Saravanan666/pypi-org huggingface dataset:
Package: pydeck
pydeck: Large-scale interactive data visualization in PythonThe pydeck library is a set of Python bindings for making spatial visualizations withdeck.gl,
optimized for a Jupyter environment. To get started,see the documentation.To install pydeck, see the instructions here.Forinteractive demos, click the binder logo below:Sample codeThe following code renders a visualization similar to the one above in a Jupyter notebook:importpydeckaspdk# 2014 locations of car accidents in the UKUK_ACCIDENTS_DATA=('https://raw.githubusercontent.com/uber-common/''deck.gl-data/master/examples/3d-heatmap/heatmap-data.csv')# Define a layer to display on a maplayer=pdk.Layer('HexagonLayer',UK_ACCIDENTS_DATA,get_position=['lng','lat'],auto_highlight=True,elevation_scale=50,pickable=True,elevation_range=[0,3000],extruded=True,coverage=1)# Set the viewport locationview_state=pdk.ViewState(longitude=-1.415,latitude=52.2323,zoom=6,min_zoom=5,max_zoom=15,pitch=40.5,bearing=-27.36)# Renderr=pdk.Deck(layers=[layer],initial_view_state=view_state)r.to_html('demo.html')If you're developing outside a Jupyter environment, you can run:r.to_html('demo.html',notebook_display=False)See the gallery for more examples.Issues and contributingIf you encounter an issue, file it in thedeck.gl issues pageand include your browser's console output, if any.If you'd like to contribute to pydeck, please follow thedeck.gl contribution guidelinesand thepydeck development installation instructions.
Package: pydeck-carto
pydeck-cartoPydeckwrapper for use withCARTO.Installpipinstallpydeck-cartoThis also ensurespydeckis installed. If you haven't previously enabled pydeck to be used with Jupyter, followits instructionsto install.Installing from sourcegitclonehttps://github.com/visgl/deck.glcddeck.gl/bindings/pydeck-carto
pipinstall.Usageimportpydeckaspdkimportpydeck_cartoaspdkcfromcarto_authimportCartoAuth# Authentication with CARTOcarto_auth=CartoAuth.from_oauth()# Register CartoLayer in pydeckpdkc.register_carto_layer()# Render CartoLayer in pydecklayer=pdk.Layer("CartoLayer",data="SELECT geom, name FROM carto-demo-data.demo_tables.airports",type_=pdkc.MapType.QUERY,connection=pdkc.CartoConnection.CARTO_DW,credentials=pdkc.get_layer_credentials(carto_auth),get_fill_color=[238,77,90],point_radius_min_pixels=2.5,pickable=True,)view_state=pdk.ViewState(latitude=0,longitude=0,zoom=1)pdk.Deck(layer,map_style=pdk.map_styles.ROAD,initial_view_state=view_state)For more information, check theexamplessection and thedocumentation.DevelopmentMake commands:init: create the environment and install dependencieslint: run linter (black + flake8)test: run tests (pytest)publish-pypi: publish package in pypi.orgpublish-test-pypi: publish package in test.pypi.orgclean: remove the environmentContributorsJesús ArroyoÓscar Ramírez
Package: pydeck-earthengine-layers
pydeck-earthengine-layersPydeck wrapper for use with Google Earth EngineInstallpipinstallpydeck-earthengine-layersThis also ensurespydeckis installed. If you haven't
previously enabled pydeck to be used with Jupyter, followits
instructionsto install.UsingFor an example, see theexamples/Introduction.ipynbJupyter Notebook.Release notesTo release, bump the version by running:bumpversionpatch
//or
bumpversionminorThen create a dist bundle with:pythonsetup.pysdistThen upload to PyPI withtwineuploaddist/pydeck-earthengine-layers-0.1.0.tar.gzreplacing with the current version number.ChangelogThis is the Changelog for the Pythonpydeck_earthengine_layerspackage.
