matlok's picture
setting size to 2.35m rows in the dataset in the readme yaml
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metadata
license:
  - other
pretty_name: python copilot large coding dataset
dataset_info:
  - config_name: view_schema
    splits:
      - name: view_schema
configs:
  - config_name: view_schema
    data_files:
      - split: view_schema
        path: files/lok-python-code-large-v1_00000013.parquet
size_categories:
  - 100K<n<1M
  - 1M<n<10M
tags:
  - python-copilot
  - python-coding
  - fine-tuning
  - training
  - alpaca
  - text
  - coding
task_categories:
  - text-generation
task_ids:
  - parsing

Python Copilot Large Coding Dataset

This dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.

Details

Each row contains python code, either a class method or a global function, imported modules, base classes (if any), exceptions (ordered based off the code), returns (ordered based off the code), arguments (ordered based off the code), and more.

  • Rows: 2350782
  • Size: 3.1 GB
  • Data type: text
  • Format: Extracted code using python AST

Schema

{
    "args": "string",
    "class_bases": "string",
    "class_docstr": "string",
    "class_docstr_tok": "string",
    "class_name": "string",
    "code": "string",
    "code_tok": "string",
    "docstr": "string",
    "docstr_tok": "string",
    "file_path": "string",
    "filename": "string",
    "imports": "string",
    "is_member": "bool",
    "label_desc": "string",
    "label_desc_len": "int64",
    "label_id": "string",
    "lend": "int64",
    "lstart": "int64",
    "name": "string",
    "num_all_bases": "float64",
    "num_bases": "float64",
    "num_classes": "float64",
    "num_functions": "int64",
    "num_imports": "int64",
    "num_methods": "float64",
    "raises": "string",
    "returns": "string",
    "total_objects": "int64"
}

How to use the dataset

from datasets import load_dataset

ds = load_dataset("matlok/python-copilot-training-from-many-repos-large", data_dir="files")