Add files using upload-large-folder tool
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README.md
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| 1 |
+
---
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| 2 |
+
tags:
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| 3 |
+
- vector-database
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| 4 |
+
- embeddings
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| 5 |
+
- parquet
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| 6 |
+
- qdrant
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| 7 |
+
- stackoverflow
|
| 8 |
+
- question-answering
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| 9 |
+
pretty_name: StackOverflow Vector Dataset - Python
|
| 10 |
+
license: cc-by-sa-4.0
|
| 11 |
+
size_categories:
|
| 12 |
+
- 1M<n<10M
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
# Python StackOverflow Vector Dataset Datasheet
|
| 16 |
+
|
| 17 |
+
## 1. What This Dataset Is
|
| 18 |
+
|
| 19 |
+
This dataset is the Python-specific vector shard of the Stack2Graph StackOverflow retrieval corpus.
|
| 20 |
+
Each Hugging Face dataset repository contains exactly one language dataset.
|
| 21 |
+
|
| 22 |
+
It is optimized for dense+sparse retrieval, Qdrant restoration, and embedding-based RAG experiments.
|
| 23 |
+
|
| 24 |
+
It is used in the Stack2Graph project as the vector counterpart to the language-scoped RDF knowledge graph shards.
|
| 25 |
+
|
| 26 |
+
See the Stack2Graph repository for more details:
|
| 27 |
+
[https://github.com/tha-atlas/Stack2Graph](https://github.com/tha-atlas/Stack2Graph)
|
| 28 |
+
|
| 29 |
+
## 2. Repository Layout
|
| 30 |
+
|
| 31 |
+
```text
|
| 32 |
+
dataset_manifest.json
|
| 33 |
+
question_metadata_*.parquet
|
| 34 |
+
chunk_records_*.parquet
|
| 35 |
+
question_records_*.parquet
|
| 36 |
+
```
|
| 37 |
+
|
| 38 |
+
- `dataset_manifest.json`: language-scoped manifest for this dataset shard.
|
| 39 |
+
- `question_metadata_*.parquet`: per-question metadata and retrieval bookkeeping.
|
| 40 |
+
- `chunk_records_*.parquet`: chunk-level vector rows when parent-child indexing is enabled.
|
| 41 |
+
- `question_records_*.parquet`: question-level vector rows when chunking is disabled or exported alongside chunk data.
|
| 42 |
+
|
| 43 |
+
## 3. Data Model And Coverage
|
| 44 |
+
|
| 45 |
+
The dataset is derived from Stack Overflow questions selected for the Python programming language.
|
| 46 |
+
It contains the structured records needed to rebuild the Stack2Graph Qdrant collection for that language.
|
| 47 |
+
|
| 48 |
+
Coverage scope:
|
| 49 |
+
|
| 50 |
+
- records are retained when they match the Stack2Graph supported language-tag set
|
| 51 |
+
- this repository contains only the Python shard
|
| 52 |
+
- the archive may contain both metadata-only and retrieval-ready vector rows depending on the export mode
|
| 53 |
+
|
| 54 |
+
## 4. Recommended Preprocessing
|
| 55 |
+
|
| 56 |
+
1. Read `dataset_manifest.json` first and use it as the source of truth for included Parquet files.
|
| 57 |
+
2. Load all Parquet shards for this repository into your vector indexing pipeline.
|
| 58 |
+
3. Rebuild or restore the Qdrant collection `stackoverflow_python_vector`.
|
| 59 |
+
4. Preserve attribution and license metadata during downstream export.
|
| 60 |
+
|
| 61 |
+
## 5. Automatic Download And Vector DB Setup
|
| 62 |
+
|
| 63 |
+
You do not need to regenerate embeddings from GraphDB to use this dataset.
|
| 64 |
+
|
| 65 |
+
In the Stack2Graph repository, you can use the automation script
|
| 66 |
+
`python -m experiment.load_hf_datasets_into_services --skip-kg` to download dataset artifacts
|
| 67 |
+
and prepare the vector database service state automatically.
|
| 68 |
+
|
| 69 |
+
Typical workflow:
|
| 70 |
+
|
| 71 |
+
1. Clone and configure Stack2Graph (`.env` with HF token and service paths).
|
| 72 |
+
1. Clone and configure Stack2Graph (`.env` with HF token and service paths).
|
| 73 |
+
1. Start required local services:
|
| 74 |
+
|
| 75 |
+
```bash
|
| 76 |
+
docker compose up -d
|
| 77 |
+
```
|
| 78 |
+
|
| 79 |
+
1. Run the loader script:
|
| 80 |
+
|
| 81 |
+
```bash
|
| 82 |
+
python -m experiment.load_hf_datasets_into_services --skip-kg
|
| 83 |
+
```
|
| 84 |
+
|
| 85 |
+
For manual usage without automation, directly ingest the listed Parquet files into your vector database.
|
| 86 |
+
|
| 87 |
+
## 6. Quality Notes And Caveats
|
| 88 |
+
|
| 89 |
+
- A Stack Overflow question may belong to multiple language shards when tagged with multiple languages.
|
| 90 |
+
- Embeddings and sparse representations depend on the configured export pipeline and model versions.
|
| 91 |
+
- As with community-generated data, content may include noise, bias, and temporal drift.
|
| 92 |
+
|
| 93 |
+
## 7. Intended Use
|
| 94 |
+
|
| 95 |
+
- semantic retrieval and reranking
|
| 96 |
+
- RAG and hybrid retriever experiments
|
| 97 |
+
- vector database benchmarking and diagnostics
|
| 98 |
+
- language-scoped developer tooling research
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| 99 |
+
|
| 100 |
+
## 8. Limitations
|
| 101 |
+
|
| 102 |
+
- Not a complete mirror of all Stack Overflow content.
|
| 103 |
+
- Not all export modes include the same row types or chunk layouts.
|
| 104 |
+
- Best used together with the Stack2Graph retrieval pipeline and Qdrant-compatible tooling.
|
| 105 |
+
|
| 106 |
+
## 9. Licensing And Attribution
|
| 107 |
+
|
| 108 |
+
This dataset inherits Stack Overflow source licensing and attribution requirements.
|
| 109 |
+
Ensure compliant attribution and redistribution practices in all derived artifacts.
|
| 110 |
+
|
| 111 |
+
## 10. Suggested Citation
|
| 112 |
+
|
| 113 |
+
If you use this dataset, cite the Stack2Graph work:
|
| 114 |
+
|
| 115 |
+
- Stack2Graph: A Structured Knowledge Representation of Stack Overflow Data for Retrieval-based Question Answering
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