tsft 0.1.0

Time Series Forecasting Tool

TSFT — Time Series Forecasting Tool

TSFT is a CLI utility for training deep learning forecasting models, generating exploratory reports, and visualizing results for time series data.

It is built on top of Darts + PyTorch Lightning and provides a simple command-line interface powered by Typer.

Features

• Deep learning forecasting models (Darts-based)
• Interactive Dash dashboards
• Clean CLI interface

Installation

pip install tsft

Or install locally:

pip install -e .

Usage

tsft [COMMAND] [OPTIONS]

Available commands:

• report — Launch exploratory dashboard for a dataset
• run — Train a forecasting model
• summary — Visualize training results

Generate Dataset Report

Launch an interactive dashboard for time series exploration:

tsft report data.csv

Optional:

tsft report data.csv --port 9000

Train a Model

Train a forecasting model on your dataset:

tsft run data.csv

With options:

tsft run data.csv \
  --model=nbeats \
  --input-chunk=24 \
  --output-chunk=12 \
  --epochs=5 \
  --no-stopper \
  --output=results/

Options

Option	Description
--model	Model name (lstm, gru, rnn, nbeats, transformer, tcn)
--input-chunk	Input window length
--output-chunk	Forecast horizon
--epochs	Number of training epochs
--stopper / --no-stopper	Enable/disable early stopping
--output	Directory to save artifacts

View Training Results

Launch dashboard with training results:

tsft summary results/

Optional:

tsft summary results/ --port 9000

Example Workflow

# 1. Explore dataset
tsft report data.csv

# 2. Train model
tsft run data.csv --output=output_dir --model=nbeats --epochs=5 --input-chunk=30 --output-chunk=10 --no-stopper

# 3. View results
tsft summary outputs/

Dashboard Preview