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fix_docume
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v0.9.5
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README.md
14
README.md
@@ -175,6 +175,20 @@ Also, users can install the latest dev version ``Qlib`` by the source code accor
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**Tips for Mac**: If you are using Mac with M1, you might encounter issues in building the wheel for LightGBM, which is due to missing dependencies from OpenMP. To solve the problem, install openmp first with ``brew install libomp`` and then run ``pip install .`` to build it successfully.
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## Data Preparation
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❗ Due to more restrict data security policy. The offical dataset is disabled temporarily. You can try [this data source](https://github.com/chenditc/investment_data/releases) contributed by the community.
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Here is an example to download the data updated on 20220720.
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```bash
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wget https://github.com/chenditc/investment_data/releases/download/20220720/qlib_bin.tar.gz
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mkdir -p ~/.qlib/qlib_data/cn_data
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tar -zxvf qlib_bin.tar.gz -C ~/.qlib/qlib_data/cn_data --strip-components=2
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rm -f qlib_bin.tar.gz
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```
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The official dataset below will resume in short future.
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----
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Load and prepare data by running the following code:
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### Get with module
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@@ -5,3 +5,4 @@ scipy
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scikit-learn
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pandas
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tianshou
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sphinx_rtd_theme
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@@ -16,7 +16,7 @@ Current version of script with default value tries to connect localhost **via de
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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 pytest coverage gdown
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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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@@ -27,7 +27,8 @@ pip install arctic # NOTE: pip may fail to resolve the right package dependency
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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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gdown https://drive.google.com/uc?id=15nZF7tFT_eKVZAcMFL1qPS4jGyJflH7e # Proxies may be necessary here.
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python ../../scripts/get_data.py _unzip --file_path highfreq_orderbook_example_data.zip --target_dir .
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```
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3. Please import the example data to your mongo db
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@@ -2,7 +2,7 @@
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# Licensed under the MIT License.
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from pathlib import Path
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__version__ = "0.9.4.99"
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__version__ = "0.9.5"
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__version__bak = __version__ # This version is backup for QlibConfig.reset_qlib_version
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import os
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from typing import Union
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@@ -12,15 +12,11 @@ import datetime
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from tqdm import tqdm
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from pathlib import Path
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from loguru import logger
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from cryptography.fernet import Fernet
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from qlib.utils import exists_qlib_data
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class GetData:
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REMOTE_URL = "https://qlibpublic.blob.core.windows.net/data/default/stock_data"
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# "?" is not included in the token.
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TOKEN = b"gAAAAABkmDhojHc0VSCDdNK1MqmRzNLeDFXe5hy8obHpa6SDQh4de6nW5gtzuD-fa6O_WZb0yyqYOL7ndOfJX_751W3xN5YB4-n-P22jK-t6ucoZqhT70KPD0Lf0_P328QPJVZ1gDnjIdjhi2YLOcP4BFTHLNYO0mvzszR8TKm9iT5AKRvuysWnpi8bbYwGU9zAcJK3x9EPL43hOGtxliFHcPNGMBoJW4g_ercdhi0-Qgv5_JLsV-29_MV-_AhuaYvJuN2dEywBy"
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KEY = "EYcA8cgorA8X9OhyMwVfuFxn_1W3jGk6jCbs3L2oPoA="
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REMOTE_URL = "https://github.com/SunsetWolf/qlib_dataset/releases/download"
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def __init__(self, delete_zip_file=False):
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"""
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@@ -33,9 +29,45 @@ class GetData:
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self.delete_zip_file = delete_zip_file
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def merge_remote_url(self, file_name: str):
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fernet = Fernet(self.KEY)
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token = fernet.decrypt(self.TOKEN).decode()
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return f"{self.REMOTE_URL}/{file_name}?{token}"
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"""
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Generate download links.
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Parameters
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----------
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file_name: str
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The name of the file to be downloaded.
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The file name can be accompanied by a version number, (e.g.: v2/qlib_data_simple_cn_1d_latest.zip),
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if no version number is attached, it will be downloaded from v0 by default.
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"""
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return f"{self.REMOTE_URL}/{file_name}" if "/" in file_name else f"{self.REMOTE_URL}/v0/{file_name}"
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def download(self, url: str, target_path: [Path, str]):
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"""
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Download a file from the specified url.
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Parameters
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----------
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url: str
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The url of the data.
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target_path: str
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The location where the data is saved, including the file name.
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"""
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file_name = str(target_path).rsplit("/", maxsplit=1)[-1]
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resp = requests.get(url, stream=True, timeout=60)
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resp.raise_for_status()
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if resp.status_code != 200:
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raise requests.exceptions.HTTPError()
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chunk_size = 1024
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logger.warning(
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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.)"
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)
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logger.info(f"{os.path.basename(file_name)} downloading......")
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with tqdm(total=int(resp.headers.get("Content-Length", 0))) as p_bar:
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with target_path.open("wb") as fp:
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for chunk in resp.iter_content(chunk_size=chunk_size):
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fp.write(chunk)
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p_bar.update(chunk_size)
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def download_data(self, file_name: str, target_dir: [Path, str], delete_old: bool = True):
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"""
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@@ -70,21 +102,7 @@ class GetData:
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target_path = target_dir.joinpath(_target_file_name)
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url = self.merge_remote_url(file_name)
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resp = requests.get(url, stream=True, timeout=60)
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resp.raise_for_status()
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if resp.status_code != 200:
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raise requests.exceptions.HTTPError()
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chunk_size = 1024
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logger.warning(
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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.)"
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)
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logger.info(f"{os.path.basename(file_name)} downloading......")
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with tqdm(total=int(resp.headers.get("Content-Length", 0))) as p_bar:
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with target_path.open("wb") as fp:
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for chunk in resp.iter_content(chunk_size=chunk_size):
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fp.write(chunk)
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p_bar.update(chunk_size)
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self.download(url=url, target_path=target_path)
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self._unzip(target_path, target_dir, delete_old)
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if self.delete_zip_file:
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@@ -99,7 +117,9 @@ class GetData:
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return status
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@staticmethod
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def _unzip(file_path: Path, target_dir: Path, delete_old: bool = True):
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def _unzip(file_path: [Path, str], target_dir: [Path, str], delete_old: bool = True):
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file_path = Path(file_path)
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target_dir = Path(target_dir)
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if delete_old:
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logger.warning(
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f"will delete the old qlib data directory(features, instruments, calendars, features_cache, dataset_cache): {target_dir}"
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