],
         [-0.3727,  0.3598],
         [ 0.6811,  0.3734],
         [ 0.4492, -0.7379]]),
 tensor([0., 1., 2., 3., 4.]))dd.plot(palette='mako_r')od=OrbitsDataset()od.getone()(tensor([[ 0.0203, -0.2043],
         [-0.3889, -0.1781],
         [ 0.0290,  0.6299],
         [-0.3386,  0.8402],
         [ 0.9571,  0.0337]]),
 tensor([0., 1., 2., 3., 4.]))od.plot(palette='mako_r')eb=EmbryoidBodies2018DataModule(primary='pca',batch_size=8,)eb.setup()EB Loader:   0%|          | 0/126 [00:00<?, ?it/s]

Loading data
Data ready!dl=eb.train_dataloader()eb.train_ds.df[eb.train_ds.df.columns[-5:]].head()<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>d97d98d99d100samples4854-0.633847-0.701649-1.466198-0.381950Day 06-0961210.4327891.089373-0.968371-0.211686Day 06-0976200.0425520.870117-1.264836-1.664296Day 12-15125601.770667-0.5941361.893129-1.064998Day 18-2110336-2.947320-1.0726011.5548070.170369Day 18-21
Package: lite3
lite3It helps to create an sqlite3 database easily and maintainable without MYSQL syntax with just using simple familar python functions with the same names as sqlite3 python builtin module.Installation'''pip install lite3'''Documentation'''https://lite3.herokuapp.com/'''Usage'''python
import lite3db = lite3.lite('customers.db', 'connect', 'cursor')table = 'Common'
cols = ['name', 'gender']db.execute(table, cols)creates a database with a Table name common with two columns'''Change Log0.0.1 (11/02/2021)First Release
Package: liteapi
Lite Framework, Easy Coding, High Performance, No Dependencies, Tested for ProductionFeaturesLite with no dependenciesThe framework built using standard python libraries and does not need third party pre-requisites.Easy CodeThe framework designed to allow different levels of skillsets to use the code and learn it fast.SupportedOur team is committed to review, test and resolve any issues related to the framework interactively. Please don’t hesitate to submit your problem in github’s issue section.RequirementsPython 3.6+InstallationpipinstallliteapiUsagefromliteapiimportliteapi,BaseAPIRequestapp=liteapi()@app.register('/')classrootMethod(BaseAPIRequest):defget(self):return{'message':'Thank you for using liteapi'}app.run()Import the framework usingfromliteapiimportliteapi,BaseAPIRequestCreate an app instance of liteapiapp=liteapi()Note: to change the socket binding you can pass the host and port arguments to liteapi as belowapp=liteapi(host='0.0.0.0',port=8080)Register class for each URI (The class has to be subclass from BaseAPIRequest)@app.register('/')classrootMethod(BaseAPIRequest):Inside your class, define your methods of get, delete, post, putdefget(self):return{'message':'Welcome to liteapi'}Run your instanceapp.run()ExampleThe below example shows different method use cases for liteapi:@app.register('/{tenant:str}')classtenantMethod(BaseAPIRequest):defget(self,tenant):return{'message':'Hello','tenant':tenant,'query':self.request.query_string}defput(self,tenant):return{'method':'Put','tenant':tenant,'json':self.request.json}defpost(self,tenant):return{'method':'Post','tenant':tenant,'json':self.request.json}defdelete(self,tenant):return{'method':'Delete','tenant':tenant,'json':self.request.json}DocumentaionClick Hereto access the documentationLicenseThis project is licensed under the terms of GPL-3.0 license.
