Saravanan666/pypi-org huggingface dataset:
Package: detkit
detKitis a Python package for computing determinant functions of matrices.LinksDocumentationPyPIAnacondaDocker HubGithubInstallInstall withpippip install detkitInstall withcondaconda install -c s-ameli detkitDocker Imagedocker pull sameli/detkitSupported PlatformsSuccessful installation and tests performed on the following operating systems, architectures, and Python andPyPyversions:PlatformArchPython VersionPyPy Version1Continuous
Integration3.93.103.113.123.83.93.10LinuxX86-64✔✔✔✔✔✔✔AARCH-64✔✔✔✔✔✔✔macOSX86-64✔✔✔✔✔✔✔ARM-64✔✔✔✔✔✔✔WindowsX86-64✔✔✔✔✔✔✔ARM-642✔✔✔✔✔✔✔Python wheels fordetkitfor all supported platforms and versions in the above are available throughPyPIandAnaconda Cloud. If you needdetkiton other platforms, architectures, and Python or PyPy versions,raise an issueon GitHub and we build its Python Wheel for you.1. Wheels for PyPy are exclusively available for installation through pip and cannot be installed using conda.2. Wheels for Windows on ARM-64 architecture are exclusively available for installation through pip and cannot be installed using conda.DocumentationSeedocumentationof the package.Benchmark TestRead about thebenchmark testofdetkitin practical applications.How to ContributeWe welcome contributions viaGitHub’s pull request. If you do not feel comfortable modifying the code, we also welcome feature requests and bug reports asGitHub issues.How to CiteIf you publish work that usesdetkit, please consider citing the manuscripts availablehere.LicenseThis project uses aBSD 3-clause license, in hopes that it will be accessible to most projects. If you require a different license, please raise anissueand we will consider a dual license.
Package: detokenize
De-TokenizeWhat is it?De-Tokenizeis a Python  package which provides fast, accurate structuring of tokens back to original sentence form.ContributorLittin RajanMain FeaturesLight-weight packageNo more dependenciesPowerful, flexibleWhere to get it?The source code is currently hosted on GitHub at:https://github.com/littinrajan/detokenizeBinary installers for the latest released version are available at thePython
Package Index (PyPI)and onConda.# condacondainstalldetokenize# or PyPIpipinstalldetokenizeUsagefromdetokenize.detokenizerimportdetokenizesample_tokens=['These','are','some','tokens','.']sentence=detokenize(sample_tokens)LicenseMITContributing to De-TokenizeAll contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
Package: detokenizer
detokenizerdetokenizer of configuration files. Inject properties in source code before
deployment.UsageThis parameters are positional parameters.ParametersDescriptionsourcesource file, all tokens in this file will be replaced with propertiestargettarget file, output after the replacementconfigconfig files, this fils is a yaml file defining the delimiters for the tokenpropertiesproperties file, this file contains the dictionary of properties which shall be injected into the source filethe following command run the tool on the test data contained in this repo:python3 -m detokenizer \
  ./test/data/source_folder/config.properties.php \
  ./build/config.php \
  ./test/data/config.yaml \
  ./test/data/default.propertiesExampleSource file:<?php

ini_set('memory_limit', '${packaging.memory_limit}');

$ENVIRONMENT_NAME = '${packaging.environment_name}';

#region URL
$site_URL = '${packaging.site_URL}';
#endregion
...Properties file:packaging.memory_limit=1024
packaging.environment_name=default
packaging.site_URL=

packaging.host=193.168.1.12
packaging.port=3000
packaging.db=db_ms_12
...Produced target:<?php

ini_set('memory_limit', '1024');

$ENVIRONMENT_NAME = 'default';

#region URL
$site_URL = '';
#endregion
...
