build factor source data (price and volumns) from qlib if no source data is provided by the user (#168)

.gitignore

@@ -139,6 +139,9 @@ dmypy.json
 # all pkl files
 *.pkl
 
+# all h5 files
+*.h5
+
 # all vs-code files
 .vscode/
 

rdagent/app/qlib_rd_loop/factor_from_report_w_sc.py

@@ -6,29 +6,26 @@ from typing import Any, Tuple
 import fire
 from jinja2 import Environment, StrictUndefined
 
-from rdagent.app.qlib_rd_loop.conf import FactorBasePropSetting
+from rdagent.app.qlib_rd_loop.conf import (
+    FACTOR_FROM_REPORT_PROP_SETTING,
+    FactorBasePropSetting,
+)
+from rdagent.app.qlib_rd_loop.factor_w_sc import FactorRDLoop
 from rdagent.components.document_reader.document_reader import (
     extract_first_page_screenshot_from_pdf,
     load_and_process_pdfs_by_langchain,
 )
-from rdagent.components.workflow.conf import BasePropSetting
 from rdagent.components.workflow.rd_loop import RDLoop
-from rdagent.core.developer import Developer
 from rdagent.core.exception import FactorEmptyError
 from rdagent.core.prompts import Prompts
-from rdagent.core.proposal import Hypothesis, HypothesisExperiment2Feedback, Trace
-from rdagent.core.scenario import Scenario
-from rdagent.core.utils import import_class
+from rdagent.core.proposal import Hypothesis
 from rdagent.log import rdagent_logger as logger
 from rdagent.oai.llm_utils import APIBackend
 from rdagent.scenarios.qlib.experiment.factor_experiment import QlibFactorExperiment
-from rdagent.scenarios.qlib.experiment.factor_from_report_experiment import (
-    QlibFactorFromReportScenario,
-)
 from rdagent.scenarios.qlib.factor_experiment_loader.pdf_loader import (
     FactorExperimentLoaderFromPDFfiles,
 )
-from rdagent.utils.workflow import LoopBase, LoopMeta
+from rdagent.utils.workflow import LoopMeta
 
 prompts_path = Path(__file__).parent / "prompts.yaml"
 prompts = Prompts(file_path=prompts_path)
@@ -90,14 +87,14 @@ def extract_hypothesis_and_exp_from_reports(report_file_path: str) -> Tuple[Qlib
     return exp, hypothesis
 
 
-class FactorReportLoop(RDLoop, metaclass=LoopMeta):
+class FactorReportLoop(FactorRDLoop, metaclass=LoopMeta):
     skip_loop_error = (FactorEmptyError,)
 
     def __init__(self, PROP_SETTING: FactorBasePropSetting):
+        super().__init__(PROP_SETTING=PROP_SETTING)
         self.judge_pdf_data_items = json.load(open(PROP_SETTING.report_result_json_file_path, "r"))
         self.pdf_file_index = 0
         self.valid_pdf_file_count = 0
-        super().__init__(PROP_SETTING=PROP_SETTING)
 
     def propose_hypo_exp(self, prev_out: dict[str, Any]):
         with logger.tag("r"):

rdagent/components/coder/factor_coder/CoSTEER/evolving_strategy.py

@@ -17,7 +17,6 @@ from rdagent.components.coder.factor_coder.CoSTEER.scheduler import (
     RandomSelect,
 )
 from rdagent.components.coder.factor_coder.factor import FactorFBWorkspace, FactorTask
-from rdagent.components.coder.factor_coder.utils import get_data_folder_intro
 from rdagent.core.conf import RD_AGENT_SETTINGS
 from rdagent.core.evolving_framework import EvolvingStrategy, QueriedKnowledge
 from rdagent.core.experiment import Workspace

rdagent/components/coder/factor_coder/CoSTEER/scheduler.py

@@ -7,7 +7,6 @@ from jinja2 import Environment, StrictUndefined
 from rdagent.components.coder.factor_coder.CoSTEER.evolvable_subjects import (
     FactorEvolvingItem,
 )
-from rdagent.components.coder.factor_coder.utils import get_data_folder_intro
 from rdagent.core.conf import RD_AGENT_SETTINGS
 from rdagent.core.prompts import Prompts
 from rdagent.core.scenario import Scenario

