Enhance generate_pipeline_code to format code to follow lint standards

[jeremyliweishih]

Currently generate_pipeline_code generates a long string for the whole pipeline. It would be easier if this string was formatted to follow our lint standards for readability.

BinaryClassificationPipeline(
  component_graph={
    'Imputer': ['Imputer', 'X', 'y'], 
    'My Drop Null Columns Transformer': [MyDropNullColumns, 'Imputer.x', 'y'], 
    'DateTime Featurizer': ['DateTime Featurizer', 'My Drop Null Columns Transformer.x', 'y'], 
    'Natural Language Featurizer': ['Natural Language Featurizer', 'DateTime Featurizer.x', 'y'], 
    'One Hot Encoder': ['One Hot Encoder', 'Natural Language Featurizer.x', 'y'], 
    'Random Forest Classifier': ['Random Forest Classifier', 'One Hot Encoder.x', 'y']}, 
  parameters={
    'Imputer':{'categorical_impute_strategy': 'most_frequent', 'numeric_impute_strategy': 'mean', 'boolean_impute_strategy': 'most_frequent', 'categorical_fill_value': None, 'numeric_fill_value': None, 'boolean_fill_value': None}, 
    'My Drop Null Columns Transformer':{'pct_null_threshold': 1.0}, 
    'DateTime Featurizer':{'features_to_extract': ['year', 'month', 'day_of_week', 'hour'], 'encode_as_categories': False, 'time_index': None}, 'One Hot Encoder':{'top_n': 10, 'features_to_encode': None, 'categories': None, 'drop': 'if_binary', 'handle_unknown': 'ignore', 'handle_missing': 'error'}, 
    'Random Forest Classifier':{'n_estimators': 100, 'max_depth': 6, 'n_jobs': -1}}, 
  custom_name='Pipeline with Custom Component', random_seed=20)'