Saravanan666/pypi-org huggingface dataset:
Package: lpmqtt
lpmqtt, like its name implies, is a tool for publish a launchpad event stream
into MQTT. It will publish all the capture events from the lp emails over imap
and publish them to MQTTMQTT Topicslpmqtt will push launchpad events to topics broken by project and event type.
The formula used is:<base topic>/<project>/<bugs, blueprints, or other event type>/<bug number>However only the base topic is a guaranteed field. Depending on the emails sent
by launchpad some of the other fields may not be present. In those cases the
topic will start from the base topic and will use fields moving towards the
right until one is missing.ConfigurationThere are a few required pieces of information to make lpmqtt work properly.
These settings are specified in the config file.IMAPTo configure lpmqtt to listen to your imap server you need to provide 3 pieces
of information in the[imap]sectionhostname- The hostname for the imap server to connect tousername- The username to connect withpassword- The password to useThere are also a number of optional settings you can use depending on the
configuration of the imap server you’re connecting to:use_ssl- Set this toTrueto establish an imaps connection with sslfolder- Specify a mailbox/folder to watch for message from launchpad.If one is not specifiedINBOXwill be useddelete-old- Set this toTrueto have lpmqtt delete messages after itfinishes processing them. By default it will just mark them
as read.MQTTJust as with imap there are a few required options for talking to MQTT, which
is the other axis of communication in lpmqtt. The options for configuring MQTT
communication go in the[mqtt]section. The 2 required options are:hostname- The hostname for the MQTT brokerbase_topic- The base topic name to use for the gerrit eventsThere are also a couple optional settings for communicating with mqtt that you
can set:port- The port to communicate to the MQTT broker on. By default thisis set to 1883, the default MQTT port. This only needs to be set
if your broker uses a non-default port.keepalive- Used to set the keepalive time for connections to the MQTTbroker. By default this is set to 60 seconds.username- Used to set the auth username to connect to the MQTT brokerwith.password- Used to set the auth password to connect to the MQTT brokerwith. A username must be set for this option to be used.
Package: lpod-python
Python library implementing the ISO/IEC 26300 OpenDocument Format standard.This library is the python implementation of the lpOD Project (Languages &
Platforms OpenDocument, definition of a Free Software API implementing the
ISO/IEC 26300 standard).This branch is the ‘current’ branch, aiming to be the next stable version.Maintained branches are:legacy  : compatible with 0.9x versionscurrent : next stable versionmaster  : currently, master = currentThe most recent version of this package is there:https://github.com/lpod/lpod-pythonHow to get the code with git:git clone git://github.com/lpod/lpod-python.git
git checkout currentDocumentation: see the ./documentation/html folder.Some usefull packages for the use of the lpod-python library:Programming recipes for the lpod-python library:https://github.com/lpod/lpod-python-recipesLpod global documentation (currently inaccurate):https://github.com/lpod/lpod-docsAbout the Lpod Project, see:http://lpod-project.netArchitect: Jean-Marie Gouarné <jean-marie.gouarne@arsaperta.com>Coordinator: Luis Belmar-Letelier <luis@itaapy.com>
Package: lppa
lppaCommand line tool to create Launchpad PPAs and push deb source packages to themInstallationpip install lppaUsagelppa ships anlppacommand line application to interact with Launchpad PPAs.
Runlppa --helpfor additional information.Create a new PPATo create a new PPA, runlppa create PPA_NAME [all|arch, ...]where arch is a Launchpad processor (you can pass multiple architectures here)
orallto enable all available architectures.The currently available Launchpad processors areamd64arm64s390xppc64elarmhfarmeli386powerpcDelete an existing PPAlppa delete PPA_NAMEList user's PPAslppa listThis will print a list with the names of the user's available PPAsFetch PPA informationOften, you may want to retrieve an URL for a PPA packages page or quickly fetch
a dput command to upload packages to a PPA. That can be achieved through theinfocommand.lppa info PPA_NAMEMoreover, passing the-voption to the info command will also display the
architectures for which the PPA can build packages.DevelopmentRunmake develto set the development environment up (a python virtual
environment is recommended).Runmake checkto run the test suite and ensure the development environment
is up to date.You can usemake coverageto ensure code coverage is not drastically reduced
by new changes (if proposing changes, try to write some tests for them).For instance, a complete bootstrap script would look like:# apt install -y python3-virtualenv python3-virtualenvwrapper
$ mkvirtualenv lppa
$ workon lppa
$ make devel
$ make checkReleasingChangelppa/__init__.pyto set the version to be publishedCreate a new git tag for the new versionRunmake publishto build a new version and push it to PyPIChangelppa/__init__.pyto set the version to the next development version
Package: lppydsmc-taltos
LPPy-DSMCLaunch unit test firstNOT UP TO DATE - won't workpython-munittestdiscoverInstalling the environmentconda create --name lpp python=3.9 pandas numpy matplotlib tqdm notebook jupyterlab numexpr pytables seabornTo run the notebooks, you will needipymplwhich allows interacting withmatplotlibplots insidejupyter lab. If you do not want to install it, simply replace%matplotlib widgetby either%matplotlib notebookforjupyter notebookor%matplotlib inlineforjupyter lab.Running a simulationYou can use themain.ipynbnotebook to launch easily a first simulation and then you can analyze it using theanalysis.ipynbnotebook.