rdagent/components/coder/factor_coder/utils.py

@@ -1,51 +0,0 @@
-from pathlib import Path
-
-import pandas as pd
-
-# render it with jinja
-from jinja2 import Environment, StrictUndefined
-
-from rdagent.components.coder.factor_coder.config import FACTOR_IMPLEMENT_SETTINGS
-
-TPL = """
-{{file_name}}
-```{{type_desc}}
-{{content}}
-````
-"""
-# Create a Jinja template from the string
-JJ_TPL = Environment(undefined=StrictUndefined).from_string(TPL)
-
-
-def get_data_folder_intro():
-    """Directly get the info of the data folder.
-    It is for preparing prompting message.
-    """
-    content_l = []
-    for p in Path(FACTOR_IMPLEMENT_SETTINGS.data_folder_debug).iterdir():
-        if p.name.endswith(".h5"):
-            df = pd.read_hdf(p)
-            # get  df.head() as string with full width
-            pd.set_option("display.max_columns", None)  # or 1000
-            pd.set_option("display.max_rows", None)  # or 1000
-            pd.set_option("display.max_colwidth", None)  # or 199
-            rendered = JJ_TPL.render(
-                file_name=p.name,
-                type_desc="generated by `pd.read_hdf(filename).head()`",
-                content=df.head().to_string(),
-            )
-            content_l.append(rendered)
-        elif p.name.endswith(".md"):
-            with open(p) as f:
-                content = f.read()
-                rendered = JJ_TPL.render(
-                    file_name=p.name,
-                    type_desc="markdown",
-                    content=content,
-                )
-                content_l.append(rendered)
-        else:
-            raise NotImplementedError(
-                f"file type {p.name} is not supported. Please implement its description function.",
-            )
-    return "\n ----------------- file splitter -------------\n".join(content_l)

rdagent/scenarios/qlib/experiment/factor_data_template/README.md

@@ -0,0 +1,24 @@
+# How to read files.
+For example, if you want to read `filename.h5`
+```Python
+import pandas as pd
+df = pd.read_hdf("filename.h5", key="data")
+```
+NOTE: **key is always "data" for all hdf5 files **.
+
+# Here is a short description about the data
+
+| Filename       | Description                                                      |
+| -------------- | -----------------------------------------------------------------|
+| "daily_pv.h5"  | Adjusted daily price and volume data.                            |
+
+
+# For different data, We have some basic knowledge for them
+
+## Daily price and volume data
+$open: open price of the stock on that day.
+$close: close price of the stock on that day.
+$high: high price of the stock on that day.
+$low: low price of the stock on that day.
+$volume: volume of the stock on that day.
+$factor: factor value of the stock on that day.

rdagent/scenarios/qlib/experiment/factor_data_template/generate.py

@@ -0,0 +1,27 @@
+import qlib
+
+qlib.init(provider_uri="~/.qlib/qlib_data/cn_data")
+
+from qlib.data import D
+
+instruments = D.instruments()
+fields = ["$open", "$close", "$high", "$low", "$volume", "$factor"]
+data = D.features(instruments, fields, freq="day").swaplevel().sort_index().loc["2008-12-29":].sort_index()
+
+data.to_hdf("./daily_pv_all.h5", key="data")
+
+
+fields = ["$open", "$close", "$high", "$low", "$volume", "$factor"]
+data = (
+    (
+        D.features(instruments, fields, start_time="2018-01-01", end_time="2019-12-31", freq="day")
+        .swaplevel()
+        .sort_index()
+    )
+    .swaplevel()
+    .loc[data.reset_index()["instrument"].unique()[:100]]
+    .swaplevel()
+    .sort_index()
+)
+
+data.to_hdf("./daily_pv_debug.h5", key="data")

rdagent/scenarios/qlib/experiment/factor_experiment.py

@@ -5,9 +5,9 @@ from rdagent.components.coder.factor_coder.factor import (
     FactorFBWorkspace,
     FactorTask,
 )
-from rdagent.components.coder.factor_coder.utils import get_data_folder_intro
 from rdagent.core.prompts import Prompts
 from rdagent.core.scenario import Scenario
+from rdagent.scenarios.qlib.experiment.utils import get_data_folder_intro
 from rdagent.scenarios.qlib.experiment.workspace import QlibFBWorkspace
 
 prompt_dict = Prompts(file_path=Path(__file__).parent / "prompts.yaml")

rdagent/scenarios/qlib/experiment/factor_from_report_experiment.py

@@ -5,7 +5,6 @@ from rdagent.components.coder.factor_coder.factor import (
     FactorFBWorkspace,
     FactorTask,
 )
-from rdagent.components.coder.factor_coder.utils import get_data_folder_intro
 from rdagent.core.prompts import Prompts
 from rdagent.core.scenario import Scenario
 from rdagent.scenarios.qlib.experiment.factor_experiment import QlibFactorScenario

