Saravanan666/pypi-org huggingface dataset:
Package: akey
akeyDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nakey--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallakeynbdev# activate conda environment$condaactivateakey# make sure the akey package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the akey package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/akey.gitor fromconda$condainstall-cdsm-72akeyor frompypi$pipinstallakeyDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find
package manager specific guidelines oncondaandpypirespectively.
Package: akeyless-api-gateway
########################
Akeyless Api Gateway - the Python library for the AKEYLESS Vault API
########################RESTFull API for interacting with AKEYLESS Vault APIMinimum requirementsPython 3.4+certifi>=2017.4.17python-dateutil>=2.1six>=1.10urllib3>=1.23Installation.. code::
$pip install akeyless_api_gatewayUsage.. code::
fromfutureimport print_functionimport time
import akeyless_api_gateway
from akeyless_api_gateway.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://127.0.0.1:8080
# See configuration.py for a list of all supported configuration parameters.
configuration = akeyless_api_gateway.Configuration()
configuration.host = "https://127.0.0.1:8080"



# create an instance of the API class
api_instance = akeyless_api_gateway.DefaultApi(akeyless_api_gateway.ApiClient(configuration))
role_name = 'role_name_example' # str | The role name to associate
am_name = 'am_name_example' # str | The auth method name to associate
token = 'token_example' # str | Access token
sub_claims = 'sub_claims_example' # str | key/val of sub claims, ex. group=admins,developers (optional)

try:
    # Create an association between role and auth method
    api_response = api_instance.assoc_role_am(role_name, am_name, token, sub_claims=sub_claims)
    pprint(api_response)
except ApiException as e:
    print("Exception when calling DefaultApi->assoc_role_am: %s\n" % e)LicenseThis SDK is distributed under theApache License, Version 2.0_ see LICENSE.txt for more information... _Apache License, Version 2.0:http://www.apache.org/licenses/LICENSE-2.0
Package: akeyless-cloud-id
########################
Akeyless Python Cloud Id
########################Retrieves cloud identityCurrently, AWS, GCP and Azure clouds are supported.
In order to get cloud identity you should import this package and call the relevant method per your chosen CSP:AWS: "generate" (If no aws access id/key and token are provided they will be retrieved automatically from the default session.)GCP: "generateGcp"Azure: "generateAzure"Minimum requirementsPython 3.5+urllib3 >= 1.15requestsOptional Dependenciesboto3google-authInstallation.. code::
pip install akeyless-python-cloud-idAWS:To install with AWS:.. code::pip install akeyless-python-cloud-id[aws]The following additional packages will be installed:boto3GCP:To install with GCP:.. code::pip install akeyless-python-cloud-id[gcp]The following additional packages will be installed:google-authUsageSuch code can be used, for example, in order to retrieve secrets from Akeyless as part of AWS Code Pipeline:.. code::
pip install git+https://github.com/akeylesslabs/akeyless-python-sdkimport akeyless_api_gateway
from akeyless_cloud_id import CloudId

configuration = akeyless_api_gateway.Configuration()
configuration.host="http://<api-gateway-host>:<port>"

api_instance = akeyless_api_gateway.DefaultApi(akeyless_api_gateway.ApiClient(configuration))

cloud_id = CloudId()
# for AWS use:
id = cloud_id.generate()
# For Azure use:
id = cloud_id.generateAzure()
# For GCP use:
id = cloud_id.generateGcp()

access_id = event['CodePipeline.job']['data']['actionConfiguration']['configuration']['UserParameters']

auth_response = api_instance.auth(access_id, access_type="aws_iam", cloud_id=id)
token = auth_response.token

postgresPassword = api_instance.get_secret_value("PostgresPassword", token)LicenseThis SDK is distributed under theApache License, Version 2.0_ see LICENSE.txt for more information... _Apache License, Version 2.0:http://www.apache.org/licenses/LICENSE-2.0
