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Merge pull request #16 from Derek-Wds/main

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Update data related information
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you-n-g
2020-09-25 00:28:26 -05:00
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parent 9f5e18fc3e 40b9203df2
commit fc7b968571
3 changed files with 15 additions and 12 deletions
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24
README.md
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@@ -11,16 +11,16 @@ With Qlib, you can easily try your ideas to create better Quant investment strat
For more details, please refer to our paper ["Qlib: An AI-oriented Quantitative Investment Platform"](https://arxiv.org/abs/2009.11189). For more details, please refer to our paper ["Qlib: An AI-oriented Quantitative Investment Platform"](https://arxiv.org/abs/2009.11189).
- [Framework of Qlib](#Framework-of-Qlib) - [Framework of Qlib](#framework-of-qlib)
- [Quick Start](#Quick-Start) - [Quick Start](#quick-start)
- [Installation](#Installation) - [Installation](#installation)
- [Data Preparation](#Data-Preparation) - [Data Preparation](#data-preparation)
- [Auto Quant Research Workflow with](#Auto-Quant-Research-Workflow) - [Auto Quant Research Workflow](#auto-quant-research-workflow)
- [Building Customized Quant Research Workflow by Code](#Building-Customized-Quant-Research-Workflow-by-Code) - [Building Customized Quant Research Workflow by Code](#building-customized-quant-research-workflow-by-code)
- [More About Qlib](#More-About-Qlib) - [More About Qlib](#more-about-qlib)
- [Offline Mode and Online Mode](#Offline-Mode-and-Online-Mode) - [Offline Mode and Online Mode](#offline-mode-and-online-mode)
- [Performance of Qlib Data Server](#Performance-of-Qlib-Data-Server) - [Performance of Qlib Data Server](#performance-of-qlib-data-server)
- [Contributing](#Contributing) - [Contributing](#contributing)
@@ -77,7 +77,9 @@ Load and prepare data by running the following code:
This dataset is created by public data collected by [crawler scripts](scripts/data_collector/), which have been released in This dataset is created by public data collected by [crawler scripts](scripts/data_collector/), which have been released in
the same repository. the same repository.
Users could create the same dataset with it. Users could create the same dataset with it.
*Please pay **ATTENTION** that the data is collected from [Yahoo Finance](https://finance.yahoo.com/lookup) and the data might not be perfect. We recommend users to prepare their own data if they have high-quality dataset. For more information, users can refer to the [related document](https://qlib.readthedocs.io/en/latest/component/data.html#converting-csv-format-into-qlib-format)*
<!-- <!--
- Run the initialization code and get stock data: - Run the initialization code and get stock data:

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docs/start/initialization.rst
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@@ -11,7 +11,7 @@ Initialization
Please follow the steps below to initialize ``Qlib``. Please follow the steps below to initialize ``Qlib``.
- Download and prepare the Data: execute the following command to download stock data. - Download and prepare the Data: execute the following command to download stock data. Please pay `attention` that the data is collected from `Yahoo Finance <https://finance.yahoo.com/lookup>`_ and the data might not be perfect. We recommend users to prepare their own data if they have high-quality datasets. Please refer to `Data <../component/data.html#converting-csv-format-into-qlib-format>` for more information about customized dataset.
.. code-block:: bash .. code-block:: bash
python scripts/get_data.py qlib_data_cn --target_dir ~/.qlib/qlib_data/cn_data python scripts/get_data.py qlib_data_cn --target_dir ~/.qlib/qlib_data/cn_data

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scripts/get_data.py
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@@ -34,6 +34,7 @@ class GetData:
raise requests.exceptions.HTTPError() raise requests.exceptions.HTTPError()
chuck_size = 1024 chuck_size = 1024
logger.warning(f"The data for the example is collected from Yahoo Finance. Please be aware that the quality of the data might not be perfect. (You can refer to the original data source: https://finance.yahoo.com/lookup.)")
logger.info(f"{file_name} downloading......") logger.info(f"{file_name} downloading......")
with tqdm(total=int(resp.headers.get("Content-Length", 0))) as p_bar: with tqdm(total=int(resp.headers.get("Content-Length", 0))) as p_bar:
with target_path.open("wb") as fp: with target_path.open("wb") as fp: