ts-data-generator 0.1.1

A Python library for generating synthetic time series data

Synthetic Time Series Data Generator

A Python library for generating synthetic time series data

^{Special thanks to: Nike-Inc repo}

Installation

PyPi (recommended)

You can install with pip directly by

pip install ts-data-generator

Repo

After cloning this repo and creating a virtual environment, run the following command:

pip install --editable .

Usage

Check the sample notebook here

CLI

You can also use the command line utility tsdata to generate the data.

(venv) ~/ts-data-generator   cli $ tsdata generate --help
Usage: tsdata generate [OPTIONS]

  Generate time series data and save it to a CSV file.

Options:
  --start TEXT                    Start datetime 'YYYY-MM-DD'  [required]
  --end TEXT                      End datetime 'YYYY-MM-DD'  [required]
  --granularity [FIVE_MIN|HOURLY|DAILY]
                                  Granularity of the time series data  [required]
  --dims TEXT                     + separated list of dimensions definition of format 'name:function:values'  [required]
  --mets TEXT                     + separated list of metrics definition trends of format 'name:trend(*params)'  [required]
  --output TEXT                   Output file name  [required]
  --help                          Show this message and exit.

For example you can call this cli tool like below to generate data

tsdata generate \
  --start "2019-01-01" \
  --end "2019-01-12" \
  --granularity "FIVE_MIN" \
  --dims "product:random_choice:A,B,C,D" \
  --dims "product_id:random_float:1,4" \
  --dims "const:constant:5" \
  --mets "sales:LinearTrend(limit=500)+WeekendTrend(weekend_effect=50)" \
  --mets "trend:LinearTrend(limit=10)" \
  --output "data.csv"

Release method

1. git tag <x.x.x>
2. git push origin <x.x.x>