How do I run FastAPI tests with Atlas before committing?

You can run your FastAPI tests using Atlas's `bash` tool. Simply execute `pytest` within the Atlas terminal. Atlas supports `httpx AsyncClient` for testing your FastAPI endpoints, allowing you to validate your `path operations` and `Pydantic v2` models before committing any changes.

Can Atlas help me find `print` statements in my FastAPI code?

Yes, Atlas can help you find debugging leftovers. Use Atlas's `grep` tool to search for `print(` or other temporary code like `breakpoint()` within your FastAPI project files, such as `main.py` or `services/`. This ensures your code is clean before it reaches a reviewer or CI.

What happens if I make a mistake in a FastAPI `Pydantic` model with Atlas?

If you make an unwanted change to a `Pydantic v2` model, Atlas's session revert feature allows you to restore your working tree from a previous snapshot. This safely undoes the mistake, ensuring your `models/schema.py` or `main.py` returns to a correct state without manual `git` commands.

Does Atlas support `ruff format` for FastAPI projects?

Absolutely. Atlas integrates with `ruff format` via its `bash` tool. You can run `ruff format` and `ruff check --fix` directly within Atlas to ensure your FastAPI codebase adheres to consistent styling and passes all linting checks defined in your `pyproject.toml`.

How does Atlas ensure my FastAPI changes are safe?

Atlas ensures safety through several mechanisms: permission-gated tool calls, a read-only plan agent that drafts changes, and presenting a unified diff for every file edit for your explicit approval. This means any modification to your FastAPI `main.py` or `dependencies.py` is reviewed by you before being written.

Can Atlas read my `pyproject.toml` for FastAPI configuration?

Yes, Atlas can read your `pyproject.toml` file. Atlas indexes code by AST declarations using tree-sitter, allowing it to understand your project structure and configurations, including those relevant to `uv` for package management or `ruff` for linting in your FastAPI application.

Self-review your working diff before committing in FastAPI with Atlas in 2026

Atlas helps FastAPI developers self-review their uncommitted diffs by integrating directly with the FastAPI toolchain, allowing you to run `pytest (httpx AsyncClient)` tests, apply `ruff format`, and `grep` for debugging leftovers before committing in 2026. This ensures your `main.py` changes are clean and adhere to `Pydantic v2` contracts, preventing issues from reaching reviewers or CI.

How to produce and review FastAPI diffs with Atlas

Atlas in 2026 helps FastAPI developers produce and review their working diffs by integrating with `git` to surface changes across `main.py` and `pyproject.toml`. It allows you to read the entire diff end to end, ensuring no change, even a small one in a `Pydantic v2` model, is overlooked before committing.

When working on a FastAPI project, it is crucial to review every change before committing. Atlas leverages its `bash` tool to execute `git diff` and then uses its `read` tool to present the full working diff directly in your terminal. This comprehensive view ensures you do not miss subtle modifications in files like `main.py`, `routers/user.py`, or `models/item.py`. Unlike relying on memory, Atlas ensures you examine every line of code that has changed, including updates to `Pydantic v2` models, `APIRouter` includes, or `Depends()` injections. This thorough review process is a foundational step in catching self-introduced errors in your FastAPI application.

How to check FastAPI changes against surrounding code

When modifying a FastAPI application in 2026, Atlas helps you check each changed file in full, ensuring your updates to `path operations` or `Depends()` injections align with existing logic. This prevents subtle regressions that a line-by-line diff might hide, especially in complex `uvicorn` setups.

A raw diff can sometimes obscure the full impact of a change by only showing modified lines. Atlas addresses this by allowing you to use its `read` tool to inspect the entire content of any changed file, such as `main.py` or `services/auth.py`. This is vital for FastAPI development, where a small change to a `response_model` in a path operation might have implications for a `Pydantic v2` schema defined elsewhere, or an adjustment to a `Depends()` function could alter the behavior of multiple endpoints. By reviewing the full file, you can verify that your modifications integrate correctly with the surrounding FastAPI idioms and existing application logic, maintaining the integrity of your codebase.

How to grep for debugging leftovers in FastAPI

Before committing your FastAPI changes in 2026, Atlas allows you to `grep` for common debugging leftovers like `print()` statements or `pytest.mark.skip` markers. This ensures your `main.py` or `tests/test_api.py` files are clean of temporary code that could impact production or CI.

Debugging code, while necessary during development, should never make it into a commit. Atlas provides a powerful `grep` tool that you can use to scan your FastAPI project for common debugging artifacts. You can search for `print(`, `breakpoint()`, `pdb.set_trace()`, `// FIXME`, or commented-out blocks of code. Specifically for FastAPI, you might also `grep` for `pytest.mark.skip` or `pytest.mark.xfail` in your `tests/test_api.py` files, ensuring all tests are active. This proactive step, run via Atlas's `bash` tool, helps maintain a clean and production-ready codebase, preventing accidental logging or skipped tests from reaching your CI pipeline or deployment via `uv`.

How to revert unwanted FastAPI changes with Atlas

If you discover an unwanted change in your FastAPI project, Atlas offers a session revert feature that restores from a snapshot, ensuring your `main.py` or `pyproject.toml` returns to a known good state. This process is safe, refusing to run on a busy session to prevent data loss in 2026.

