> ## 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.

# Find Duplicate File in System Python Solution

> Tested Python solution for LeetCode 609 with 16 pytest cases. Generate a practice environment with lcpy.

LeetCode 609, [Medium](/catalog/medium). Topics: [Array](/catalog/topics/array), [Hash Table](/catalog/topics/hash-table), [String](/catalog/topics/string). [View on LeetCode](https://leetcode.com/problems/find-duplicate-file-in-system/description/).

Generate this problem as a practice environment: tested reference solution, 16 [parametrized pytest cases](/practice/testing), and a playground notebook:

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
lcpy gen -n 609   # by problem number
lcpy gen -s find_duplicate_file_in_system   # by problem name
```

## Problem

Given a list `paths` of directory info, including the directory path, and all the files with contents in this directory, return *all the duplicate files in the file system in terms of their paths*. You may return the answer in **any order**.

A group of duplicate files consists of at least two files that have the same content.

A single directory info string in the input list has the following format:

```
"root/d1/d2/.../dm f1.txt(f1_content) f2.txt(f2_content) ... fn.txt(fn_content)"
```

It means there are `n` files `(f1.txt, f2.txt ... fn.txt)` with content `(f1_content, f2_content ... fn_content)` respectively in the directory `root/d1/d2/.../dm`. Note that `n >= 1` and `m >= 0`. If `m = 0`, it means the directory is just the root directory.

The output is a list of groups of duplicate file paths. For each group, it contains all the file paths of the files that have the same content. A file path is a string that has the following format:

```
"directory_path/file_name.txt"
```

### Examples

```
Input: paths = ["root/a 1.txt(abcd) 2.txt(efgh)","root/c 3.txt(abcd)","root/c/d 4.txt(efgh)","root 4.txt(efgh)"]
Output: [["root/a/2.txt","root/c/d/4.txt","root/4.txt"],["root/a/1.txt","root/c/3.txt"]]
```

```
Input: paths = ["root/a 1.txt(abcd) 2.txt(efgh)","root/c 3.txt(abcd)","root/c/d 4.txt(efgh)"]
Output: [["root/a/2.txt","root/c/d/4.txt"],["root/a/1.txt","root/c/3.txt"]]
```

### Constraints

* `1 <= paths.length <= 2 * 10^4`
* `1 <= paths[i].length <= 3000`
* `1 <= sum(paths[i].length) <= 5 * 10^5`
* `paths[i]` consist of English letters, digits, `'/'`, `'.'`, `'('`, `')'`, and `' '`.
* You may assume no files or directories share the same name in the same directory.
* You may assume each given directory info represents a unique directory. A single blank space separates the directory path and file info.

**Follow up:**

* Imagine you are given a real file system, how will you search files? DFS or BFS?
* If the file content is very large (GB level), how will you modify your solution?
* If you can only read the file by 1kb each time, how will you modify your solution?
* What is the time complexity of your modified solution? What is the most time-consuming part and memory-consuming part of it? How to optimize?
* How to make sure the duplicated files you find are not false positive?

## Solution

Reference implementation from [solution.py on GitHub](https://github.com/wislertt/leetcode-py/blob/main/leetcode/find_duplicate_file_in_system/solution.py), full suite in [test\_solution.py](https://github.com/wislertt/leetcode-py/blob/main/leetcode/find_duplicate_file_in_system/test_solution.py):

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
from collections import defaultdict


class Solution:
    # Time: O(total characters across all paths)
    # Space: O(total characters) for the content-to-paths map
    def find_duplicate(self, paths: list[str]) -> list[list[str]]:
        groups: dict[str, list[str]] = defaultdict(list)
        for info in paths:
            dir_path, _, files = info.partition(" ")
            for token in files.split(" "):
                name, content = token[:-1].split("(", 1)
                groups[content].append(f"{dir_path}/{name}")
        return [group for group in groups.values() if len(group) > 1]
```

## Complexity

| Time | Space |
| - | - |
| O(total characters across all paths) | O(total characters) for the content-to-paths map |

## Tags


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