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
- (Optional) Please follow the first part of this section to get 1min data of Qlib.
- 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 .
- 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