Package: detool
常用装饰器工具集pip安装pipinstalldetool1.统计函数执行时长装饰器importtimefromdetoolimporttimer_cost@timer_costdeft_time():time.sleep(0.01)print(123)2.redis缓存装饰器fromdetoolimportRedisCacheredis_cache=RedisCache(host='127.0.0.1',password='',port=6379,db=0)@redis_cache.cache(ttl=30)defsum_t(a,b):print(f'{a}+{b}={a+b}')returna+br=sum_t(1,2)print(r)3.日志装饰器fromdetoolimportclass_log_decorator,log_decorator@class_log_decoratorclassCal(object):def__init__(self,c):self.c=cdefsum(self,a,b):returna+b@log_decoratordefcalculate(a,b):returna+bCal(3).sum(a=3,b=6)4.异常捕获装饰器fromdetoolimportclass_exception_decorator,exception_decorator@exception_decoratordefr_exception():raiseException("function Exception raised")@class_exception_decoratorclassClassException(object):defr_exception(self):raiseException("class Exception raised")r_exception()ClassException().r_exception()5.分析内存装饰器fromdetoolimportprofile@profiledeft_memory():return[iforiinrange(1,1001)]t_memory()
Package: detorch
Minimal PyTorch Library for Differential EvolutionRequirementsnumpy
torchOptionalmpi4py # If you want to run in parallel
gym # For examplesTo installmpi4pyyou needMPIinstalled in the system.
Check:https://mpi4py.readthedocs.io/en/stable/install.htmlA Dockerfile is provided for convenience.Installationpipinstalldetorch--userSourcegitclone--recursivehttps://github.com/goktug97/de-torchcdde-torch
python3setup.pyinstall--userUsageSeehttps://github.com/goktug97/de-torch/blob/master/examplesCheckhttps://github.com/goktug97/de-torch/blob/master/detorch/config.pyfor parameters.You can run the example withPYTHONPATH="$(pwd):$PYTHONPATH"pythonexamples/example.pyor in parallel for faster training (requires mpi4py).PYTHONPATH="$(pwd):$PYTHONPATH"mpirun-np2pythonexamples/example.pyAnother Evolution Library for PyTorchhttps://github.com/goktug97/nes-torch
Package: detox-bridge
Detox Python BridgeA bridge to enable python code to use the detox grey-box testing API (https://github.com/wix/detox)RequirementsNVMThe package requires nvm to be installed. Either the NVM environment variable needs to contain the full path of the nvm.sh script, or
the NVM_DIR environment variable needs to point at the root directory of nvm containing the nvm.sh script.NODEThe code emitted by this bridge requires node 7.6.0 or higher.Python3.5 or 3.6 is required to use the package.DetoxFollow the getting started guide from detox (https://github.com/wix/detox/blob/master/docs/Introduction.GettingStarted.md)Usagefromdetox_bridgeimportawait,by,detox,device,element,expect,node_with_detoxapp_path="detox/examples/demo-react-native"# Start Node server in app_path root folder that contains node_moduleswithnode_with_detox(app_path=app_path,default_timeout=10)asappserver:# Detox Config (we could also load this from package.json)ios_sim_release={"binaryPath":"ios/build/Build/Products/Release-iphonesimulator/example.app","type":"ios.simulator","name":"iPhone 7 Plus"}configurations_obj={"configurations":{"ios.sim.release":ios_sim_release}}# Longer timeout since the app may be installedappserver(await(detox.init(configurations_obj)),timeout=360)# Reload react nativeappserver(await(device.reloadReactNative()))# Expectationappserver(await(expect(element(by.id('welcome'))).toBeVisible()))# Cleanupappserver(await(detox.cleanup()))DevelopmentRequirementsBoth python 3.5 and python 3.6 are required to run the suite suite.CheckoutAfter checkout run:git submodule update --init --recursiveRunning testsTo run the test suite:make testOnce the venv is there you can also run some tests via tox:venv/bin/tox -e py35 -- -k <regex>
Package: detoxifier
Detoxifier" For a Safe, Secure and Positivity enriched Digital World "1) detoxify_text()Given a input query with toxic comments, this library will exactly spot the toxic words and replace the letters of that particular word with asterisk (*). (eg: moron --> *****)from detoxifier import detoxify_text#DialoguefromAmericanSeriesSiliconValley(Season1)input_text = "Hello, Richard Hendricks. I'm a total fucking retard."detoxify_text(input_text)OutputHello, Richard Hendricks. I'm a total ******* ******."2) check_textual_toxicity()Given a input query with toxic comments, this library will check for the presence of toxic words in the query.from detoxifier import check_textual_toxicity#DialoguefromAmericanSeriesSiliconValley(Season1)input_text = "Hello, Richard Hendricks. I'm a total fucking retard."check_textual_toxicity(input_text)Output1## returns 1 if toxic word is present else it returns 0. ##
Package: detoxpy
detoxdetoxis a Python tool that can be used to rename directories/files with unsafe characters or spaces[^1].RequirementsPython>=3.6Installationpipinstall-UdetoxpyUsageusage: detox [-h] [-r] [-R REPLACE_WITH] [-t] [-l] [-n] [-p] path [path ...]