Package: akeyra
Agent forSakeyraWhat is it?Akeyra is the client-side of Sakeyra.It serves the purpose of creating/updating~/.ssh/authorized_keysIt also create users that don’t exist on your server but that are in
the key-bundle.How to install ?Use Pippip install akeyraHow to use it?You have to fill the configuration file (see below) to connect to your
SAKman Server.Then you just have to runakeyraas root.Make sure you have a Cron somewhere to update as frequently as
possible.Optionsusage: akeyra [-h] [-H HOST] [-E ENV] [-K KEY] [-P PROXY] [-F FILE] [-D]You can provide all informations in CLI, use the basic configfile
(/etc/akeyra.cfg), or an alternative one. If nothing is passed by CLI,
then the basic configfile will be used.CLI > CLI-File > base fileoptional arguments: * -h, –help show this help message and exit * -H
HOST, –host HOST Key Server * -E ENV, –env ENV Environment * -K KEY,
–key KEY Secret key * -P PROXY, –proxy PROXY Proxy * -F FILE, –cnf
FILE Alt Conffile * -D, –dry Dry runIf you need to use a proxy, you either set environment variable like
http_proxy or use proxy in the configfile.Configuration file/etc/akeyra.cfg[agent]
host =
key =
environment =
proxy =Format between Akeyra and Sakeyra (decode){"environment":"rec","users":[{"user1":{"email":"userkey1@test.com","name":"userkey1","pubkey":"laclepubliquedeuserkey1"}},{"user2":{"email":"userkey2@test.com","name":"userkey2","pubkey":"laclepubliquedeuserkey2"}}],"pub_date":"2017-10-18T17:15:46.799689"}
Package: ak_file
ak-fileA base module to manipulate files and foldersView Demo·Documentation·Report Bug·Request FeatureTable of Contents1. About the Project1.1. Features2. Getting Started2.1. Dependencies2.2. Installation3. Usage4. Roadmap4. License5. Contact6. Acknowledgements1. About the ProjectA base project to simplify file manipulation1.1. FeaturesCan sanitize filename based on windows limitaionsCan search for and return files with specified filenames2. Getting Started2.1. DependenciesThe repo comes pre-compiled with all dependencies. Needs Python 3.11+2.2. InstallationInstall from pypipipinstallak_file3. Usageimportak_fileimportFilefile=File("<path/to/file>")file.exists()# Returns boolfile.properties()# Returns dictfile.encrypt(password='Some Fancy Password')# Returns bytes datafile._DEFAULT_SALT=b'SuperSecureSaltForEncryption'# Change default encryption saltfile.decrypt(password='Some Fancy Password')# Returns bytes data# To sanitize filenamefromak_fileimportsanitizersanitizer.sanitize("Dirty_windows_file_name.ext",strict=False)# Obfuscate/Unobfuscate filename with simple char shiftsanitizer.obfuscate('Filename to obfuscate')# Returns 'WzCvErDvqKFqFswLJtrKv'sanitizer.unobfuscate('WzCvErDvqKFqFswLJtrKv')# Returns 'Filename to obfuscate'# Searchfromak_fileimportSearchFoldersearch=SearchFolder(folder_path="Folder\path",recurse=True)search.extension(extension_str='py')# by extensionsearch.size(min_size=1024,max_size=2048)# Bytes; by sizesearch.regex(pattern=r'[A-Z]{3}\.py',case_sensitive=False)# By regexsearch.modification_date(start_date=datetime(2023,01,01),end_date=datetime(2023,10,10))## search by generic functionsearch.search(condition=lambdafile:'Alpha'infile.parent)4. RoadmapException HandlingFile OperationsAdding methods to write content to files.Methods for appending content to files.Support for working with directories: create, remove, list contents, move, etc.Checksum AlgorithmsMetadata ExtractionSupport for More Encryption OptionsContext ManagersFile Comparison MethodsLogging and DebuggingAsynchronous I/O SupportSerialization and DeserializationSupport Different File Types4. LicenseSee LICENSE for more information.5. ContactArun Kishore -@rpakishoreProject Link:https://github.com/rpakishore/ak-file6. AcknowledgementsAwesome README TemplateShields.io
Package: akfraction
akfraction is a Python library for dealing with arithmetic operation.InstallationUse the package managerpipto
