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* download orderbook data * fix CI error * fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * test fix CI error * optimize get_data code * optimize get_data code * optimize get_data code * optimize README --------- Co-authored-by: Linlang <v-linlanglv@microsoft.com>
50 lines
1.8 KiB
Markdown
50 lines
1.8 KiB
Markdown
# Introduction
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This example tries to demonstrate how Qlib supports data without fixed shared frequency.
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For example,
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- Daily prices volume data are fixed-frequency data. The data comes in a fixed frequency (i.e. daily)
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- Orders are not fixed data and they may come at any time point
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To support such non-fixed-frequency, Qlib implements an Arctic-based backend.
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Here is an example to import and query data based on this backend.
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# Installation
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Please refer to [the installation docs](https://docs.mongodb.com/manual/installation/) of mongodb.
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Current version of script with default value tries to connect localhost **via default port without authentication**.
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Run following command to install necessary libraries
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```
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pip install pytest coverage
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pip install arctic # NOTE: pip may fail to resolve the right package dependency !!! Please make sure the dependency are satisfied.
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```
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# Importing example data
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1. (Optional) Please follow the first part of [this section](https://github.com/microsoft/qlib#data-preparation) to **get 1min data** of Qlib.
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2. Please follow following steps to download example data
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```bash
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cd examples/orderbook_data/
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python ../../scripts/get_data.py download_data --target_dir . --file_name highfreq_orderbook_example_data.zip
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```
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3. Please import the example data to your mongo db
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```bash
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python create_dataset.py initialize_library # Initialization Libraries
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python create_dataset.py import_data # Initialization Libraries
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```
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# Query Examples
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After importing these data, you run `example.py` to create some high-frequency features.
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```bash
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pytest -s --disable-warnings example.py # If you want run all examples
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pytest -s --disable-warnings example.py::TestClass::test_exp_10 # If you want to run specific example
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```
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# Known limitations
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Expression computing between different frequencies are not supported yet
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