Saravanan666/pypi-org huggingface dataset:
Package: dwcm
DWCMa word cloud of data visualization base on D3.jsWho are we?Hello everyone. I am Sunny. I graduated with an HD in Data Science and Analytics. My alma mater has a series of good practices in developing the practical application of dynamic data visualization/interactive dashboards. We are continuously concentrating on simplifying the data visualization process. Word cloud is one of our essential parts of data visualization in NLP. We found that the existing python package is challenging to complete an interactive word cloud dashboard. Therefore, the python package is based on D3.js/react.js/DASH, which can be executed in python or cooperate with Dash for word cloud development.Keyword arguments:id (string; optional):
the unique identity of keyword in word cloud html DOM.data (list; required):
dataset for word cloud visualising. datatype is array. on the array you need a
words columns and the freq columns of each word.
for example [{'word':'a','freq':100}].filterString (list; optional):
the word cloud filtrate the selected keyword(s). you should not set/input this parameter.freqs (string; required):
frequency or occurence of each keywordheight (string; optional):
the height of the boundary of the word cloud.width (string; optional):
the width of the boundary of the word cloud.value (string; optional):
just for future may be to use.ExampleimportDwcmdata=[{'word':'A','freq':15},{'word':'B','freq':22}],Dwcm.Wordcloud(data=data,words='word',freqs='freq').show()
Package: dwcontents
A Jupyter content provider for data.world.This content provider allows data.world users to store and manage their notebooks and files
directly on data.world using Jupyter Notebook or Jupyter Lab.Once enabled, the content provider will allow you to browse and access your entire data.world
library, including datasets and projects that you have created, contribute to or have bookmarked.Quick startInstallYou can install it usingpipdirectly from PyPI:pip install dwcontentsConfigureFind or create a file namedjupyter_notebook_config.pyunder your Jupyter folder (~/.jupyter).Update it to define two configuration parameters:
-NotebookApp.contents_manager_class: Must be set todwcontents.DwContents-DwContents.dw_auth_token: Must be your data.world API token (obtained athttps://data.world/settings/advanced)For example:importdwcontentsc=get_config()c.NotebookApp.contents_manager_class=dwcontents.DwContentsc.DwContents.dw_auth_token='YOUR TOKEN GOES HERE'You can also use this to access data.world alongside your local files usingdwcontents.HybridContents.In that case, this is what yourjupyter_notebook_config.pymight look like:importdwcontentsfromnotebook.services.contents.filemanagerimportFileContentsManagerc=get_config()c.NotebookApp.contents_manager_class=dwcontents.HybridContentsc.HybridContents.manager_classes={# Associate the root directory with data.world'':dwcontents.DwContents,# Associate /~local with your working directory, completely disconnected from data.world'~local':FileContentsManager}c.HybridContents.manager_kwargs={'':{'dw_auth_token':'YOUR TOKEN GOES HERE'}}RunOnce installation and configuration are complete, run Jupyter Notebook or Labs like you normally would.For example:jupyter notebookKnown IssuesJupyter supports a wide variety of file operations, whereas support for directories on data.world is limited.
For a better experience, try to keep a flat file structure under your datasets and projects.
Package: dw-content-tools
Content CLI ToolsInstallation$ pip3 install dw-content-toolsModule Repository ValidatorValidates that a module repo structure and content is valid, based
on the following rules:

* metadata.yml exists
* metadata.yml is valid
    * validate JSON schema
* docker-compose.yml exists
* docker-compose.yml is valid
    * validate JSON schema
* english.md exists
* validating english.md:
    * pages:
        * unique IDs
        * all pages contain a valid ID
        * all pages have a name
    * all images referenced in md exist as static files
    * activities:
        * all activities have an unique `id`
        * all activities have `type` defined
        * input:
            * has required `correct-answer` tag
        * multiple-choice:
            * has required `answer` (many) tags
            * at least one answer is marked as `is-correct`
            * when more than one answer is correct, `widget` has to be `checkbox`
        * code:
            * `template` and `device` attrs are defined
            * has required `validation-code` tag
Package: dw-core
[![GitHub Actions badge](https://github.com/DeskWatch/dw-core/workflows/Build/badge.svg)](https://github.com/DeskWatch/dw-core/actions)
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[![PyPI](https://img.shields.io/pypi/v/dw-core)](https://pypi.org/project/dw-core/)
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[![Typechecking: Mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/)Core library for DeskWatch.## Modulesdw_core, contains basic datatypes and utilities, such as theEventclass, helpers for configuration and logging, as well as schemas for buckets, events, and exports.dw_datastore, contains the datastore classes used by dw-server-python.dw_transform, all event-transforms used in queries.dw_query, the query-language used by DeskWatch.## How to installTo install the latest git version directly from github without cloning, runpip install git+https://github.com/DeskWatch/dw-core.gitTo install from a cloned version, cd into the directory and runpoetry installto install inside an virtualenv. If you want to install it
system-wide it can be installed withpip install ., but that has the issue
that it might not get the exact version of the dependencies due to not reading
the poetry.lock file.
Package: dwd
OverviewThis package implements Distance Weighted Discrimination (DWD). DWD For details see
(Marron et al 2007,Wang and Zou 2018). Originally
implemented in Python byIain Carmichael. Currently maintained byKitware, Inc.The package currently implements:Original DWD formulation solved with Second Order Cone Programming (SOCP) and solved
using cvxpy.Genralized DWD (gDWD) and kernel gDWD solved with the Majorization-Minimization
algorithm presented in Wang and Zou, 2018.Marron, James Stephen, Michael J. Todd, and Jeongyoun Ahn. "Distance-weighted
discrimination." Journal of the American Statistical Association 102, no. 480 (2007):
1267-1271.Wang, Boxiang, and Hui Zou. "Another look at distance‐weighted discrimination." Journal
of the Royal Statistical Society: Series B (Statistical Methodology) 80, no. 1 (2018):
177-198.InstallationThe DWD package can be installed via pip or github. This package is currently only
tested in python 3.6.$ pip install dwdThe conic solversocp_dwd.DWDdepends oncvxpy, which is not available on all platforms. Seethecvxpyinstallation instructions. Ifcvxpydependencies are met, then usepip install dwd[socp].Flitis used for packaging, and all package metadata is stored inpyproject.toml. To install this project locally or for development, useflit installor build a pip-installable wheel withflit build.Examplefromsklearn.datasetsimportmake_blobsfromdwd.socp_dwdimportDWD# sample sythetic training dataX,y=make_blobs(n_samples=200,n_features=2,centers=[[0,0],[2,2]],)# fit DWD classifierdwd=DWD(C='auto').fit(X,y)# compute training accuracydwd.score(X,y)# 0.94fromsklearn.datasetsimportmake_circlesfromdwd.gen_kern_dwdimportKernGDWD# sample some non-linear, toy dataX,y=make_circles(n_samples=200,noise=0.2,factor=0.5,random_state=1)# fit kernel DWD wit gaussian kernelkdwd=KernGDWD(lambd=.1,kernel='rbf',kernel_kws={'gamma':1},).fit(X,y)# compute training accuracykdwd.score(X,y)# 0.915For more example code seethese example notebooks(including the code
to generate the above figures). If the notebooks aren't loading on github you can copy/paste the notebook url intohttps://nbviewer.jupyter.org/.Help and SupportAdditional documentation, examples and code revisions are coming soon.DocumentationThe source code is located on github:https://github.com/slicersalt/dwdTestingTesting is done usingnose.ContributingWe welcome contributions to make this a stronger package: data examples,
bug fixes, spelling errors, new features, etc.
