Saravanan666/pypi-org huggingface dataset:
Package: pyembedded
pyembeddedPython library to get data from embedded modules like RFID, GPS, GSM, Raspberry PiNote that some of the hardware like RFID, GPS, GSM can directly be interfaced with Windows or Linux based machine but some of the modules will require Raspberry Pi or other similar embedded devices.PyPi:https://pypi.org/project/pyembedded/Installation:Package can be installed via pip:$ pip3 install pyembeddedVerify if it is installed:$ import pyembedded
$ pyembedded.__version__RFID Usage:Run below basic code to get the rfid idNote: Use port as ‘COM1’, ‘COM2’ etc in case of windows machine. Use port as ‘/dev/ttyUSB0’ in case of linux based devices:$ from pyembedded.rfid_module.rfid import RFID
$ rfid = RFID(port='COM3', baud_rate=9600)
$ print(rfid.get_id())GPS Usage:Run below code to get GPS related dataNote: Use port as ‘COM1’, ‘COM2’ etc in case of windows machine. Use port as ‘/dev/ttyUSB0’ in case of linux based devices:$ from pyembedded.gps_module.gps import GPS
$ gps = GPS(port='COM3', baud_rate=9600)
$ print(gps.get_lat_long())Other methods available:$ get_lat_long()
$ get_time()
$ get_quality_indicator()
$ get_no_of_satellites()
$ get_raw_data()GSM Usage:Run below code to interface with GSM SIMCOM moduleNote: Use port as ‘COM1’, ‘COM2’ etc in case of windows machine. Use port as ‘/dev/ttyUSB0’ in case of linux based devices:$ from pyembedded.gsm_module.gsm import GSM
$ import time
$ phone = GSM(port='COM3', baud_rate=9600)
$ if phone.modem_active():
$     phone.make_call(number='9876543210')
$     time.sleep(4)
$     phone.end_ongoing_call()Other methods available:$ phone.make_miss_call(number='9876543210', timeout=5)
$ phone.get_international_subscriber_identity()
$ phone.get_modem_serial_number()
$ phone.get_modem_revision_number()
$ phone.get_modem_model_no()
$ phone.get_modem_manufacturer()
$ phone.get_signal_strength()
$ phone.send_sms(number="+14691234567", message="Hello World")
$ phone.read_all_sms()
$ phone.read_sms_by_msg_id(msg_id=3)Raspberry Pi Usage:Run below code to get some useful data from Raspberry PiNOTE: Some of the below methods can also run on other linux based os:$ from pyembedded.raspberry_pi_tools.raspberrypi import PI
$ pi = PI()
$ pi.get_ram_info()
$ pi.get_disk_space()
$ pi.get_cpu_usage()
$ pi.get_connected_ip_addr(network='wlan0')
$ pi.get_cpu_temp()
$ pi.get_wifi_status()Change Log1.0 (12/6/2020)First Release1.14 (12/6/2020)Added RFID module2.1 (12/6/2020)Added GPS module3.1 (12/27/2020)Added GSM moduleAdded modem and phone related functionsAdded end ongoing call3.3 (12/28/2020)Added sms functionality in GSM3.4 (1/2/2021)Added Pi tools3.5 (1/2/2021)Added Pi tools
Package: pyembeddedfhir
pyembeddedfhirA simple way to use a 🔥 FHIR server in 🐍 Python integration tests.Free software: MIT licenseDocumentation:https://pyembeddedfhir.readthedocs.io.FeaturesUses Docker to run a FHIR server in a container.Supported implementations:HAPI FHIRserver.Microsoft’sfhir-server.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History1.1.3 (2021-11-07)#11 Improved error handling.1.1.2 (2021-11-07)#16 Renamed the project to pyembeddedfhir.1.1.1 (2021-11-07)#8 Added Microsoft’s fhir-server implementation.1.0.0 (2021-10-30)#1 Added HAPI FHIR implementation.0.2.0 (2021-10-18)Version bumped to bypass an issue with redeploying to PyPI.0.1.0 (2021-10-17)First release on PyPI.