Package: litebem
LiteBEMA lightweight, Apache 2.0 distribution of Matthieu Ancellin's Capytaine BEM code.RequirementsConda is recommended for managing your Python distribution, dependencies and environment:https://docs.conda.io/en/latest/miniconda.htmlcurrent development efforts are based on Python 3.9Microsoft Visual Studio is required for linking the fortran   binarieshttps://visualstudio.microsoft.com/downloads/during installation check the box to include"Desktop development with C++"Intel oneAPI HPC toolkit is required for compiling the fortran binaries (you do not need the base kit)https://www.intel.com/content/www/us/en/developer/tools/oneapi/hpc-toolkit-download.htmlinstall to the default file locationcreate"LIB"environment variable to point towards the intel directory for compiler ".lib" filesif oneAPI is installed to the default location, assign the LIB user variable a value of: "C:\Program Files (x86)\Intel\oneAPI\compiler\2022.1.0\windows\compiler\lib\intel64_win"if oneAPI is installed to a different location then adjust the path above as necessaryInstallation for UsersRecommended approach:Open the anaconda powershell and create a new environment for the LiteBEM project (e.g. "liteBemProject")>condacreate--nameliteBemProjectpythonInstall LiteBEM from PyPI by entering the following command within your new environment>condaactivateliteBemProject
>python-mpipinstalllitebemInstallation for DevelopersRecommended approach:Open the anaconda powershell and create a new environment for LiteBEM-related development (e.g. "liteBemDev")>condacreate--nameliteBemDevpythonInstall numpy (numpy's f2py is required to compile Fortran code) within your LiteBEM development environment:>condaactivateliteBemDev
>pipinstallnumpyClone the LiteBEM repo to your preferred location (e.g. "C:/code/")>cdC:/code/
>gitclonehttps://github.com/dav-og/LiteBEM.gitInstall LiteBEM as a developer!>cdLiteBEM
>pipinstall-e.Be sure to check setup.py => install_requires = [...] to ensure that your environment has all required packages installed. You can check your environment's packages using:>condalistIf any packages are missing simply install them using:>pipinstall<packagename>Run TestsMake surepytestis installed in your working environment:(liteBemDev)>condalistif its not installed then do:(liteBemDev)>pipinstallpytestNavigate toLiteBEMand run:(liteBemDev)>pytesttests/unit/preprocessor_unit_tests.py(liteBemDev)>pytesttests/unit/solver_unit_tests.pyTutorialsFor a tutorial on how to use LiteBEM, it is currently recommended that users utilizeCapytaine's documentation, as it remains largely consistent with LiteBEM
Package: litebird-sim
LiteBIRD Simulation FrameworkMain repository of the LiteBIRD Simulation Framework, a set of Python modules to simulate the instruments onboard the LiteBIRD spacecraft.Explore the docs »View Demo·Report Bug·Request FeatureTable of ContentsAbout the ProjectBuilt WithGetting StartedUsageRoadmapContributingLicenseContactHow to cite this codeAbout The ProjectThe LiteBIRD Simulation Framework is being developed for theLiteBIRD collaboration.Built WithLove!Python 3PoetryNumPyAstropyHealpixSphinxNumbaduccGetting StartedRefer to thedocumentationto learn how to install the LiteBIRD simulation framework on your
computer or on a HPC cluster.UsageAn example notebook is avalablehere.The documentation is available online atlitebird-sim.readthedocs.io/en/master/.To create a local copy of the documentation, make sure you ranpoetrywith the flag--extras=docs, then run the following
command:Linux or Mac OS X:./refresh_docs.shWindows:poetry shell
cd docs
make.bat htmlRoadmapSee theopen issuesfor a list of proposed features (and known issues).ContributingIf you are part of the LiteBIRD collaboration and have something that
might fit in this framework, you're encouraged to contact us! Any
contributions you make aregreatly appreciated.ReadCONTRIBUTING.mdFork the projectCreate your feature branch (git checkout -b feature/AmazingFeature)Commit your changes (git commit -m 'Add some AmazingFeature')Push to the Branch (git push origin feature/AmazingFeature)Open a Pull RequestLicenseDistributed under theGPL3 License.ContactLiteBIRD Simulation Team -litebird_pipe@db.ipmu.jpProject Link:https://github.com/litebird/litebird_simHow to cite this codeTODO!
Package: lite-cache