Sometimes, during self-review, you might identify changes that should not be committed, such as an experimental `Pydantic v2` model modification or an incorrect `APIRouter` include. Atlas's session revert feature provides a safe and reliable way to undo these unwanted modifications. Backed by snapshots, this tool can restore your working tree to a previous state, effectively rolling back changes to files like `main.py` or `dependencies.py`. Crucially, Atlas's revert mechanism asserts that the session is not busy, preventing a half-written turn from being rolled back mid-flight and safeguarding your ongoing work in your FastAPI project.

How to run FastAPI tests and linting with Atlas

Atlas enables FastAPI developers to run their `pytest (httpx AsyncClient)` tests and apply `ruff format` directly from the terminal before committing, catching issues in `tests/test_api.py` or `main.py`. This crucial step ensures your code adheres to standards and passes all 100% of your tests in 2026.

A critical part of self-review for any FastAPI project is verifying functionality and code style. Atlas integrates direct with your existing FastAPI toolchain. You can use Atlas's `bash` tool to run your tests with `pytest`, specifically leveraging `httpx AsyncClient` for your API endpoints defined in `main.py` or `routers/`. After tests pass, you can then execute `ruff format` to automatically apply consistent code styling across your project, followed by `ruff check --fix` to address any linting issues. Atlas can iterate on failures, allowing you to fix issues in `tests/test_api.py` or `models/` and re-run checks until your FastAPI code is robust and compliant with your `pyproject.toml` configurations.

Atlas's safety and approval for FastAPI changes

Atlas provides robust safety features for FastAPI development in 2026, including permission-gated tool calls and a unified diff for every file edit. Before any change is written to `main.py` or `models/user.py`, Atlas surfaces it for explicit approval, giving you full control over your codebase.

Atlas is designed with developer safety at its core. Every tool call, whether it is `bash` to run `pytest` or `edit` to modify a `Pydantic v2` model in `models/schema.py`, is permission-gated against allow, ask, and deny rules. Atlas first drafts a plan in a read-only agent, asking for your approval before switching to a build agent to make changes. For every file edit, Atlas computes and surfaces a unified diff for your approval, ensuring you see exactly what will be written to your FastAPI project files. This granular control, combined with session snapshots for easy rollback, means you are always in charge of your FastAPI codebase, even when Atlas is assisting with complex refactors or new feature implementations.

Step by step

01Use Atlas's `bash` tool to run `git diff` and then `read` the entire working diff for your FastAPI project, including changes to `main.py`, `models/item.py`, and `pyproject.toml`.
02For each changed file, use Atlas's `read` tool to inspect the full context, ensuring `Pydantic v2` model updates or `Depends()` injections align with surrounding FastAPI logic and `APIRouter` definitions.
03Employ Atlas's `grep` tool to search for debugging leftovers like `print(` or `pytest.mark.skip` within your FastAPI codebase, specifically checking `tests/test_api.py` and `main.py`.
04If an unwanted change is found, use Atlas's session revert feature to restore from a snapshot, ensuring the session is not busy before rolling back `main.py` or `dependencies.py` modifications.
05Execute your FastAPI tests using Atlas's `bash` tool with `pytest` (leveraging `httpx AsyncClient`) and then run `ruff format` and `ruff check --fix` to ensure code quality and style compliance.
06Approve the unified diff presented by Atlas, confirming all changes to your FastAPI application are correct and ready for commit.

Frequently asked questions

How do I run FastAPI tests with Atlas before committing?: You can run your FastAPI tests using Atlas's `bash` tool. Simply execute `pytest` within the Atlas terminal. Atlas supports `httpx AsyncClient` for testing your FastAPI endpoints, allowing you to validate your `path operations` and `Pydantic v2` models before committing any changes.
Can Atlas help me find `print` statements in my FastAPI code?: Yes, Atlas can help you find debugging leftovers. Use Atlas's `grep` tool to search for `print(` or other temporary code like `breakpoint()` within your FastAPI project files, such as `main.py` or `services/`. This ensures your code is clean before it reaches a reviewer or CI.
What happens if I make a mistake in a FastAPI `Pydantic` model with Atlas?: If you make an unwanted change to a `Pydantic v2` model, Atlas's session revert feature allows you to restore your working tree from a previous snapshot. This safely undoes the mistake, ensuring your `models/schema.py` or `main.py` returns to a correct state without manual `git` commands.
Does Atlas support `ruff format` for FastAPI projects?: Absolutely. Atlas integrates with `ruff format` via its `bash` tool. You can run `ruff format` and `ruff check --fix` directly within Atlas to ensure your FastAPI codebase adheres to consistent styling and passes all linting checks defined in your `pyproject.toml`.
How does Atlas ensure my FastAPI changes are safe?: Atlas ensures safety through several mechanisms: permission-gated tool calls, a read-only plan agent that drafts changes, and presenting a unified diff for every file edit for your explicit approval. This means any modification to your FastAPI `main.py` or `dependencies.py` is reviewed by you before being written.
Can Atlas read my `pyproject.toml` for FastAPI configuration?: Yes, Atlas can read your `pyproject.toml` file. Atlas indexes code by AST declarations using tree-sitter, allowing it to understand your project structure and configurations, including those relevant to `uv` for package management or `ruff` for linting in your FastAPI application.

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