VAST Orbit Statistics¶

Numbers say more than adjectives. Every figure on this page is generated directly from the VAST Orbit source when the documentation is built — the library inspects its own modules and counts what it actually ships. Nothing here is hand-written or rounded up, so the page always reflects exactly the version you are reading.

Summary¶

The chart below summarizes VAST Orbit by counting the public building blocks in each area of the library: the loaders and generators that get data in, the visualization layer, the DataFrame and column operations you use to prepare and explore data, the SQL function layer, and machine learning. Read together, they show how much of a complete, in-database data-science toolkit already ships in the box.

The same breakdown in exact numbers, grouped by category with a running total for each, is below.

Category	Subcategory	Functions
Loaders & Generators	Loaders Generators Total	24 3 27
Data Visualization Functions	Matplotlib Plotly Total	48 39 87
Data Preparation/Exploration Functions	VastFrame VastColumn TableSample Total	143 93 16 252
SQL Functions & Extensions	SQL Functions SQL Statements SQL Geo Extensions Total	92 12 1 105
Machine Learning	Statistical Tests Algorithms/Functions Extensions Metrics Evaluation Functions Total	15 40 23 41 12 131
	Total	602

Code coverage¶

Breadth is only half the story — the tests behind it are the other half. This pie shows how much of the VAST Orbit codebase is exercised by the test suite, a quick read on how much of the library is verified and where there is still room to grow.

How these numbers are produced¶

There is no manual tally. VAST Orbit ships a small inspection module, vastorbit._utils._inspect_statistics, that imports the library, walks its modules, and counts the public functions, classes, and methods in each area before rendering the summary and coverage charts. You can reproduce everything on this page yourself in a few lines:

import vastorbit as vo
from vastorbit._utils._inspect_statistics import (
    summarise_vastorbit_chart,
    gen_rst_summary_table,
    codecov_vastorbit_chart,
)

vo.set_option("plotting_lib", "plotly")

# The summary pie of public building blocks, by area
summarise_vastorbit_chart()

# The same breakdown as a table, with per-category totals
print(gen_rst_summary_table())

# The test code-coverage pie
codecov_vastorbit_chart()

Because the counts come straight from the installed package, they stay honest: every new function or model added to VAST Orbit shows up here on the next build, automatically.