Saravanan666/pypi-org huggingface dataset:
Package: amazonadapi
# amazonadapiClient for the Amazon Ad API# Notes:## The Amazon Ad API pulls only the IDs for each ad tech object.# E.G. client.get_orders('AD_ID') just returns the order IDs.# Take the array of order IDs and call client.get_order('ORDER_ID').#order_ids = client.get_orders('AD_ID')for order_id in order_ids:order = client.get_order(order_id)# FOR ETL or automated job servers, e.g. SMP, use the following to initialize:from amazonadapi import AmazonClientimport osclient = AmazonClient()client.refresh_token = os.environ['AMZN_REFRESH_TOKEN']client.auto_refresh_token()client.set_region()client.get_profiles()client.profile_id = 'BE_SURE_TO_SET_THIS_FOR_YOUR_ORGANIZATION'client.get_advertisers()client.get_orders('AD_ID')client.get_order('ORDER_ID')# Sample code for using browser and command-line to auth:from amazonadapi import AmazonClientclient = AmazonClient()client.cli_auth_dance()client.get_profiles()client.profile_id = 'BE_SURE_TO_SET_THIS'# create an orderorder = AmazonOrder()order.advertiserId = '3678742709207'order.name = 'amazon api test {}'.format(time.time())order.startDateTime = 1511909961000 # unix time * 1000order.endDateTime = 1512514761000   # unix time * 1000hash_order = {"object": {"advertiserId": {"value": order.advertiserId},"name": order.name,"startDateTime": order.startDateTime,"endDateTime": order.endDateTime,"deliveryActivationStatus": order.status}}created_order = client.create_order(hash_order)# create a line itemline_item = AmazonLineItem()line_item.orderId = 'ORDER_ID'line_item.advertiserId = 'AD_ID'line_item.name = 'Test API Line Item Creation'# types: NON_GUARANTEED_DISPLAY,NON_GUARANTEED_MOBILE_APP,NON_GUARANTEED_VIDEOline_item.type = 'NON_GUARANTEED_DISPLAY'line_item.startDateTime = 1506873006000line_item.endDateTime = 1507045806000line_item.status = 'INACTIVE'line_item.budget['amount'] = 100line_item.budget['deliveryProfile'] = 'FRONTLOADED'line_item.budget['deliveryBuffer'] = 1# recurrenceTypes: DAILY, MONTHLY, LIFETIMEline_item.deliveryCaps.append({'amount': 0.9, 'recurrenceType': 'DAILY'})hashline_item = {"object": {"orderId": {"value": line_item.orderId},"advertiserId": {"value": line_item.advertiserId},"name": line_item.name,"type": line_item.type,"startDateTime": line_item.startDateTime,"endDateTime": line_item.endDateTime,"deliveryActivationStatus": line_item.status,"budget" : line_item.budget,"deliveryCaps" : line_item.deliveryCaps}}result = client.create_line_item(hashline_item)client.create_line_item(hashline_item)
Package: amazon-affiliate-scraper
Amazon Affiliate - Scraper ToolQuickstartCreating Affiliate URL:fromamazon_affiliateimportAmazonAffiliatedefmain():amazon_affiliate=AmazonAffiliate(cookies_file_path="path/to/amazon_cookies.json",# Path to Amazon site cookiesorigin_url="https://www.amazon.com.br/",# Amazon root URL in your countrywebdriver_file_path="path/to/webdriver.exe",# Path to browser webdriverheadless=True# If the browser will appear)# Create an affiliate URL like: https://amzn.to/3qAp1rZaffiliate_url=amazon_affiliate.create_affiliate_url("https://www.amazon.com.br/Introdu%C3%A7%C3%A3o-Programa%C3%A7%C3%A3o-com-Python-Algoritmos/dp/8575227181/?_encoding=UTF8&pd_rd_w=cLgOh&content-id=amzn1.sym.142cf30d-cd8e-4f67-a147-740799e27bf0&pf_rd_p=142cf30d-cd8e-4f67-a147-740799e27bf0&pf_rd_r=Q5SHBAZH69HSPBRR2MGS&pd_rd_wg=98FtW&pd_rd_r=ffa375c6-01c9-4e9c-9f87-2aef974a89af&ref_=pd_gw_ci_mcx_mr_hp_atf_m")print(affiliate_url)if__name__=="__main__":main()
Package: amazon-affiliate-url
amazon_affiliate_urlInstallpipinstallamazon_affiliate_url
or
pip3installamazon_affiliate_urlUsagefromamazon_affiliate_urlimportAmazonAffiliateUrl,CountryASIN='SOME_ASIN'TAG='YOUR_AFFILIATE_TAG'BITLY_TOKEN='YOUR_BITLY_TOKEN'print(AmazonAffiliateUrl.url_cls(asin_or_url=ASIN,affiliate_tag=TAG,# bitly_token=BITLY_TOKEN,# shorten_url=True,country=Country.Netherlands))
Package: amazon-bedrock-haystack
amazon-bedrock-haystackTable of ContentsInstallationContributingLicenseInstallationpip install amazon-bedrock-haystackContributinghatchis the best way to interact with this project, to install it:pipinstallhatchWithhatchinstalled, to run all the tests:hatch run testNote: there are no integration tests for this project.To run the lintersruffandmypy:hatch run lint:allLicenseamazon-bedrock-haystackis distributed under the terms of theApache-2.0license.
