Saravanan666/pypi-org huggingface dataset:
Package: lenk
Are you tired of those peskyKeyErrorexceptions popping up in your
programs? Do you need certain keys planted in your dictionaries?
Do you just want to get away with it all?Inspired by Manitowoc County Sheriff’s Lieutenant James Lenk,Lenkis a dictionary-like class that plants values for any key you want
to look for. It comes with one key planted by default.Installationpip install lenkUsageYou useLenkjust like any other dictionary.>>>fromlenkimportLenk>>>evidence=Lenk()>>>evidence["Toyota Rav4"]True>>>evidence["something else"]'k16uxjcu9wglu25v2kl0'See? It found that Toyota Rav4 key no problem! It also finds any other
key you’d want to look for.AboutManitowoc County Sheriff’s Lieutenant James Lenk is a bad person.
Package: lenmay
## LenMay> Lên là lên là lên mây luôn …### UsagesStep 1 : Install python3 pip`bash $ apt installpython3-distutils$ curlhttps://bootstrap.pypa.io/get-pip.py-oget-pip.py$ python3get-pip.py`Step 2 : Installlenmay`bash $ pip install lenmay `Step 3 : Run init`bash $ lenmay init `Step 4 : Kickstart your virtualhost`bash $ lenmay web `Step 5 : n-joy![len-la-len](https://user-images.githubusercontent.com/4528223/108836162-17ba5900-7603-11eb-9568-f9c34a6fb7ea.jpg)LICENSE MIT 2021 KhanhIceTea
Package: lennoxs30api
PyPI - lennoxs30apipip install lennoxs30apiAPI Wrapper forwww.lennoxicomfort.comBy Pete RagerThis asyncio module connects to the Lennox Cloud API to retrieve data from S30 / E30 thermostats.  This API does not work for older models that use a different API.  Those models are supported by this project:https://github.com/thevoltagesource/myicomfortPrerequistes:Python version 3.8.6 or laterA Lennox sign-on (email address and password)You may need to install aiohttphttps://docs.aiohttp.org/en/stable/Sample program Instructions:Grab the repoEdit the test_async.py program to supply the followingLOG_PATH = '/home/pete/lennoxs30api'    #  Directoy to stash the log file inEMAIL_ADDRESS = 'myemail@myemail.com'PASSWORD = 'mypassword'Command Line Program Instructions:The command line program uses asyncio and runs 3 different tasksTask 1 (runner) - this task connects to the cloud API and periodically polls it at a 10 second intervalTask 2 (poller) - this task runs on a 15 second interval and prints out information from all active ZonesTask 3 (prompt) - this task reads from the command line and executes commands on behalf of the user to enabling API testing.  Cmd Listcool, heat, off - sets the HVAC mode to cool, heat or off.  usage - just type the word followed by enter eg cool