positional arguments:
  path                  Path to a single or multiple files/directories to detox

optional arguments:
  -h, --help            show this help message and exit
  -r, --recursive       Rename files recursively
  -R REPLACE_WITH, --replace-with REPLACE_WITH
                        Replace spaces and unsafe characters with this character (default: '_')
  -t, --keep-trailing   Keep the trailing character if exists (e.g., 'foo_')
  -l, --keep-leading    Keep the leading character if exists (e.g., '_foo')
  -n, --dry-run         Do a trial run with no permanent changes
  -p, --plain-print     Print the change as plain textExamplesExample 1: Detox a single file/directory:detox'(foo)^bar.txt'# '(foo)^bar.txt' --> 'foo_bar.txt'detox'foo&bar/'# 'foo&bar' --> 'foo_bar'Example 2: Detox a directory recursively:# foo bar# └── foo1&foo2#     ├── foo bar (copy 1).jpg#     └── foo bar (copy 2).jpgdetox-r'foo bar'# foo_bar# └── foo1_foo2#     ├── foo_bar_copy_1.jpg#     └── foo_bar_copy_2.jpgExample 3: Duplicate names after detoxingdetoxwill avoid overwriting if the detoxed name already exists. For example:tree'foo foo'# foo foo#   ├── foo^bar.jpg#   └── foo%bar.jpgdetox-r-i'foo foo'# foo_foo#   ├── foo_bar.jpg#   └── foo_bar-1.jpg[^1]: The namedetoxis inspired by the tooldetox.
Package: de-tpl-namespace-root
de_tpl_namespace_root module 0.0.0de_tpl_namespace_root is a Python multi-platform module project based on theKivyFrameworkand some portions of theaenamespace(Application Environment).the source code is available atGitlabmaintained by the user group degroup.additional credits to:Erokiaandplasterbrainatfreesound.orgfor the sounds.iconmonstrfor the icon images.
Package: de-tpl-project
tpl_project portion of de namespace packagethis portion belongs to theApplication Environment for Python- thedenamespace, which provides
useful classes and helper methods to develop full-featured applications with Python, running on multiple platforms.installationexecute the following command to use the de.tpl_project module in your application. it will install de.tpl_project
into your python (virtual) environment:pipinstallde-tpl-projectif you want to contribute to this portion then first forkthe de_tpl_project repository at GitLab. after that pull
it to your machine and finally execute the following command in the root folder of this repository (de_tpl_project):pipinstall-e.[dev]the last command will install this module portion into your virtual environment, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute to the unit tests or to the documentation
of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.namespace portion documentationdetailed info on the features and usage of this portion is available atReadTheDocs.