install akfraction.pipinstallakfractionUsagefromakfractionimportFractiona,b,c,d=[int(e)foreininput().split()]fraction1=Fraction(a,b)fraction2=Fraction(c,d)print(f"fraction1 ={fraction1}")print(f"fraction2 ={fraction2}")print(f"fraction1+fraction2 ={fraction1+fraction2}")print(f"fraction1-fraction2 ={fraction1-fraction2}")print(f"fraction1*fraction2 ={fraction1*fraction2}")print(f"fraction1/fraction2 ={fraction1/fraction2}")ContributingPull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.Please make sure to update tests as appropriate.AuthorAdisak KarnbanjongLicenseMIT
Package: akgoodreads
Goodreads ScraperA python wrapper forgoodreads APIView Demo·Documentation·Report Bug·Request FeatureTable of Contents1. Getting Started1.1. Dependencies1.2. Installation2. Usage2.1. Initialize the client2.2. Search for books2.3. Search for books3. License4. Contact5. Acknowledgements1. Getting StartedYou will need a Goodreads API key for this to work. Unfortunately, Goodreads is not giving out new keys at this time, so unless you have signed up from a while ago - this wont work for you.On the launch of the script, you will be prompted for the API key. If you are using windows, you will be prompted to save this key locally for ease (usingkeypasslibrary).1.1. DependenciesAll the dependencies should automatically be installed when installing the script. This project heavily relies on therequestslibrary to make the api calls.1.2. InstallationInstall with pippipinstallakgoodreads2. Usage2.1. Initialize the clientimportakgoodreadsclient=goodreads.Goodreads("<your email>")2.2. Search for booksWith titleclient.book("Ender's Game",limit=5)or with goodreads IDclient._book_from_id(50)2.3. Search for booksWith titleclient.author("Rowling")or with goodreads IDclient._author_from_id(7995)3. LicenseSee LICENSE.txt.4. ContactArun Kishore -@rpakishoreGithub Link:https://github.com/rpakishore/5. AcknowledgementsAwesome README TemplateBanner MakerShields.ioCarbon
Package: akhdefo-functions
AkhdefoClick on the Logo to Navigate to the Main PageComputer Vision for Slope Stability: Land Deformation MonitoringBackground of Akh-DefoAkh-Defois derived from two distinct words:'Akh' in the Kurdish language, representing land, earth, or soil (originating from the Kurdish Badini dialect).'Defo', a shorthand for the English term 'deformation'.Recommended CitationMuhammad M, Williams-Jones G, Stead D, Tortini R, Falorni G, and Donati D (2022) Applications of Image-Based Computer Vision for Remote Surveillance of Slope Instability.Front. Earth Sci.10:909078. doi:10.3389/feart.2022.909078UpdatesDeprecated:Akhdefo version one.Current recommendation:Use Akhdefo version 2.New Feature:Cloud-based real-time processing capabilities.Expansion:Over 20 modules for end-to-end Python-based GIS and Image Processing, and Customized Figure generation.Integration:Access, filter, and download capabilities for Planet Labs data using the Planet Lab API.Enhancement:Orthorectification feature for satellite images.Installation of Akhdefo SoftwareFollow these steps to install the Akhdefo software:Create a new Python Anaconda environment using the command:condacreate--nameakhdefo_envCreate  Anaconda environment and install the following libraries with Anacondadependencies:-python=3.8# Assuming Python 3.8, can be changed as needed-cmocean-pip-opencv-earthpy-flask-geopandas-glob2-gstools-hyp3_sdk-ipywidgets-json5-matplotlib-numpy-gdal-pandas-recommonmark-sphinx-nbsphinx-sphinx-book-theme-myst-parser-plotly-pykrige-rasterio-requests-rioxarray-scipy-seaborn-shapely-scikit-image# skimage-scikit-learn# sklearn-statsmodels-tensorflow-tqdm-xmltodictDownload the Python package requirement file:pip_req.txt.Install required Python packages with the command:pipinstall-rpip_req.txtInstall Akhdefo using the following command:pipinstallakhdefo-functions
Package: akhenaten-py