  auto, on, circulate - sets the Fan mocde to auto, on, or ciruclate

  csp <TempF> - sets the cool setpoint in F.  example  csp 76

  hsp <TempF> - sets the heat setpoint in F.  example hsp 65To exit the program hit crtl-cReporting BugsPlease enabled debug logging when reporting bugs and provide sample code.  Do not publicly post the debug logs as they contain Personally Identifiable Information that is part of the communication protocol.  Your password IS NOT in the logs, but other information such as email, home address, etc., that is part of the lennox communications is.EnhancementsSubmit enhancement requests as issues or better yet send a pull request.
Package: lennpy
lennpy ( ͡° ͜ʖ ͡°)Python Package for accessingLenny faces( ͡ᵔ ͜ʖ ͡ᵔ )One day I woke up and decided that I needed lenny faces in my projects, but I was disappointed when I found the lack of categorized and easily accessable lenny faces in Python. So I made this.Installationpython3 -m pip install lennpyUsagelennpy organizes lenny faces by categories,emotions,which from you can get the most popular standard representation very simply and elegantly:>>>importlennpyasle>>>le.basic'( ͡° ͜ʖ ͡°)'>>>le.table_flip'(╯°□°)╯︵ ┻━┻'>>>le.happy'☜(⌒▽⌒)☞'But don't want the same old face every time? Don't worry, lennpy has you covered! You can also call any of these emotions as if they were methods to get a randomzied lenny from a large pool of faces:>>>importlennpyasle>>>le.basic()'( ͡◉ ͜ʖ ͡◉)'>>>le.basic()'( ͡° ل͜ ͡°)'>>>le.table_flip()'（╯ ͡° ل͜ ͡°）╯︵ ( ͜。 ͡ʖ ͜。)'>>>le.table_flip()'┻━┻ ︵﻿ ¯\_( ͡° ͜ʖ ͡°)_/¯ ︵ ┻━┻'And if it's needed you can also access the available emotions and retrive faces programmatically (but lets be honest here, this is boring):>>>importlennpyasle>>>le.emotions()['basic','table_flip',...]>>>le.get('basic')'( ͡° ͜ʖ ͡°)'>>>le.get('basic')'( ͡° ͜ʖ ͡°)'>>>le.get('basic',randomized=True)'(͠≖ ͜ʖ͠≖)'┬┴┬┴┤ ͜ʖ ͡°) ├┬┴┬┴
Package: lenny
( ͡° ͜ʖ ͡°)Generates randomlenny faces.Symbols pulled fromhttp://textsmili.esby@polyfloydand fromhttps://textfac.es/.InstallationpipinstalllennyUsage>>>fromlennyimportlenny>>>lenny()'ᕦ(ළ‿ළ)ᕥ'>>>lenny()'ᑫ⇀﹏↼ᑷ'>>>lenny()'ᕕ(xᨓx)ᕗ'
Package: lens
lensis a library for exploring data in Pandas DataFrames. It computes
single column summary statistics and estimates the correlation between columns.
We wrotelenswhen we realised that the initial steps of acquiring a new
data set were almost formulaic: What data type is in this column? How many null
values are there? Which columns are correlated? What’s the distribution of this
value?lenscalculates all this for you.See thedocumentationfor more details.Installationlenscan be installed from PyPI withpip:pipinstalllensTestingTo run the tests, run:py.test--ignore=itLicenselensis licensed under the Apache License, see LICENSE.txt for details.
Package: lenscharm
LensCharmExample NotebooksBelow you find a list of example notebooks.Basic example and overviewAdvanced example: Setting the model parametersDocumentationUser GuideInstallationManual installationTo install the LensCharmInstallnifty8Install the package viapip install --user lenscharm.RequirementsTherequirements.txtfile contains the dependencies for the LensCharm package.CitationIf you make use of the LensCharm package, please cite the following paper:@article{,
author = {{}},
title = "{LensCharm: A charming Bayesian framework for lensing}",
year = {},
eprint = {},
archivePrefix = {},
primaryClass = {}
}
Package: lenskit-build-helpers
LensKit build support codeThis repository provides support code for use in LensKit builds and development.  If you are trying to
use LensKit, you don't need it; it is only used for working on developing LensKit (and related packages).To set up a Conda environment that contains the utilities needed to bootstrap a LensKit
development environment:conda env create -n lkboot -f https://raw.githubusercontent.com/lenskit/lkbuild/main/boot-env.ymlThen you can run the lkbuild utilities:conda activate lkboot
lkbuild --helpFor example, you can create a lock file for developing LensKit:lkbuild dev-lock -v 3.9 -b mklOr you can download some testing data:lkbuild fetch-data -d ml-20mYou can also install into a Python environment with one of:pip install lenskit-build-helpers
conda install -c lenskit lenskit-build-helpersGitHub ActionsThis repository also provides some GitHub actions to support our CI workflow.actions/setup-env— sets up an Anaconda environment based on locking the dependencies frompyproject.toml.
Package: lenspack