Package: dwdatareader
DEWESoft produces hardware and software for test measurement, data aquisition,
and storage. Data files are stored with the extension .d7d in a proprietary
format. DEWESoft provides a free Windows application to work with the data
and a free shared library for developers on Windows and Linux.This is a Python module to interact with the DEWESoft DWDataReaderLib shared library
available fromhttps://download.dewesoft.com/list/developers.InstallationThe module is available onhttps://pypi.python.org/pypi/dwdatareaderso all
one needs to do is:pip install dwdatareaderExample usageScripts like the following may be run from the command line or, more
interactively, fromJupyter NotebookYou can work with alive Binder example here.importdwdatareaderasdwwithdw.open('myfile.d7d')asf:print(f.info)ch1=f['chname1'].series()ch1.plot()forchinf.values():print(ch.name,ch.series().mean())ContributeBug reports and pull requests should be directed to the project home onGithub
Package: dwd-opendata-get-grib
dwd-opendata-get-gribIntroductionFunctions to get grib data from the DWD OpenData Server and
convert it to a format that is more readable and
easier to access and perform Data Science on it.RequirementsecCodes (Installation instructionshere)InstallationAs a package with pip:pip install dwd-opendata-get-gribor with conda/mamba to get the eccodes library as a direct binaryconda install -c conda-forge dwd-opendata-get-gribmamba install -c conda-forge dwd-opendata-get-gribAs a standalone:Download .zip archive from GitHub Releases. Built with pyinstaller.Table of full height levelslevel idx.height [m]level idx.height [m]level idx.height [m]level idx.height [m]120700.926188446.611353639.53552924.048218707.630198073.640363434.41453855.630317459.836207715.350373235.97654752.427416432.216217370.106383044.02955654.479515538.089227039.106392858.39956561.856614738.074236719.557402678.92657474.652714009.789246411.462412505.46158393.002813338.901256114.219422337.87059317.092912715.508265827.280432176.03260247.1721012132.398275550.148442019.83661183.5921111584.105285282.374451869.18562126.8571211066.360295023.548461723.9916377.7451310575.747304773.294471584.1796437.6061410109.477314531.269481449.6866510.000159665.235324297.157491320.458169241.077334070.672501196.457178835.344343851.546511077.658Table of full pressure levelspressure level [hPa]2002503004005006007008509509751000
Package: dwdparse
dwdparseParsers for DWD's open weather data.The DWD (Deutscher Wetterdienst), as Germany's
meteorological service, publishes a myriad of meteorological observations and
calculations as part of theirOpen Data
program.dwdparseis a Python library for parsing the various formats that this data
is published in, with no dependencies outside the standard library. It serves
as the parsing backend forBright Sky.Our development effort focuses mainly on the data that is made available
through Bright Sky, although we are very open to requests or contributions
regarding other parsing targets. If you are looking for a more complete set of
parsers - including for data from other weather agencies - and you don't mind
the extra dependencies, take a look at the excellentwetterdienst.Looking for something specific?I just want to retrieve some weather dataYou can use the freepublic Bright Sky instance!I want to parse DWD weather files or contribute to dwdparse's source codeRead on. :)QuickstartYou can use this package both as a stand-alone command-line tool or as a Python
library.Stand-alone DWD file parsingInstall thedwdparsepackage from PyPI:$pipinstalldwdparseCalldwdparse, providing your target file (or URL) as argument:$dwdparsestundenwerte_TU_01766_akt.zipThis will output a newline-separated list of JSON records.Note that all
numerical weather data is converted to SI units.If you wish to use DWD
units, or if you need both DWD and WMO station IDs, check out the--unitsoption and the example section withdwdparse --help.Parsing DWD files from Python codeInstall thedwdparsepackage from PyPI:$pipinstalldwdparseIn Python, import one of thedwdparseparsers (or theget_parserutility function) fromdwdparse, then call it'sparse()method with the
path of the file you would like to parse. This will return an iterable over
weather records:frombrightskyimportget_parserDWD_FILE_PATH='stundenwerte_TU_01766_akt.zip'parser_class=get_parser(DWD_FILE_PATH)parser=parser_class()forrecordinparser.parse(DWD_FILE_PATH):print(record)Acknowledgementsdwdparseis developed as the main parsing core forBright
Sky. Bright Sky's development is
boosted by the priceless guidance and support of theOpen Knowledge
Foundation'sPrototype Fundprogram, and is generously funded by Germany'sFederal Ministry of Education
and Research. Obvious as it may be, it should be
mentioned that none of this would be possible without the painstaking,
never-ending effort of theDeutscher Wetterdienst.