There's a separate "What's New" page that covers JavaScript changes.1.2.1 (2020-09-10)Bump JavaScript bundle used by pydeck to1.2.1. This in turn bumps theearthengine-apidependency to^0.1.234.1.2.0 (2020-08-19)NewEarthEngineTerrainLayerexposed through Pydeck. Allows for visualizing EarthEngineImageobjects over 3D terrainReduced positional arguments. For theEarthEngineLayer, onlyee_objectandvis_paramsmay be positional arguments; all others must be keyword arguments. For theEarthEngineTerrainLayer, onlyee_object,ee_terrain_object, andvis_paramsmay be positional arguments; all others must be keyword arguments.Various JavaScript-side improvements, which trickle down to Pydeck. SeeWhat's Newfor more information.1.1.0Skipped to maintain identical versions as JS bundle1.0.1 (2020-08-06)Pin JS bundle used by pydeck to1.0.0, since1.1.0upgrades the TileLayer to deck.gl 8.2 and is currently broken.1.0.0 (2020-06-05)Release in conjunction with NPM 1.0 release.0.2.2 (2020-06-05)Update Python module to point tobetaNPM module via unpkg for now0.2.1 (2020-06-04)Update Python module to point to released NPM module via unpkg, instead of serving directly from Github. #770.2.0 (2020-05-26)Setvis_paramsas the second positional argument #56Use a minified bundle #51Option to set a custom EE Layer bundle url #310.1.1 (2020-04-27)Includerequirements.txtandrequirements_dev.txtinMANIFEST.into fix install.0.1.0 (2020-04-23)First release on PyPI.
Package: pydeck-grid
pydeck-gridPydeck layers for gridded dataFree software: MIT licenseDocumentation:https://pydeck-grid.readthedocs.io.FeaturesPydeck layers for gridded dataLayers for pcolor, vector particle flows, image overlays and contoursUse xarray datasets as input dataHistory0.1.0 (2023-04-20)First release on PyPI.0.1.2 (2023-05-01)Revise docs
Package: pydecklib
pydecklibA deck of cardsInstallation$pipinstallpydecklibUsagepydecklibcan be used to use a deck of cards in a game context.frompydecklib.deckimportDeckdeck=Deck()deck.shuffle()card=deck.draw()ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepydecklibwas created by amaurylekens. It is licensed under the terms of the MIT license.Creditspydecklibwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pydeck-overlays
pydeck-overlaysPydeck layers for gridded dataFree software: MIT licenseDocumentation:https://pydeck-overlays.readthedocs.io.FeaturesPydeck layers for gridded dataLayers for pcolor, vector particle flows, image overlayss and contoursUse xarray datasets as input dataHistory0.1.0 (2023-04-20)First release on PyPI.0.1.2 (2023-05-01)Revise docs
Package: pydeclares
PyDeclaresThis library provides a simple API for encoding and decoding declared classes to and from JSON, XML, FORM-DATA or QueryString.It's very easy to get started.Quickstartpip install pydeclaresfrompydeclaresimportvar,DeclaredclassPerson(Declared):name=var(str)age=var(int)# decode json stringdata='{"name": "Tom", "age": 18}'person=Person.from_json(data)assertperson.name=="Tom"assertperson.age==18# you can encode to xml after decode json stringresult=person.to_xml()assertresult=='<person><name>Tom</name><age>18</age></person>'# or form-dataresult=person.to_form_data()assertresult=="name=Tom&age=18"# or query stringperson=Person(name="tom@a",age=18)result=person.to_query_string()assertresult=="name=tom%40a&age=18"
Package: pydeco
PyDecoThis package enables to decorate any specified class methods with a passed decorator.
The resulting wrapped class ispicklable.DocumentationPyDeco documentationis available online.Installing PyDecoTo install the latest stable version of PyDeco, you can use pip in a terminal:pipinstall-UpydecoSource codeYou can check the latest sources with the command:gitclonehttps://github.com/paulroujansky/pydeco.gitContributingTo learn more about making a contribution to PyDeco, please see theContributing guide.LicenseThis software is licensed under theMIT license.© 2019 Paul Roujansky.
