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qlib/docs/start/initialization.rst
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$ `flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics`
```
./qlib/qlib/contrib/model/pytorch_tabnet.py:567:38: F821 undefined name 'inp'
            self.independ.append(GLU(inp, out_dim, vbs=vbs))
                                     ^
./qlib/examples/model_rolling/task_manager_rolling.py:75:18: F821 undefined name 'task_train'
        run_task(task_train, self.task_pool, experiment_name=self.experiment_name)
                 ^
2     F821 undefined name 'task_train'
2
```

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.. _initialization:
====================
Qlib Initialization
====================
.. currentmodule:: qlib
Initialization
=========================
Please follow the steps below to initialize ``Qlib``.
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
python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/cn_data --region cn
Please refer to `Data Preparation <../component/data.html#data-preparation>`_ for more information about `get_data.py`,
Initialize Qlib before calling other APIs: run following code in python.
.. code-block:: Python
import qlib
# region in [REG_CN, REG_US]
from qlib.config import REG_CN
provider_uri = "~/.qlib/qlib_data/cn_data" # target_dir
qlib.init(provider_uri=provider_uri, region=REG_CN)
.. note::
Do not import qlib package in the repository directory of ``Qlib``, otherwise, errors may occur.
Parameters
-------------------
Besides `provider_uri` and `region`, `qlib.init` has other parameters. The following are several important parameters of `qlib.init`:
- `provider_uri`
Type: str. The URI of the Qlib data. For example, it could be the location where the data loaded by ``get_data.py`` are stored.
- `region`
Type: str, optional parameter(default: `qlib.config.REG_CN`).
Currently: ``qlib.config.REG_US`` ('us') and ``qlib.config.REG_CN`` ('cn') is supported. Different value of `region` will result in different stock market mode.
- ``qlib.config.REG_US``: US stock market.
- ``qlib.config.REG_CN``: China stock market.
Different modes will result in different trading limitations and costs.
- `redis_host`
Type: str, optional parameter(default: "127.0.0.1"), host of `redis`
The lock and cache mechanism relies on redis.
- `redis_port`
Type: int, optional parameter(default: 6379), port of `redis`
.. note::
The value of `region` should be aligned with the data stored in `provider_uri`. Currently, ``scripts/get_data.py`` only provides China stock market data. If users want to use the US stock market data, they should prepare their own US-stock data in `provider_uri` and switch to US-stock mode.
.. note::
If Qlib fails to connect redis via `redis_host` and `redis_port`, cache mechanism will not be used! Please refer to `Cache <../component/data.html#cache>`_ for details.
- `exp_manager`
Type: dict, optional parameter, the setting of `experiment manager` to be used in qlib. Users can specify an experiment manager class, as well as the tracking URI for all the experiments. However, please be aware that we only support input of a dictionary in the following style for `exp_manager`. For more information about `exp_manager`, users can refer to `Recorder: Experiment Management <../component/recorder.html>`_.
.. code-block:: Python
# For example, if you want to set your tracking_uri to a <specific folder>, you can initialize qlib below
qlib.init(provider_uri=provider_uri, region=REG_CN, exp_manager= {
"class": "MLflowExpManager",
"module_path": "qlib.workflow.expm",
"kwargs": {
"uri": "python_execution_path/mlruns",
"default_exp_name": "Experiment",
}
})
- `mongo`
Type: dict, optional parameter, the setting of `MongoDB <https://www.mongodb.com/>`_ which will be used in some features such as `Task Management <../advanced/task_management.html>`_, with high performance and clustered processing.
Users need to follow the steps in `installation <https://www.mongodb.com/try/download/community>`_ to install MongoDB firstly and then access it via a URI.
Users can access mongodb with credential by setting "task_url" to a string like `"mongodb://%s:%s@%s" % (user, pwd, host + ":" + port)`.
.. code-block:: Python
# For example, you can initialize qlib below
qlib.init(provider_uri=provider_uri, region=REG_CN, mongo={
"task_url": "mongodb://localhost:27017/", # your mongo url
"task_db_name": "rolling_db", # the database name of Task Management
})