Package: dwd-pollen-api
DWD Pollen APIDISCLAIMER: This project is a private open source project and doesn't have any connection with Deutscher Wetterdienst.This is a python package to access the pollen data from DWD. The data is updated daily.Available region IDs can be foundhere.Help and ContributionFeel free to open an issue if you find one and I will do my best to help you. If you want to contribute, your help is appreciated! If you want to add a new feature, add a pull request first so we can chat about the details.LicensesThis package uses public data fromDWD OpenData. The Copyright can be viewedhere.
Package: dweather-client
dWeather-Python-ClientQuickstartInstall dweather_client:pip3 install dweather_clientGet valid dataset names and associated hashes:http_client.get_heads()Get the metadata for a given dataset name:http_client.get_metadata('chirps_05-daily')Get a rainfall dict for a gridded dataset:http_client.get_rainfall_dict(41.175, -75.125, 'chirps_05-daily')Get a rainfall dataframe:df_loader.get_rainfall_df(41.125, -75.125, 'chirps_05-daily')Get a station dataframe:df_loader.get_station_rainfall_df('USW00024285')
df_loader.get_station_temperature_df('USW00024285')
df_loader.get_station_snow_df('USW00024285')See further examples intestsDevelopmentcd dweather-python-client
python3 -m venv .
bin/pip3 install -r requirements.txt
bin/python3 -m pytest dweather_clieht/testsSome dweather_client features require an ipfs daemon to work.Download Go-IPFS version 0.6.0See Assets list at the bottom of this page:https://github.com/ipfs/go-ipfs/releases/tag/v0.6.0Download the build appropriate for your machine, or just download the source tar if you're not sure.Install go-IPFSUnzip the file that you downloaded.tar xvfz {filename}.tar.gzMove the binary into your path.sudomay be required for this.mv go-ipfs/ipfs /usr/local/bin/ipfsInitialize a ~/.ipfs directory. This is where your files and config will be saved.ipfs initConfigure go-IPFSRemove default peers for performance.ipfs bootstrap rm --allAdd the dWeather server as a peer.ipfs bootstrap add  "/ip4/198.211.104.50/tcp/4001/p2p/QmWsAFSDajELyneR7LkMsgfaRk2ib1y3SEU7nQuXSNPsQV"Make sure go-IPFS it worksStart the IPFS daemon. You will need to have the daemon running to use some functionality of the dWeather client.ipfs daemonIn a new window, confirm that you can pull content.ipfs cat QmVsy2HZCi39ePJRpNqXEJvHgRMqjcyu1FLqgiFkPTMknq/USW00014704.csv.gzConfirm that the dWeather server is a peer.ipfs swarm peersInstall the Python dWeather ClientCreate an isolated Python installation and install the dependencies.git clone https://github.com/Arbol-Project/dWeather-Python-Client.git
cd dWeather-Python-Client
python3 -m venv .
bin/pip3 install -r requirements.txtRun the tests, if you want.bin/python3 -m pytest -s --log-cli-level=20 dweather_client/testsLocal dataCertain dweather functions will try to save query results locally to disk for faster performance on subsequent loads. This can be overridden by passingpin=Falsein these function calls.Load the ipfs UI to browse what files are stored locally. Paste the following into a web browser.http://127.0.0.1:5001/webuiNavigate to Files, then click "pins." Content can be unpinned via the UI.If you just want to remove everything, delete ~/.ipfs and rerun the installation and configuration fromipfs init.rm -rf ~/.ipfsFurther documentationSeetestsdirectory for example usage. Documented examples of usage should appear in a docs repository or in product-dev-notebook.
