Initial commit: sales analysis template
Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Jonathan Pressnell
238
export_utils.py
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238
export_utils.py
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"""
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Export utilities for analysis results
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Provides functions to export DataFrames and summary data to CSV and Excel
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Usage:
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from export_utils import export_to_csv, export_to_excel, export_summary_table
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# Export DataFrame to CSV
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export_to_csv(df, 'results.csv')
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# Export DataFrame to Excel
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export_to_excel(df, 'results.xlsx', sheet_name='Data')
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# Export summary table
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export_summary_table({'Metric1': 100, 'Metric2': 200}, 'summary.xlsx')
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"""
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import pandas as pd
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from pathlib import Path
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from config import REPORTS_DIR, ensure_directories
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def export_to_csv(df, filename, output_dir=None, index=True):
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"""
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Export DataFrame to CSV with proper formatting
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Args:
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df: DataFrame to export
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filename: Output filename (e.g., 'results.csv')
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output_dir: Output directory (defaults to config.REPORTS_DIR)
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index: Whether to include index in export (default: True)
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Returns:
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Path to exported file
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"""
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if output_dir is None:
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output_dir = REPORTS_DIR
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else:
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output_dir = Path(output_dir)
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ensure_directories()
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output_dir.mkdir(exist_ok=True)
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filepath = output_dir / filename
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df.to_csv(filepath, index=index, encoding='utf-8-sig')
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print(f"Exported to CSV: {filepath}")
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return filepath
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def export_to_excel(df, filename, sheet_name='Data', output_dir=None, index=True):
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"""
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Export DataFrame to Excel with formatting
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Args:
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df: DataFrame to export
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filename: Output filename (e.g., 'results.xlsx')
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sheet_name: Excel sheet name (default: 'Data')
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output_dir: Output directory (defaults to config.REPORTS_DIR)
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index: Whether to include index in export (default: True)
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Returns:
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Path to exported file
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Raises:
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ImportError: If openpyxl is not installed
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"""
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try:
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import openpyxl
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except ImportError:
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raise ImportError(
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"openpyxl is required for Excel export. Install with: pip install openpyxl"
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)
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if output_dir is None:
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output_dir = REPORTS_DIR
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else:
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output_dir = Path(output_dir)
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ensure_directories()
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output_dir.mkdir(exist_ok=True)
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filepath = output_dir / filename
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# Create Excel writer
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with pd.ExcelWriter(filepath, engine='openpyxl') as writer:
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df.to_excel(writer, sheet_name=sheet_name, index=index)
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# Auto-adjust column widths
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worksheet = writer.sheets[sheet_name]
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for idx, col in enumerate(df.columns, 1):
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max_length = max(
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df[col].astype(str).map(len).max(),
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len(str(col))
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)
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# Cap at 50 characters for readability
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adjusted_width = min(max_length + 2, 50)
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worksheet.column_dimensions[chr(64 + idx)].width = adjusted_width
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print(f"Exported to Excel: {filepath}")
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return filepath
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def export_summary_table(data_dict, filename, output_dir=None, title=None):
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"""
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Export summary statistics to formatted table (Excel)
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Args:
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data_dict: Dictionary of {metric_name: value} pairs
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filename: Output filename (e.g., 'summary.xlsx')
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output_dir: Output directory (defaults to config.REPORTS_DIR)
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title: Optional title for the summary table
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Returns:
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Path to exported file
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Example:
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export_summary_table({
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'Total Revenue': 1000000,
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'Customer Count': 500,
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'Average Order Value': 2000
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}, 'summary.xlsx')
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"""
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try:
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import openpyxl
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except ImportError:
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raise ImportError(
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"openpyxl is required for Excel export. Install with: pip install openpyxl"
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)
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if output_dir is None:
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output_dir = REPORTS_DIR
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else:
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output_dir = Path(output_dir)
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ensure_directories()
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output_dir.mkdir(exist_ok=True)
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filepath = output_dir / filename
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# Create DataFrame from dictionary
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df = pd.DataFrame({
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'Metric': list(data_dict.keys()),
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'Value': list(data_dict.values())
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})
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# Format numeric values
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def format_value(val):
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if isinstance(val, (int, float)):
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if abs(val) >= 1e6:
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return f"${val / 1e6:.2f}m"
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elif abs(val) >= 1e3:
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return f"${val / 1e3:.2f}k"
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else:
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return f"${val:.2f}"
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return str(val)
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df['Formatted_Value'] = df['Value'].apply(format_value)
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# Create Excel writer
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with pd.ExcelWriter(filepath, engine='openpyxl') as writer:
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df.to_excel(writer, sheet_name='Summary', index=False)
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# Format worksheet
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worksheet = writer.sheets['Summary']
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# Set column widths
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worksheet.column_dimensions['A'].width = 30
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worksheet.column_dimensions['B'].width = 20
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worksheet.column_dimensions['C'].width = 20
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# Add title if provided
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if title:
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worksheet.insert_rows(1)
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worksheet.merge_cells('A1:C1')
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worksheet['A1'] = title
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worksheet['A1'].font = openpyxl.styles.Font(bold=True, size=14)
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worksheet['A1'].alignment = openpyxl.styles.Alignment(horizontal='center')
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print(f"Exported summary table to Excel: {filepath}")
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return filepath
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def export_multiple_sheets(data_dict, filename, output_dir=None):
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"""
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Export multiple DataFrames to Excel with multiple sheets
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Args:
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data_dict: Dictionary of {sheet_name: DataFrame} pairs
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filename: Output filename (e.g., 'results.xlsx')
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output_dir: Output directory (defaults to config.REPORTS_DIR)
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Returns:
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Path to exported file
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Example:
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export_multiple_sheets({
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'Revenue': revenue_df,
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'Customers': customer_df,
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'Products': product_df
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}, 'analysis_results.xlsx')
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"""
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try:
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import openpyxl
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except ImportError:
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raise ImportError(
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"openpyxl is required for Excel export. Install with: pip install openpyxl"
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)
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if output_dir is None:
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output_dir = REPORTS_DIR
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else:
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output_dir = Path(output_dir)
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ensure_directories()
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output_dir.mkdir(exist_ok=True)
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filepath = output_dir / filename
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# Create Excel writer
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with pd.ExcelWriter(filepath, engine='openpyxl') as writer:
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for sheet_name, df in data_dict.items():
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# Truncate sheet name to 31 characters (Excel limit)
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safe_sheet_name = sheet_name[:31]
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df.to_excel(writer, sheet_name=safe_sheet_name, index=True)
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# Auto-adjust column widths
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worksheet = writer.sheets[safe_sheet_name]
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for idx, col in enumerate(df.columns, 1):
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max_length = max(
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df[col].astype(str).map(len).max(),
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len(str(col))
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)
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adjusted_width = min(max_length + 2, 50)
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col_letter = openpyxl.utils.get_column_letter(idx)
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worksheet.column_dimensions[col_letter].width = adjusted_width
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print(f"Exported {len(data_dict)} sheets to Excel: {filepath}")
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return filepath
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