Fix code and docs for issues (#853)

* Docs for model and strategy

* add some docs about workflow and online

* safe_load yaml

* DDG-DA paper link and comments for code

docs/component/model.rst

@@ -106,6 +106,9 @@ Example
         `SignalRecord` is the `Record Template` in ``Qlib``, please refer to `Workflow <recorder.html#record-template>`_.
 
 Also, the above example has been given in ``examples/train_backtest_analyze.ipynb``.
+Technically, the meaning of the model prediction depends on the label setting designed by user.
+By default, the meaning of the score is normally the rating of the instruments by the forecasting model. The higher the score, the more profit the instruments. 
+
 
 Custom Model
 ===================

docs/component/online.rst

@@ -23,6 +23,10 @@ The `examples <https://github.com/microsoft/qlib/tree/main/examples/online_srv>`
 
 **NOTE**: User should keep his data source updated to support online serving. For example, Qlib provides `a batch of scripts <https://github.com/microsoft/qlib/blob/main/scripts/data_collector/yahoo/README.md#automatic-update-of-daily-frequency-datafrom-yahoo-finance>`_ to help users update Yahoo daily data.
 
+Known limitations currently
+- Currently, the daily updating prediction for the next trading day is supported. But generating orders for the next trading day is not supported due to the `limitations of public data <https://github.com/microsoft/qlib/issues/215#issuecomment-766293563>_`
+
+
 Online Manager
 =============
 

docs/component/strategy.rst

@@ -29,6 +29,8 @@ Qlib provides a base class ``qlib.strategy.base.BaseStrategy``. All strategy cla
 
 - `generate_order_list`
     Return the order list.
+    The frequency to call this method depends on the executor frequency("time_per_step"="day" by default). But the trading frequency can be decided by users' implementation.
+    For example, if the user wants to trading in weekly while the `time_per_step` is "day" in executor, user can return non-empty TradeDecision weekly(otherwise return empty like `this <https://github.com/microsoft/qlib/blob/main/qlib/contrib/strategy/signal_strategy.py#L132>`_ ).
 
 Users can inherit `BaseStrategy` to customize their strategy class.
 

docs/component/workflow.rst

@@ -124,9 +124,47 @@ Configuration File
 ===================
 
 Let's get into details of ``qrun`` in this section.
-
 Before using ``qrun``, users need to prepare a configuration file. The following content shows how to prepare each part of the configuration file.
 
+The design logic of the configuration file is very simple. It predefines fixed workflows and provide this yaml interface to users to define how to initialize each component. 
+It follow the design of `init_instance_by_config <https://github.com/microsoft/qlib/blob/2aee9e0145decc3e71def70909639b5e5a6f4b58/qlib/utils/__init__.py#L264>`_ .  It defines the initialization of each component of Qlib, which typically include the class and the initialization arguments.
+
+For example, the following yaml and code are equivalent.
+
+.. code-block:: YAML
+
+    model:
+        class: LGBModel
+        module_path: qlib.contrib.model.gbdt
+        kwargs:
+            loss: mse
+            colsample_bytree: 0.8879
+            learning_rate: 0.0421
+            subsample: 0.8789
+            lambda_l1: 205.6999
+            lambda_l2: 580.9768
+            max_depth: 8
+            num_leaves: 210
+            num_threads: 20
+
+
+.. code-block:: python
+
+        from qlib.contrib.model.gbdt import LGBModel
+        kwargs = {
+            "loss": "mse" ,
+            "colsample_bytree": 0.8879,
+            "learning_rate": 0.0421,
+            "subsample": 0.8789,
+            "lambda_l1": 205.6999,
+            "lambda_l2": 580.9768,
+            "max_depth": 8,
+            "num_leaves": 210,
+            "num_threads": 20,
+        }
+        LGBModel(kwargs)
+
+
 Qlib Init Section
 --------------------