Akhenaten-pyClient to use the plotly hosting service at akhenaten.euThis library can be used to upload Plotly plots to the akhenaten plotly hosting service!To use this service first get an account by contacting frank (at) amunanalytics.euIf you would like to use a GUI, simply use your client Id and key to login tohttps://console.akhenaten.euInstallationpython3 -m pip install akhenaten-pyUsageimportos# authentication can be done with environment variables or directly# this example shows both, this is just to show the possibilities!os.environ['AKHENATEN_ID']='<your client ID>'os.environ['AKHENATEN_KEY']='<your client key'fromakhenatenimportAkhenatenClient,MetadataClassclient_hoster=AkhenatenClient(# not needed when using environment variables!akhenaten_id='<your client ID>',akhenaten_key='<your client key>',bucket_name='<bucketname>'# only applicable if you are using custom access key, otherwise deduced from client id)# get all current uploaded figsprint(client_hoster.list_figs())# create some figfig=get_some_plotly_fig()# upload it and display the urls# if no slug is specified then a random uuid4 will be generatedresult=client_hoster.upload_fig(fig,slug='<optional slug>',meta_obj=MetadataClass(title='some plot title',author='some author'))print(result['json_url'])# the url to use in your own embeddingprint(result['fig_url'])# direct html access# to get back a fig to plotlyfig,meta_obj=client_hoster.download_fig('<slug>')Alternative usageThis service is backed by minio which is fully AWS S3 compatible.
Thus if you would like more extensive features you can use theboto3package.The hosting url will then behttps://s3.akheaten.eu/BUCKET_NAME/ITEM_NAME.json
Package: akid
akidis a python package written for doing research in Neural Network (NN). It
also aims to be production ready by taking care of concurrency and
communication in distributed computing (which depends on the utilities provided
byPyTorchandTensorflow). It
could be seen as a user friendly front-end to torch, or tensorflow, likeKeras. It grows out of the motivation to reuse my old
code, and in the long run, to explore alternative framework for building NN. It
supports two backends, i.e., Tensorflow and Pytorch. If combining withGlusterFS,DockerandKubernetes, it is able to provide dynamic and elastic
scheduling, auto fault recovery and scalability (which is not to brag
the capability ofakid, since the features are not features ofakidbut
features thanks to open source (and libre software), but to mention the
possibilities that they can be combined.).Seehttp://akid.readthedocs.io/en/latest/index.htmlfor documentation. The
document is dated, and has not been updated to include new changes e.g., the
PyTorch backend. But the backbone design is the same, and main features are
there.NOTE: the PyTorch end support has been way ahead of Tensorflow support now ...
Package: akiFlagger
AKIFlaggerIntroductionAcute Kidney Injury (AKI) is a sudden onset of kidney failure and damage marked by an increase in the serum creatinine levels (amongst other biomarkers) of the patient. Kidney Disease Improving Global Outcomes (KDIGO) has a set of guidelines and standard definitions of AKI:Stage 1: 50% increase in creatinine in < 7 days or 0.3 increase in creatinine in < 48 hoursStage 2: 100% increase in (or doubling of) creatinine in < 48 hoursStage 3: 200% increase in (or tripling of) creatinine in < 48 hoursThis package contains a flagger to determine if a patient has developed AKI based on longitudinal data of serum creatinine measurements. More information about the specific data input format can be found in the documentation under theGetting Startedsection.InstallationYou can install the flagger withpip. Simply type the following into command line and the
package should install properly.pipinstallakiFlaggerTo ensure that it is working properly, you can open a Python session and test it with.importakiFlaggerprint(akiFlagger.__version__)>>'1.0.0'Alternatively, you can download the source and wheel files to build manually fromhttps://pypi.org/project/akiFlagger/.Getting startedThere is awalk-through notebookavailable on Github to introduce the necessary components and parameters of the flagger. The notebook can be accessed via Google Colab notebooks. The notebook has also been adapted in thedocumentation.Change LogVersion 0.1.x- Function-based implementation of flagger.Version 0.2.x- Switched to class-based implementation (OOP approach).Version 0.3.x- Switched to single-column output for AKI column.Version 0.4.x- Removed encounter and admission as optional columns.
