![]() Use random.choice(someList) and random.shuffle(someList) to assure referential integrity. So you might have ChildEntity picking a random element from ParentEntity to assure that the FK-PK relationship was correct. Instead of generating random keys, you want to make a random selection from the other entities. MyData = įor multiple entities, you have to work out the cardinality. Self.append( random.randrange( 100, 1000 ) ) Here's a stripped-down one-table-only version of a data generator that writes a CSV file. Extensible, open source, written in a dynamic language (these are nice-to-haves, not strong requirements). A command-line interface for easy scripting. I actually don't like this as much, but you might. Generate in SQL script format ( INSERT statements) or else in a flat file format suitable for bulk import (which is usually faster). Use an ODBC connection to generate data directly into the database. Generate CSV files of data which you can load manually. Generally, you want to build an entity model of your own so that you can be sure you have ranges and key relationships correct. That's why many businesses use dummy data generators to get the information they need. Why use a Mock Data Generator When it comes to data, more is often better. Looking at 3 and 4 together, you don't want simple reverse engineering - you want something you can control to produce realistic values. A test data generator can help you create dummy data for things like user profiles, credit card data, weather data, addresses, and more. Need more data Plans start at just 60/year. Follow all of the DB referential integrity rules and constraints. Mockaroo - Random Data Generator and API Mocking Tool JSON / CSV / SQL / Excel Need some mock data to test your app Mockaroo lets you generate up to 1,000 rows of realistic test data in CSV, JSON, SQL, and Excel formats. ![]() A repeatable set of data that you can for performance testing and get consistent results. Considerations: Simple to modify and configure. There are ways to discover the database metadata and constraints. For generating sample data, I use simple Python applications. The first two indicate that you want to produce script files that will load your data. For generating sample data, I use simple Python applications.Ī repeatable set of data that you can for performance testing and get consistent results.įollow all of the DB referential integrity rules and constraints.
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