Skip to content
MMake Prompt AI Get Started
Home > ChatGPT Guide > /python
Custom prompt shortcut / Software Development

/python — ChatGPT Prompt Guide

Explore the /python custom ChatGPT prompt shortcut with a practical template, examples, and review steps. Learn how to refine outputs for your workflow.

What does /python do?

Purpose: Process a CSV of monthly expenses.

This is a custom prompt convention, not a built-in or official ChatGPT slash command. Entering the slash text alone does not guarantee that ChatGPT will invoke a special tool. Use the complete structured prompt below or configure your own app to interpret this shortcut.

Key decision for this workflow

Use /python when the task is build a python script that summarizes a local csv expense ledger; specify the evidence needed to accept the result.

Copy-ready task brief

/python Objective: Build a Python script that summarizes a local CSV expense ledger Inputs: CSV header sample, currency format, expected totals and Python version Deliverable: Readable script using csv or pandas with input validation and grouped totals

Reusable prompt template

/python Objective: Build a Python script that summarizes a local CSV expense ledger Available materials: CSV header sample, currency format, expected totals and Python version Required output: Readable script using csv or pandas with input validation and grouped totals Acceptance test: Test empty files, quoted commas, malformed amounts and totals against a hand calculation Boundary: Never execute untrusted spreadsheet formulas or expose financial data in logs Return the requested deliverable first, then a brief verification checklist and any unresolved questions.

How to use this shortcut

  1. Collect the source inputs: CSV header sample, currency format, expected totals and Python version
  2. Run /python with the copy-ready task brief above.
  3. Request the concrete output: Readable script using csv or pandas with input validation and grouped totals
  4. Check the result: Test empty files, quoted commas, malformed amounts and totals against a hand calculation

Quality checks and limitations

Acceptance criteria: Test empty files, quoted commas, malformed amounts and totals against a hand calculation Limitation: Never execute untrusted spreadsheet formulas or expose financial data in logs

Related tools and learning

Continue with the 35 prompt generators, the technical AI Guides, and the Image Guides for deeper examples.

/code/debug/refactor/codeaudit/contentbrief/contentaudit

Worked example: Process a CSV of monthly expenses

Illustrative output: Read columns date, category, amount; reject malformed rows; group by category; print totals and a list of rejected records. Use decimal arithmetic for money.

Review and limitations

Test negative amounts and duplicate rows explicitly.

Worked workflow: Build a Python script that summarizes a local CSV expense ledger

Practical scenario: Build a Python script that summarizes a local CSV expense ledger

Inputs to provide: CSV header sample, currency format, expected totals and Python version

Requested deliverable: Readable script using csv or pandas with input validation and grouped totals

How to verify the result: Test empty files, quoted commas, malformed amounts and totals against a hand calculation

Important limitation: Never execute untrusted spreadsheet formulas or expose financial data in logs

Frequently asked questions

Is /python an official ChatGPT command? No. It is a reusable custom shorthand from this catalog. Does it work without a plugin? You can copy the full prompt into an assistant; automatic slash-command routing requires application logic. Can the output be trusted without review? No. Review accuracy, safety, and suitability before use.