Package: akilan
AKILAN :Image Classification EngineAkilan is a Python library for quick image classification usingTensorFlow. It is a wrapper aroundTensorFlow'stf.keraslibrary. It is designed to be easy to use and easy to understand. The library is currently in development and is not yet ready for use. The library usesnumpy,pandas,matplotlibandseabornfor data manipulation and visualization. The library is written in Python 3.6. It is tested on windows and linux.InstallationUse the package managerpipto install the library.pipinstallakilanUsageimportICE# Convert directory into dataframedf=ICE.dir_to_df(path)# Create train and test dataframestrain_df,test_df=ICE.split_df(df,test_size=0.2)
Package: akilib
This Library is Hardware Library. and You can buy parts in Japan Akihabara .Akihabara Library =>  akilibhttps://github.com/nonNoise/akilib1.InstallEdison> opkg install python-pip> pip install pip –upgrade> pip install akilibRaspberryPi> sudo apt-get install python-pip> sudo pip install pip –upgrade> sudo pip install akilib1.LibraryEdisonHDC1000       [ AKI_I2C_HDC1000 ]L3GD20        [ AKI_I2C_L3GD20 ]LPS25H        [ AKI_I2C_LPS25H ]LIS3DH        [ AKI_I2C_LIS3DH ]MCP23017      [ AKI_I2C_MCP23017 ]SO1602AWYB    [ AKI_I2C_SO1602AWYB ]S11059        [ AKI_I2C_S11059 ]AQM0802A      [ AKI_I2C_AQM0802A ]AQM1248A      [ AKI_SPI_AQM1248A ]SG12864ASLB   [ AKI_GPIO_SG12864ASLB ]RaspberryPi A+.B+,2B,3B.ZeroAQM0802A      [ AKI_I2C_AQM0802A ]AQM1602A      [ AKI_I2C_AQM1602A ]HDC1000       [ AKI_I2C_HDC1000 ]LPS25H        [ AKI_I2C_LPS25H ]ADT7410       [ AKI_I2C_ADT7410 ]S11059        [ AKI_I2C_S11059 ]SHT31         [ AKI_I2C_SHT31 ]2.LicenseThe MIT License (MIT)
Copyright (c) 2015 Yuta Kitagami (kitagami@artifactnoise.com,@nonnoise)
Package: akima
Akima is a Python library that implements Akima’s interpolation method
described in:A new method of interpolation and smooth curve fitting based on local
procedures. Hiroshi Akima, J. ACM, October 1970, 17(4), 589-602.A continuously differentiable sub-spline is built from piecewise cubic
polynomials. It passes through the given data points and will appear smooth
and natural.This module is no longer being actively developed. Consider usingscipy.interpolate.Akima1DInterpolatorinstead.Author:Christoph GohlkeLicense:BSD 3-ClauseVersion:2024.1.6QuickstartInstall the akima package and all dependencies from thePython Package Index:python -m pip install -U akimaSeeExamplesfor using the programming interface.Source code, examples, and support are available onGitHub.RequirementsThis revision was tested with the following requirements and dependencies
(other versions may work):CPython3.9.13, 3.10.11, 3.11.7, 3.12.1NumPy1.26.3Revisions2024.1.6Add type hints.Remove support for Python 3.8 and 1.22 (NEP 29).2022.9.12Remove support for Python 3.7 (NEP 29).Update metadata.Examples>>> import numpy
>>> from matplotlib import pyplot
>>> from scipy.interpolate import Akima1DInterpolator
>>> def example():
...     '''Plot interpolated Gaussian noise.'''