Package: amazon-braket-algorithm-library
Amazon Braket Algorithm LibraryThe Braket Algorithm Library provides Amazon Braket customers with pre-built implementations of prominent quantum algorithms and experimental workloads as ready-to-run example notebooks.Currently, Braket algorithms are tested on Linux, Windows, and Mac.Running notebooks locally requires additional dependencies located innotebooks/textbook/requirements.txt. See notebooks/textbook/README.md for more information.Installing the Amazon Braket Algorithm LibraryThe Amazon Braket Algorithm Library can be installed from source by cloning this repository and running a pip install command in the root directory of the repository.gitclonehttps://github.com/amazon-braket/amazon-braket-algorithm-library.gitcdamazon-braket-algorithm-library
pipinstall.To run the notebook examples locally on your IDE, first, configure a profile to use your account to interact with AWS. To learn more, seeConfigure AWS CLI.After you create a profile, use the following command to set theAWS_PROFILEso that all future commands can access your AWS account and resources.exportAWS_PROFILE=YOUR_PROFILE_NAMEConfigure your AWS account with the resources necessary for Amazon BraketIf you are new to Amazon Braket, onboard to the service and create the resources necessary to use Amazon Braket using theAWS console.SupportIssues and Bug ReportsIf you encounter bugs or face issues while using the algorithm library, please let us know by posting
the issue on ourGitHub issue tracker.For other issues or general questions, please ask on theQuantum Computing Stack Exchangeand add the tag amazon-braket.Feedback and Feature RequestsIf you have feedback or features that you would like to see on Amazon Braket, we would love to hear from you!GitHub issuesis our preferred mechanism for collecting feedback and feature requests, allowing other users
to engage in the conversation, and +1 issues to help drive priority.LicenseThis project is licensed under the Apache-2.0 License.
Package: amazon-braket-build-tools
Braket Build ToolsInstalling the Amazon Braket Build ToolsThe Amazon Braket Build Tools can be installed with pip as follows:pipinstallamazon-braket-build-toolsYou can also install from source by cloning this repository and running a pip install command in the root directory of the repository:gitclonehttps://github.com/aws/amazon-braket-build-tools.gitcdamazon-braket-build-tools
pipinstall.Flake8 Checkstyle PluginThis tool checks python source code for Braket checkstyle standards as a Flake8 plugin.
Installing amazon-braket-build-tools automatically registers this plugin with flake8 and
will be run by default whenever flake8 is used.Testing The InstallationTo test if the extension has been installed run:flake8--enable-extensions=BCS--helpAt the bottom of the output you should see braket checkstyle among your installed plugins:Installed plugins: braket.flake8_plugins.braket_checkstyle_plugin: 0.1.0RunningTo run with the extension enabled, just run flake8 on the module of your choice.
For example:flake8--enable-extensions=BCSsrcSecuritySeeCONTRIBUTINGfor more information.LicenseThis project is licensed under the Apache-2.0 License.
Package: amazon-braket-default-simulator
Amazon Braket Default SimulatorThe Amazon Braket Default Simulator is a Python open source library that provides an implementation of a quantum simulator
that you can run locally. You can use the simulator to test quantum tasks that you construct for theAmazon Braket SDKbefore you submit them to the Amazon Braket service for execution.Setting up Amazon Braket Default Simulator PythonYou must have theAmazon Braket SDKinstalled to use the local simulator.
Follow the instructions in theREADMEfor setup.Checking the version of the default simulatorYou can check your currently installed version ofamazon-braket-default-simulatorwithpip show:pipshowamazon-braket-default-simulatoror alternatively from within Python:>>> from braket import default_simulator
>>> default_simulator.__version__UsageThe quantum simulator implementationsStateVectorSimulatorandDensityMatrixSimulatorplug into theLocalSimulatorinterface inAmazon Braket SDK, with thebackendparameters as"braket_sv"and"braket_dm", respectively.
