Documentation

Example Project

Dictum is a Business Intelligence framework written in Python. It includes a general-purpose metrics engine and allows your organization to have a shared, version-controlled and well-documented understanding of what the important metrics are and how they are computed from the source data.

The main features are:

• 🧑‍🔧 A structured way to describe your metrics. Metrics are defined in simple, readable YAML files. 👉 Learn how to get started with your own project
• 🪄 Interactive analytics in Jupyter. Slice and dice your metrics quickly and easily. Get the data as a Pandas DataFrame. 👉 Learn how to query Dictum
• 🤩 Dataviz powered by Altair. Quickly build visualizations based on your metric data. 👉 Demo Jupyter notebook
• 😎 SQL-like expression language. Write metric expressions in the familiar SQL syntax.
• 🦥 Reusable expressions. Define metrics using other previously-defined metrics.
• 🐇 Automatic multi-hop joins. You define foreign keys for tables, Dictum writes boring boilerplate SQL for you.
• 🤖 Python API. Build data applications powered by your Dictum project.

🚂 Supported backends:

• SQLite
• Postgres
• Vertica
• Snowflake, BigQuery, DuckDB and more coming soon.

Example Metric definition:

# metrics/revenue.yml
name: Revenue
description: |
  Sum of all order amounts excluding
  bonus currency spending.
table: orders
expr: sum(amount - coalesce(bonus_spent, 0))
format:
  kind: currency
  currency: USD

Example Table Definition:

# tables/orders.yml
source:
  schema: marts
  table: orders

related:
  user: user_id -> users.id
  product: project_id -> products.id

Installation

Install from PyPi:

pip install dictum

Basic usage

Learn how to query the example project