Files
JPMC-quant/run_filter_combinations.py

234 lines
7.6 KiB
Python

#!/usr/bin/env python
"""
Batch runner for quant report with different filter combinations.
Runs 03_quant_report.script.py for each single-filter combination:
- Each age group (with all others active)
- Each gender (with all others active)
- Each ethnicity (with all others active)
- Each income group (with all others active)
- Each consumer segment (with all others active)
Usage:
uv run python run_filter_combinations.py
uv run python run_filter_combinations.py --dry-run # Preview combinations without running
"""
import subprocess
import sys
import json
from pathlib import Path
from tqdm import tqdm
from utils import QualtricsSurvey
# Default data paths (same as in 03_quant_report.script.py)
RESULTS_FILE = 'data/exports/2-2-26/JPMC_Chase Brand Personality_Quant Round 1_February 2, 2026_Labels.csv'
QSF_FILE = 'data/exports/OneDrive_2026-01-21/Soft Launch Data/JPMC_Chase_Brand_Personality_Quant_Round_1.qsf'
REPORT_SCRIPT = Path(__file__).parent / '03_quant_report.script.py'
def get_filter_combinations(survey: QualtricsSurvey) -> list[dict]:
"""
Generate all single-filter combinations.
Each combination isolates ONE filter value while keeping all others at "all selected".
Returns list of dicts with filter kwargs for each run.
"""
combinations = []
# Add "All Respondents" run (no filters = all options selected)
combinations.append({
'name': 'All_Respondents',
'filters': {} # Empty = use defaults (all selected)
})
# Age groups - one at a time
for age in survey.options_age:
combinations.append({
'name': f'Age-{age}',
'filters': {'age': [age]}
})
# Gender - one at a time
for gender in survey.options_gender:
combinations.append({
'name': f'Gender-{gender}',
'filters': {'gender': [gender]}
})
# Ethnicity - grouped by individual values
# Ethnicity options are comma-separated (e.g., "White or Caucasian, Hispanic or Latino")
# Create filters that include ALL options containing each individual ethnicity value
ethnicity_values = set()
for ethnicity_option in survey.options_ethnicity:
# Split by comma and strip whitespace
values = [v.strip() for v in ethnicity_option.split(',')]
ethnicity_values.update(values)
for ethnicity_value in sorted(ethnicity_values):
# Find all options that contain this value
matching_options = [
opt for opt in survey.options_ethnicity
if ethnicity_value in [v.strip() for v in opt.split(',')]
]
combinations.append({
'name': f'Ethnicity-{ethnicity_value}',
'filters': {'ethnicity': matching_options}
})
# Income - one at a time
for income in survey.options_income:
combinations.append({
'name': f'Income-{income}',
'filters': {'income': [income]}
})
# Consumer segments - combine _A and _B options, and also include standalone
# Group options by base name (removing _A/_B suffix)
consumer_groups = {}
for consumer in survey.options_consumer:
# Check if ends with _A or _B
if consumer.endswith('_A') or consumer.endswith('_B'):
base_name = consumer[:-2] # Remove last 2 chars (_A or _B)
if base_name not in consumer_groups:
consumer_groups[base_name] = []
consumer_groups[base_name].append(consumer)
else:
# Not an _A/_B option, keep as-is
consumer_groups[consumer] = [consumer]
# Add combined _A+_B options
for base_name, options in consumer_groups.items():
if len(options) > 1: # Only combine if there are multiple (_A and _B)
combinations.append({
'name': f'Consumer-{base_name}',
'filters': {'consumer': options}
})
# Add standalone options (including individual _A and _B)
for consumer in survey.options_consumer:
combinations.append({
'name': f'Consumer-{consumer}',
'filters': {'consumer': [consumer]}
})
# Business Owner - one at a time
for business_owner in survey.options_business_owner:
combinations.append({
'name': f'BusinessOwner-{business_owner}',
'filters': {'business_owner': [business_owner]}
})
# AI User - one at a time
for ai_user in survey.options_ai_user:
combinations.append({
'name': f'AIUser-{ai_user}',
'filters': {'ai_user': [ai_user]}
})
# Investable Assets - one at a time
for investable_assets in survey.options_investable_assets:
combinations.append({
'name': f'Assets-{investable_assets}',
'filters': {'investable_assets': [investable_assets]}
})
# Industry - one at a time
for industry in survey.options_industry:
combinations.append({
'name': f'Industry-{industry}',
'filters': {'industry': [industry]}
})
return combinations
def run_report(filters: dict, name: str = None, dry_run: bool = False) -> bool:
"""
Run the report script with given filters.
Args:
filters: Dict of filter_name -> list of values
name: Name for this filter combination (used for .txt description file)
dry_run: If True, just print command without running
Returns:
True if successful, False otherwise
"""
cmd = [sys.executable, str(REPORT_SCRIPT)]
# Add filter-name for description file
if name:
cmd.extend(['--filter-name', name])
for filter_name, values in filters.items():
if values:
cmd.extend([f'--{filter_name}', json.dumps(values)])
if dry_run:
print(f" Would run: {' '.join(cmd)}")
return True
try:
result = subprocess.run(
cmd,
capture_output=True,
text=True,
cwd=Path(__file__).parent
)
if result.returncode != 0:
print(f"\n ERROR: {result.stderr[:500]}")
return False
return True
except Exception as e:
print(f"\n ERROR: {e}")
return False
def main():
import argparse
parser = argparse.ArgumentParser(description='Run quant report for all filter combinations')
parser.add_argument('--dry-run', action='store_true', help='Preview combinations without running')
args = parser.parse_args()
# Load survey to get available filter options
print("Loading survey to get filter options...")
survey = QualtricsSurvey(RESULTS_FILE, QSF_FILE)
survey.load_data() # Populates options_* attributes
# Generate all combinations
combinations = get_filter_combinations(survey)
print(f"Generated {len(combinations)} filter combinations")
if args.dry_run:
print("\nDRY RUN - Commands that would be executed:")
for combo in combinations:
print(f"\n{combo['name']}:")
run_report(combo['filters'], name=combo['name'], dry_run=True)
return
# Run each combination with progress bar
successful = 0
failed = []
for combo in tqdm(combinations, desc="Running reports", unit="filter"):
tqdm.write(f"Running: {combo['name']}")
if run_report(combo['filters'], name=combo['name']):
successful += 1
else:
failed.append(combo['name'])
# Summary
print(f"\n{'='*50}")
print(f"Completed: {successful}/{len(combinations)} successful")
if failed:
print(f"Failed: {', '.join(failed)}")
if __name__ == '__main__':
main()