Alternatively, to useStateVectorSimulator, you can instantiateLocalSimulatorwith no arguments or withbackend="default":Executing a circuit using the default simulatorfrombraket.circuitsimportCircuitfrombraket.devicesimportLocalSimulatordevice=LocalSimulator()bell=Circuit().h(0).cnot(0,1)print(device.run(bell,shots=100).result().measurement_counts)DocumentationDetailed documentation, including the API reference, can be found onRead the DocsTo generate the API Reference HTML in your local environmentFirst, install tox:pipinstalltoxTo generate the HTML, first change directories (cd) to position the cursor in theamazon-braket-default-simulator-pythondirectory. Then, run the following command to generate the HTML documentation files:tox-edocsTo view the generated documentation, open the following file in a browser:../amazon-braket-default-simulator-python/build/documentation/html/index.htmlTestingIf you want to contribute to the project, be sure to run unit tests and get a successful result
before you submit a pull request. To run the unit tests, first install the test dependencies using the following command:pipinstall-e"amazon-braket-default-simulator-python[test]"To run the unit tests:tox-eunit-testsYou can also pass in various pytest arguments to run selected tests:tox-eunit-tests--your-argumentsFor more information, please seepytest usage.To run linters and doc generators and unit tests:toxTo run the performance tests:tox-eperformance-testsThese tests will compare the performance of a series of simulator executions for your changes against the latest commit on the main branch.Note: The execution times for the performance tests are affected by the other processes running on the system.
In order to get stable results, stop other applications when running these tests.LicenseThis project is licensed under the Apache-2.0 License.
Package: amazon-braket-default-simulator-kshitijc
Amazon Braket Default SimulatorThe Amazon Braket Default Simulator is a Python open source library that provides an implementation of a quantum simulator
that you can run locally. You can use the simulator to test quantum tasks that you construct for theAmazon Braket SDKbefore you submit them to the Amazon Braket service for execution.Setting up Amazon Braket Default Simulator PythonYou must have theAmazon Braket SDKinstalled to use the local simulator.
Follow the instructions in theREADMEfor setup.Checking the version of the default simulatorYou can check your currently installed version ofamazon-braket-default-simulatorwithpip show:pipshowamazon-braket-default-simulatoror alternatively from within Python:>>> from braket import default_simulator
>>> default_simulator.__version__UsageThe quantum simulator implementationsStateVectorSimulatorandDensityMatrixSimulatorplug into theLocalSimulatorinterface inAmazon Braket SDK, with thebackendparameters as"braket_sv"and"braket_dm", respectively.
Alternatively, to useStateVectorSimulator, you can instantiateLocalSimulatorwith no arguments or withbackend="default":Executing a circuit using the default simulatorfrombraket.circuitsimportCircuitfrombraket.devicesimportLocalSimulatordevice=LocalSimulator()bell=Circuit().h(0).cnot(0,1)print(device.run(bell,shots=100).result().measurement_counts)DocumentationDetailed documentation, including the API reference, can be found onRead the DocsTo generate the API Reference HTML in your local environmentFirst, install tox:pipinstalltoxTo generate the HTML, first change directories (cd) to position the cursor in theamazon-braket-default-simulator-pythondirectory. Then, run the following command to generate the HTML documentation files:tox-edocsTo view the generated documentation, open the following file in a browser:../amazon-braket-default-simulator-python/build/documentation/html/index.htmlTestingIf you want to contribute to the project, be sure to run unit tests and get a successful result
before you submit a pull request. To run the unit tests, first install the test dependencies using the following command:pipinstall-e"amazon-braket-default-simulator-python[test]"To run the unit tests:tox-eunit-testsYou can also pass in various pytest arguments to run selected tests:tox-eunit-tests--your-argumentsFor more information, please seepytest usage.To run linters and doc generators and unit tests:toxTo run the performance tests:tox-eperformance-testsThese tests will compare the performance of a series of simulator executions for your changes against the latest commit on the main branch.Note: The execution times for the performance tests are affected by the other processes running on the system.
In order to get stable results, stop other applications when running these tests.LicenseThis project is licensed under the Apache-2.0 License.
Package: amazon-braket-qrack-cuda-simulator
Amazon Braket (SDK) Qrack SimulatorThis is an Amazon Braket SDK back end for the open-sourceunitaryfund/qracksimulator. (PyQrackprovides pure Python language bindings from C++ Qrack.) This simulator can be run locally, via either a (vendor-agnostic) OpenCL implementation or a (NVIDIA-specific) CUDA implementation. (CPU-only local simulation is also supported, when compiling and installing Qrack from source.) You can use the simulator to test quantum tasks that you construct for theAmazon Braket SDKbefore you submit them to the Amazon Braket service for execution.Setting up Amazon Braket Qrack Simulator PythonInstalling this package will install theAmazon Braket SDK, necessary to use the local simulator.
