Saravanan666/pypi-org huggingface dataset:
Package: capsolver-api
Capsolver API for PythonCaptcha solution api for capsolver.comDownloadpython -m pip install capsolver-apiExamplesHcaptchafromcapsolver_apiimportHCaptchaTaskcapsolver=HCaptchaTask('your_capsolver_api_key')task_id=capsolver.create_task(task_type='HCaptchaTaskProxyLess',website_url='https://accounts.hcaptcha.com/demo',website_key='a5f74b19-9e45-40e0-b45d-47ff91b7a6c2')captcha_key=capsolver.get_solution(task_id)print(captcha_key)Funcaptchafromcapsolver_apiimportHCaptchaTaskcapsolver=HCaptchaTask('your_capsolver_api_key')task_id=capsolver.create_task(task_type='HCaptchaTaskProxyLess',website_url='https://accounts.hcaptcha.com/demo',website_key='a5f74b19-9e45-40e0-b45d-47ff91b7a6c2')captcha_key=capsolver.get_solution(task_id)print(captcha_key)RecaptchaV2fromcapsolver_apiimportReCaptchaV2Taskcapsolver=ReCaptchaV2Task('your_capsolver_api_key')task_id=capsolver.create_task(task_type='ReCaptchaV2TaskProxyLess',website_url='https://www.google.com/recaptcha/api2/reload?k=6Le-wvkSAAAAAPBMRTvw0Q4Muexq9bi0DJwx_mJ-',website_key='6Le-wvkSAAAAAPBMRTvw0Q4Muexq9bi0DJwx_mJ-',user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36'# optional)captcha_key=capsolver.get_solution(task_id)print(captcha_key)And others:Cloudflare (Turnstile / Challenge)DatadomeGeetestMtcaptchaOther recognitionsMore information fordocs
Package: capsolver-extension-python
Capsolver Extension PythonCapsolver Extension Python helps you easily use Capsolver Extension in Botasaurus, Selenium, and Playwright.You can easily configure Capsolver with an API key without needing to download the Capsolver Extension, update config files, etc.Installationpython-mpipinstallcapsolver_extension_pythonUsage withBotasaurus Web Scraping Frameworkfrombotasaurusimport*fromcapsolver_extension_pythonimportCapsolver@browser(extensions=[Capsolver(api_key="CAP-MY_KEY")],# TODO: Replace with your own CapSolver Key)defsolve_captcha(driver:AntiDetectDriver,data):driver.get("https://recaptcha-demo.appspot.com/recaptcha-v2-checkbox.php")driver.prompt()solve_captcha()Usage with Seleniumfromseleniumimportwebdriverfromselenium.webdriver.chrome.optionsimportOptionsfromchromedriver_autoinstallerimportinstallfromcapsolver_extension_pythonimportCapsolver# Set Chrome optionsoptions=Options()options.add_argument(Capsolver(api_key="CAP-MY_KEY").load())# TODO: Replace with your own CapSolver Key# Install and set up the driverdriver_path=install()driver=webdriver.Chrome(driver_path,options=options)# Navigate to the desired URLdriver.get("https://recaptcha-demo.appspot.com/recaptcha-v2-checkbox.php")# Prompt for user inputinput("Press Enter to exit...")# Clean updriver.quit()Usage with Playwrightfromplaywright.sync_apiimportsync_playwrightfromcapsolver_extension_pythonimportCapsolverimportrandomdefgenerate_random_profile():returnstr(random.randint(1,1000))withsync_playwright()asp:extension_path=Capsolver(api_key="CAP-MY_KEY").load(with_command_line_option=False)# TODO: Replace with your own CapSolver Keybrowser=p.chromium.launch_persistent_context(user_data_dir=generate_random_profile(),headless=False,args=['--disable-extensions-except='+extension_path,'--load-extension='+extension_path,],)page=browser.new_page()page.goto("https://recaptcha-demo.appspot.com/recaptcha-v2-checkbox.php")input("Press Enter to exit...")browser.close()Love It?Star It ⭐!Become one of our amazing stargazers by giving us a star ⭐ on GitHub!It's just one click, but it means the world to me.
