from qlib.data.backend.ddb_qlib import (
    create_feature_daily_table,
    create_calendar_table,
    create_instrument_table,
)

# 连接格式: dolphindb://用户名:密码@主机:端口
uri = "dolphindb://admin:123456@localhost:8848"

# 创建特征数据表
create_feature_daily_table(uri)

# 创建股票信息表
create_instrument_table(uri)

# 创建交易日历表
create_calendar_table(uri)

from qlib.data.backend.ddb_qlib import init_qlib_ddb_from_mysql

ddb_uri = "dolphindb://admin:123456@localhost:8848"
mysql_uri = "mysql+mysqlconnector://root:123456@localhost:3306/windDB"

init_qlib_ddb_from_mysql(ddb_uri, mysql_uri)

import qlib
from qlib.constant import REG_CN
from qlib.data import D

# 初始化（使用 dolphindb:// 前缀）
uri = "dolphindb://admin:123456@localhost:8848"
qlib.init(database_uri=uri, region=REG_CN)

# 获取股票池
pool = D.instruments("ashares")
codes = D.list_instruments(pool, as_list=True)

# 获取交易日历
calendar = D.calendar()

# 使用 QLib 标准表达式
D.features(
    codes,
    start_time="2021-01-01",
    end_time="2024-04-12",
    fields=["Ref($S_DQ_ADJCLOSE, -2)/Ref($S_DQ_ADJCLOSE, -1) - 1"],
)

D.features(
    instruments=codes,
    fields=[
        "WQAlpha1($close)",                              # WorldQuant 101 Alpha #1
        "gtjaAlpha1($open, $close, $volume)",            # 国泰君安 191 Alpha #1
        "qlib158Alpha1($open, $close)",                   # Alpha158 #1
        "$high",                                          # 基础字段
        "Ref($S_DQ_ADJCLOSE, -2)/Ref($S_DQ_ADJCLOSE, -1) - 1",  # 自定义表达式
    ],
    start_time="2020-01-01",
    end_time="2023-12-31",
    freq="day",
)

from qlib.contrib.data.loader import Alpha158DL
from qlib.data.dataset.loader import QlibDataLoader

conf = {
    "kbar": {},
    "price": {"windows": [0], "feature": ["OPEN", "HIGH", "LOW", "VWAP"]},
    "rolling": {},
}

alpha158_expression, alpha158_names = Alpha158DL().get_feature_config(conf)

qdl = QlibDataLoader(config=(alpha158_expression, alpha158_names))
dataset = qdl.load(instruments=codes, start_time="2021-01-01", end_time="2023-12-31")

from qlib.data.dataset.loader import DolphinDBDataLoader

uri = "dolphindb://admin:123456@localhost:8848"
qlib.init(database_uri=uri, region=REG_CN)

loader = DolphinDBDataLoader(
    table_name="stockDerivative",    # 表名（第一个参数）
    db_name="DailyBase",             # 数据库名（可选）
    config={
        "fields": ["S_PQ_HIGH_52W_", "S_VAL_PE"],
        "datetime_colName": "TRADE_DT",
        "instruments_colName": "S_INFO_WINDCODE",
        "pivot": False,
    },
)

data = loader.load(start_time="2025-01-01", end_time="2025-01-31")

from qlib.contrib.report.graph import (
    plot_bar,
    plot_timeseries,
    plot_distribution,
    plot_qq,
    CalendarGraph,     # 日历热力图
    ScatterGraph,      # 散点图
    BarGraph,          # 柱状图
    DistplotGraph,     # 分布图
)

from qlib.contrib.report.analysis_model.analysis_model_performance import (
    model_performance_graph,
    compute_group_return,
    compute_ic,
)

# 生成完整的模型性能报告（IC、分组收益、 autocorrelation 等）
model_performance_graph(pred_label, show_notebook=True)

from qlib.contrib.report.analysis_position.risk_analysis import risk_analysis_graph

# 生成风险分析图表（累计收益、回撤、波动率等）
risk_analysis_graph(analysis_df, report_normal_df, show_notebook=True)

from qlib.contrib.report.analysis_alpha.factor_stats import (
    FactorAnalyzer,
    run_factor_analysis,
)

# 一键运行完整因子分析（IC、分组收益、换手率等）
result = run_factor_analysis(
    factor_data=factor_df,
    return_data=return_df,
    group_count=5,
)

from qlib.contrib.report.display_config import ReportGraphConfig

# 自定义图表配置（图例、标题、颜色等）
config = ReportGraphConfig(
    width="100%",
    height=500,
    legend_position="top",
)

# 实际连接
dolphindb://admin:123456@172.17.0.1:8848

# 日志输出
DolphinDB(dolphindb://admin:***@172.17.0.1:8848)

qlib.init(database_uri=uri, log_mask_sensitive=False)