Package: dweba
Dweba is a framework and work environmentto develop and run distributed and web applications usingthe python programming language. It contains SPyRO and DOM3K (the libraries forDistributed applications and AJAX framework).In this package you will find packages (named objects in SPyRO) as follows:+ Useradmin: Management of users and groups+ Packadmin: Package manager and editor. You can update, upload, pack, unpack, backup,files and packages, and connects the objects pools to GuiGo!+ ProxyKong: A Simple and flexible http proxy, with support for authentication+ GuiGo!: The Graphical User Interface Object Generator, it uses databases to createobject GUIs that can be easy customizables.+ forum: A simple forum+ ft3k: An lightweight SQL fulltext indexer for sqlite3+ locale3k: A locale manager and locale editor for spyro's objects======Guigo! focuses in creation of GUI APIs, not only Web UIsshttp/http.py now has fully multithreading support for medusaDOM3K now it's more remotelly customizable (see show.js for the handle_commands function)DocumentationToo many changes and bug fixes
Package: dwell
This package contains a number of independent modules that are used by other packages.It currently includes the following modules:constants : physical constants derived from NIST datafft : interfaces to scipy, anfft, fftw FFT packages that can deal with 2D dataio : NetCDF interface to wrap functions in higher level codeplanck : Black body calculations and integratorsrad : development tools, including a colored log package, function deprecation wrapper, file IO debugging wrappersmoothing : vector smoothing interface to scipy smoothing and kernelscaselessdict : A case free dictionarytesting: internal testing code.CreditsAuthor:Christopher Lee
Package: dwf
What is this?This is a python library for controlling Analog Discovery and
Electronics Explorer series presetned byDigilent inc.This library needs Waveforms SDK.I tested this library with Analog Discovery 2 andWaveforms 2015in below environment.python 3.5.1, python 2.7.10 on OSX 10.11python 3.4.3, python 2.7.6 on Ubuntu 14.04LTSpython 3.5.1 on Windows 7I wrote this library for supporting python 2.6, 2.7, 3.3 or above.This software is released under the MIT License, see LICENSE.txt.InstallingYou can install the latest stable version from PyPI:pipinstalldwfor if you prefer, install it from this repo like this:pythonsetup.pyinstallAPI of this libraryThis library has two sets of API. There are Function-based API and
Class-based API.Function-based APIThis API is like as C functions which supplied by Digilent. But
some modifications are applied for pythonic-way programming.When error is returned by SDK, the exceptionDWFErroris
raised.All output values, which are passed by reference, are changed
to return-value of function.Arrays of parameters are converted from/to python’s list.ExamplesSDK version check in C language is like as:charversion[32];FDwfGetVersion(version);printf("DWF version: %s\n",version);With this library using function-based API, same code is