Package: pyembed-jinja2
PyEmbed-Jinja2PyEmbedplugin for rendering embeddings usingJinja2templates.UsageInitialize the plugin like this:renderer = Jinja2Renderer(path)wherepathis the path to a directory containing Jinja2 templates:link.htmlphoto.htmlrich.htmlvideo.htmlIf you don’t supply one of these files, a default embedding will be used
instead.For more information, see thePyEmbedwebsite.CompatibilityPyEmbed-Jinja2 has been tested with Python 2.7, 3.3 and 3.4.InstallationPyEmbed-Jinja2 can be installed using pip:pip install pyembed-jinja2ContributingTo report an issue, request an enhancement, or contribute a patch, go to
the PyEmbed-Jinja2GitHubpage.LicensePyEmbed-Jinja2 is distributed under the MIT license.Copyright (c) 2013 Matt ThomsonPermission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
“Software”), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.Changesv1.1.0, 2014-08-02Upgrade to PyEmbed v1.1.0.v1.0.0, 2014-02-05Initial stable releasev0.7.0, 2014-01-20Changes to tests only.v0.6.0, 2014-01-11Initial release
Package: pyembed-mustache
PyEmbed-MustachePyEmbedplugin for rendering embeddings usingMustachetemplates.UsageInitialize the plugin like this:renderer = MustacheRenderer(path)wherepathis the path to a directory containing Mustache templates:link.mustachephoto.mustacherich.mustachevideo.mustacheIf you don’t supply one of these files, a default embedding will be used
instead.For more information, see thePyEmbedwebsite.CompatibilityPyEmbed-Mustache has been tested with Python 2.7, 3.3 and 3.4.InstallationPyEmbed-Mustache can be installed using pip:pip install pyembed-mustacheContributingTo report an issue, request an enhancement, or contribute a patch, go to
the PyEmbed-MustacheGitHubpage.LicensePyEmbed-Mustache is distributed under the MIT license.Copyright (c) 2013 Matt ThomsonPermission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
“Software”), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.Changesv1.1.0, 2014-08-02Upgrade to PyEmbed v1.1.0.v1.0.0, 2014-02-05Initial stable releasev0.7.0, 2014-01-20Changes to tests only.v0.6.0, 2014-01-05Initial release
Package: pyembed-rst
PyEmbed-RstPython reStructuredText directive for embedding content usingOEmbed.PyEmbed-Rst allows you to embed content in your reStructuredText websites and
documents from a wide range of producers.  You don’t need to configure
anything - the extension automatically discovers how to embed content.UsageInitialize the directive like this:PyEmbedRst().register()You can then embed content by entering a link with the special text.. embed::,
like this:.. embed:: http://www.youtube.com/watch?v=9bZkp7q19f0This will be turned into the following HTML:<iframe width="480" height="270" src="http://www.youtube.com/embed/9bZkp7q19f0?feature=oembed" frameborder="0" allowfullscreen></iframe>For more information, see thePyEmbedwebsite.CompatibilityPyEmbed-Rst has been tested with Python 2.7, 3.3 and 3.4.InstallationPyEmbed-Rst can be installed using pip:pip install pyembed-rstContributingTo report an issue, request an enhancement, or contribute a patch, go to
the PyEmbed-RstGitHubpage.LicensePyEmbed-Rst is distributed under the MIT license.Copyright (c) 2013 Matt Thomson

Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:

The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.Changesv1.1.0, 2014-08-02Upgrade to PyEmbed v1.1.0.v1.0.0, 2014-02-05Initial stable releasev0.7.0, 2014-02-02Initial release
Package: pyembeds-sssa
pyEmbedsSSSA PackagePackage for Introduction to Programming and Machine Learning in PythonInstalling pyEmbedsSSSApip install pyembeds-sssaUSAGEAUTOTESTING ASSIGNMENTfrompyembeds.testing.auto_testingimportrun_and_test# Simple Testdefasgn01_01Hello_world():print('Ciao, mondo!')run_and_test([],["Ciao, mondo!"],asgn01_01Hello_world)TESTING DOWNLOAD FILE FUNCTIONfrompyembeds.data.load_dataimportdonwload_fileurl='https://raw.githubusercontent.com/EMbeDS-education/SNS-IProML2022/main/jupyter/jupyterNotebooks/data/WBCD.csv'donwload_file(url)LOAD CAPYTHONE ASSIGNMENT DATAfrompyembeds.data.load_dataimportload_capythone_datadata=load_capythone_data()reviews=data['reviews']positive_word=data['positive_word']negative_word=data['negative_word']LOAD WORDCLOUD ASSIGNMENT DATAfrompyembeds.data.load_dataimportload_wordcloud_ita_datadata=load_wordcloud_ita_data()text=data['manzoni']stop_words=data['stopwords_italian']VISUALIZATION FUNCTIONfrompyembeds.vis.utilsimportdraw_euclidean_distancedraw_euclidean_distance((20,10),(5,0),(5,20))Course responsible:Andrea Vandin,andrea.vandin@santannapisa.itDaniele Licari,daniele.licari@santannapisa.itDescription:The course introduces students to programming and data analysis, using python as a reference
language.Module 1Introduces students to the fundamental principles of structured programming with basic applications to data processingModule 2Introduces the students to the components of typical data analysis processes and machine learning pipelines.