lite-cacheBranchBuild StatusmasterdevelopSimple sqlite key-value storage for Python3.Python3 module for caching data during a program's runtime, with optional persistence.FeaturesProgram specific cache.Simple encoding of data using standardjsonpackage.Optional persistence of data across multiple executions.Useful for keeping some runtime data available to a program after a full exit.ex.raise Exceptionorsys.exit(), etcInstallation (from PyPI, with PIP)lite-cacherequiresPython>= 3.6.If not already installed,install pipfor Python 3Installlite_cache$pip3installlite-cacheUsageTo use in default configuration:Entire cache is in 1 database file,~/.local/litecache/cache.dbTo use in custom configuration:importlite_cacheprogram_cache=lite_cache.LiteCache(name='MyProgramCache',location='~/.local/litecache')# This initializes and creates a new Sqlite3 database file in `location` directory,# named as "`name`.cache".# If directory does not exist, error is raised.This strategy of having unique caches for each program is designed to navigate "same thread" or "single thread" issues with Python & Sqlite3.This would not prevent issues occurring if multiple instances of the same program were launched on the same machine.ie. Executing same Python script in 2 terminal tabs. This would lead to two(2) threads attempting to access one(1) Sqlite3 with samenameDevelopmentThis project usespipenvfor managing virtual-environments and Python3 dependencies  for development and testing.Reference:https://pypi.org/project/pipenv/The standardrequirements.txtis included for installation viasetup.pyTestsUsesunittestsRun all tests fromsetup.pypipenvrunpythonsetup.pytestRun specific testpipenvrunpython-munittesttests/test_main.pyPlansInterface for handling Python+Sqlite3 thread limitations.Data compression optionsLicenseGPLv3
Package: litecli
litecliDocsA command-line client for SQLite databases that has auto-completion and syntax highlighting.InstallationIf you already know how to install python packages, then you can install it via pip:You might need sudo on linux.$ pip install -U litecliThe package is also available on Arch Linux through AUR in two versions:litecliis based the latest release (git tag) andlitecli-gitis based on the master branch of the git repo. You can install them manually or with an AUR helper such asyay:$ yay -S liteclior$ yay -S litecli-gitFor MacOS users, you can also use Homebrew to install it:$ brew install litecliUsage$ litecli --help

Usage: litecli [OPTIONS] [DATABASE]

Examples:
  - litecli sqlite_db_nameA config file is automatically created at~/.config/litecli/configat first launch. For Windows machines a config file is created at~\AppData\Local\dbcli\litecli\configat first launch. See the file itself for a description of all available options.DocsVisit:litecli.com/features
Package: litecoin-requests
Forked from fiatjaf/bitcoin-requests; modified for Litecoin CoreThe simplest Litecoin Core RPC library for when you just want to talk to Litecoin Core.UsageIf you started Litecoin Core like this:litcoind-regtest-rpcuser=user-rpcpassword=passInstantiate thelitcoin_requestsRPC client like this:fromlitcoin_requestsimportLitcoinRPCrpc=LitecoinRPC('http://127.0.0.1:9332, 'user', 'pass')blocks=rpc.generate(101)tx=rpc.sendtoaddress(address,20)Installationpip install litcoin-requests
Package: litecounter
litecounterVery simple counter implemented on top of SQLiteWhy?You can use this to implement a persistent counter. It also uses some SQLite syntax to initialize keys to0when the counter starts on them, just as if you had acollections.defaultdictwhere the default is0.Installationpip install litecounterIMPORTANT: This package uses SQLite'sUPSERTstatment so it needs to run at least with SQLite version 3.24.0 (released 2018-06-04).If you need to run the latest version, you can usepysqlite3.All the litements libraries (including this one) accept either a filename or an already created sqlite connection. Apart from that, if you have pysqlite3 installed it will use that instead of the sqlite3 module from the standard library.ExamplesThe examples are taken from the tests intests.ipynbTEST_1="key_test_1"TEST_2="key_test_2"fromlitecounterimportSQLCountercounter=SQLCounter(":memory:")# Increment from 0 to 20for_inrange(20):counter.incr(TEST_1)assertcounter.count(TEST_1)==20# Decrement 10 (from 20 to 10)for_inrange(10):counter.decr(TEST_1)assertcounter.count(TEST_1)==10# From 0 to -10, then -20.for_inrange(10):counter.decr(TEST_2)assertcounter.count(TEST_2)==-10for_inrange(10):counter.decr(TEST_2)assertcounter.count(TEST_2)==-20# Set fist key to 0.counter.zero(TEST_1)assertcounter.count(TEST_1)==0# Increment the second test key by 100, from -20 to 80.for_inrange(100):counter.incr(TEST_2)assertcounter.count(TEST_2)==80# Delete key worksassertcounter.count(TEST_1)==0counter.delete(TEST_1)assertcounter.count(TEST_1)isNone# When the key does not exist, delete just ignores itcounter.delete("foobar")# Check `__repr__`importrandomforkeyin["foo","bar","baz","foobar","asd",TEST_1]:for_inrange(random.randint(0,10)):counter.incr(key)print(counter)# SQLCounter(dbname=':memory:', items=[('key_test_2', 80), ('foo', 8), ('baz', 5), ('foobar', 6), ('key_test_1', 10)])MetaRicardo Ander-Egg Aguilar –@ricardoanderegg–ricardoanderegg.comgithub.com/polyrandlinkedin.com/in/ricardoandereggDistributed under the MIT license. SeeLICENSEfor more information.ContributingThe only hard rules for the project are:No extra dependencies allowedNo extra files, everything must be inside the main module's.pyfile.Tests must be inside thetests.ipynbnotebook.
Package: litecrypt
OverviewSo I made this library for personal use to secure some of my personal files & hit theconnectfrom time to time.