Package: de-transformation
Advanced Python & Linux Shell Commands: ProjectPython package projectDescriptionThis project has a python packagede-transformationcode to make data transformations. The package consists of 3 functions:transpose2dwindow1dconvolution2dtranspose2dDescriptionTransposes a 2D matrix.Parametersinput_matrix(list[list[float]]): The input 2D matrix to be transposed.Return Valuelist[list[float]]: The transposed 2D matrix, where rows become columns and columns become rows.Examplefromde_transformation.utilsimporttranspose2d# Example input matrixinput_matrix=[[1.0,2.0,3.0],[4.0,5.0,6.0]]# Transpose the matrixtransposed_matrix=transpose2d(input_matrix)# Output:# transposed_matrix is now:# [[1.0, 4.0],#  [2.0, 5.0],#  [3.0, 6.0]]window1dDescriptionExtracts window sub-arrays from a 1D list or numpy array, with the option to specify the size of the windows,
the shift for the starting position of the window, and the stride between consecutive windows.Parametersinput_array(list or np.ndarray): The input 1D array or list from which windows are extracted.size(int): The size of the windows to extract.shift(int, optional): The number of elements to shift the starting position of the window (default is 1).stride(int, optional): The step size between consecutive windows (default is 1).Return Valuelist of lists or np.ndarrays: A list containing windows of the specified size extracted from the input array.Examplefromde_transformation.utilsimportwindow1d# Example input arrayinput_array=[1,2,3,4,5,6,7,8,9]# Extract windows of size 3 with a shift of 2windows=window1d(input_array,size=3,shift=2)# Output:# windows is now:# [[1, 2, 3],#  [3, 4, 5],#  [5, 6, 7],#  [7, 8, 9]]convolution2dDescriptionPerforms 2D convolution on a numpy array using a specified convolution kernel and stride.Parametersinput_matrix(numpy.ndarray): The input 2D matrix to be convolved.kernel(numpy.ndarray): The convolution kernel (filter) to apply.stride(int, optional): The stride for the convolution operation (default is 1).Return Valuenumpy.ndarray: The result of the 2D convolution operation, which is a numpy array.Usage Examplefromde_transformation.utilsimportconvolution2d# Example input matrixinput_matrix=np.array([[1,2,3],[4,5,6],[7,8,9]])# Example kernelkernel=np.array([[1,0],[0,-1]])# Perform 2D convolutionresult=convolution2d(input_matrix,kernel)# Output:# result is now:# [[  1.  -2.]#  [ -1.  -2.]]
Package: detransliterator
detransliteratorTable of ContentsInstallationUsageLicenseInstallationpip install detransliteratorUsageas a software libraryfromdetransliteratorimportDetransliteratordetransliterator=Detransliterator('latin2nqo_001.35')latin="musa dunbuya"nqo=detransliterator.detransliterate(latin,beam_size=5)assertnqo=="ߡߎߛߊ߫ ߘߎ߲ߓߎߦߊ"as a console tool#detransliterationtoolpython -m detransliterator.tool --help#csv/tsvextractiontoolpython -m detransliterator.csv_tool --helpexample: detransliterate a streamecho "musa dunbuya" | python -m detransliterator.tool --model-name latin2nqo_001.35example: extract a column from a csv filecat test_csv_no_header.csv \| python -m detransliterator.csv_tool \extract-column --column-ix 1 \> tmp_col1.txtexample: extract a column from  a tsv filecat test_tsv_with_header.tsv \| python -m detransliterator.csv_tool \extract-column --column-ix 1 --skip-lines 1 --csv-formatting-params delimiter tab \> tmp_col2.txtexample: detransliterate a column from a csv filecat test_tsv_no_header.tsv \| python -m detransliterator.csv_tool extract-column --column-ix 1 \--csv-formatting-params delimiter tab \| python -m detransliterator.tool --model-name latin2nqo_001.35 \> tmp_detransliterated_1.nqoexample: detransliterate a column from a tsv filecat test_csv_with_header.csv \| python -m detransliterator.csv_tool extract-column --column-ix 1 --skip-lines 1 \| python -m detransliterator.tool --model-name latin2nqo_001.35 \> tmp_detransliterated_2.nqoexample: use a particular GPUCUDA_VISIBLE_DEVICES="1" echo "musa dunbuya" | python -m detransliterator.toolDetransliteration ModelsModelSource ScriptTarget Script#ParametersValidation BLEUTest BLEUlatin2nqo_001.35latinnqo2 520 57675.5674.14latin2nqo_001.38latinnqo3 909 12078.5177.06Licensedetransliteratoris distributed under the terms of theMITlicense.
