Go-Code-Large Corpus
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- mit
- Source / creator
- ajibawa-2023/Go-Code-Large
- Collection method
- Per the publisher, the corpus is a curated collection of Go source code aggregated to focus on idiomatic Go covering concurrent programming, distributed systems, and modern backend patterns. The dataset is distributed as JSONL with one code sample per line. The publisher does not document the exact crawl/source provenance or deduplication strategy in detail.
- Coverage start
- Not documented
- Coverage end
- Not documented
- Data last updated
- Not documented
- Update schedule
- Not documented
Source does not document the collection pipeline, deduplication, license auditing of underlying Go files, or filtering criteria in detail; buyers should validate empirically. Go-only (no multi-language coverage). Potential overlap with publicly scraped GitHub Go code, which may include code under varied upstream licenses despite the dataset's MIT wrapper — downstream users training models should perform their own license/PII review. No train/test split or contamination check against common code benchmarks (HumanEval, MBPP, etc.) is provided.
Sample structure score: 100 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (JSON) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 50 / 50 | 20 of 20 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 20 of 20 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| code | 0 / 10 | string | 0 / 10 |
| language | 0 / 10 | string | 0 / 10 |
About this data
Curated collection of Go source code samples in JSONL format, designed for LLM pretraining, code generation fine-tuning, and static analysis research on cloud-native and backend systems.
Retrieve with your agent or Python
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Download the Python examplepython3 retrieve-dataset.py 8d376b8a-a3ee-4ffd-88c0-8b3573c5af62 --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| code | VARCHAR | Go source code sample as a string, may contain complete files or code snippets with comments and imports |
| language | VARCHAR | Programming language identifier; value is 'Go' for all records in this dataset |
Sample Data
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