Package: pyemblib
# pyemblibA module for reading, writing, and using trained word embeddings.## InstallationInstall with pip!`bash pip install pyemblib `## UsageThis package currently supports word embeddings trained by the following packages:[word2vec](https://code.google.com/archive/p/word2vec/)[GloVe](https://nlp.stanford.edu/projects/glove/)### ReadingBoth text-format and binary embedding files are supported.The example below shows reading each format of embedding:`python ## import text embeddings text_embs =pyemblib.read('/tmp/text_embeddings.txt',mode=pyemblib.Mode.Text) ## import binary embeddings bin_embs =pyemblib.read('/tmp/bin_embeddings.bin',mode=pyemblib.Mode.Binary) `Embeddings are read as apyemblib.Embeddingsobject, which inherits from Python’s dictionary class; keys are words, and values are the embedding arrays.To get the word vector for “python”, just use dictionary access:`python vec =embs['python']print(vec) # [ 0.001-0.237... ] `### WritingThe same text and binary modes can be used for writing out embedding files as for reading.`python embs = { 'a' :np.array([0.30.1-0.2]),'b' :np.array([-0.9,-0.2,-0.2])} ## write as text pyemblib.write(embs, '/tmp/text_embeddings.txt', mode=pyemblib.Mode.Text) ## write as binary pyemblib.write(embs, '/tmp/bin_embeddings.bin', mode=pyemblib.Mode.Binary) `## Feedback
Please report any issues you encounter to the [Github Issues page](https://github.com/drgriffis/pyemblib/issues)!
Package: pyemddf
EMD-DF is a sound file format developed in java.
—
Example notebook inside the [pyemddf/docs](https://gitlab.com/ManelPereira/pyemddf/-/tree/master/pyemddf/docs) folderInstall it from [PyPI](https://pypi.org/project/pyemddf/) by usingpip install pyemddfCore project available at: [EMD-DF](https://gitlab.com/alspereira/EMD-DF)
Package: pyemer
PyEmerPython API for Emercoin blockchain.UsagefrompyemerimportEmer# Emer(user, password, host, port)emer=Emer("emccoinrpc","emcpassword")emer.name_show("dns:flibusta.lib").record.valueemer.name_new("some:name","some value",365)emer.name_new("some:name2",b"byte value",365,emer.get_account_address())emer.name_history("some:name")[0].tx.heightemer.get_names_by_type("dns")[0].record.nameemer.get_block_count()# You can call RPC manuallyemer.rpc_connection.signmessage(emer.rpc_connection.getaccountaddress(""),"some message")
Package: pyemerald
pyemeraldPyemerald is a python package which lets you modify save files from Pokemon Emerald (Sapphire, Ruby, Leaf Green and Fire Red to come). It lets you modify Pokemon in your team and on the PC, and lets you modify items on the PC. It can also be used to inspect a Pokemons attributes like EV's (IV's to come).Other and more advanced projects exist e.g.pkHexwhich inspired this project. However, it annoyed me that I was unable to run pkHex on Linux, and thus pyemerald was created.Please make sure to never overwrite your original save file, as this software could accidentially make an invalid save file. You are responsible for using the software correctly.InstallationPyemerald can be installed from pypi with the following command:pip install pyemeraldIt has no dependencies so it should be a simple install.UsageSeveral examples are available in theexamplesfolder. But basically it works by loading an.savfile