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dataset_info:
features:
- name: id
dtype: string
- name: chapter
dtype: string
- name: section
dtype: string
- name: title
dtype: string
- name: source_file
dtype: string
- name: question_markdown
dtype: string
- name: answer_markdown
dtype: string
- name: code_blocks
list:
- name: lang
dtype: string
- name: code
dtype: string
- name: has_images
dtype: bool
- name: image_refs
list: string
splits:
- name: train
num_bytes: 1282175
num_examples: 1016
download_size: 609478
dataset_size: 1282175
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# CLRS Solutions QA
**Short description.**
A compact Q&A dataset distilled from the community-maintained **CLRS solutions** project. Each row contains:
- the exercise **question** (markdown),
- the **answer** (markdown),
- book **chapter/section** metadata,
- optional **code blocks** (language-tagged),
- optional **image references** (relative paths from the source repo).
This set is useful for building retrieval, RAG, tutoring, and evaluation pipelines for classic algorithms & data structures topics.
> ⚠️ **Attribution:** This dataset is **derived** from the open-source repository **[walkccc/CLRS](https://github.com/walkccc/CLRS)** (MIT license). Credit belongs to **@walkccc** and all contributors. This packaging only restructures their content into a machine-friendly format.
---
## Contents & Stats
- **Split(s):** `train`
- **Rows:** ~1,016
- **Source:** Parsed from markdown files in `walkccc/CLRS` (third-edition exercises/solutions)
> Note: A small number of rows reference images present in the original repo (`docs/img/...`). This dataset includes the image *references* (paths) as metadata; actual image files are not bundled here.
---
**Also available (human-readable copies):**
```python
# JSONL
ds_json = load_dataset(
"json",
data_files="hf://datasets/Siddharth899/clrs-qa/data/train.jsonl.gz",
token=True, # needed if the repo is private
)
# CSV
ds_csv = load_dataset(
"csv",
data_files="hf://datasets/Siddharth899/clrs-qa/data/train.csv.gz",
token=True,
)
```
## Data Fields
| Field | Type | Description |
| ------------------- | -------------------------------- | --------------------------------------------------------------------- |
| `id` | `string` | Stable row id composed from chapter/section/title (e.g., `02-2.3-5`). |
| `chapter` | `string` | Chapter number as a zero-padded string (e.g., `"02"`). |
| `section` | `string` | Section identifier as in the source (e.g., `"2.3"` or `"2-1"`). |
| `title` | `string` | Exercise/problem label (e.g., `"2.3-5"` or `"2-1"`). |
| `source_file` | `string` | Original markdown relative path in the source repo. |
| `question_markdown` | `string` | Exercise prompt in markdown. |
| `answer_markdown` | `string` | Solution/answer in markdown (often includes LaTeX). |
| `code_blocks` | `list` of objects `{lang, code}` | Zero or more language-tagged code snippets extracted from the answer. |
| `has_images` | `bool` | Whether this item references images. |
| `image_refs` | `list[string]` | Relative paths to referenced images in the original repo. |
Example `code_blocks` entry:
```json
[
{"lang": "cpp", "code": "INSERTION-SORT(A)\n ..."},
{"lang": "python", "code": "def merge(...):\n ..."}
]
```
---
## Data Construction
* **Source:** [`walkccc/CLRS`](https://github.com/walkccc/CLRS)
* **License upstream:** MIT
* **Method:** A small script parses chapter/section markdown files, extracts headings, prompts, answers, fenced code blocks, and image references, and emits JSONL → uploaded to the Hub (Parquet auto-materialized).
* **Known quirks:**
* Some answers are brief/telegraphic (mirroring the original).
* Image references point to paths in the upstream repo; not all images are bundled here.
* Math is plain markdown with LaTeX snippets (`$...$`, `$$...$$`); rendering depends on your viewer.
---
## License
* **This dataset (packaging)**: MIT
* **Upstream content**: MIT (from `walkccc/CLRS`)
You must preserve the original MIT license notice and attribute **@walkccc** and contributors when using this dataset.
```
MIT License
Copyright (c) walkccc
... (see upstream repository for the full license text)
```
Additionally, include attribution similar to:
> “Portions of the content are derived from walkccc/CLRS (MIT). © The respective contributors.”
---
## Citation
If you use this dataset, please cite both the dataset and the upstream project:
**Dataset (this repo):**
```
@misc{clrs_qa_dataset_2025,
title = {CLRS Solutions QA (walkccc-derived)},
author = {Siddharth899},
year = {2025},
howpublished = {\url{https://huggingface.co/datasets/Siddharth899/clrs-qa}},
note = {Derived from walkccc/CLRS (MIT)}
}
```
**Upstream CLRS solutions:**
```
@misc{walkccc_clrs,
title = {Solutions to Introduction to Algorithms (Third Edition)},
author = {walkccc and contributors},
howpublished = {\url{https://github.com/walkccc/CLRS}},
license = {MIT}
}
```
## Contact & Maintenance
* **Maintainer of this dataset packaging:** @Siddharth899
* Issues / requests: open an issue on the HF dataset repo.
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