Package: lprettytable
Metadata-Version: 1.0
Name: lprettytable
Version: 0.5
Summary: A simple Python library for easily displaying tabular data in a visually appealing ASCII table format
Home-page:https://github.com/cloudnull/lprettytableAuthor: Luke Maurits
Author-email:luke@maurits.id.auMaintainer: Kevin Carter
Maintainer-email:kevin.carter@rackspace.comLicense:http://www.luke.maurits.id.au/software/bsdlicense.txt
Package: lpr-pkg
IntroductionThis repo serves as a Model release template repo. This includes everything from onnx conversion up to model release into production with all nessasry configs.Getting StartedTo get started you need to fork this repo, and start going through it and fitting it to your use case as described below.MakefileDependency managementConfigsPackage codeOnnx conversionTrt conversionHandlersTestingFlask app1. MakefileThe makefile is the interface where developers interact with to perform any task. Below is the description of each command:download-saved-model: Download artifacts stored on mlflow at a certain epoch. Make sure to fill configs/config.yamldownload-registered-model: Pull artifacts from model registry. Pass DEST as directory to store in. Make sure to fill configs/config.yamlconvert-to-onnx: Run convert to onnx script.convert-trt: build & run container that performs trt
conversion and yeild to artifacts/trt_converted. Pass FP(floating point) BS(batch size) DEVICE(gpu device) ONNX_PATH(path to onnx weights)trt-exec: command to be executed from inside the trt container, perform the conversion and copies the model to outside containerpredict-onnx: predict using onnx weights. Pass DATA_DIR(directory of data to be predicted) ONNX_PATH(path to onnx weights) CONFIG_PATH(Model config path) OUTPUT(output path directory)predict-triton: predict by sending to a hosted triton server. Pass DATA_DIR(directory of data to be predicted) IP(ip of server) PORT(port of triton server) MODEL_NAME(model name on triton) CONFIG_PATH(Model config path) OUTPUT(output path directory)evaluate: evaluate predicted results and write out metrics. Pass MODEL_PREDS(model predictions directory) GT(ground truth directory) OUTPUT(output path)python-unittest: Run python tests defined.bash-unittest: Run defined bash tests.quick-host-onnx: setup triton folder structure by copying nessasarry files, then hosting a triton server container. Pass ONNX_PATHquick-host-trt: setup triton folder structure by copying nessasarry files, then hosting a triton server container. Pass FP(floating point) BS(batch size) DEVICE(gpu device)host-endpoint: preform quick-host-trt and build and start flask container. Pass FP(floating point) BS(batch size) DEVICE(gpu device)setup-flask-app: command to be executed from inside the flask container.push-model: push model to Model registry.build-publish-pypi: build package folder into a pypi package and push the package to registry.2. Dependency Management
Package: lps
Takes an image, printed height or width (in mm) and page size then
splits image across multiple pages with alignment marks and generates a
PDF.It is intended for printing projections exported as SVGs from Openscad.For the image it supports anything that Pillow supports, as well as SVGs
thanks to CairoSVG.PDF generation is done by ReportLab.$ lps -h
usage: lps [-h] (--width WIDTH | --height HEIGHT) [--page_size PAGE_SIZE]
           [--overlap OVERLAP] [--margins MARGINS] [--outfile OUTFILE]
           [--svg_start_scale SVG_START_SCALE]
           image_file

positional arguments:
  image_file            Image to parse

optional arguments:
  -h, --help            show this help message and exit
  --width WIDTH         Width of image in millimeters
  --height HEIGHT       Height of image in millimeters
  --page_size PAGE_SIZE
                        Page size, e.g. a3, a4
  --overlap OVERLAP     Print overlap in mm
  --margins MARGINS     Print margins in mm
  --outfile OUTFILE     Filename to save pdf to
  --svg_start_scale SVG_START_SCALE
                        When using SVG, this is the largest scale factor to
                        attempt to generate an image

$ lps --width 970 --page_size a3 --overlap 20 wrap.svg
Loading Image
Trying to generate raster image of svg at 3x scale
The image will not fit on a single page
Calculating crop list
This will require 3 pages
Chunking image
Generating PDFLicensed underMIT License
Package: lps22hh
LPS22HH Pico DriverMicropython library for the ST LPS22HH and the LPS27HH pressure sensorOverviewThe LPS22HH and LPS27HH sensors are high-resolution digital output pressure sensors manufactured by STMicroelectronics.