Package: pydecoder
PyDecoderA XML, JSON,… decode libraryFree software: BSD licenseDocumentation:https://pydecoder.readthedocs.io.FeaturesDecode and validate values from XML and JSON.InstallTo install PyDecoder, run this command in your terminal:$pipinstallpydecoderExample>>>frompydecoder.fieldsimportrequired,optional>>>frompydecoder.jsonimportto_int,to_string,decode# Define data>>>data={'foo':'Text','bar':1}# Describe data>>>decoders=[...required('foo',to_string),...required('bar',to_int),...optional('baz',to_int,-5),...]# Decode/verify data>>>decode(lambdax:x,decoders,data)Result(status='Ok',value=['Text',1,-5])CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2017-05-21)First release on PyPI.
Package: pydecomp
pydecompA Python implementation ofDecompUtilfor fast convex decomposition of obstacle-free spaces.QuickstartInstall dependencies withsudo apt-get install libcdd-dev libblas3 libblas-dev liblapack3 liblapack-dev gfortranand (in a virtual environment) install the package withpip install -i https://test.pypi.org/pypi/ --extra-index-url https://pypi.org/simple pydecomp==0.0.4UsageConvex decomposition of free space from occupancy grid mapGiven an occupancy grid map and a pieciwise linear path, the package returns a convex decomposition of the free space. The free space is represented by a collection of convex sets, whose halspace representation fulfillsAx-b<0. The package returns the matrixesAandbfor each convex set. The matrixAis an x 3matrix andbis an x 1vector, wherenis the number of planes in the halfspace.To check a script to perform a convex decomposition out of a given occupancy grid map, seethis filefor a planar (2D) case orthis filefor a spatial (3D) case. We provide two exemplary maps (forest and office), which you can select by modifyingthis line.Forest - 2DOffice - 2DOffice - 3DFor the most minimal example seethis file, which replicates atest casein the original repository.Environment generationRunthis fileto see how to generate random corridors. When doing so, feel free to change the randomization parameters. These are given inthis function definition.Note: Currently the randomization algorithm works better for 3D (set planar=False inhere). For 2D, the randomization algorithm is not very good and, in some cases, the resultant corridor has a weird shape. This should be fixed in the future.See here two examples of corridors (planar and spatial) generated with the randomization algorithm:PlanarSpatialThe blue polyhedrons are the convex decomposition of the obstacle-free space. The inner black line depicts the underlying piecewise linear path used to construct the polyhedrons. The green and red dots, alongside their frames, refer to the starting and ending pose of the agent.Transformation and normalization of the polyhedronsWhen using the environment generator for generating a dataset of corridors, it might be beneficial to represent all of them in a normalized and standard representation. Towards this aim, we provide the feature to normalize and translate the polyhedrons, so that the matrixes for the halfspaces are given by values between 0 and 1 and the origin coincides with the starting pose of the agent (green dot and frame). Seethese functionsfor more details.Installing from sourceAfter installing the dependencies given above, initialize git submodules withgit submodule init
    git submodule updateInstall the package withpip install .
Package: pydecompress
PyDecompressLightweight package that allows you to decompress archive files.Supported formats.zip.tar.tar.gz.tar.xz.tar.bz2.tar.xz.tar.Z- Requires the Linuxuncompresspackage.Installationviapip:pipinstallpydecompressUsage examplefrompydecompress.extractorimportExtractorres=Extractor.extract('path/to/archive.tar.gz','/destination/folder')print(res)# Output: PosixPath('/destination/folder')
Package: pydeconz
Python library wrappingdeCONZ Rest APIfor Home-Assistant.This implementation should cover most devices supported by deCONZ, if that is not the case please create an issue with debug logs and we will get it supported.Only host address and API key are necessary for normal operations.AcknowledgementsMattias Flodins custom deCONZ component was a great source of inspiration.Maija Vilkina and her blogSnillevillahas been a huge help in getting deCONZ up and running.Thanks to donnib, dkmh, simonporter007, kroimon, Henrik Nilsson for requesting and verifying functionality!Special thanks to Dresden Elektronik for sponsoring with extra Conbee and Raspbee hardware.
