> ## Documentation Index
> Fetch the complete documentation index at: https://leetcode-py.wisl.dev/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> leetcode-py is a Python LeetCode practice environment generator with one CLI: lcpy. It is not a service or platform.
> Each problem is a directory under leetcode/ with README.md, solution.py, test_solution.py, helpers.py, and playground.ipynb. lcpy gen creates them from JSON templates bundled with the package.
> Examples are backed by tests; copy them verbatim.

# Quickstart

> Generate your first problem, run its tests, and solve it.

From a clean install to a solved problem in five commands.

## 1. Generate a problem

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
lcpy gen -n 1   # Two Sum
```

This creates a `leetcode/two_sum/` directory with a complete, testable
scaffold. You can also generate a whole collection at once:

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
lcpy gen -t grind-75      # all Grind 75 problems
lcpy gen -t neetcode-250  # the full NeetCode 250 roadmap
```

Browse every collection in the [Catalog](/catalog).

## 2. Look at what you got

```
leetcode/two_sum/
├── README.md           # Problem description with examples and constraints
├── solution.py         # Implementation with type hints and TODO placeholder
├── test_solution.py    # Parametrized tests, 10+ cases
├── helpers.py          # Test helper functions
├── playground.py       # Interactive debugging environment
└── __init__.py         # Package marker
```

Every problem has the same shape; see
[Problem Anatomy](/practice/problem-anatomy) for what each file does.

## 3. Run the tests

The tests fail out of the box because `solution.py` is a TODO stub. That is
the point: red, implement, green.

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
cd leetcode/two_sum
python -m pytest test_solution.py
```

## 4. Solve it

Open `solution.py` and replace the TODO with your implementation:

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
class Solution:
    def two_sum(self, nums: list[int], target: int) -> list[int]:
        seen: dict[int, int] = {}
        for i, n in enumerate(nums):
            if target - n in seen:
                return [seen[target - n], i]
            seen[n] = i
        return []
```

## 5. Rerun the tests

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
python -m pytest test_solution.py
```

All green? Move to the next problem. Stuck? Drop into `playground.py` and
inspect your data structures: trees, linked lists, and graphs all render as
diagrams. See [Visualizations](/practice/visualizations).

## Working inside this repository

If you cloned the repo for development, the same loop goes through `bake`:

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
bake p-test -p two_sum   # test one problem
bake p-gen -p two_sum    # regenerate one problem from its JSON template
bake test                # run the whole suite
```

See the [bakefile reference](/contributing/bakefile) for everything else the
runner provides.