Save Schema

Use the save_schema method to export schema information from specified source modules to CSV (default) or YAML files.

Usage Examples

Click the below button to run this example in Colab:

Loader:
  load_benchmark_with_schema:
    filepath: benchmark://adult-income
    schema: benchmark://adult-income_schema
Splitter:
  basic_split:
    num_samples: 1
    train_split_ratio: 0.8
Preprocessor:
  default:
    method: 'default'
Synthesizer:
  default:
    method: 'default'
Postprocessor:
  default:
    method: 'default'

Reporter:
  save_schema:
    method: save_schema  # Required: Fixed to save_schema method
    source:              # Required: Specify modules to extract schema from
      - Loader
      - Preprocessor
      - Synthesizer
      - Postprocessor
    yaml_output: true    # Optional: Output individual YAML files (default: false)
    # output: petsard    # Optional: Output file name prefix (default: petsard)
    # properties:        # Optional: Specify properties to output (default: all properties)
    #   - dtype
    #   - nullable
    #   - min
    #   - max

Main Parameters

Required Parameters

Parameter	Type	Description	Example
`method`	`string`	Fixed as `save_schema` (case-insensitive)	`save_schema` or `SAVE_SCHEMA`
`source`	`string` or `list`	Target module name(s)	`Loader` or `["Loader", "Preprocessor"]`

source Parameter Details

The source parameter specifies which modules’ schemas to export. Supported formats:

Single Module: Export schema from one module
```
source: Preprocessor
```

Multiple Modules: Export schemas from multiple modules

source:
  - Loader
  - Preprocessor
  - Synthesizer

Supported Modules:

Loader: Original data schema
Splitter: Split data schema
Preprocessor: Preprocessed data schema
Synthesizer: Synthetic data schema
Postprocessor: Postprocessed data schema
Constrainer: Constrained data schema

Reference Notes:

Execution Order: Can only reference modules executed before the current Reporter
Module Names: Must exactly match module names defined in the YAML configuration
Data Availability: Schema extraction requires the module to have successfully executed

Optional Parameters

Parameter	Type	Default	Description	Example
`output`	`string`	`petsard`	Output file name prefix	`my_experiment`
`yaml_output`	`boolean`	`false`	Whether to output YAML format additionally	`true`, `false`
`properties`	`string` or `list`	All properties	Specify property names to output	`dtype` or `["dtype", "nullable", "min", "max"]`

properties Parameter Details

The properties parameter filters which attributes to output. Only specified properties will appear in output files. Supported formats:

Single Property: Output only the specified property
```
properties: dtype
```

Multiple Properties: Output multiple specified properties

properties:
  - dtype
  - nullable
  - min
  - max

Common Properties:

dtype: Data type
nullable: Whether null values are allowed
min, max, mean, std: Statistics for numeric columns
categories: Category values for categorical columns
unique_count: Number of unique values

Usage Example:

Reporter:
  save_schema:
    method: save_schema
    source:
      - Loader
      - Synthesizer
    properties:
      - dtype
      - nullable
    output: filtered_schema

Effect:

CSV file will only include {column_name}_dtype and {column_name}_nullable columns
Other attributes (like min, max, categories, etc.) will not be output
Applies to all columns regardless of their data type

Output Format

Default CSV Format (Summary)

Schema information is output as CSV format by default, with one row per source (experiment) and all column attributes expanded:

Filename format:

{output}_schema_{source1-source2-...}_summary.csv

The filename includes all source module names connected by hyphens, similar to the save_data method.

Examples:

With output: "petsard" and source: ["Loader", "Preprocessor", "Synthesizer"]:
```
petsard_schema_Loader-Preprocessor-Synthesizer_summary.csv
```
With output: "petsard" and source: "Loader":
```
petsard_schema_Loader_summary.csv
```

CSV Structure:

First column: source (source experiment name)
Remaining columns: {column_name}_{attribute_name}, for example:
- age_dtype: Data type of age column
- age_nullable: Whether age column allows null values
- age_min, age_max, age_mean: Statistics for age column
- workclass_categories: Category values for workclass column

When using properties parameter:

Only specified properties will be output
For example, with properties: ["dtype", "nullable"], CSV will only include age_dtype, age_nullable, workclass_dtype, workclass_nullable, etc.
Unspecified attributes (like min, max, categories) will not appear in the output

Advantages:

Easy to compare schema differences across experiments
Can be opened directly with Excel or other tools for analysis
Suitable for version control and diff comparison

Optional YAML Format

When yaml_output: true is set, individual YAML files for each experiment will be output additionally:

{output}_schema_{full_experiment_name}.yaml

Example output filenames:

petsard_schema_Loader[load_benchmark_with_schema].yaml
petsard_schema_Loader[load_benchmark_with_schema]_Preprocessor[scaler].yaml

Usage:

Reporter:
  save_schema:
    method: save_schema
    source:
      - Loader
      - Preprocessor
    yaml_output: true  # Output YAML files additionally

Use Cases

Data Transformation Tracking: Track how data structure changes through the processing pipeline
Quality Assurance: Verify that synthetic data maintains expected structure
Documentation Generation: Generate comprehensive data documentation for your project

Common Questions

Q: What’s the difference between save_schema and save_data?

save_schema: Exports data structure information (column types, statistics) in CSV format by default (flattened table), optionally YAML
save_data: Exports actual data content in CSV format

Q: Can I specify a custom save path?

A: Yes, use the output parameter with a relative path. Files will be saved relative to the current working directory.

Q: Why isn’t my module’s schema being saved?

A: Check:

Module name is spelled correctly in source
Module has been executed before Reporter
Module has data available (not empty or failed)

Notes

File Overwrite: Files with the same name will be overwritten
Module Execution: Only modules that have successfully executed can have their schemas exported
Encoding: All CSV and YAML files use UTF-8 encoding
Case Insensitivity: The method parameter is case-insensitive (save_schema, SAVE_SCHEMA, or Save_Schema all work)
Performance: Schema extraction is fast and doesn’t require loading full datasets
Comparison: CSV format is especially suitable for comparing data structure changes across experiments
Missing Values: If a column in one source doesn’t have a certain attribute (e.g., changed from numeric to categorical), that field will be left empty (NA)

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