Package: pydecos
pydecos - is a set of useful decorators.deprecate:
to deprecate class/method/function. Deprecation reason can be specified....InstallationFor most users, the recommended method to install is via pip:pip install pydedecosor from a source:python setup.py installImportfrompydecosimportdeprecatedUsage examples- @deprecatedfunctionfrompydecosimportdeprecated@deprecateddefsome_func(t):print('weeeee'*t)some_func(3)# <input>:1: DeprecationWarning: Call to deprecated function some_func.# weeeeeweeeeeweeeeeclassfrompydecosimportdeprecated@deprecatedclassSomeClass:defsome_method(self):...SomeClass()# DeprecationWarning: Deprecated class has been invoked "SomeClass".# SomeClass()methodfrompydecosimportdeprecatedclassSomeClass:@deprecateddefsome_method(self):...SomeClass().some_method()# DeprecationWarning: Deprecated function/method "some_method" has been invoked.# SomeClass().some_method()deprecation with reason specifiedfrompydecosimportdeprecated@deprecated('Use the new function "awesome_func()" instead')defsome_func(t):returntsome_func(3)# DeprecationWarning: Deprecated function/method "some_func" has been invoked: Use the new function "awesome_func()" instead.#  some_func(3)- @timestampfrompydecosimporttimestamp@timestampdefsome_func(t):returntsome_func(3)print(some_func.created_at)# 2021-01-15 20:58:45.071720- @count_callfrompydecosimportcount_call@count_calldefsome_func():passsome_func()some_func()some_func()print(some_func.counter)# 3Changelog0.0.2 (15.01.2021)Added new decoratorstime_limit (linux only)count_calltimestamptimermakeboldmakeitalic0.0.1 (14.01.2021)initial commit
Package: pydecotools
pydecotoolsThe collection of decorator utilities.SummaryThis library offers tools that can be used when employing decorators.How to use this repositoryThe markdown file indocsdirectory explain how to use this library for your projects
and the implementation details adopted here.Issues and DiscussionsAs usual for any GitHub-based project, raise anissueif you find any bug or
want to suggest an improvement, or open adiscussionif you want to discuss
or chat :wink:Projects using pydecotoolsCurrently, none of the projects using this repository.If you use this repository as a reference for your works, let me know, so I
list your work above.Copyrightjoaomcteixeira's python-project-skeletonis used for this project.Changelogv0.2.2 (2024-02-21)Renamepipelineasdecoratorv0.2.1 (2023-01-01)Make islice usablev0.2.0 (2023-12-17)Refine READMEMake smart_partial internalRemove github actionsv0.1.0 (2023-12-17)Initial release
Package: pydee
pydeelib is intended to be an extension to PyQt4 providing a simple development environment named “Pydee” - a powerful alternative to IDLE (see screenshots:http://pydee.googlecode.com) based on independent widgets interacting with each other: workspace (globals explorer with dict/list editor and numpy arrays editor), docstring viewer (calltip), history log, multiline code editor (support drag and drop, autocompletion, syntax coloring, …), environment variables editor (including a Windows-specific editor to change current user environement variables) and working directory browser.