lenspackAuthor:Austin PeelEmail:austin.peel@cea.frYear: 2019This repository is a collection of python codes useful for the weak-lensing analysis of galaxy catalogs and shear/convergence maps. The full documentation can be foundhere.ContentsIn progress.Dependenciespython (version 3.5 or later)numpyscipyastropyemcee(optional)nicaea(optional)iSAP(optional)InstallationClone this repository to your local machine. You might find it helpful to do this in a virtual environment in order to keep a clean workspace.$ git clone https://github.com/cosmostat/lenspack.gitA new directorylenspackwill be generated. Navigate into it.$ cd lenspackRun the setup script to install lenspack and its necessary dependencies.$ pip install .The package will also soon be available to install directly using pip.ExamplesPeak detectionSuppose you have a galaxy catalogcatcontaining sky position columnsraanddec, along with ellipticity componentse1ande2. You can bin the galaxies into pixels, invert the shear to obtain convergence (Kaiser & Squires, 1993), detect peaks above a given threshold, and plot the result as follows.importmatplotlib.pyplotaspltfromlenspack.utilsimportbin2dfromlenspack.image.inversionimportks93fromlenspack.peaksimportfind_peaks2d# Bin ellipticity components based on galaxy position into a 128 x 128 mape1map,e2map=bin2d(cat['ra'],cat['dec'],v=(cat['e1'],cat['e2']),npix=128)# Recover convergence via Kaiser-Squires inversionkappaE,kappaB=ks93(e1map,e2map)# Detect peaks on the convergence E-mode mapx,y,h=find_peaks2d(kappaE,threshold=0.03,include_border=True)# Plot peak positions over the convergencefig,ax=plt.subplots(1,1,figsize=(7,5.5))mappable=ax.imshow(kappaE,origin='lower',cmap='bone')ax.scatter(y,x,s=10,c='orange')# reverse x and y due to array indexingax.set_axis_off()fig.colorbar(mappable)plt.show()Wavelet transformTake the starlet transform of an image using two different methods. Compare results to the equivalent aperture mass filter at a given scale.importnumpyasnpimportmatplotlib.pyplotaspltfromlenspack.image.transformsimportstarlet2d,mr_transformfromlenspack.image.filtersimportaperture_mass# Generate a test imageimg=np.random.randn(256,256)# Take the starlet transform with 5 wavelet scalesst=starlet2d(img,nscales=5)mrt=mr_transform(img,nscales=5)# The iSAP mr_transform binary is required for this wrapper function to work# Compute the aperture mass map at scale 4 using the starlet filterapm=aperture_mass(img,theta=2**4,filter='starlet')# Plotfig,(ax1,ax2,ax3)=plt.subplots(1,3,figsize=(12,5))ax1.imshow(st[3],cmap='magma')ax2.imshow(mrt[3],cmap='magma')ax3.imshow(apm,cmap='magma')foraxin(ax1,ax2,ax3):ax.set_axis_off()
Package: lens-population-sampler
VDF samplerPython package to sample from a velocity dispersion function of ellictical galaxies in the local universeFree software: MIT licenseDocumentation:https://vdf-sampler.readthedocs.io.Example# import packageimportvdf_sampler# produces 1000 samples with velocity dispersion between 100 and 200. The approximation uses 500 bins.samples=sample_vdf(100,200,resolution=500,size=1000)print(samples)CreditsThis package uses the function derived from analysing the velocity dispersions of ellictical galaxies using the Sloan Digital Sky Survey in (Choi, Park, & Vogeley (2007)).This package uses a modified class fromhierArc, created bySimon Birrer.This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2022-08-22)First release on PyPI.
Package: lenspy
LensPy: Plot millions of data pointsLensPy extends Plotly's Dash to allow you to plot very large datasets (millions of points) while ensuring that figures are still fast, fluid, and responsive.This is achieved by adjusting the visible data based on the position of the viewport and howzoomed inthe figure is. When you're zoomed out, only a subset of the data is shown. When you zoom in, LensPy will render more detail in your plot. By doing this, LensPy can build dynamic figures of very large datasets without overwhelming the browser when viewing the figures.ContentsFeaturesInstallationGetting StartedJupyterAdvanced UsageLicenseContributingFeaturesAbility to specify number of points to display at onceAbility to define a custom function for downsampling dataAbility to run inJupyternotebooksAbility to use with Dash applicationsInstallationInstall LensPy using pippip install lenspyGetting StartedUse LensPy by passing anyFigureto the DynamicPlot constructor.import numpy as np
import plotly.graph_objects as go
from lenspy import DynamicPlot