Package: capsolver-python
CapSolver.com package for PythonCapSolver.compackage for Python3Register now fromhere.If you have any problem with usage,read the documentationorcreate an issueInstallationpip install capsolver_pythonSupported captcha typesImage to TextRecaptcha V2Recaptcha V2 EnterpriseRecaptcha V3FunCaptchaHCaptchaGeeTestAntiAkamaiBMPHCaptcha ClassificationDataDome SliderFunCaptcha ClassificationUsage examplesImageToTextfromcapsolver_pythonimportImageToTextTaskcapsolver=ImageToTextTask("API_KEY")task_id=capsolver.create_task(image_path="img.png")result=capsolver.join_task_result(task_id)print(result.get("text"))Recaptcha v2fromcapsolver_pythonimportRecaptchaV2Taskcapsolver=RecaptchaV2Task("API_KEY")task_id=capsolver.create_task("website_url","website_key")result=capsolver.join_task_result(task_id)print(result.get("gRecaptchaResponse"))Recaptcha v2 enterprisefromcapsolver_pythonimportRecaptchaV2EnterpriseTaskcapsolver=RecaptchaV2EnterpriseTask("API_KEY")task_id=capsolver.create_task("website_url","website_key",{"s":"payload value"},"api_domain")result=capsolver.join_task_result(task_id)print(result.get("gRecaptchaResponse"))GeeTestfromcapsolver_pythonimportGeeTestTaskcapsolver=GeeTestTask("API_KEY")task_id=capsolver.create_task("website_url","gt","challenge")result=capsolver.join_task_result(task_id)print(result.get("challenge"))print(result.get("seccode"))print(result.get("validate"))For other examples and api documentation please visitwiki
Package: capsolver-python3
Capsolver Python3Capsolver python3 libraryInstallationUse pip to install the library:pip3install--upgradecapsolver-python3Install from source with:pythonsetup.pyinstallUsageImageToTextfromcapsolver_pythonimportImageToTextTaskcapsolver=ImageToTextTask("API_KEY")task_id=capsolver.create_task(image_path="img.png")result=capsolver.join_task_result(task_id)print(result.get("text"))Recaptcha v2fromcapsolver_pythonimportRecaptchaV2Taskcapsolver=RecaptchaV2Task("API_KEY")task_id=capsolver.create_task("website_url","website_key")result=capsolver.join_task_result(task_id)print(result.get("gRecaptchaResponse"))Recaptcha v2 enterprisefromcapsolver_pythonimportRecaptchaV2EnterpriseTaskcapsolver=RecaptchaV2EnterpriseTask("API_KEY")task_id=capsolver.create_task("website_url","website_key",{"s":"payload value"},"api_domain")result=capsolver.join_task_result(task_id)print(result.get("gRecaptchaResponse"))GeeTestfromcapsolver_pythonimportGeeTestTaskcapsolver=GeeTestTask("API_KEY")task_id=capsolver.create_task("website_url","gt","challenge")result=capsolver.join_task_result(task_id)print(result.get("challenge"))print(result.get("seccode"))print(result.get("validate"))
Package: capstone
To install Capstone, you should runpip install capstone.If you would like to build Capstone with just the source distribution, without
pip, just runpython setup.py installin the folder with setup.py in it.In order to use this source distribution, you will need an environment that can
compile C code. On Linux, this is usually easy, but on Windows, this involves
installing Visual Studio and using the "Developer Command Prompt" to perform the
installation. See BUILDING.txt for more information.By default, attempting to install the python bindings will trigger a build of
the capstone native core. If this is undesirable for whatever reason, for
instance, you already have a globally installed copy of libcapstone, you may
inhibit the build by setting the environment variable LIBCAPSTONE_PATH. The
exact value is not checked, just setting it will inhibit the build. During
execution, this variable may be set to the path of a directory containing a
specific version of libcapstone you would like to use.If you don't want to build your own copy of Capstone, you can use a precompiled
binary distribution from PyPI. Sayingpip install capstoneshould
automatically obtain an appropriate copy for your system. If it does not, please
open an issue athttps://github.com/aquynh/capstoneand tag @rhelmot - she
will fix this, probably!Capstone is a disassembly framework with the target of becoming the ultimate
disasm engine for binary analysis and reversing in the security community.Created by Nguyen Anh Quynh, then developed and maintained by a small community,
Capstone offers some unparalleled features:Support multiple hardware architectures: ARM, ARM64 (ARMv8), Mips, PPC, Sparc,
SystemZ, XCore and X86 (including X86_64).Having clean/simple/lightweight/intuitive architecture-neutral API.Provide details on disassembled instruction (called “decomposer” by others).Provide semantics of the disassembled instruction, such as list of implicit
registers read & written.Implemented in pure C language, with lightweight wrappers for C++, C#, Go,
Java, NodeJS, Ocaml, Python, Ruby & Vala ready (available in main code,
or provided externally by the community).Native support for all popular platforms: Windows, Mac OSX, iOS, Android,
Linux, *BSD, Solaris, etc.Thread-safe by design.Special support for embedding into firmware or OS kernel.High performance & suitable for malware analysis (capable of handling various
X86 malware tricks).Distributed under the open source BSD license.Further information is available athttp://www.capstone-engine.org[License]This project is released under the BSD license. If you redistribute the binary
or source code of Capstone, please attach file LICENSE.TXT with your products.
