Introduction

This example tries to demonstrate how Qlib supports data without fixed shared frequency.

For example,

• Daily prices volume data are fixed-frequency data. The data comes in a fixed frequency (i.e. daily)
• Orders are not fixed data and they may come at any time point

To support such non-fixed-frequency, Qlib implements an Arctic-based backend. Here is an example to import and query data based on this backend.

Installation

Please refer to the installation docs of mongodb. Current version of script with default value tries to connect localhost via default port without authentication.

Run following command to install necessary libraries

pip install pytest coverage gdown
pip install arctic  # NOTE: pip may fail to resolve the right package dependency !!! Please make sure the dependency are satisfied.

Importing example data

1. (Optional) Please follow the first part of this section to get 1min data of Qlib.
2. Please follow following steps to download example data

cd examples/orderbook_data/
gdown https://drive.google.com/uc?id=15FuUqWn2rkCi8uhJYGEQWKakcEqLJNDG  # Proxies may be necessary here.
python ../../scripts/get_data.py _unzip --file_path highfreq_orderbook_example_data.zip --target_dir .

3. Please import the example data to your mongo db

python create_dataset.py initialize_library  # Initialization Libraries
python create_dataset.py import_data  # Initialization Libraries

Query Examples

After importing these data, you run example.py to create some high-frequency features.

pytest -s --disable-warnings example.py   # If you want run all examples
pytest -s --disable-warnings example.py::TestClass::test_exp_10  # If you want to run specific example

Known limitations

Expression computing between different frequencies are not supported yet