TimeFeatures

TimeFeatures is an Orange3 add-on for time-series feature engineering. It ships four widgets that work together to define, visualise, persist and re-load derived variables built on top of an existing dataset.

Widget

What it does

Time Features Constructor

Defines new variables from existing ones using Python-style expressions and time-window functions (shift, sum, mean, min, max, sd, count).

Variable Dependency Graph

Builds a directed, weighted dependency graph from the resulting variable / expression table. Edge weights summarise how far back or forward in time each variable looks.

Save to DB

Persists the resulting dataset to a SQL database (PostgreSQL or MySQL), with full SQL-injection defences and an optional completion email.

Load from DB

Lists the datasets previously stored by Save to DB and pulls the chosen one back into Orange, optionally marking the class column directly so no Select Columns widget is needed.

Workflow

A typical pipeline:

File → Time Features Constructor → ┬→ <downstream models>
                                   └→ Variable Dependency Graph
                                           ↓
                                   Network Explorer

The Time Features Constructor outputs both the transformed data (top arrow) and the variable / expression definition table (bottom arrow). Feed the latter into the Variable Dependency Graph to visualise the dependencies, and send the data into Save to DB if you want to keep it in a database.

Getting started

Widgets

Project

Building this documentation

Development build (for previewing locally):

pip install -e ".[docs]"
python -m sphinx -b html docs docs/build/html

In-app help (bundled with the wheel so Orange’s Help panel works offline):

python -m sphinx -b html docs timefeatures/help_html

The HTML build is also bundled with the wheel so Orange’s in-app help panel can resolve every widget’s Help action without internet access.

Indices