Package: capstone-project-g5-udd
capstone-projectcapstone projectProject Organization├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │
│   ├── features       <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│   │
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
└── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.ioProject based on thecookiecutter data science project template. #cookiecutterdatascience
Package: capstone-text-mining
CAPSTONE-TEXT-MINING READMEVersion 0.1.2What is it?The Capstone-Text-Mining is a Python package developed for a graduate analytics program capstone project for a specific client. The client is a data analytics consulting and software-as-a-service provider with its own Machine Learning Operations (MLOps) Platform. The client specializes in paid search and marketing analytics.The package allows an end user to apply text mining and natural language processing (NLP) techniques to analyze, evaluate, and identify superior keywords for paid search campaigns. It integrates typical text data cleanup steps, text mining and NLP approaches, and modeling techniques to evaluate the effectiveness of the keywords.Main FeaturesThe package provides the following capabilities:Ability to load paid search campaign data, including keywords, campaign metadata, and outcome metrics (e.g., clickthrough rates)Application of common text data cleaning techniques, including removal of punctuation and stopwords, tokenization, etc.Application of various text mining and NLP techniques to the keywords to develop a variety of features. These methods include:Topic ModelingNamed Entity RecognitionHand Labeling of text featuresGraph model of textSentiment AnalysisRegression and classification model creation using a baseline model (without text mining) and with text mining to estimate the improvement or “lift” the keyword provides in terms an outcome metric (e.g., CTR)Data visualization to evaluate the most impactful text-based features to aid in the analysis and evaluation of keywords. This includes graph and SHAP.Where to get it?The source code is currently hosted on GitHub at:https://github.com/mfligiel/Capstone_Text_MiningThe package can installed from the Python Package Index (PyPI):pip install Capstone_Text_MiningGetting StartedWe recommend sourcing or creating a campaign-level paid search dataset. Each record in the data set should represent a specific campaign and keyword option. Additional level of granularity may be added – e.g., by week, day, channel, etc. In addition to the keyword, each record should have some additional campaign variables to establish a baseline for evaluating the effectiveness of the keyword. The various text mining feature engineering functions may then be applied to the keyword(s) to generate various text-based features for your data set. This data can then be visualized. Models can also be applied to the data to evaluate the effectiveness of the keyword selected.
Package: capstone-windows
NOTE: This package includes prebuilt Windows core of Capstone, so no externalCapstone library is needed.On Windows, download this PyPi package and run "python setup.py install" from"Command Prompt" is all you need to install it.If you want to compile everything from source code instead, use thePyPi package "capstone" instead.https://pypi.python.org/pypi/capstone--------------------------------------------------------------------------------Capstone is a disassembly framework with the target of becoming the ultimatedisasm engine for binary analysis and reversing in the security community.Created by Nguyen Anh Quynh, then developed and maintained by a small community,Capstone offers some unparalleled features:- Support multiple hardware architectures: ARM, ARM64 (ARMv8), Mips, PPC, Sparc,SystemZ, XCore and X86 (including X86_64).- Having clean/simple/lightweight/intuitive architecture-neutral API.- Provide details on disassembled instruction (called “decomposer” by others).- Provide semantics of the disassembled instruction, such as list of implicitregisters read & written.- Implemented in pure C language, with lightweight wrappers for C++, C#, Go,Java, NodeJS, Ocaml, Python, Ruby & Vala ready (available in main code,or provided externally by the community).- Native support for all popular platforms: Windows, Mac OSX, iOS, Android,Linux, *BSD, Solaris, etc.- Thread-safe by design.- Special support for embedding into firmware or OS kernel.- High performance & suitable for malware analysis (capable of handling variousX86 malware tricks).- Distributed under the open source BSD license.Further information is available at http://www.capstone-engine.org[License]This project is released under the BSD license. If you redistribute the binaryor source code of Capstone, please attach file LICENSE.TXT with your products.
