Template code for building a Tableau .hyper data extract from a Pandas DataFrame.

tableau-hyper-api-pandas-dataframe.py

#  this code snippet will not run by itself; this is a piece of a larger workflow.
#  a Pandas DataFrame named 'combined_df' is the source of data in this example

PATH_TO_HYPER = 'workbooks_and_owners.hyper'

# Step 1: Start a new private local Hyper instance
with HyperProcess(Telemetry.SEND_USAGE_DATA_TO_TABLEAU, 'myapp' ) as hyper:

# Step 2:  Create the the .hyper file, replace it if it already exists
    with Connection(endpoint=hyper.endpoint, 
                    create_mode=CreateMode.CREATE_AND_REPLACE,
                    database=PATH_TO_HYPER) as connection:

# Step 3: Create the schema
        connection.catalog.create_schema('Extract')

# Step 4: Create the table definition
        schema = TableDefinition(table_name=TableName('Extract','Extract'),
            columns=[
            TableDefinition.Column('workbook_name', SqlType.text()),
            TableDefinition.Column('workbook_id', SqlType.text()),
            TableDefinition.Column('workbook_project', SqlType.text()),
            TableDefinition.Column('view_type', SqlType.text()),
            TableDefinition.Column('view_name', SqlType.text()),
            TableDefinition.Column('view_id', SqlType.text()),
            TableDefinition.Column('upstr_table_name', SqlType.text()),
            TableDefinition.Column('upstr_table_id', SqlType.text()),
            TableDefinition.Column('upstr_db_name', SqlType.text()),
            TableDefinition.Column('upstr_db_type', SqlType.text()),
            TableDefinition.Column('upstr_db_id', SqlType.text()),
            TableDefinition.Column('upstr_db_isEmbedded', SqlType.bool()),
            TableDefinition.Column('database_hostname', SqlType.text()),
            TableDefinition.Column('database_port', SqlType.text()),
            TableDefinition.Column('database_id', SqlType.text()),
            TableDefinition.Column('upstr_ds_name', SqlType.text()),
            TableDefinition.Column('upstr_ds_id', SqlType.text()),
            TableDefinition.Column('upstr_ds_project', SqlType.text()),
            TableDefinition.Column('emb_ds_name', SqlType.text()),
            TableDefinition.Column('summary_date', SqlType.text()),
            TableDefinition.Column('site_name', SqlType.text()),
            TableDefinition.Column('last_interaction_date', SqlType.text()),
            TableDefinition.Column('num_views', SqlType.double())
         ])
    
# Step 5: Create the table in the connection catalog
        connection.catalog.create_table(schema)
    
        with Inserter(connection, schema) as inserter:
            for index, row in combined_df.iterrows():
                inserter.add_row(row)
            inserter.execute()

    print("The connection to the Hyper file is closed.")