Package: pydeep2
pydeepPython/C bindings for thessdeeplibrary.Forked fromkbandla/pydeepFixedDeprecationWarning: PY_SSIZE_T_CLEAN will be required for '#' formatsPublished wheels at PyPI for x86_64 and aarch64pydeep.compareaccepts also stringSmall optimisationsInstallationRequires Python 3.6 or later. For older Python version, you can useoriginal pydeep.From PyPI:pip install pydeep2From source (ssdeep library must be already installed):python setup.py build
python setup.py test
sudo python setup.py installUsageMethods:pydeep.hash_buf/pydeep.hash_bytes- returns the ssdeep hash for a given bufferpydeep.hash_file- returns the ssdeep hash for filepathpydeep.compare- returns the % match between 2 hashesExample:importpydeephash1=pydeep.hash_buf('somedata')hash2=pydeep.hash_file('/path/to/file')pydeep.compare(hash1,hash2)Copyright2011-2012 Kiran Bandlakbandla@in2void.com2022 Jakub Onderka
Package: pydeepchainmap
DeepChainMap from the Python documentationpip install pydeepchainmapUseful stuff from the Python documentation:https://docs.python.org/3/library/collections.html#collections.ChainMapTested against Windows 10 / Python 3.10 / Anaconda>>>d=DeepChainMap({'zebra':'black'},{'elephant':'blue'},{'lion':'yellow'})>>>d['lion']='orange'# update an existing key two levels down>>>d['snake']='red'# new keys get added to the topmost dict>>>deld['elephant']# remove an existing key one level down>>>d# display resultDeepChainMap({'zebra':'black','snake':'red'},{},{'lion':'orange'})
Package: pydeepl
Note: The comercialDeepL APIhas been released. You should use it instead subscribing to DeepL Pro.pydeeplA Python API wrapper for theDeepLtranslation service.InstallationpipinstallpydeeplGetting StartedPython VersionPydeepl was written for both Python 2 and Python 3.Add pydeepl to your applicationimportpydeeplsentence='I like turtles.'from_language='EN'to_language='ES'translation=pydeepl.translate(sentence,to_language,from_lang=from_language)print(translation)# Using auto-detectiontranslation=pydeepl.translate(sentence,to_language)print(translation)Supported LanguagesPydeepl supports these languages:CodeLanguageautoAuto detectDEGermanENEnglishFRFrenchESSpanishITItalianNLDutchPLPolishNote that auto detection is only possible for the source language.DisclaimerDeepL is a product from DeepL GmbH. More info:deepl.com/publisher.htmlThis package has been heavily inspired bynode-deeplsandDeepLy.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: pydeepmerge
DeepMergeA lightweight python package for performing deep-merges of python dictionariesInstallationInstall this package with pip!$pipinstallpydeepmergeTo install this package from source, clone the repo and run:$pipinstall.If you would like to develop, remember to install the extras.# for bash$pipinstall-e.[test,dev]# for zsh$pipinstall-e.\[test,dev\]UsageUsage is simple:frompydeepmergeimportdeep_merge>some_data={'foo':{'bar':'baz','spam':'eggs'},'ham':'eggs'}>more_data={'spam':{'eggs':'ham'},'foo':{'baz':'bar','bar':'foo'}}>deep_merge(some_data,more_data){'foo':{'bar':'foo','baz':'bar','spam':'eggs'},'spam':{'eggs':'ham'},'ham':'eggs'}pydeepmergealso allows users to specify their own merge strategy function. By default, it uses the functionprefer_right.A merge strategy is any function that can accept exactly two inputs. The output of the merge strategy function should be what the merge result between two values should be.When writing your own merge strategy function, keep in mind that if the key does not exist on the left-hand mapping, the valueKey.NoKeyFoundwill be passed to the first parameter of the function. This is done deliberately so the user can determine if they want to do special behaviour if it is the first occurrence of the key in the sequence of dictionaries.An example of a merge strategy function can be found below:frompydeepmergeimportdeep_mergefrompydeepmerge.typesimportKeyfromtypingimportMappingdefpick_shallower(left_value,right_value):ifleft_valueisKey.NoKeyFound:returnright_valueifisinstance(right_value,Mapping):ifnotisinstance(left_value,Mapping):returnleft_valuereturndeep_merge(left_value,right_value)returnright_valueThedeep_mergefunction does not mutate any mapping but instead creates a new dictionary.