Package: capsule
This package is meant to help manage development environments using docker, while providing an interface similar to that of python’s virtualenvwrapper module.Features:Simple cli to create, switch to and delete environments that allow you to fiddle to your heart’s content without breaking anything else.Currently this is based on a clean Ubuntu install (ubuntu:latest docker image) with basic python 2.7 configured.Save your environment to a tarfile in case you want to take it with you anywhere.Export the python history of anything you tried while using the python interpreter within your environment into a JupyterNotebook file that can be used with any Jupyter server (like the jupyter/notebook docker image).
Package: capsule8
Capsule8 api-pythonThis repo is as a wrapper repo around theCapsule8sensor api.Install with pippip install capsule8Install with virtualenvvirtualenv test_capsule8
cd test_capsule8
source bin/activate
pip install capsule8ExamplesIn order to run the examples you need to have a runningcapsule8sensor on your machine. Once you have a running sensor you can run the examples. Be sure that the capsule8 sensor socket chowned by the current user.sudo chown $USER /var/run/capsule8/sensor.sockThen you can run the SensorClient and start streaming capsule8 sensor telemetry. In this example, every process events pid will be printed to stdoutfrom capsule8.sensor import SensorClient
from itertools import islice

s = SensorClient()


s.subscribe({"event_filter": {
    "process_events": [
        {"type": "PROCESS_EVENT_TYPE_FORK"},
        {"type": "PROCESS_EVENT_TYPE_EXEC"},
        {"type": "PROCESS_EVENT_TYPE_EXIT"}
    ]
}})

max_events = 5
for event in islice(s.telemetry(), max_events):
    print(event.events[0].event.process_pid)
Package: capsule-cli
##CapsuleStore and clone the github repositories you like without any commit history.##Installation```pip install capsule_cli```##Usage```usage:Save  your favorite repocapsule <command> <param>These are the commands:-----------------------------------------------------add         Adds a new url record to capsule with namerupture     Clones the urls to the specified directorylist        List all saved repos-h for helppositional arguments:command     Subcommand to runoptional arguments:-h, --help  show this help message and exit```## Instructions```#adding a repocapsule add https://github.com/facebook/react.git#rupture a capsulecapsule rupture react#add helpusage: capsule [-h] [-n NAME] url#rupture helpusage: capsule [-h] [-b BRANCH] [-o OUT] [-d DNAME] name```##LicenseMIT
Package: capsulecrm-python
capsulecrm-pythonCapsule CRM API wrapper written in python.Installingpip install capsulecrm-pythonRequirementsrequestsUsagefrom capsulecrm.client import Client
client = Client(client_id, client_secret)Advanced filtering for parties, organisations and projects# Example:
order_by= [{"field": "addedOn", "direction":"descending"}]
conditions= [{"field":"email", "operator": "is", "value": "juan@mail.com"}]
parties = client.filter_order_data('parties',conditions=conditions, order_by=order_by, page=1, per_page=1)Create Person or Organisationclient.create_person('embed')
client.create_organisation('embed')List Partiesclient.list_parties('since, page, perpage, embed')Create and list Milestoneclient.create_milestone('name, description, probability, complete')
client.list_milestone('page, perpage')Create and List Opportunitiesclient.create_oppotunity('embed')
client.list_opportunities('since, page, perpage, embed')Create and list tasksclient.create_task('embed')
client.list_tasks('since, page, perpage, embed')Create and list tagsclient.create_tag('entity, name, description, datatag')
client.list_tag('entity, page, perpage')List projects, users, countries, currencies and categoriesclient.list_projects('since, page, perpage, embed')
client.list_users()
client.list_countries()
client.list_currencies()
client.list_categories()Get custom Fields by entity (parties, organisations or projects):client.get_custom_fields('entity, page, perpage')TODOshow_partyshow_multiple_partiesupdate_partydelete_partylist_deleted_partieslist_opportunities_by_partyshow_opportunityshow_multiple_opportunitiesupdate_opportunitydelete_opportunitylist_deleted_opportunitieslist_additional_partiesadd_additional_partyremove_additional_partydelete tagshow_tagupdate_tagdelete_milestoneshow_milestoneupdate_milestone