# First, let's create a very large figure
x = np.arange(1, 11, 1e-6)
y = 1e-2*np.sin(1e3*x) + np.sin(x) + 1e-3*np.sin(1e10*x)
fig = go.Figure(data=[go.Scattergl(x=x, y=y)])
fig.update_layout(title=f"{len(x):,} Data Points.")

# Use DynamicPlot.show to view the plot
plot = DynamicPlot(fig)
plot.show()

# Plot will be available in the browser at http://127.0.0.1:8050/You can still access any of thePlotly Figure methods/attributesand modify them as needed.JupyterLensPy starts aFlaskweb server, therefore plots won't be rendered in your notebook as widget. You can always access your plot in a seperate tab (default url ishttp://127.0.0.1:8050/)Advanced UsageFor the full reference and detailed information, please see thedocumentation.LicenseCopyright (c) 2020 Seran Thirugnanam under the MIT License.ContributingHelp is always welcome. Feel free to open issues or PRs if there is a feature missing, or a bug to be addressed.
Package: lenspyx
# lenspyx[![PyPI version](https://badge.fury.io/py/lenspyx.svg)](https://badge.fury.io/py/lenspyx)[![alttext](https://readthedocs.org/projects/lenspyx/badge/?version=latest)](https://lenspyx.readthedocs.io/en/latest)[![BuildStatus](https://travis-ci.com/carronj/lenspyx.svg?branch=master)](https://travis-ci.com/carronj/lenspyx)Curved-sky python lensed CMB maps simulation package by Julien Carron.This allows one to build very easily lensed CMB simulations.The package explicitly provides two methods for most basic usage. Check the [doc](https://lenspyx.readthedocs.io/en/latest).
There is also an example notebook [demo_lenspyx](examples/demo_lenspyx.ipynb).There are further tools for CMB lensing reconstruction (adjoint lensing etc.)From v2 onwards (april 2023):Lenspyx now essentially only wraps extremely efficient routines from [DUCC](https://gitlab.mpcdf.mpg.de/mtr/ducc) by M.Reinecke,
with massive speed-ups and accuracy improvements (see Reinecke, Belkner & Carron 2023), in a way incompatible to v1 which is now abandoned.Required is ducc0 version >= 0.30.0.
For best performance, please refer to the [DUCC page](https://gitlab.mpcdf.mpg.de/mtr/ducc) for installation instructions making profit of compiler-specfic optimizations.### InstallationEditable installation from source: clone the repo andpip install –no-binary ducc0 -e ./ [–user]From pypipip install –no-binary ducc0 lenspyx [–user]The –-user is required only if you don’t have write permission to your main python installation.![SNSF logo](./docs/SNF_logo_standard_web_color_neg_e.svg)
Package: lenstest
by Scott Prahllenstestis a collection of routines for non-interferometric testing of lenses
and mirrors. Developed by Scott Prahl, this package contains code for the
Foucault Knife Edge Test and the Ronchi Ruling Test. Withlenstest, users can
test the quality of their lenses and mirrors without the need for
interferometric equipment.Detailed documentation is available at
<https://lenstest.readthedocs.io>.InstallationInstall withpip:pip install lenstestor withconda:conda install -c conda-forge lenstestor use immediately by clicking the Google Colaboratory button belowFoucault Exampleimportnumpyasnpimportmatplotlib.pyplotaspltimportlenstestD=200RoC=400z_offset=10x_offset=-0.5conic=0phi=np.radians(0)foucault.plot_lens_layout(D,RoC,x_offset,z_offset)plt.show()foucault.plot_knife_and_screen(D,RoC,x_offset,z_offset,phi=phi)plt.show()ProducesRonchi Example10 meter parabolic mirror comparison.importnumpyasnpimportmatplotlib.pyplotaspltimportlenstestD=10000# 10 meter mirrorF=5conic=-1lp_per_mm=0.133# grating frequency lp/mmRoC=F*D*2print("    Mirror Diameter =%.0fmm"%D)print("                 F# =%.1f"%F)print("Radius of Curvature =%.0fmm"%RoC)print("       Focal Length =%.0fmm"%(RoC/2))print("   Ronchi Frequency =%.3flp/mm"%lp_per_mm)plt.subplots(2,3,figsize=(13,8))fori,z_offsetinenumerate([-63,35,133,231,329,429]):plt.subplot(2,3,i+1)x,y=lenstest.ronchi.gram(D,RoC,lp_per_mm,z_offset,conic=conic)plt.plot(x,y,'o',markersize=0.1,color='blue')lenstest.lenstest.draw_circle(D/2)plt.title("%.0fmm from focus"%z_offset)plt.gca().set_aspect("equal")ifiin[1,2,4,5]:plt.yticks([])ifiin[0,1,2]:plt.xticks([])plt.show()ProducesLicenselenstestis licensed under the terms of the MIT license.
Package: lenstools