For manual installation of the SDK, follow the instructions in theREADMEfor setup.Checking the version of the Qrack simulatorYou can check your currently installed version ofamazon-braket-qrack-simulatorwithpip show:pipshowamazon-braket-qrack-simulatoror alternatively from within Python:>>> from braket import qrack_simulator
>>> qrack_simulator.__version__UsageThe quantum simulator implementationBraketQrackSimulatorplugs into theLocalSimulatorinterface inAmazon Braket SDK, with thebackendparameter as"qrack".Executing a circuit using the default simulatorfrombraket.circuitsimportCircuitfrombraket.devicesimportLocalSimulatordevice=LocalSimulator(backend="qrack")bell=Circuit().h(0).cnot(0,1)print(device.run(bell,shots=100).result().measurement_counts)DocumentationBraketQrackSimulatorfollows a subset of theAmazon Braket SDKdefault simulator input and output interfaces. Detailed documentation for the default simulator, including the API reference, can be found onRead the Docs.To generate the API Reference HTML in your local environmentFirst, install tox:pipinstalltoxTo generate the HTML, first change directories (cd) to position the cursor in theamazon-braket-qrack-simulator-pythondirectory. Then, run the following command to generate the HTML documentation files:tox-edocsTo view the generated documentation, open the following file in a browser:../amazon-braket-qrack-simulator-python/build/documentation/html/index.htmlTestingIf you want to contribute to the project, be sure to run unit tests and get a successful result
before you submit a pull request. To run the unit tests, first installpytest, if necessary:pipinstallpytestWith pytest installed, use this command in theamazon-braket-qrack-simulator-pythondirectory:pytest.LicenseThis project is licensed under the Apache-2.0 License.
Package: amazon-braket-qrack-simulator
Amazon Braket (SDK) Qrack SimulatorThis is an Amazon Braket SDK back end for the open-sourceunitaryfund/qracksimulator. (PyQrackprovides pure Python language bindings from C++ Qrack.) This simulator can be run locally, via either a (vendor-agnostic) OpenCL implementation or a (NVIDIA-specific) CUDA implementation. (CPU-only local simulation is also supported, when compiling and installing Qrack from source.) You can use the simulator to test quantum tasks that you construct for theAmazon Braket SDKbefore you submit them to the Amazon Braket service for execution.Setting up Amazon Braket Qrack Simulator PythonInstalling this package will install theAmazon Braket SDK, necessary to use the local simulator.
For manual installation of the SDK, follow the instructions in theREADMEfor setup.Checking the version of the Qrack simulatorYou can check your currently installed version ofamazon-braket-qrack-simulatorwithpip show:pipshowamazon-braket-qrack-simulatoror alternatively from within Python:>>> from braket import qrack_simulator
>>> qrack_simulator.__version__UsageThe quantum simulator implementationBraketQrackSimulatorplugs into theLocalSimulatorinterface inAmazon Braket SDK, with thebackendparameter as"qrack".Executing a circuit using the default simulatorfrombraket.circuitsimportCircuitfrombraket.devicesimportLocalSimulatordevice=LocalSimulator(backend="qrack")bell=Circuit().h(0).cnot(0,1)print(device.run(bell,shots=100).result().measurement_counts)DocumentationBraketQrackSimulatorfollows a subset of theAmazon Braket SDKdefault simulator input and output interfaces. Detailed documentation for the default simulator, including the API reference, can be found onRead the Docs.To generate the API Reference HTML in your local environmentFirst, install tox:pipinstalltoxTo generate the HTML, first change directories (cd) to position the cursor in theamazon-braket-qrack-simulator-pythondirectory. Then, run the following command to generate the HTML documentation files:tox-edocsTo view the generated documentation, open the following file in a browser:../amazon-braket-qrack-simulator-python/build/documentation/html/index.htmlTestingIf you want to contribute to the project, be sure to run unit tests and get a successful result
before you submit a pull request. To run the unit tests, first installpytest, if necessary:pipinstallpytestWith pytest installed, use this command in theamazon-braket-qrack-simulator-pythondirectory:pytest.LicenseThis project is licensed under the Apache-2.0 License.