...     x = numpy.sort(numpy.random.random(10) * 100)
...     y = numpy.random.normal(0.0, 0.1, size=len(x))
...     x2 = numpy.arange(x[0], x[-1], 0.05)
...     y2 = interpolate(x, y, x2)
...     y3 = Akima1DInterpolator(x, y)(x2)
...     pyplot.title('Akima interpolation of Gaussian noise')
...     pyplot.plot(x2, y2, 'r-', label='akima')
...     pyplot.plot(x2, y3, 'b:', label='scipy', linewidth=2.5)
...     pyplot.plot(x, y, 'go', label='data')
...     pyplot.legend()
...     pyplot.show()
>>> example()
Package: akimous
AkimousAkimous is a Python IDE with unique features boosting developers' productivity.FeaturesMachine-learning-assisted/NLP-assisted context-aware auto completionBeautifully rendered function documentationLayered keyboard control (a more intuitive key binding than vim and Emacs)Real-time code formatterInteractive console (integration with IPython kernel)For more information and documentation, visit the official website.InstallationPrerequisitePython 3.7 or 3.8 (with pip)Git (for version control integration)C/C++ compiler (may be required by some dependencies during installation)A modern browserInstalling From PyPIThe recommended way for installing Akimous is through PyPI.pipinstall-UakimousStarting ApplicationStart it in the terminal. The browser should be automatically opened.akimousTo see available arguments, doakimous --help.Using Docker ImageIf you have difficulty installing, or you are running in a cloud environment, try the prebuilt docker image.dockerrun--mounttype=bind,source=$HOME,target=/home/user-p127.0.0.1:3179:3179-itred8012/akimousakimousCommandsStart the app by typing in the terminal (the browser will automatically open if available):akimousOptions--help: show help message and exit.--host HOST: specify the host for Akimous server to listen on. (default to 0.0.0.0 if inside docker, otherwise 127.0.0.1)--port PORT: The port number for Akimous server to listen on. (default=3179)--no-browser: Do not open the IDE in a browser after startup.--verbose: Print extra debug messages.DevelopmentMake sure you have recent version of the following build dependencies installed.Node (12+)Python (3.7+)PoetryYarnMakeZopfliParallelRun the following commands according to your need.make# build everythingmaketest# run testsmakelint# run lintersmakeinstall# (re)install the packageRunningmakewill install all Python and Javascript dependencies listed inpyproject.tomlandui/package.jsonautomatically.ContributingThis program is at pre-alpha stage. Please do report issues if you run into some problems. Contributions of any kind are welcome, including feature requests or pull requests (can be as small as correcting spelling errors) .LicenseBSD-3-ClauseLinksOfficial websitePyPIDocker Hub
Package: akinator
InstallingTo install the regular library without asynchronous support, just run the following command:# Unix / macOSpython3-mpipinstall"akinator"# Windowspy-mpipinstall"akinator"Otherwise, to get asynchronous support, do:# Unix / macOSpython3-mpipinstall"akinator[async]"# Windowspy-mpipinstall"akinator[async]"To get async support plus faster performance (via theaiodnsandcchardetlibraries), do:# Unix / macOSpython3-mpipinstall"akinator[fast_async]"# Windowspy-mpipinstall"akinator[fast_async]"To install the development version, do the following:gitclonehttps://github.com/Infiniticity/akinator.pyRequirementsPython ≥ 3.8.0requestsaiohttp(Optional, for async)aiodnsandcchardet(Optional, for faster performance with async)Usuallypipwill handle these for you.LinksAkinatorDocumentation
Package: akinator.py
Akinator-pyPython bindings forakinator-rs, a wrapper around the undocumented akinator API, made usingpyo3designed for easy implementation of an akinator game in code, providing a simple and easy to use API.InstallationPrebuilt wheels are uploaded onto pypi, if you platform is supported, you can install with:$py-mpipinstallakinator.pyYou can also build from source yourself if you haverustinstalledExamplesrefer to thetestsfor full examples on usageRefer to thedocumentationherefor more information