4.1K skills · sorted by relevance
Implement or modify Composio's Python SDK, the code used to integrate its features into Python applications. Covers tools, sessions, authentication settings, connected accounts, client integration, and shared models under python/composio.
Install the CARLA Python client into a chosen Python environment using bundled packages or PyPI. The skill checks existing installations, selects a suitable package, and verifies imports and version compatibility with a reachable simulator.
Prepare an isolated Python environment for SageMaker deployments and AWS automation. The skill selects a supported Python version, installs current AWS packages, and checks versions so installation and execution use the same environment.
Create, modify, test, or package Python provider adapters, the components used for framework connections. Work covers framework dependencies, public imports, type inference, and provider metadata within python/providers, with a referenced workflow to consult before changes.
Write Python for n8n Code nodes to transform, filter, aggregate, and validate workflow data. Get guidance on reading input items, returning the required JSON structure, using standard library modules, and avoiding common errors within n8n's Python execution modes.
Choose and run checks for Python SDK changes using nox, Makefile targets, Ruff, mypy, and pytest markers. It supports adding tests, diagnosing CI issues, and checking basic behavior, type inference, and builds.
Answer Python questions and write code using examples fetched from pythonsheets.com. Find patterns for syntax, asynchronous tasks, networking, databases, machine learning, and distributed computing, or use topic-based questions to prepare for Python interviews.
Set up Python projects with uv, manage required packages, and create isolated environments for each project. Covers Python versions, dependency updates, migration from existing tools, and lockfiles that record package versions for repeatable installations.
Run Python through run_shell when execute_code_sandbox fails unexpectedly. The skill explains how to pass multiline code using a heredoc, a shell syntax for inline text, then check standard output and error messages.
Run Python through shell commands when sandbox execution fails because required packages are unavailable. The skill explains short commands, multiline scripts, package checks, and output verification, with examples for creating Excel and Word files.
Run Python through a saved script when execute_code_sandbox or shell_agent repeatedly fails. The workflow writes code to a file, executes it through run_shell, and checks errors and expected outputs such as spreadsheets or documents.
Write, review, and refactor Python code using PEP 8 style conventions, type hints that describe expected data types, and clear error handling. Includes package organization and memory-conscious patterns to support readable, maintainable applications.
Investigate Python bugs by pausing execution, inspecting variables, and stepping through code. Choose between local debugging with pdb or breakpoint(), exception inspection, and connecting debugpy to remote or already running processes.
Set up a Python environment inside the project and install its packages. Follow existing environment tools when present, avoid changing the system Python, and provide commands that work from a fresh shell.
Write small, reproducible Python scripts and run them in a sandbox using execute_python. Check the script's logic and output, then report the actual results or errors while clearly distinguishing executed results from code that has not been run.
Review Python code for common mistakes in error handling, asynchronous operations, type annotations, and tests. Use a practical checklist and correction examples to guide code reviews, investigate bugs, and improve existing implementations.
Develop and verify changes to Apache Beam's Python SDK. Set up a virtual environment, run tests, build installable packages or containers, and run data processing pipelines with the modified SDK.
Diagnose Python script failures by showing error output and exit codes alongside the working directory and file listing. Use these clues to investigate missing files, missing modules, permission errors, or scripts that produce no output.
Package Python apps as Windows installers using Nuitka and Inno Setup. Review compilation settings, remove unnecessary files, and analyze DLLs, shared library files, to reduce package size and improve startup behavior.
Turn Python code into installable libraries or command-line tools. The skill guides project structure, package metadata, dependency settings, building wheel and source archives, and publishing releases to PyPI or private package repositories.
Measure Python execution time and memory use to locate slow or resource-heavy code. Use profiling results to guide improvements in data structures, caching, input and output operations, algorithms, and parallel processing.
Set up a Python project with AWS CDK, a toolkit for defining cloud infrastructure in code. Follow guidance on prerequisites, AWS credentials, virtual environments, dependencies, template generation, deployment preparation, and reviewing changes before deployment.
Add or verify model support in SGLang's Rust processor so chat requests produce the same prompt text and token IDs as Python. Use reference-generated test cases to find differences in tools, reasoning settings, conversation history, and errors.
Prepare Python SDK releases by updating versions, package metadata, pinned dependencies, lockfiles, and build workflows. The skill covers release process changes and publication verification, helping agents handle packaging work within the repository’s release procedures.