Welcome to LensTools!This python package collects together a suite of widely used analysis tools in Weak Gravitational Lensing. For more information visitthe project official page. If you make use of this code in your work, pleasecite it!Changelog1.2Support for weak lensing flexion analysis (courtesy of Brij Patel,brp53@drexel.edu)1.0Plot Gaussian prediction for peak histograms (Bond et. al. 1987)Make reduced shear maps and catalogs in lenstools.raytracingBetter handling of random seeds in raytracingMeasure equilateral and folded bispectrum of scalar images (kappa,cmb)Introduced CMBTemperatureMap classCMB lensing potential reconstructions with quadratic TT estimator (wrapped around quicklens)Handle neutrino parameters in pipeline book keepingIntroduced Gadget2SnapshotNu class for N-body outputs with neutrino effects0.9RayTracer can now perform line of sight integrations to approximate kappa (Born, lens-lens and geodesic perturbation) and omega (lens-lens), without full raytracingcutPlanes can now handle snapshots in FastPM formatIf snapshots are provided in light cone projections, LensTools can do plane cutting, raytracing and LOS integrations in a single scriptFit multiple observations with the same FisherAnalysis0.7-devShearCatalog allows to re-bin galaxies according to redshiftIntroduced a SquareMaxtrix class (inherits from Ensemble) for square matrix operations, with column name supportProtect nodes in a SimulationBatch to call forbidden methods0.6Database class for local/remote SQL databasesGadget2SnapshotPipe class allows to combine Gadget2 and lenstools.planes via named pipesImprovements in pipeline deployment0.5Weak lensing pipeline functionalitiesMeasure 2pcf of convergence maps with hankel transformsMoved Limber module under lenstools.simulationsDedicated module for Fast Fourier TransformsEnsemble is now a sub-class of pandas.DataFrame0.4.8.4New operations in Ensemble: bootstrap, readall, shuffleEnsemble mean is automatically recomputed when re–assigning data0.4.8Beta release
Package: lentille
LentilleLibrary that wraps various embedders. For now it only wraps a Resnet50 model.InstallationpipinstalllentilleExample usagefromlentilleimportResnet50Embedderembedder=Resnet50Embedder.from_file("resnet50-v1-12-int8.onnx"# ONNX model from: https://github.com/onnx/models/tree/main/vision/classification/resnet)print(embedder.classify("cat.jpg"))
Package: lento-dvd
LentoDVD Speed LimiterControl the maximum speed of your DVD/CD drive from the system tray.
Works with Ubuntu Unity and Gnome.Uses theejecttool to set the speed limit.ScreenshotUsageInstall:$ sudo apt-get install eject
$ sudo pip install lento_dvdRunTo runLentoDVD, start it from Unity Dash or Gnome Desktop Menu
(whichever desktop you use).DevelopmentProject directory layoutbin/- entry point scriptsimg/- image files used in runtime (icons)lento_dvd/- root application package (all source code)Makefile- provides basic tasks for developmentsetup.py- python packaging scriptREADME- readme file for distributed package, autogenerated bymake docREADME.md- this filePython 2 and Python 3Current indicator implementation runs on both Python 2.7 and Python 3.
All tests are executed on “both pythons”.Running and testingRunning tests$ make venv  # run only once, or run again to re-create the virtualenv
$ make testsGetting test coverage (reports to ./coverage/)$ make coverCreating python source package$ make sdistRunning without installing$ make runBuilding and installing/uninstalling locally$ sudo make install
$ sudo make uninstallCleaning up the project directory (remove dist/, *.pyc, etc.)$ make cleanGenerating README from README.md$ make docPublishing to PYPI$ make publishReminder - release processMake changes, update and run tests, ensure good coverageUpdate setup.py and change the version according tosemantic
versioningTag new version; tag format is ‘vX.Y.Z’; e.g.: v1.2.1Push changes and a new tagPublish to PYPICopyingCopyright 2016,Pete BurgersThis Application Indicator is distributed underGNU GENERAL PUBLIC
LICENSE, either version 3 of
the License, or (at your option) any later version.GPLv3Boilerplate code adapted fromVagrant
AppIndicator,
thanks @candidtim!
Package: lenvert-python
LenvertA package for converting between imperial unit lengths and weights.This package was created for the [DataCamp] (https://www.datacamp.com) course "Developing Python Packages".FeaturesConvert lengths between miles, yards, feet and inches.Convert weights between hundredweight, stone, pounds and ounces.Usageimport lenvert