This driver enables seamless integration of the sensors with the Raspberry Pi Pico.FeaturesInterface to communicate with the LPS22HH and LPS27HH pressure sensor.Reading of pressure and temperature valuesConfiguration of registers via dedicated functionsCommunication via SPI (I2C not implemented yet)Designed to be compatible with the Raspberry Pi Pico running on Micropython. Other boards not testedInstallationUsepip(seePython Package Index)>pipinstalllps22hhorUsemip(see MicroPythonPackage management):>mpremotemipinstallgithub:cbraissant/lps22hh-pico-driverGetting StartedfrommachineimportSPI,Pinfromlps22hhimportLPS22HH# Create a new SPI device, and assign the pins corresponding to your devicecs_pin=Pin(1,Pin.OUT)spi=SPI(0,baudrate=1000000,firstbit=SPI.MSB,sck=Pin(2),mosi=Pin(3),miso=Pin(0))# Create a new instance of the LPS22HH sensorsensor=LPS22HH(spi,cs_pin)# By default, the device is in power-down mode and the ODR need to be changed# for the device to take continuous measurementssensor.data_rate=200# The Block Data Update (BDU) is used to inhibit the update of the output# registers until all output registers parts are read, to avoids reading values# from different sample timessensor.block_data_update=1whileTrue:ifsensor.new_pressure_data:print(sensor.pressure)TODOFIFO functionalitiesInterruptsI2C, I3C communicationsContributingContributions to this project are welcome. If you find any issues, have suggestions for improvements, or want to add new features, feel free to open an issue or submit a pull request.LicenseThis project is licensed under theMIT License. Feel free to use, modify, and distribute the code in accordance with the terms of the license.
Package: lps28
IntroductionLPS28 pressure sensor drive for CircuitPythonDependenciesThis driver depends on:Adafruit CircuitPythonBus DeviceRegisterPlease ensure all dependencies are available on the CircuitPython filesystem.
This is easily achieved by downloadingthe Community Bundle library and driver bundleor individual libraries can be installed usingcircup.Installing from PyPIOn supported GNU/Linux systems like the Raspberry Pi, you can install the driver locallyfrom
PyPI.
To install for current user:pip3installcircuitpython-lps28To install system-wide (this may be required in some cases):sudopip3installcircuitpython-lps28To install in a virtual environment in your current project:mkdirproject-name&&cdproject-namepython3-mvenv.venvsource.env/bin/activatepip3installcircuitpython-lps28Installing to a Connected CircuitPython Device with CircupMake sure that you havecircupinstalled in your Python environment.
Install it with the following command if necessary:pip3installcircupWithcircupinstalled and your CircuitPython device connected use the
following command to install:circupinstalllps28Or the following command to update an existing version:circupupdateUsage ExampleTake a look at the examples directoryDocumentationAPI documentation for this library can be found onRead the Docs.ContributingContributions are welcome! Please read ourCode of Conductbefore contributing to help this project stay welcoming.
Package: lpsd
Python 3 LPSD algorithmOverviewThis repository contains a Python 3 implementation of the LPSD algorithm.
The implementation is similiar to the LPSD implementation in the Matlab package LTPDA.
The core of the algorithm can be run as Python 3 or as (faster) C code.
Both deliver thesame results.
