Supported Schemas for Tables

Schema is needed for Fakeme to know that columns and of that data types must be generated.

As default, library use Schema style from BigQuery - https://cloud.google.com/bigquery/docs/schemas#creating_a_json_schema_file but without ‘description’ field.

Usually schema looks like a list of dicts - one dict per column and inside each dict: - ‘name’: column name, - ‘type’: data type of values in column, - ‘mode’: contains information nullabe / required. This field is not sensitive to capitalization.

Example:

[{
  "type": "STRING",
  "name": "part_identification",
  "mode": "Required"
 },
 {
  "type": "FLOAT",
  "name": "ship_type",
  "mode": "NULLABLE"
 },
 {
  "type": "INTEGER",
  "name": "price",
  "mode": "NULLABLE"
 }]

If you don’t provide a type, like this:

And Fakeme does not have base rule for generating columns with such name - output will be random string.

But if we have generator for field. For example, with name “price”:

{
  "name": "price",
  "mode": "NULLABLE"
}

Result will be of float type based on existed Rule for Generating (check rules in fakeme/rules.py).

Schemas from DDL

Supported Databases

• MSSql
• MySql
• PostgreSql
• Oracle DB
• Hive (HQL)
• SQLite

How to fix errors in process of DDL parsing?

How to add new DDL-notation/custom implementation/database ?