It provides support for both fast and highly computationally intensive encryption. Also, it includes a database integration system which facilitates the restoration of files to their original state if necessary, and a GUI is also included to obviate the need to write code.The docs can be accessedhere, I made it so I don't forget wtf I was yapping about a couple of months ago, probably not so useful for visitors.InstallationpipinstalllitecryptUsagefromlitecryptimportCryptFile,gen_keykey=gen_key()CryptFile('file_of_any.type',key).encrypt()# the file is now called ==> 'file_of_any.type.cryptThe encryption process isblazingly fastby default, to make it computationally intensiveDo thisfromlitecryptimportCryptFile,gen_keykey=gen_key()CryptFile('anyfile.txt',key=key,intensive_compute=True,iteration_rounds=10000).encrypt()Runningintensive_computewith noiteration_roundssets the rounds to 50 (minimum) by defaultTo decrypt simply run:fromlitecryptimportCryptFilekey='THE_KEY_YOU_USED'CryptFile('anyfile.txt.crypt',key=key).decrypt()For messages:fromlitecryptimportCrypt,gen_keykey=gen_key()encrypted=Crypt('any message',key).encrypt()# can also be a bytes messageprint(encrypted)# Check the return valueDetailsAlgorithm:AES-256 CBCLayout:+-------------+  +--------+  +------------+  +-------------+  +-------------+  +------------------+
|    HMAC     | →|   IV   | →|   Salt     | →|  Pepper     | →| Iterations  | →|     KDF ID     |  →
+-------------+  +--------+  +------------+  +-------------+  +-------------+  +------------------+
                              +------------------+
                              |   Ciphertext    ...
                              +------------------+AES and HMAC keys, each 32 bytes, are derived from the main key (gen_key()) using the chosen KDF with SHA256. Iterations range from 50 to 100,000 the higher they go the more time it takes to compute, that's 4 bytes. IV that's 16, Salt, and Pepper are also 16 byte random values, both mixed with the KDF. The ciphertext size varies, with the crypto process employing PKCS7 padding.Supported DatabasesCurrently, supports MySQL, PostgresSQL and SQLite.Check thedocsfor more info.GUIHere's how it workshttps://github.com/AshGw/litecrypt/assets/126174609/190b6ab8-3f8a-4656-9525-dbaf5e56db5eLicenseLitecrypt is open-source project & licensed under theMIT License.
Package: lite-cryptography
project-templateA lightweight module for simple encryption and decryption of data using passwords.first of allspecifics:writen and owned by: Shahaf Frank-Shapirall the rights are saved for: Shahaf Frank-Shapirprogramming languages: python 3.9.12 (100%)before we startdescription:visit the docs to learn more about this project and how to develop with it.dependencies:opening:
For this is a complex program, which uses a lot of modules, there are required dependencies needed
in order to run the program. keep in mined the program was writen in python 3.9, so any python version lower
than 3.9 might not work properly.install app dependencies by writing the "-r" option to install the requirements
writen in a file, and write the following line in the project directory:pip install -r requirements.txtrun a testrun from windows command line (inside the project directory)run with python by writing to the command line in the project directory:python test.py
Package: litedao
This project is deprecated since the class Database exists in the librarySharedLitedaoIntuitive interaction with SQLite databaseThis project is part of thePyrustic Ecosystem.Installation|Reference|SharedOverviewHere is an example of an interaction with an SQL database:fromlitedaoimportLitedao# Database path (if this file does not exist, it will be created)DATABASE_PATH="/home/alex/litedao_test.db"# SQL code to initialize the databaseINIT_SCRIPT="""\CREATE TABLE friend (username TEXT PRIMARY KEY, email TEXT NOT NULL);CREATE TABLE enemy (username TEXT PRIMARY KEY, email TEXT NOT NULL)"""# Insertion SQL codeINSERTION_SQL="""\INSERT INTO friend (username, email)VALUES (?, ?), (?, ?)"""# Selection SQL codeSELECTION_SQL="SELECT * from friend"definsert_data(litedao):# inserts data in the database then returns a booleanreturnlitedao.edit(INSERTION_SQL,param=("alex","alex@earth.invalid","rustic","rustic@earth.invalid"))defselect_data(litedao):# returns the selectionreturnlitedao.query(SELECTION_SQL)# litedao instancelitedao=Litedao(DATABASE_PATH,init_script=INIT_SCRIPT)# insert data if this database is newly creatediflitedao.is_new:insert_data(litedao)selection=select_data(litedao)tables=litedao.tables()columns=litedao.columns("friend")litedao.close()# if you forget to close Litedao, it will close itself at exitprint(selection)# output: (['username', 'email'], [('alex', 'alex@earth.invalid'), ('rustic', 'rustic@earth.invalid')])print(tables)# output: ['friend', 'enemy']print(columns)# output: [(0, 'username', 'TEXT', 0, None, 1), (1, 'email', 'TEXT', 1, None, 0)]Read thereference!Do you need to store data collections with another simpler paradigm ? CheckShared!Installationpipinstalllitedao