using aSaveobject, which can then emit aGameobject that is modifiable. Once modification is done, theGameobject is passed back to theSaveobject and saved to a new file (Please always save to a new file, so you don't accidentially delete your current save file!).frompyemerald.saveimportSavefrompyemerald.pokemonimportPCPokemonfrompyemerald.movesimportMovesave=Save.from_file("data/marie_treecko_pokedex_pc.sav")game=save.to_game()# Simple create pokemonflygon=PCPokemon.from_name(name="Flygon",level=48,move_1=Move.from_name("Thunder"),move_2=Move.from_name("Thunder Punch"),move_3=Move.from_name("Ice Beam"),move_4=Move.from_name("Fly"),)# Add Pokemon to user PCgame.add_pc_pokemon(flygon)# Put modification back to the Save Objectsave.update_from_game(game)# Write new Save filesave.to_file("data/emerald.sav")
Package: pyemgpipeline
EMG Signal Processing Pipelinepyemgpipelineis an electromyography (EMG) signal processing pipeline package.This package implements internationally accepted EMG processing conventions
and provides a high-level interface for ensuring user adherence to those conventions,
in terms of (1) processing parameter values, (2) processing steps, and (3) processing step order.The processing steps included in the package are
DC offset removal, bandpass filtering, full wave rectification, linear envelope,
end frame cutting, amplitude normalization, and segmentation.ScopeThis package defines the processing pipeline for both surface EMG and
intramuscular EMG but not for high density EMG.
The EMG recording requires that the minimum sample rate be at least twice the
highest cutoff frequency of the bandpass filter based on the Nyquist theorem.OverviewInpyemgpipeline, classDataProcessingManagerin modulewrappersis
designed as the main wrapper for high-level, guided processing,
and users are encouraged to use it to adhere to accepted EMG processing conventions.
The other classes, methods, and functions are considered as lower level processing
options.The package is organized in modulesprocessors,wrappers, andplots.Moduleprocessorsincludes the base classBaseProcessorof all signal
processors and seven classes for different processing steps:DCOffsetRemover,BandpassFilter,FullWaveRectifier,LinearEnvelope,EndFrameCutter,AmplitudeNormalizer, andSegmenter.Modulewrappersincludes three wrapper classes to facilitate the signal
processing by integrating data and individual processors.
ClassEMGMeasurementworks for data of a single trial,
classEMGMeasurementCollectionworks for data of multiple trials,
and classDataProcessingManageris the high-level, guided processing wrapper
with EMG processing conventions.Moduleplotsincludes
the functionplot_emgto plot EMG signals onmatplotlibfigures
and the classEMGPlotParamsto manage the plot-related parameters.DocumentationThedocumentationdescribes how to use this package, including
package installation, quick start, examples explaining the breadth of the package’s functionality,
and API reference.Community GuidelinesFor contribution, please clone the repository, make changes, and create a pull request.For reporting any issues, please usegithub issues.For support, please contact the authors via their emails
orgithub issues.CitationIf you use this package in your project, please cite this work.
