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"""
Dataset loading script for Fenic 0.4.0 API Documentation.
This script can be used with the Hugging Face datasets library to load the dataset.
"""
import pandas as pd
from datasets import Dataset, DatasetDict, Features, Value, Sequence
def load_fenic_api_dataset(data_dir="."):
"""
Load the Fenic API documentation dataset.
Args:
data_dir: Directory containing the parquet files
Returns:
DatasetDict with three splits: api, hierarchy, and summary
"""
# Load the parquet files
api_df = pd.read_parquet(f"{data_dir}/api_df.parquet")
hierarchy_df = pd.read_parquet(f"{data_dir}/hierarchy_df.parquet")
summary_df = pd.read_parquet(f"{data_dir}/fenic_summary.parquet")
# Convert DataFrames to Hugging Face Datasets
api_dataset = Dataset.from_pandas(api_df)
hierarchy_dataset = Dataset.from_pandas(hierarchy_df)
summary_dataset = Dataset.from_pandas(summary_df)
# Create a DatasetDict
dataset_dict = DatasetDict({
'api': api_dataset,
'hierarchy': hierarchy_dataset,
'summary': summary_dataset
})
return dataset_dict
def get_dataframe_methods(dataset):
"""
Get all DataFrame methods from the dataset.
Args:
dataset: The loaded Fenic API dataset
Returns:
Filtered dataset containing only DataFrame methods
"""
api_data = dataset['api']
# Filter for DataFrame methods
df_methods = []
for item in api_data:
if (item['qualified_name'] and
'fenic.api.dataframe.DataFrame.' in item['qualified_name'] and
item['type'] == 'method' and
item['is_public']):
df_methods.append(item)
return Dataset.from_list(df_methods)
def get_semantic_functions(dataset):
"""
Get all semantic functions from the dataset.
Args:
dataset: The loaded Fenic API dataset
Returns:
Filtered dataset containing only semantic functions
"""
api_data = dataset['api']
# Filter for semantic functions
semantic_funcs = []
for item in api_data:
if (item['qualified_name'] and
'fenic.api.functions.semantic.' in item['qualified_name'] and
item['type'] == 'function'):
semantic_funcs.append(item)
return Dataset.from_list(semantic_funcs)
if __name__ == "__main__":
# Example usage
dataset = load_fenic_api_dataset()
print("Dataset loaded successfully!")
print(f"API entries: {len(dataset['api'])}")
print(f"Hierarchy entries: {len(dataset['hierarchy'])}")
print(f"Summary entries: {len(dataset['summary'])}")
# Get DataFrame methods
df_methods = get_dataframe_methods(dataset)
print(f"\nDataFrame methods found: {len(df_methods)}")
# Get semantic functions
semantic_funcs = get_semantic_functions(dataset)
print(f"Semantic functions found: {len(semantic_funcs)}") |