Package: capsules
Python library for depositing a function definition inside a temporary module file (mostly for use with multiprocessing and Jupyter Notebook).Package Installation and UsageThe package is available on PyPI:python -m pip install capsulesThe library can be imported in the usual ways:import capsules
from capsules import capsulesAdding thecapsulesdecorator to a function definition will (1) automatically deposit that definition inside a temporary module file on disk, (2) import that module file, and (3) assign to the variable of the function being defined the function that was imported from that module:@capsules
def double(x):
    return x + xTesting and ConventionsAll unit tests are executed and their coverage is measured when usingnose(seesetup.cfgfor configution details):nosetestsStyle conventions are enforced usingPylint:pylint capsulesContributionsIn order to contribute to the source code, open an issue or submit a pull request on the GitHub page for this library.VersioningThe version number format for this library and the changes to the library associated with version number increments conform withSemantic Versioning 2.0.0.
Package: capsule-terra
capsulecapsule is a small tool with a simple but noble goal; to make deployment of CosmWasm contracts easier.Firstly we are targetingTerraas the Sponsor User chain as we build out the capsule tool. Eventually we aim to make capsule one of the tools of choice for deploying CosmWasm contracts on all chains!InstallationInstall from pypipipinstall-ihttps://test.pypi.org/simple/capsuleWe have published the package also under capsule_terra. This is temporary until a final package namespace is chosen.pipinstall-ihttps://test.pypi.org/simple/capsule_terrapipinstall-ihttps://test.pypi.org/simple/capsule_terraInstall locallyGit clone the project and change into its parent directory.gitclonecdInstall the project using setup tools.pythonsetup.pyinstallAccess the tool using the command line.capsule-hNote: If you have an issue with the above an the command line tool, depending on your platform you will need to prepare a standard distribution and install that. To do so here is two commands together:pythonsetup.pysdist&&pipinstalldist/capsule-0.0.0.tar.gzAvailable Commands and UsageDeploy - Deploy a given cosm wasm contract artifact to a chain of your choicecapsuledeploy-h
usage:$capsuledeploy-p./my_contract.wasm-ccolumbus-5$capsuledeploy--path./artifacts/my_contract.wasm--chaintequila-0004$capsuledeploy--path./artifacts/my_contract.wasm--initmsg{'count':3}HelpertoolwhichenablesyoutoprogramaticallydeployaWasmcontractartifacttoachainasacodeobjectandinstantiateitConfigurationThe capsule tool offers the ability to store details you need in a configuration file using the toml format.The config file by default is located in a capsule specific hidden directory at the home dir level:~/.capsuleIt is possible also to specify the path to a custom config file using theCAPSULE_CONFIG_FILEenvironment variable.Something to be explored is also enabling both the Mnemonic and the chain to deploy too as env vars also. If this was to happen the
order of priority would then become Credentials in the environment -> Config file in the environment -> Default or specified config file.
Following this pattern in theory should make this tool very easy to use in CI/CD as a given user can just specify the Mnemonic and chain ID for as secrets in the job for a quick start.CI/CDThis project uses Github Actions to perform automatic testing on each push and PR as well as a deployment to both test and prod pypi.Some notes:
When deploying to pypi, a version number can only be deployed once! All subsequent deployments will get a 400 and the job will fail.As a procedure we should update the version number when a new deployed build is needed. Or have its patch versions done automatically.Lastly the production build which pushes to Pypi only works with a tagged commit.
Package: captain-hooks
Captain HooksCollection of pre-commit hooksUsageYou can use hooks from this repository to your code by adding the following to
your.pre-commit-config.yamlfile:-repo:https://github.com/abadger/captain-hooksrev:0.2.0# Update using: pre-commit autoupdate --repo https://github.com/abadger/captain-hookshooks:-id:meson-file-list# [...]Provided hooksmeson-file-list: Ensure that meson.build files contain all of the source code files.