Package: pyemir
This is PyEmir, the data reduction pipeline for EMIR.EMIR is a wide-field, near-infrared, multi-object spectrograph
designed for the Gran telescopio Canarias (GTC).You can installpyemirusing
thereleased code in PyPIor
thedevelopment version in Github.The installation instructions are available in theonline documentationordoc/installation/index.rstin the source distribution.Licensingpyemiris distributed under GNU GPL, either version 3 of the License,
or (at your option) any later version. See the file LICENSE.txt
for details.AuthorsWebpage:https://pyemir.readthedocs.io/en/latest/Maintainers: Sergio Pascualsergiopr@fis.ucm.es, Nicolás Cardielcardiel@ucm.es
Package: pyemit
py-emitlight-weight asynchronous event system, support in-process communication, remote message server (currently redisonly) communication and remote procedure call (RPC).Free software: MIT licenseDocumentation:https://pyemit.readthedocs.io.Featuresasynchronous support.support in-process communicationsupport remote message server (currently redis, aioredis is required)RPC (Remote procedure call)CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-04-23)First release on PyPI.0.3.0 (2020-04-25)RPC feature implementeduse pickle instead of json for serialization for better performance. Currently protocol 4 is used.0.4.0 (2020-04-30)Change signature ofRemote.executetoRemote.invoke0.4.5 (2020-06-15)fixed #10.4.6 (2021-12-28)Fixed that the stop method did not empty hannlers0.4.7 (2021-12-29)Fixed that the stop method did not empty hannlers, then add function error0.4.8 (2021-12-29)Add asynchronous registration0.5.0 (2021-12-30)Update aioredis version to 2.0.1
Package: pyemittance
PyEmittancePyEmittance is a tool for the adaptive measurement of beam emittance (e.g.of an electron beam at OTR/YAG beam profile monitors) using a single quadrupole scan developed at SLAC National Accelerator Laboratory. The Twiss parameters and the 'Bmag' match parameter can also be obtained. It can be used in different beamlines/machines by defining machine-specific configuration files.This tool was designed for robustness during online machine learning optimizations where each measurement needs to be reliable. It is still a work in progress, with version 1.0 to be released soon.For more information, please see the IPAC coneference proceedingsDOI: 10.18429/JACoW-IPAC2022-TUPOST059InstallationClone the repository and run the command below to install:pip install -e .Or install by running:pip install pyemittanceSetting the correct configuration parameters for the machine/simulationFor examples on how to set the correct configuration and how to use the new API, please seeexamples/tutorial.ipynb.CitationsFor citing this work, please use:{@article{Miskovich:2022kqg,
    author = "Miskovich, Sara and Edelen, Auralee and Mayes, Christopher",
    title = "{PyEmittance: A General Python Package for Particle Beam Emittance Measurements with Adaptive Quadrupole Scans}",
    doi = "10.18429/JACoW-IPAC2022-TUPOST059",
    journal = "JACoW",
    volume = "IPAC2022",
    pages = "TUPOST059",
    year = "2022"
}
Package: pyEMLearn
pyEMLearnA computational E&M library written in python, intended for learning the fundamentalsInstallationpyEMLearnis available throughpip:$pip3installpyEMLearn(or justpipif you are on windows, or have aliased yourpython3installation)DevelopmentTo install toward developing this package: fork and download this repo from github, open a terminal in the head directory and run:$python3-mvenvvenv$sourcevenv/bin/activate(venv)$pipinstall-rrequirements.txt(venv)$pythonsetup.pyinstallThis will create a virtual environment, activate it, install the required packages,
then install the current version ofpyEMLearninto your virtual environment.After you have made changes to the source code, re-run the last line to install
your modified version.Creating source packages$python3setup.pysdistbdist_wheelUploading to PyPI$python3-mtwineuploaddist/*Development PhilosophyThis package is really intended as a learning tool, rather than a full computational workhorse. As a result, much of the core code isdeliberatelyinefficient so as to be more closely connected with the theory of the scattering (transfer) matrix methods. There are plenty of other computational E&M libraries which are both more efficient and have more sophisticated features (likeEMpy,EMUstackandRigorous-Couple-Wave-Analysis] to name a few). So, development inpyEMLearnwill always prioritize user-clarity over code-efficiency.AcknowledgementsThe authors would like to thank Dr. Raymond Rumpf (of UTEP) for his extensiveeducational resources, on which this project is principally based.To DoComment Everything . . .Add some descriptive examplesAdd some better examplesRestructure the catalogAdd more materials to the catalogAdd transmittance matrix approachCreatesourceobject, which can produce k-vecs and polarization vecsCreatefieldobject? which can track E?Add Poynting vector functionality tofieldobjectBegin thinking about RCWAFix RCWA, its broke AFV1 To Do, ObsoleteFlesh out interface object with "t" matrixAdd interface object to layers objects (and halfplane objects)Modify utils objects to be more generalChange materials repr functions to NOT return parameters, put that in a "summary" functionFinish Docstring-ingRestructure the materials catalogAdd more asserts to System.initto make sure that transmission layers arn't actually injection layers, or gap layers arn't actually just thickness zero layers, etc.Improve computational efficiency for LHI materials? (using 2c.pdf)Spend some time making all the class variable names consistent in their case/-/_ usageAdd config and license filesGet Setup on PyPiAdd anisotropy functionalityMake some better examples (bragg reflectors)Add parallelization options for parameter sweep calculationsAdd ellipsometric variable supportAdd internal field support