tbls

The bigquery-public-data:census_bureau_international dataset contains United States Census Bureau international estimates for country populations from 1950 to 2050. It includes midyear population figures (broken down by age and gender), fertility rates, birth rates, death rates, and migration rates.

Dataset Details:

• Source: United States Census Bureau
• Update Frequency: Historic
• Labels: dg_data_confidentiality:public, dg_data_context:metadata, dg_data_source:public, freebqcovid:freebqcovid
• Terms of Use: Publicly available under data.gov privacy policy.

The testdb sample documentation for ClickHouse organizes database metadata into three main categories:

1. Tables: Detailed documentation for individual tables (e.g., source_table, materialized_view, t1) including columns, types, and comments.
2. Stored procedures and functions: Documentation for database-level logic like linear_equation.
3. Relations: An Entity-Relationship (ER) diagram provided as schema.svg to visualize table connections.

When using tbls to document a Google Cloud Spanner database, the tool generates a structured documentation site. For a database located at projects/tbls-spanner-test/instances/test-instance/databases/testdb, the documentation includes:

• Tables: Individual Markdown files for each table (e.g., users.md, posts.md) containing column details, types, and comments.
• Relations: An ER diagram (typically schema.svg) visualizing the relationships between tables.

Each table documentation file is linked from the main index page.

tbls is a CI-friendly tool written in Go for documenting databases. It operates by dispatching commands to specialized sub-commands (e.g., tbls-mysql, tbls-postgres) found in your PATH.

To use it, call tbls followed by the desired subcommand and any subcommand-specific arguments. You can provide global configuration via a config file or a DSN (Data Source Name).

In tbls, a viewpoint file (e.g., viewpoint-2.md) is a generated documentation file that groups related database entities. It provides a high-level overview of a specific domain or functional area of the database, such as 'Around the users table'.

Each viewpoint typically contains:

• Description: A summary of the functional area.
• Tables: A categorized list of tables, including their column counts, comments, types, and labels.
• Relations: An ER diagram (usually as an SVG) visualizing the relationships between the tables in that viewpoint.

The testdb sample provides a demonstration of documentation generated by tbls. It includes documentation for various database objects such as tables, views, stored procedures, functions, and relations.

Key components documented in this sample include:

• Tables: Examples of different naming conventions (e.g., CamelizeTable, hyphen-table, long_long_long_long_long_long_long_long_table_name) and table types (BASE TABLE, VIEW).
• Stored Procedures and Functions: Documentation of arguments, return types, and procedure names.
• Relations: An ER diagram (schema.png) representing the database schema.

The bigquery-public-data:crypto_bitcoin dataset contains documentation for Bitcoin blockchain data exported via bitcoin-etl. The documentation includes details on tables, views, and their relationships.

Tables and Views

• blocks: Contains all blocks (13 columns). Type: TABLE.
• inputs: Contains inputs from all transactions (14 columns). Type: VIEW.
• outputs: Contains outputs from all transactions (11 columns). Type: VIEW.
• transactions: Contains all transactions (34 columns). Type: TABLE.

Relations

Entity-relationship diagrams (ER diagrams) are available as schema.svg within the documentation directory.