To run the C core the file ltpda_dft.c has to be compiled to a shared library.InstallationInstall directly with pip:pipinstalllpsdUsageFully working examples can be found in/doc/examples.With a DataFrameRecommended interface, direct usage of aDataFrameimportpandasaspdfromlpsdimportlpsd# read time seriesdata=pd.read_csv("time_series.csv.gz",index_col=0)# select column and calculatespectrum=lpsd(data["column"])# plot PSDspectrum["psd"].plot(logx=True,logy=True)Using numpy arraysUse the traditional methodlpsd_trad, which uses simple numpy arrays.ReferencesImproved spectrum estimation from digitized time series on a logarithmic frequency axisAuthors: Michael Tröbs and Gerhard HeinzelSpectrum and spectral density estimation by the Discrete Fourier transform (DFT), including a comprehensive list of window functions and some new flat-top windowsAuthors: Gerhard Heinzel, Albrecht Rüdiger and Roland SchillingMATLAB Toolbox LTPDAAuthor:  Martin Hewitson
Package: lpsds
fast-dsHelper functions for data science projectsCommon tools for data science projects.You must set the following environment variables:LPSDS_HANDLERThis variable defines which file handler to use. It can have 2 values:LocalFileHandler: for files located in your local machine.S3FileHandler: for files located in an S3 bucket. You must have your AWS access tokens properly set for that.LPSDS_BUCKETA base directory (if using LocalFileHandler) or the S3 bucket (if using S3FileHandler) that will be used as base point for input and output operations. The value should not have "S3://" in case it is a S3 bucket. Just the bucket name will do.
Package: lp-show-my-bugs
Launchpad show my bugs======================Console utility that displays your current bug list from Launchpad.netHow to use==========# InstallationUsing pip```shell$ pip install lp-show-my-bugs```Using pip + github```shell$ pip install git+https://github.com/niedbalski/lp-show-my-bugs```# Usage## Using the ClIBasic usage:```bash$ lp-show-my-bugs --author="niedbalski" --project="any-project" --sort_by="date_created:asc"```Limiting results:```bash$ lp-show-my-bugs --author="niedbalski" --project="any-project" --sort_by="date_created:asc --limit=10"```The output will looks like:![Output](https://raw.github.com/niedbalski/lp-show-my-bugs/master/images/output.png)## Programmatically```pythonfrom lp_show_my_bugs import LaunchpadShowMyBugs#specify the authorlp = LaunchpadShowMyBugs('niedbalski')#add filters, (multiple supported)lp.add_filter('bug_target_name', 'any-project')#sort by date_created in descending orderlp.sort_by('date_created', 'desc')#fetch the assigned bugsbugs = lp.fetch()for bug in bugs:print bug.date_created, bug.title```=======lp-show-my-bugs===============Console client for displaying your Launchpad.net bugs
Package: lpsn
LPSN APINew in v1.0.0: Better error handling and new methodflex_search()Using the LPSN API requires registration. Registration is free but the usage of LPSN data is only permitted when in compliance with the LPSN copyright. Seethe LPSN copyright noticefor details.For questions, requests and comments regarding the LPSN API, please use theLPSN contact form.Please registerhere.The Python package can be initialized using your login credentials:importlpsnclient=lpsn.LpsnClient('name@mail.example','password')# the prepare method fetches all LPSN-IDs matching your query# and returns the number of IDs foundcount=client.search(taxon_name='Sulfolobus',correct_name='yes')print(count,'entries found.')# the retrieve method lets you iterate over all results# and returns the full entry as dict# Entries can be further filtered using a list of keys (e.g. ['keywords'])forentryinclient.retrieve():print(entry)Example queries:You can use IDs to query LPSN as describedhere. Note that when using the parameterid, all other parameters are ignored.# Search by LPSN-IDs (either semicolon separated or as list):query={"id":520424}query={"id":"520424;4948;17724"}query={"id":[520424,4948,17724]}# run queryclient.search(**query)Or you can use all the advanced search parameters that are describedhere.Note that dashes (-) are replaced by underscores when used as python parameters.# Example looking for validly published names of species in the genus Escherichia that have risk group 1:client.search(taxon_name='Escherichia',category='species',riskgroup='1',validly_published='yes')# The same example using a Python dictionary:query={'taxon-name':'Escherichia','category':'species','riskgroup':'1','validly-published':'yes'}client.search(**query)New in v1.0: Flexible searchTheflexible searchhas been implemented in v1.0.0.