Package: detroit
detroit is wrapper for Python ofd3jsandObservable Plot.DocumentationInstallationpipinstalldetroitThen you will need to install a browser through the Python packageplaywright.
For the moment, onlychromiumis supported.playwrightinstallchromiumFeaturesWrite as close as possibled3andPlotcodeRender one or multiple plots in your browser or in your jupyter notebookCustomize style as you wantSave them into.svg,.pngor.pdfQuick Exampleimportpolarsasplfromsklearn.datasetsimportload_digitsfromsklearn.decompositionimportPCAfromsklearn.preprocessingimportStandardScalerfromdetroitimportPlot,js,render,savemnsit=load_digits()scaler=StandardScaler()X_scaled=scaler.fit_transform(mnsit.data)pca=PCA(n_components=2)components=pca.fit_transform(X_scaled)# Prepare your data with Polars, Pandas or manuallydf=pl.DataFrame(components,schema=["Component 1","Component 2"])df=df.insert_column(2,pl.Series("digit",mnsit.target))plot=Plot.plot({"style":{"backgroundColor":"#161b22","color":"#e6edf3"},"symbol":{"legend":js("true")},"color":{"scheme":"rainbow"},"marks":[Plot.dot(js("data"),{"x":"Component 1","y":"Component 2","stroke":"digit","symbol":"digit"})]})render(df,plot,style={"body":{"background":"#161b22","color":"#e6edf3"}})
Package: det-sys-calc-eziped
determinant-calccalculate systems of equations and determinants to your heart's content with tkinter and eddieinstallationprerequisites: python 3.6 or abovego to terminal or command promptpip install det-sys-calc-ezipedpython3 -m det-sys-calculator OR python -m det-sys-calculatorhttps://pypi.org/project/det-sys-calc-eziped/0.0.1/'''Uses row reduction and tkinter as a basis for the program, packaged into two different windows-determinant and sys of equations.
tkinter makes calls to the backend and the backend returns a result for tkinter to display.'''for v2:make tabbing workfix lables for system of eqnsadd show steps buttonfinal windows
Package: dettectinator
DettectinatorDettectinator - The Python library to yourDeTT&CTYAML files.Dettectinator is built to be included in your SOC automation tooling. It can be included as a Python library or it can be used via the command line.Dettectinator provides plugins to read detections from your SIEM or EDR and create/update the DeTT&CT YAML file, so that you can use it to visualize your ATT&CK detection coverage in the ATT&CK Navigator.Currently de CLI is limited to processing detections through these plugins, the library can also be used for processing data sources.See thedocumentationfor more information on how to use it.
Package: deuce-client
source:https://github.com/rackerlabs/deuce-clientkeywords:Deuce, Deduplication, Clientmaintainer:Rackspace Atlanta Data Services Team <deuce at rackspace.com>Deuce Python Client** Table of Contents**OverviewInstallationOverviewDeuce Client is a Python-based client application and API for interacting with the
Deuce Deduplication-As-A-Service (https://github.com/rackerlabs/deuce) Cloud-based API.InstallationDeuce Client uses Python 3.3+ and can be installed into a Python 3.3+ environment as follows:# pip install deuce-client
Package: deuces-numpy
Home-page:https://github.com/grabantot/deuces-numpyAuthor: Anatol Grabowski
License: MIT
Description: descr
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Games/Entertainment
Description-Content-Type: text/plain
Package: deuce-valere
source:https://github.com/rackerlabs/deuce-valerekeywords:Deuce, Deduplication, Validationmaintainer:Rackspace Atlanta Data Services Team <ds.atl.rackspace.com>Validation Process for the Deuce project** Table of Contents**OverviewOverviewDeuce Valere is a Python-based API for validation the Deuce Deduplication-As-A-Service
(https://github.com/rackerlabs/deuce) Cloud-based API.
Package: deutsche-bahn-api
Deutsche Bahn ApiThis is a small Python package to access the Deutsche Bahn timetables api.
