Datasets:
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license: apache-2.0
language:
- code
task_categories:
- text-generation
---
# LeetCode multilingual benchmark dataset
LeetCode problems for the msl-multilingual-self-learning benchmark, flattened to
one row per (problem, language) in 9 languages, stored as `data/<split>/<lang>-NNN.jsonl`.
Each row has the `interface` for its `language` (from LeetCode's code snippets),
the shared `canonical_tests` (Python asserts from newfacade/LeetCodeDataset),
the `problem_description` (from the LeetCode page) and `metadata`.
Tests that break the problem's Constraints, do not fit a declared type in some
language, or expect inf/nan were removed; problems that take trees or linked
lists, modify their input in place, or kept fewer than 10 tests were dropped.
The test split also drops problems with several valid answers or whose text
refers to a figure. Where answers may come in any order or are decimals,
the asserts call `answers_match` (defined at the top of the test source), and
`canonical_tests.comparison` says which rule applies ("unordered", "float" or "exact").
`public_tests` holds the inputs of LeetCode's Testcase panel (one string per
case, one JSON value per line in parameter order; LeetCode publishes no
outputs), and `hints` the page's hints as plain text.
`reports/dropped.md` lists every dropped problem and test count, and
`reports/<split>.json` has the details.
## Splits
- `train`: 2103 problems x 9 languages = 18927 rows (2641 in the source dataset)
- `test`: 191 problems x 9 languages = 1719 rows (228 in the source dataset)
## Load
```python
from datasets import load_dataset
train = load_dataset("neulab/leetcode", split="train")
test = load_dataset("neulab/leetcode", split="test")
python_rows = test.filter(lambda r: r["language"] == "python")
```
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