automatic generation of all plots with all combinations

03_quant_report.script.py

@@ -18,27 +18,39 @@ from speaking_styles import SPEAKING_STYLES
 # CLI argument parsing for batch automation
 # When run as script: python 03_quant_report.script.py --age '["18 to 21 years"]' --consumer '["Starter"]'
 # When run in Jupyter: args will use defaults (all filters = None = all options selected)
+
+# Central filter configuration - add new filters here only
+# Format: 'cli_arg_name': 'QualtricsSurvey.options_* attribute name'
+FILTER_CONFIG = {
+    'age': 'options_age',
+    'gender': 'options_gender',
+    'ethnicity': 'options_ethnicity',
+    'income': 'options_income',
+    'consumer': 'options_consumer',
+    # Add new filters here: 'newfilter': 'options_newfilter',
+}
+
 def parse_cli_args():
     parser = argparse.ArgumentParser(description='Generate quant report with optional filters')
-    parser.add_argument('--age', type=str, default=None, help='JSON list of age groups')
-    parser.add_argument('--gender', type=str, default=None, help='JSON list of genders')
-    parser.add_argument('--ethnicity', type=str, default=None, help='JSON list of ethnicities')
-    parser.add_argument('--income', type=str, default=None, help='JSON list of income groups')
-    parser.add_argument('--consumer', type=str, default=None, help='JSON list of consumer segments')
+    
+    # Dynamically add filter arguments from config
+    for filter_name in FILTER_CONFIG:
+        parser.add_argument(f'--{filter_name}', type=str, default=None, help=f'JSON list of {filter_name} values')
+    
+    parser.add_argument('--filter-name', type=str, default=None, help='Name for this filter combination (used for .txt description file)')
     
     # Only parse if running as script (not in Jupyter/interactive)
     try:
         # Check if running in Jupyter by looking for ipykernel
         get_ipython()  # noqa: F821
-        return argparse.Namespace(age=None, gender=None, ethnicity=None, income=None, consumer=None)
+        # Return namespace with all filters set to None
+        return argparse.Namespace(**{f: None for f in FILTER_CONFIG}, filter_name=None)
     except NameError:
         args = parser.parse_args()
         # Parse JSON strings to lists
-        args.age = json.loads(args.age) if args.age else None
-        args.gender = json.loads(args.gender) if args.gender else None
-        args.ethnicity = json.loads(args.ethnicity) if args.ethnicity else None
-        args.income = json.loads(args.income) if args.income else None
-        args.consumer = json.loads(args.consumer) if args.consumer else None
+        for filter_name in FILTER_CONFIG:
+            val = getattr(args, filter_name)
+            setattr(args, filter_name, json.loads(val) if val else None)
         return args
 
 cli_args = parse_cli_args()
@@ -100,13 +112,60 @@ BEST_CHOSEN_CHARACTER = "the_coach"
 # %%
 # mo.stop(filter_form.value is None, mo.md("**Please submit filter above to proceed**"))
 # CLI args: None means "all options selected" (use S.options_* defaults)
-_filter_age = cli_args.age if cli_args.age is not None else S.options_age
-_filter_gender = cli_args.gender if cli_args.gender is not None else S.options_gender
-_filter_ethnicity = cli_args.ethnicity if cli_args.ethnicity is not None else S.options_ethnicity
-_filter_income = cli_args.income if cli_args.income is not None else S.options_income
-_filter_consumer = cli_args.consumer if cli_args.consumer is not None else S.options_consumer
+# Build filter values dict dynamically from FILTER_CONFIG
+_active_filters = {}
+for filter_name, options_attr in FILTER_CONFIG.items():
+    cli_value = getattr(cli_args, filter_name)
+    all_options = getattr(S, options_attr)
+    _active_filters[filter_name] = cli_value if cli_value is not None else all_options
 
-_d = S.filter_data(data_all, age=_filter_age, gender=_filter_gender, income=_filter_income, ethnicity=_filter_ethnicity, consumer=_filter_consumer)
+_d = S.filter_data(data_all, **_active_filters)
+
+# Write filter description file if filter-name is provided
+if cli_args.filter_name and S.fig_save_dir:
+    # Get the filter slug (e.g., "All_Respondents", "Cons-Starter", etc.)
+    _filter_slug = S._get_filter_slug()
+    _filter_slug_dir = S.fig_save_dir / _filter_slug
+    _filter_slug_dir.mkdir(parents=True, exist_ok=True)
+    
+    # Build filter description
+    _filter_desc_lines = [
+        f"Filter: {cli_args.filter_name}",
+        "",
+        "Applied Filters:",
+    ]
+    _short_desc_parts = []
+    for filter_name, options_attr in FILTER_CONFIG.items():
+        all_options = getattr(S, options_attr)
+        values = _active_filters[filter_name]
+        display_name = filter_name.replace('_', ' ').title()
+        if values != all_options:
+            _short_desc_parts.append(f"{display_name}: {', '.join(values)}")
+            _filter_desc_lines.append(f"  {display_name}: {', '.join(values)}")
+        else:
+            _filter_desc_lines.append(f"  {display_name}: All")
+    
+    # Write detailed description INSIDE the filter-slug directory
+    _filter_file = _filter_slug_dir / f"{cli_args.filter_name}.txt"
+    _filter_file.write_text('\n'.join(_filter_desc_lines))
+    
+    # Append to summary index file at figures/<export_date>/filter_index.txt
+    _summary_file = S.fig_save_dir / "filter_index.txt"
+    _short_desc = "; ".join(_short_desc_parts) if _short_desc_parts else "All Respondents"
+    _summary_line = f"{_filter_slug}  |  {cli_args.filter_name}  |  {_short_desc}\n"
+    
+    # Append or create the summary file
+    if _summary_file.exists():
+        _existing = _summary_file.read_text()
+        # Avoid duplicate entries for same slug
+        if _filter_slug not in _existing:
+            with _summary_file.open('a') as f:
+                f.write(_summary_line)
+    else:
+        _header = "Filter Index\n" + "=" * 80 + "\n\n"
+        _header += "Directory  |  Filter Name  |  Description\n"
+        _header += "-" * 80 + "\n"
+        _summary_file.write_text(_header + _summary_line)
 
 # Stop execution and prevent other cells from running if no data is selected
 # mo.stop(len(_d.collect()) == 0, mo.md("**No Data available for current filter combination**"))