translated to:version=dwf.FDwfGetVersion()print("DWF version: "+version)Another example is here. This piece of code is quoted fromanalogout_custom.cin Waveforms SDK sample.HDWFhdwf;doublergdSamples[4096];for(inti=0;i<4096;i++)rgdSamples[i]=2.0*i/4095-1;FDwfDeviceOpen(-1,&hdwf);FDwfAnalogOutNodeSet(hdwf,0,AnalogOutNodeCarrier,true);FDwfAnalogOutNodeFunctionSet(hdwf,0,AnalogOutNodeCarrier,funcCustom);FDwfAnalogOutNodeDataSet(hdwf,0,AnalogOutNodeCarrier,rgdSamples,4096);...In python with this library, like as:rgdSamples=[]foriinrange(4096):rgdSamples.append(2.0*i/4095-1)hdwf=dwf.FDwfDeviceOpen()dwf.FDwfAnalogOutNodeSet(hdwf,0,dwf.AnalogOutNodeCarrier,True)dwf.FDwfAnalogOutNodeFunctionSet(hdwf,0,dwf.AnalogOutNodeCarrier,dwf.funcCustom)dwf.FDwfAnalogOutNodeDataSet(hdwf,0,dwf.AnalogOutNodeCarrier,rgdSamples)...Class-based APIClass-based APIs are made from function-based APIs. Documents of
this API is now writing.This API has below function and classes.DwfEnumeration()Device enumeration. This function returns list ofDwfDevice.class DwfDevicecallFDwfEnum*()functions.class DwfcallFDwfDevice*()functions.class DwfAnalogIncallFDwfAnalogIn*()functions.class DwfAnalogOutcallFDwfAnalogOut*()functions.class DwfAnalogIOcallFDwfAnalogIO*()functions.class DwfDigitalIOcallFDwfDigitalIO*()functions.class DwfDigitalIncallFDwfDigitalIn*()functions.class DwfDigitalOutcallFDwfDigitalOut*()functions.With this API,example codeis translated torgdSamples=[]foriinrange(4096):rgdSamples.append(2.0*i/4095-1)dwf_ao=dwf.DwfAnalogOut()dwf_ao.nodeSet(0,dwf_ao.NODE.CARRIER,True)dwf_ao.nodeFunctionSet(0,dwf_ao.NODE.CARRIER,dwf_ao.FUNC.CUSTOM)dwf_ao.nodeDataSet(0,dwf_ao.NODE.CARRIER,rgdSamples)...
Package: dw-feature-tool
请调用get_feature_info(data, table_name)函数data格式: 数组、字典、dataFrame、numpy.array、csv、excel（表格使用路径传入）table_name格式: 字符串说明:读取第一行/表头并输出 (一维数组直接输出)第一行输出标签第二行输出列名 (特征列名称)第三行输出表名输出格式:[ALIOTH - INFO - FEATURE_NAME] 
[xxx,xxx,xxx]
xxx
Package: dwfpy
Python Bindings for Digilent WaveForms APIDwfPyis a Python package that allows you to accessDigilent WaveFormsdevices via Python. It provides a low-level API with complete access to the Digilent WaveForms API, and also a simple but powerful high-level API, which allows you to configure WaveForms devices with a single statement.For instance, to output a 1kHz sine-wave on aAnalog Discovery 2, you can simply write:importdwfpyasdwfwithdwf.AnalogDiscovery2()asdevice:print('Generating a 1kHz sine wave on WaveGen channel 1...')device.analog_output['ch1'].setup('sine',frequency=1e3,amplitude=1,start=True)input('Press Enter key to exit.')FeaturesPythonic abstraction of Digilent Waveforms API.Low-level API with complete access to the Digilent Waveforms API.Powerful high-level API that supports one-line configuration statements.Supports all sub-modules, such as oscilloscope, arbitrary waveform generator, logic analyzer, pattern generator, digital I/O, and power supplies.Works with all WaveForms devices, such as theAnalog Discovery 2or theDigital Discovery.Installing DwfPyYou can install theDwfPy packagefrom PyPI using pip:pip install dwfpyIn order to use theDwfPypackage, you needPython 3.6or higher.AsDwfPybuilds on top of the WaveForms API, you need to install theWaveForms software, which includes the required runtime components to access the WaveForms devices.The source code for theDwfPypackage can be found at GitHub athttps://github.com/mariusgreuel/dwfpy.ExamplesYou can find Python examples usingDwfPyin the dwfpy GitHub repository athttps://github.com/mariusgreuel/dwfpy/tree/main/examples.DocumentationYou can find theDwfPyuser's guide athttps://dwfpy.readthedocs.io/.Detailed information about the Digilent Waveforms API is available from theDigilent WaveForms SDK Reference Manual.Getting helpFor issues withDwfPy, please visit thedwfpy issue tracker.