rdagent/scenarios/qlib/experiment/utils.py

@@ -0,0 +1,98 @@
+import shutil
+from pathlib import Path
+
+import pandas as pd
+
+# render it with jinja
+from jinja2 import Environment, StrictUndefined
+
+from rdagent.components.coder.factor_coder.config import FACTOR_IMPLEMENT_SETTINGS
+from rdagent.utils.env import QTDockerEnv
+
+
+def generate_data_folder_from_qlib():
+    template_path = Path(__file__).parent / "factor_data_template"
+    qtde = QTDockerEnv()
+    qtde.prepare()
+
+    # Run the Qlib backtest
+    execute_log = qtde.run(
+        local_path=str(template_path),
+        entry=f"python generate.py",
+    )
+
+    assert (
+        Path(__file__).parent / "factor_data_template" / "daily_pv_all.h5"
+    ).exists(), "daily_pv_all.h5 is not generated."
+    assert (
+        Path(__file__).parent / "factor_data_template" / "daily_pv_debug.h5"
+    ).exists(), "daily_pv_debug.h5 is not generated."
+
+    Path(FACTOR_IMPLEMENT_SETTINGS.data_folder).mkdir(parents=True, exist_ok=True)
+    shutil.copy(
+        Path(__file__).parent / "factor_data_template" / "daily_pv_all.h5",
+        Path(FACTOR_IMPLEMENT_SETTINGS.data_folder) / "daily_pv.h5",
+    )
+    shutil.copy(
+        Path(__file__).parent / "factor_data_template" / "README.md",
+        Path(FACTOR_IMPLEMENT_SETTINGS.data_folder) / "README.md",
+    )
+
+    Path(FACTOR_IMPLEMENT_SETTINGS.data_folder_debug).mkdir(parents=True, exist_ok=True)
+    shutil.copy(
+        Path(__file__).parent / "factor_data_template" / "daily_pv_debug.h5",
+        Path(FACTOR_IMPLEMENT_SETTINGS.data_folder_debug) / "daily_pv.h5",
+    )
+    shutil.copy(
+        Path(__file__).parent / "factor_data_template" / "README.md",
+        Path(FACTOR_IMPLEMENT_SETTINGS.data_folder_debug) / "README.md",
+    )
+
+
+def get_data_folder_intro():
+    """Directly get the info of the data folder.
+    It is for preparing prompting message.
+    """
+
+    if (
+        not Path(FACTOR_IMPLEMENT_SETTINGS.data_folder).exists()
+        or not Path(FACTOR_IMPLEMENT_SETTINGS.data_folder_debug).exists()
+    ):
+        generate_data_folder_from_qlib()
+
+    JJ_TPL = Environment(undefined=StrictUndefined).from_string(
+        """
+{{file_name}}
+```{{type_desc}}
+{{content}}
+```
+"""
+    )
+    content_l = []
+    for p in Path(FACTOR_IMPLEMENT_SETTINGS.data_folder_debug).iterdir():
+        if p.name.endswith(".h5"):
+            df = pd.read_hdf(p)
+            # get  df.head() as string with full width
+            pd.set_option("display.max_columns", None)  # or 1000
+            pd.set_option("display.max_rows", None)  # or 1000
+            pd.set_option("display.max_colwidth", None)  # or 199
+            rendered = JJ_TPL.render(
+                file_name=p.name,
+                type_desc="generated by `pd.read_hdf(filename).head()`",
+                content=df.head().to_string(),
+            )
+            content_l.append(rendered)
+        elif p.name.endswith(".md"):
+            with open(p) as f:
+                content = f.read()
+                rendered = JJ_TPL.render(
+                    file_name=p.name,
+                    type_desc="markdown",
+                    content=content,
+                )
+                content_l.append(rendered)
+        else:
+            raise NotImplementedError(
+                f"file type {p.name} is not supported. Please implement its description function.",
+            )
+    return "\n ----------------- file splitter -------------\n".join(content_l)

rdagent/utils/workflow.py

@@ -7,6 +7,7 @@ Postscripts:
   However, Python generator is not picklable (dill does not support pickle as well)
 
 """
+
 import datetime
 import pickle
 from collections import defaultdict
@@ -27,7 +28,9 @@ class LoopMeta(type):
         """
         steps = []
         for base in bases:
-            steps.extend(LoopMeta._get_steps(base.__bases__) + getattr(base, "steps", []))
+            for step in LoopMeta._get_steps(base.__bases__) + getattr(base, "steps", []):
+                if step not in steps:
+                    steps.append(step)
         return steps
 
     def __new__(cls, clsname, bases, attrs):