Module scikit_rest
Automatically serve ML model as a REST API
Sub-modules
- scikit_rest.resource
- scikit_rest.types
- scikit_rest.validator
Functions
infer(input_df)
: Automatically infer the column list and column types from the input DataFrame
Args:
input_df: DataFrame, where the column list and column types will be inferred from.
Returns:
col_list: List of Column names, where the order of the values will dictate the order within the pandas DataFrame
col_types: Dictionary of Column Names and the type of the variable, used for input Validation. If the values
of the dictionary is instead a list, We assume that any input for the variable can only be any of
the ones listed within the list
serve(col_list, col_types, transform_fn, predict_fn, port=1234, is_nullable=False, name='model')
: Setting up ML model as a REST API server
Args:
col_list: List of Column names, where the order of the values will dictate the order within the pandas DataFrame
col_types: Dictionary of Column Names and the type of the variable, used for input Validation. If the values
of the dictionary is instead a list, We assume that any input for the variable can only be any of
the ones listed within the list
transform_fn: Function which convert the input dataframe into test dataframe,
where we can call model.predict upon to get the final result
predict_fn: Function which convert the test dataframe into result. If a ML model instance is passed in, we will
instead try to call model.predict_proba / model.predict to get the result
port: Port Number where the REST API should be served upon
is_nullable: Whether input API can be nullable
name: Name of the program