64 lines
2.3 KiB
Python
64 lines
2.3 KiB
Python
import re
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from typing import Dict
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import pandas as pd
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def increment_count(d: Dict[str, int], category: str) -> None:
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"""Increment the count of a category in the dictionary.
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Args:
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d (Dict[str, int]): Dictionary storing category counts.
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category (str): The category to increment.
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"""
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d[category] = d.get(category, 0) + 1
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def process_import_lines(file_path: str) -> Dict[str, int]:
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"""Extract and categorize import lines from a Python file.
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Args:
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file_path (str): Path to the Python file.
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Returns:
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Dict[str, int]: Dictionary containing category counts.
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"""
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category_counts = {}
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with open(file_path, "r") as f:
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for line in f:
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if "import" in line:
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module_name = re.sub(r"^.*import ", "", line).strip()
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if module_name.startswith("SNS"):
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increment_count(category_counts, "Seaborn")
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elif module_name.startswith("MPL"):
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increment_count(category_counts, "Matplotlib")
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elif module_name.startswith("Pt"):
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increment_count(category_counts, "PyTorch")
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elif module_name.startswith("Pandas"):
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increment_count(category_counts, "Pandas")
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elif module_name.startswith(("CDA", "Python")):
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increment_count(category_counts, "Misc")
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elif module_name.startswith("Numpy"):
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increment_count(category_counts, "NumPy")
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else:
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increment_count(category_counts, "Misc")
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return category_counts
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def save_category_counts_to_csv(category_counts: Dict[str, int], output_file: str) -> None:
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"""Save category counts as a sorted CSV file.
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Args:
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category_counts (Dict[str, int]): Dictionary containing category counts.
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output_file (str): Path to the output CSV file.
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"""
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df = pd.DataFrame(list(category_counts.items()), columns=["Category", "Count"])
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df = df.sort_values(by=["Count"], ascending=False)
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df.to_csv(output_file, index=False)
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def main() -> None:
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"""Main function to process the import categories and save results."""
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category_counts = process_import_lines("__init__.py")
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save_category_counts_to_csv(category_counts, "node_count_breakdown.csv")
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if __name__ == "__main__":
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main()
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