# Example looking for all entries with a basonym id that has been retreived by a previous fetch:client.flex_search(search={"basonym_id":4370},negate=False)forentryinclient.retrieve():print(entry)FilteringResults from theretrieveMethod of both clients can be further filtered. The result contains a list of matched keyword dicts:result=client.retrieve(filter=["full_name","lpsn_taxonomic_status"])print({k:vforxinresultfork,vinx.items()})The printed result will look like this:{782310:[{'full_name':'Sulfolobus acidocaldarius'},{'lpsn_taxonomic_status':'correct name'}],782311:[{'full_name':'Sulfolobus brierleyi'},{'lpsn_taxonomic_status':'synonym'}],782312:[{'full_name':'Sulfolobus hakonensis'},{'lpsn_taxonomic_status':'synonym'}],782313:[{'full_name':'Sulfolobus metallicus'},{'lpsn_taxonomic_status':'synonym'}],...Known issuesThis package depends onpython-keycloakfor authorization and login handling. However, python-keycloak seems to have issues with older versions of requests and urllib3. See the related issue ongithub. This might lead to the following error when trying to access the API:AttributeError:'Retry'objecthasnoattribute'allowed_methods'You might be able to resolve this issue by updating the mentioned libraries, e.g. via pip:pipinstallrequests>=2.25.1urllib3>=1.26.5
Package: lpsolvers
LP Solvers for PythonWrapper around Linear Programming (LP) solvers in Python, with a unified interface.InstallationTo install the library and all available LP solvers at the same time:$pipinstalllpsolvers[open_source_solvers]To install the library only, assuming LP solvers are installed separately:pip install lpsolvers.UsageThe functionsolve_lpis called with thesolverkeyword argument to select the backend solver. The linear program it solves is, in standard form:$$
\begin{split}
\begin{array}{ll}
\mbox{minimize} &
c^T x \
\mbox{subject to}
& G x \leq h \
& A x = b
\end{array}
\end{split}
$$Vector inequalities are taken coordinate by coordinate.ExampleTo solve a linear program, build the matrices that define it and call thesolve_lpfunction:fromnumpyimportarrayfromlpsolversimportsolve_lpc=array([1.,2.,3.])G=array([[1.,2.,-1.],[2.,0.,1.],[1.,2.,1.],[-1.,-1.,-1.]])h=array([4.,1.,3.,2.])x=solve_lp(c,G,h,solver="cvxopt")# select solver hereprint(f"LP solution:{x=}")This example outputs the solution[2.2, -0.8, -3.4].SolversThe list of supported solvers currently includes:cddCVXOPTCVXPY(interface)PDLPProxQP
Package: lptrack
LPTrackLavaPlayer encoded track encoder and decoder.IntroductionLPTrack is a small library which allows you to interpret the encoded
track data used by LavaPlayer.This is useful when you're dealing with standalone LavaLink instances
likeLavalinkandAndesite,
because it allows you to interpret the track data directly.InstallationFrom PyPIpipinstalllptrackUsageimportlptracktrack=lptrack.Track(version=2,source=lptrack.Youtube(),info=lptrack.TrackInfo(title="A song",author="Some random artist",duration=120,# duration is in seconds!identifier="dQw4w9WgXcQ",is_stream=False,),)encoded=lptrack.encode(track)print(encoded)# b'QAAARQIABkEgc29uZwASU29tZSByYW5kb20gYXJ0aXN0AAAAAAAB1MAAC2RRdzR3OVdnWGNRAAAAB3lvdXR1YmUAAAAAAAAAAA=='decoded=lptrack.decode(encoded)assertdecoded==encodedObligatory rant about CESU-8Without going into too much detail, LavaPlayer (or Java, to be more
specific) uses a special encoding for strings calledMUTF-8which in turn is based onCESU-8.
Characters from theBMP(which contains pretty much all characters from modern languages) are
encoded like normal UTF-8. But special characters like
emojis will be encoded in an incompatible manner.While lptrack doesn't force you to use it, it's strongly recommended to
haveftfyinstalled.
It allows lptrack to properly decode MUTF-8 encoded strings. If ftfy
isn't installed lptrack will treat the strings as UTF-8, but allows
surrogates. Note that it doesn't parse the surrogates properly (i.e. it
will look like a mess), but it will include them in the re-encoded track
data.ftfy is listed as a dependency of lptrack, so unless you really don't
want it, you'll enjoy its benefits.lptrack itself doesn't produce CESU-8 strings, so it's possible that
the re-encoded track data differs from the original track data.It's possible to manually set the desired codec using the
keyword-argumentstring_codecwhich accepts alptrack.strcodec.Codecinstance. The following values are pre-defined:lptrack.strcodec.UTF8: Allows surrogates but doesn't parse them
properly. Should be used if re-encoded track data needs to be equal
to the input.lptrack.strcodec.MUTF8: Codec handling CESU-8. Requires ftfy to
work.lptrack.strcodec.DEFAULT: MUTF8 if ftfy is installed, UTF8 otherwise.
This codec is used by default.lptrack.strcodec.UTF8STRICT: Same as UTF8 but rejects surrogates
outright.