The timetable api is able to request the timetable of a specific station and access all dynamic changes on the timetable e.g. changed departure or arrival of the train, changed platform of arrival or a changed path of the train.SetupCreate a account at:https://developers.deutschebahn.comCreate a new application using this url:https://developers.deutschebahn.com/db-api-marketplace/apis/application/newand choose a name that you wantAfter that save you the client id and the client secret. You need it to interact with the apiNavigate to all available apis page at:https://developers.deutschebahn.com/db-api-marketplace/apis/productand select the "Timetables" apiAnd click the red subscribe button and select your applicationNow you are done and can start using the apiApiAuthenticationCreate a new ApiAuthentication class and pass to it the newly created client id and client secret.
And test with theapi.test_credentials()function if the api authentication works.api=ApiAuthentication("YOUR_CLIENT_ID","YOUR_CLIENT_SECRET")success:bool=api.test_credentials()StationsTo get the timetable of a specific train station you can use the name or lat and long values.station_helper=StationHelper()found_stations=station_helper.find_stations_by_lat_long(47.996713,7.842174,10)found_stations_by_name=station_helper.find_stations_by_name("Freiburg")TimetableWith the station object you are able to request the timetable from the station using the following code.timetable_helper=TimetableHelper(YOUR_STATION_OBJECT,YOUR_API_AUTHENTICATION_OBJECT)trains_in_this_hour=timetable_helper.get_timetable()trains_at_given_hour=timetable_helper.get_timetable(12)This method returns you a list with all trains that are scheduled for departure at this station in the current hour.
You can also pass theget_timetable()function the hour you want to request.Importantthis listdon'tcontains delays, platform changes or changed stations.
This can be achieved by using theget_timetable_changes()function and passing the list from the previous step.trains_with_changes=timetable_helper.get_timetable_changes(trains)
Package: deutscher-befrager
Deutscher BefragerPurposeI'm in the process of learning german but I don't work in german so I made this as a way to practice
while I'm on the command line.UsageAsk questions:$ befrager ask "Wo wohnen Sie?"Answer questions:$ befrager answerDevUseful linksclick docs:https://click.palletsprojects.com/en/7.x/quickstart/yaml docs:https://pyyaml.org/wiki/PyYAMLDocumentationyaml lang docs:https://yaml.org/yaml loader info:https://github.com/yaml/pyyaml/wiki/PyYAML-yaml.load(input)-Deprecationunittest:https://docs.python.org/2/library/unittest.htmlguide to unittest:https://realpython.com/python-testing/TipsRemember to write requirements.txt when adding packages:$ pipenv run pip freeze > requirements.txtRun commands locally with:pipenv run python -m interviewer.core --help
Package: deux
Version:1.2.0Web:https://deux.readthedocs.org/Download:https://pypi.python.org/pypi/deuxSource:https://github.com/robinhood/deuxKeywords:authentication, two-factor, multifactorAboutMultifactor Authentication provides multifactor authentication integration for
the Django Rest Framework. It integrates with Token Authentication built into
DRF and OAuth2 provided bydjango-oauth-toolkit.What is Multifactor Authentication?Multifactor Authentication (MFA) is a security system that requires more than
one method of authentication from independent categories of credentials to
verify the user’s identity for a login or other transaction.
(Source:SearchSecurity)InstallationYou can install deux either via the Python Package Index (PyPI)
or from source.Requirementsdeuxversion 1.2.0 runs on Python (2.7, 3.4, 3.5).Installing with pipTo install usingpip:$ pip install -U deuxDownloading and installing from sourceDownload the latest version of deux fromhttp://pypi.python.org/pypi/deuxYou can install it by doing the following:$ tar xvfz deux-0.0.0.tar.gz
$ cd deux-0.0.0
$ python setup.py build
# python setup.py installThe last command must be executed as a privileged user if
you are not currently using a virtualenv.Using the development versionWith pipYou can install it by doing the following:$ pip install https://github.com/robinhood/deux/zipball/master#egg=deux