Package: amazon-braket-schemas
Amazon Braket Python SchemasAmazon Braket Python Schemas is an open source library that contains the schemas for Braket, including:intermediate representations (IR) for Amazon Braket quantum tasks and offers serialization and deserialization of those IR payloads. Think of the IR as the contract between the Amazon Braket SDK and Amazon Braket API for quantum programs.schemas for the S3 results of each quantum taskschemas for the device capabilities of each deviceInstallationPrerequisitesPython 3.9+StepsThe preferred way to get Amazon Braket Python Schemas is by installing theAmazon Braket Python SDK, which will pull in the schemas.
Follow the instructions in theREADMEfor setup.However, if you only want to use the schemas, it can be installed on its own as follows:pipinstallamazon-braket-schemasYou can install from source by cloning this repository and running a pip install command in the root directory of the repository:gitclonehttps://github.com/amazon-braket/amazon-braket-schemas-python.gitcdamazon-braket-schemas-python
pipinstall.You can check your currently installed version ofamazon-braket-schemaswithpip show:pipshowamazon-braket-schemasor alternatively from within Python:>>> import braket._schemas as braket_schemas
>>> braket_schemas.__version__UsageOpenQASM (Open Quantum Assembly Language) is one type of IR. See below for its usage.Serializing python structuresfrombraket.ir.openqasmimportProgramasOpenQASMProgramprogram=OpenQASMProgram(source="OPENQASM 3.0; cnot $0, $1;")print(program.json(indent=2))"""{"braketSchemaHeader": {"name": "braket.ir.openqasm.program","version": "1"},"source": "OPENQASM 3.0; cnot $0, $1;","inputs": null}"""Deserializing into python structuresfrombraket.ir.openqasmimportProgramasOpenQASMProgramopenqasm_string="""{"braketSchemaHeader": {"name": "braket.ir.openqasm.program","version": "1"},"source": "OPENQASM 3.0; cnot $0, $1;"}"""program=OpenQASMProgram.parse_raw(openqasm_string)print(program)"""braketSchemaHeader=BraketSchemaHeader(name='braket.ir.openqasm.program', version='1') source='OPENQASM 3.0; cnot $0, $1;' inputs=None"""DocumentationDetailed documentation, including the API reference, can be found onRead the Docs.You can also generate the docs from source. First, install tox:pipinstalltoxTo build the Sphinx docs, run the following command in the root repo directory:tox-edocsYou can then find the generated HTML files inbuild/documentation/html.TestingMake sure to install test dependencies first:pipinstall-e"amazon-braket-schemas-python[test]"To run the unit tests:tox-eunit-testsYou can also pass in various pytest arguments to run selected tests:tox-eunit-tests--your-argumentsTo run linters and doc generators and unit tests:toxFor more information, please seepytest usage.LicenseThis project is licensed under the Apache-2.0 License.
Package: amazon-buddy
amazon_buddyDescriptionAmazon scraper.Installpipinstallamazon_buddy# orpip3installamazon_buddyUsagefromamazon_buddyimportProduct,AmazonBuddy,Category,SortTypeab=AmazonBuddy(debug=True,user_agent='ADD_USER_AGENT')# # products = ab.search_products(# #     'face wash',# #     sort_type=SortType.PRICE_HIGH_TO_LOW,# #     min_price=0,# #     category=Category.BEAUTY_AND_PERSONAL_CARE,# #     max_results=20# # )# # print(len(products))asin='B07RZV9LB7'# # reviews = ab.get_reviews(asin=asin)# # print(reviews)ab.get_product_details(asin).save('{}.json'.format(asin))# ab.get_product_details(asin).jsonprint()# Product.load('/Users/kristofk/github/py_amazon_buddy/B0758GYJK2.json').jsonprint()
Package: amazoncaptcha-api
DescriptionSimpleanti-captcha.comcompatable API (createTask/getTaskResult) to solve the Amazon's text captcha for free.InstallationUse the package managerpipto install amazoncaptcha-apipip3installamazoncaptcha-apiorgitclonehttps://github.com/melehin/amazoncaptcha-apicdamazoncaptcha-api
pip3install.RunUnder flask development server (bind local ip)python3-mamazoncaptcha_apiUnder supervisor and gunicorn (bind external ip)Put this snippet to/etc/supervisor/conf.d/amazoncaptcha_api.conf[program:amazoncaptcha_api]
directory=/tmp/
command=gunicorn amazoncaptcha_api:app -b 0.0.0.0:5000
autostart=true
autorestart=true
stderr_logfile=/var/log/amazoncaptcha_api.err.log
stdout_logfile=/var/log/amazoncaptcha_api.out.logAnd runsupervisorctlreloadContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.LicenseMIT