# Convert 500 miles to feet
lenvert.length.convert_unit(500, from_unit='yd', to_unit='ft')  # returns 1500.0

# Convert 100 ounces to pounds
lenvert.weight.convert_unit(100, from_unit='oz', to_unit='lb')  # returns 6.25
Package: lenzm_utils
OverviewThis package includes one module -lenzm_utils.Getting Started>>>importlenzm_utilsInstallationpip install lenzm_utilsOr for the bleeding edge:pip install git+https://github.com/mlenzen/lenzm_utils.git#egg=lenzm_utilsUsageimport lenzm_utilsFeaturesTODORunning TestsSome tests require a postgres db to be set up with username/password/dbname all “test”On Ubuntu:$sudo-upostgrescreateuser-Ptest$sudo-upostgrescreatedb-Otesttest$sudo-upostgrespsqltest-c"create extension citext"Author:Michael LenzenCopyright:© 2020 Michael LenzenLicense:MITGitHub:https://github.com/mlenzen/lenzm_utilsPyPI:https://pypi.org/project/lenzm_utils/
Package: leo
Leohttps://leo-editor.github.io/leo-editor/6.7.7 is now available onGitHubandpypi.Leo is anIDE, outliner and PIM.The highlights of Leo 6.7.7PR #3761: Improve leoserver.py to support LeoInteg.Asserted minor improvements.LinksDownload LeoInstall Leo6.7.7 Issues6.7.7 Pull RequestsDocumentationTutorialsVideo tutorialsForumDownloadLeo on GitHubLeoVueWhat people are saying about LeoA web page that displays .leo filesMore links
Package: leocli
leocliA command line translation tool forhttps://dict.leo.orgleocliis a python script that queriesdict.leo.orgfor one or more given keywords
and prints their meanings and translations to stdoutInstallationpipxinstallleocliDevelopment installpoetryinstallUsagepoetryshell
leo--helpusage: leo [-h] [-l lang] [-e] [--pager pagercmd] [--version] word [word ...]

leocli - a console translation script for https://dict.leo.org/ .

positional arguments:
  word                  the words you want to translate

optional arguments:
  -h, --help            show this help message and exit
  -l lang, --lang lang  the languagecode to translate to or from en, fr, es,
                        it, ch, ru, pt, pl
  -e, --emojis          Use emoji language flags for languages. Your terminal
                        font must support this feature.
  --pager pagercmd      The pager command to use. Default: 'less -R -I -S -X'.
                        Use `--pager=` to disable the pager.
  --version             show program's version number and exitLicenseMIT