Package: pydeepspeech
pydeepspeechThe simpliest way to use AI to generate transcriptions from a wav file.This project uses the Mozilla DeepSpeech engine built from the included demo:https://github.com/mozilla/DeepSpeech-examples/tree/r0.9/vad_transcriberWhy you need thisMozilla's deep speech can't process long voice samples.pydeepspeechfixes this by "chunking" the input sound into seperate wav files that are then individualy processed. Wav files are cut along periods of detected silence, controlled by theaggressiveparameter.Besides this,pydeepspeechis probably better to use anyway because it'smuchsimpler to install than Mozilla's Deepspeech because the required data models needed forpydeepspeechare automatically downloaded and installed on first use.Quick startConsole api:$ pip install pydeepspeech
$ pydeepspeech --wav_file <WAVE_FILE> --aggressive 1 --out_file <TEXT_FILE>-or-$ pip install pydeepspeech
$ pydeepspeech --wav_file <WAVE_FILE> --out_file <TEXT_FILE> --model_dir <MY_PBMM_AND_SCORER_FILES>-or-$ pip install pydeepspeech
$ pydeepspeech_installmodels --pbmm <PBMM_FILE_OR_URL> --scorer <SCORER_FILE_OR_URL>
$ pydeepspeech --wav_file <WAVE_FILE> --out_file <TEXT_FILE>Or in pythonfrom pydeepspeech.transcribe import transcribe
transcribe(...)Optional: Create a virtual python packageDownload and install virtual env:# Download
curl -X GET https://raw.githubusercontent.com/zackees/make_venv/main/make_venv.py -o make_env.py
python make_env.py  # Make the environment
source activate.sh  # Enter environment
$ pip install pydeepspeechTo get back into the environment executesource activate.sh(if windows, you must be using git-bash)TestingTesting and linting is very simple. Just runtox(link).$ pip install tox
$ tox
Package: pydeepxlsx
pydeepxlsxpydeepxlsxis a package used to build a XLSX file usingopenpyxland a XLSX file as a template.flowchart LR
    id1[(Database)]
    id2(XLSX template file)
    id3[[pydeepxl]]
    id4(XLSX generated file)
    id1-->id3
    id2-->id3
    id3-->id4Install it from PyPIpipinstallproject_nameUsageSeeDocumentationSimple use casefrompydeepxlsximportPyDeepXLSXxlsx=PyDeepXLSX('./demo.xlsx')xlsx.copy_as_it('Demo',0)xlsx.append_lines('Demo',[{'item':'Titi','unit_price':3500,'quantity':0.05,'vat':0.1},{'item':'Toto','unit_price':1500,'quantity':0.001,'vat':0.2}])xlsx.wb.save('./test.xlsx')DevelopmentRead theCONTRIBUTING.mdfile.
Package: pyDEER
pyDEERpyDEER is a python package for processing Double Electron-Electron Resonance (DEER) data.The source code for pyDEER is availablehere.The complete documentation for pyDEER is availablehere.Installing pyDEERpython -m pip install pyDEERPython RequirementsPython2 (>= 2.7)Python3 (>= 3.6)Required Modulesscipynumpypython -m pip install scipy numpyImporting ELEXSYS Datafrommatplotlib.pylabimport*importpyDEERasdeer# Define path to datapath='./data/20170602_NR119_test/DEER_NR119_55ave'# Import datat,data=deer.load_elexsys(path)# Plot datafigure()plot(t,data)xlabel('Time (ns)')ylabel('Signal (a.u.)')show()Performing Tikhonov Regularizationimportnumpyasnpfrommatplotlib.pylabimport*importpyDEERasdeer# Define time and distance axest=np.r_[-100e-9:5e-6:500j]r=np.r_[1.5e-9:10e-9:100j]# Generate Kernel MatrixK=deer.kernel(t,r)# Simulate Gaussian P(r)P_gauss=deer.gaussian(r,0.2e-9,4e-9)# Calculate DEER trace from Gaussian P(r)S=np.dot(K,P_gauss)# Add noise to DEER traceS_noisy=deer.add_noise(S,0.1)# Perform Tikhonov RegularizationP_lambda=deer.tikhonov(K,S_noisy,lambda_=1.0)# Calculate Fit of DEER traceS_fit=np.dot(K,P_lambda)# Plot Resultfigure()plot(t*1e9,S_noisy,label='data')plot(t*1e9,S_fit,label='Tikhonov')xlabel('Time (ns)')ylabel('Signal (a.u.)')legend()figure('P(r)')plot(r*1e9,P_gauss,label='Exact')plot(r*1e9,P_lambda,label='Tikhonov')xlabel('r (nm)')ylabel('P(r)')legend()show()