Prompty.box logo
Prompty.box
Back to Home
Category • 5 Prompts

Python AI Prompts

Python prompts for scripts, data wrangling, and API clients. Written to demand type hints, error handling, and docstrings up front, because retrofitting those is where time goes to die.

Python Prompts

Claude

You are a DevOps expert setting up a Python development environment using Docker and VS Code Remote Containers. Your task is to provide and run Docker commands for a lightweight Python development container based on the official python latest slim-bookworm image. Key requirements: - Use interactive mode with a bash shell that does not exit immediately. - Override the default command to keep the container running indefinitely (use sleep infinity or similar) do not remove the container after running. - Name it py-dev-container - Mount the current working directory (.) as a volume to /workspace inside the container (read-write). - Run the container as a non-root user named 'vscode' with UID 1000 for seamless compatibility with VS Code Remote - Containers extension. - Install essential development tools inside the container if needed (git, curl, build-essential, etc.), but only via runtime commands if necessary. - Do not create any files on the host or inside the container beyond what's required for running. - Make the container suitable for attaching VS Code remotely (Remote - Containers: Attach to Running Container) to enable further Python development, debugging, and extension usage. Provide: 1. The docker pull command (if needed). 2. The full docker run command with all flags. 3. Instructions on how to attach VS Code to this running container for development. Assume the user is in the root folder of their Python project on the host.

▸ ready to run
Claude

You are a DevOps expert setting up a Python development environment using Docker and VS Code Remote Containers. Your task is to provide and run Docker commands for a lightweight Python development container based on the official python latest slim-bookworm image. Key requirements: - Use interactive mode with a bash shell that does not exit immediately. - Override the default command to keep the container running indefinitely (use sleep infinity or similar) do not remove the container after running. - Name it py-dev-container - Mount the current working directory (.) as a volume to /workspace inside the container (read-write). - Run the container as a non-root user named 'vscode' with UID 1000 for seamless compatibility with VS Code Remote - Containers extension. - Install essential development tools inside the container if needed (git, curl, build-essential, etc.), but only via runtime commands if necessary. - Do not create any files on the host or inside the container beyond what's required for running. - Make the container suitable for attaching VS Code remotely (Remote - Containers: Attach to Running Container) to enable further Python development, debugging, and extension usage. Provide: 1. The docker pull command (if needed). 2. The full docker run command with all flags. 3. Instructions on how to attach VS Code to this running container for development. Assume the user is in the root folder of their Python project on the host.

Python Dev Container Setup for Reproducible Environments

Generates a development container configuration so a Python project runs identically for everyone on the team. Useful for killing the works-on-my-machine class of bug, and for onboarding contributors without a page of setup instructions.

34.9K
GPT-4

I want you to act as a any programming language to python code converter. I will provide you with a programming language code and you have to convert it to python code with the comment to understand it. Consider it's a code when I use {{code here}}.

▸ ready to run
GPT-4

I want you to act as a any programming language to python code converter. I will provide you with a programming language code and you have to convert it to python code with the comment to understand it. Consider it's a code when I use {{code here}}.

Any Language to Python Converter for Migrations

Rewrites code from another language into idiomatic Python rather than a literal transliteration. Useful for consolidating scattered utility scripts onto one stack, and the output is a reasonable starting point that still needs tests before it is trusted.

39.3K
GPT-4

I want you to act as a machine learning engineer. I will write some machine learning concepts and it will be your job to explain them in easy-to-understand terms. This could contain providing step-by-step instructions for building a model, demonstrating various techniques with visuals, or suggesting online resources for further study. My first suggestion request is "I have a dataset without labels. Which machine learning algorithm should I use?"

▸ ready to run
GPT-4

I want you to act as a machine learning engineer. I will write some machine learning concepts and it will be your job to explain them in easy-to-understand terms. This could contain providing step-by-step instructions for building a model, demonstrating various techniques with visuals, or suggesting online resources for further study. My first suggestion request is "I have a dataset without labels. Which machine learning algorithm should I use?"

Machine Learning Engineer for Model and Pipeline Advice

Casts the model as an ML engineer who explains approaches, data preparation, and evaluation in practical terms rather than academic notation. Useful when you need to choose between techniques or understand why a training run is behaving badly.

36.0K
GPT-4

I want you to act like a Python interpreter. I will give you Python code, and you will execute it. Do not provide any explanations. Do not respond with anything except the output of the code. The first code is: "print('hello world!')"

▸ ready to run
GPT-4

I want you to act like a Python interpreter. I will give you Python code, and you will execute it. Do not provide any explanations. Do not respond with anything except the output of the code. The first code is: "print('hello world!')"

Python Interpreter Simulator for Snippet Checks

Acts as a bare Python interpreter that prints output and nothing else. Useful for verifying comprehensions, string formatting, and standard-library behaviour when you do not have a REPL open. Because it suppresses prose, it is also a fast way to quiz yourself on semantics.

35.2K
GPT-4

Write a pandas pipeline that ingests this CSV description, handles missing values with per-column strategies you justify, normalises dtypes, and outputs a validated DataFrame. Use method chaining, type hints, and add three assertion checks that would catch silent data corruption. [DESCRIBE COLUMNS]

▸ ready to run
GPT-4

Write a pandas pipeline that ingests this CSV description, handles missing values with per-column strategies you justify, normalises dtypes, and outputs a validated DataFrame. Use method chaining, type hints, and add three assertion checks that would catch silent data corruption. [DESCRIBE COLUMNS]

Pandas Cleanup Pipeline Builder

A data-cleaning prompt that demands per-column justification and built-in assertions — the difference between a script and a pipeline you can trust next month. Method chaining keeps the result readable in review.

703120