modify scripts

2025-07-31 17:42:47 +08:00
parent cbd9b18ef4
commit 76cb84d401
17 changed files with 1654 additions and 0 deletions
--- a/src/sqlalchemy/alembic.ini
+++ b/src/sqlalchemy/alembic.ini
@ -0,0 +1,147 @@
+# A generic, single database configuration.
+
+[alembic]
+# path to migration scripts.
+# this is typically a path given in POSIX (e.g. forward slashes)
+# format, relative to the token %(here)s which refers to the location of this
+# ini file
+script_location = %(here)s
+
+# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
+# Uncomment the line below if you want the files to be prepended with date and time
+# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
+# for all available tokens
+# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
+
+# sys.path path, will be prepended to sys.path if present.
+# defaults to the current working directory.  for multiple paths, the path separator
+# is defined by "path_separator" below.
+prepend_sys_path = .
+
+
+# timezone to use when rendering the date within the migration file
+# as well as the filename.
+# If specified, requires the python>=3.9 or backports.zoneinfo library and tzdata library.
+# Any required deps can installed by adding `alembic[tz]` to the pip requirements
+# string value is passed to ZoneInfo()
+# leave blank for localtime
+# timezone =
+
+# max length of characters to apply to the "slug" field
+# truncate_slug_length = 40
+
+# set to 'true' to run the environment during
+# the 'revision' command, regardless of autogenerate
+# revision_environment = false
+
+# set to 'true' to allow .pyc and .pyo files without
+# a source .py file to be detected as revisions in the
+# versions/ directory
+# sourceless = false
+
+# version location specification; This defaults
+# to <script_location>/versions.  When using multiple version
+# directories, initial revisions must be specified with --version-path.
+# The path separator used here should be the separator specified by "path_separator"
+# below.
+# version_locations = %(here)s/bar:%(here)s/bat:%(here)s/alembic/versions
+
+# path_separator; This indicates what character is used to split lists of file
+# paths, including version_locations and prepend_sys_path within configparser
+# files such as alembic.ini.
+# The default rendered in new alembic.ini files is "os", which uses os.pathsep
+# to provide os-dependent path splitting.
+#
+# Note that in order to support legacy alembic.ini files, this default does NOT
+# take place if path_separator is not present in alembic.ini.  If this
+# option is omitted entirely, fallback logic is as follows:
+#
+# 1. Parsing of the version_locations option falls back to using the legacy
+#    "version_path_separator" key, which if absent then falls back to the legacy
+#    behavior of splitting on spaces and/or commas.
+# 2. Parsing of the prepend_sys_path option falls back to the legacy
+#    behavior of splitting on spaces, commas, or colons.
+#
+# Valid values for path_separator are:
+#
+# path_separator = :
+# path_separator = ;
+# path_separator = space
+# path_separator = newline
+#
+# Use os.pathsep. Default configuration used for new projects.
+path_separator = os
+
+# set to 'true' to search source files recursively
+# in each "version_locations" directory
+# new in Alembic version 1.10
+# recursive_version_locations = false
+
+# the output encoding used when revision files
+# are written from script.py.mako
+# output_encoding = utf-8
+
+# database URL.  This is consumed by the user-maintained env.py script only.
+# other means of configuring database URLs may be customized within the env.py
+# file.
+sqlalchemy.url = driver://user:pass@localhost/dbname
+
+
+[post_write_hooks]
+# post_write_hooks defines scripts or Python functions that are run
+# on newly generated revision scripts.  See the documentation for further
+# detail and examples
+
+# format using "black" - use the console_scripts runner, against the "black" entrypoint
+# hooks = black
+# black.type = console_scripts
+# black.entrypoint = black
+# black.options = -l 79 REVISION_SCRIPT_FILENAME
+
+# lint with attempts to fix using "ruff" - use the module runner, against the "ruff" module
+# hooks = ruff
+# ruff.type = module
+# ruff.module = ruff
+# ruff.options = check --fix REVISION_SCRIPT_FILENAME
+
+# Alternatively, use the exec runner to execute a binary found on your PATH
+# hooks = ruff
+# ruff.type = exec
+# ruff.executable = ruff
+# ruff.options = check --fix REVISION_SCRIPT_FILENAME
+
+# Logging configuration.  This is also consumed by the user-maintained
+# env.py script only.
+[loggers]
+keys = root,sqlalchemy,alembic
+
+[handlers]
+keys = console
+
+[formatters]
+keys = generic
+
+[logger_root]
+level = WARNING
+handlers = console
+qualname =
+
+[logger_sqlalchemy]
+level = WARNING
+handlers =
+qualname = sqlalchemy.engine
+
+[logger_alembic]
+level = INFO
+handlers =
+qualname = alembic
+
+[handler_console]
+class = StreamHandler
+args = (sys.stderr,)
+level = NOTSET
+formatter = generic
+
+[formatter_generic]
+format = %(levelname)-5.5s [%(name)s] %(message)s
+datefmt = %H:%M:%S
--- a/src/sqlalchemy/config.py
+++ b/src/sqlalchemy/config.py
@ -0,0 +1,12 @@
+import os
+from pathlib import Path
+
+# MySQL 配置
+db_config = {
+    'host': 'testdb',
+    'user': 'root',
+    'password': 'mysqlpw',
+    'database': 'stockdb'
+}
+
+global_db_url = f"mysql+pymysql://{db_config['user']}:{db_config['password']}@{db_config['host']}:3306/{db_config['database']}?charset=utf8mb4"
--- a/src/sqlalchemy/migrations/stockdb/README
+++ b/src/sqlalchemy/migrations/stockdb/README
@ -0,0 +1 @@
+Generic single-database configuration.
--- a/src/sqlalchemy/migrations/stockdb/alembic.ini
+++ b/src/sqlalchemy/migrations/stockdb/alembic.ini
@ -0,0 +1,147 @@
+# A generic, single database configuration.
+
+[alembic]
+# path to migration scripts.
+# this is typically a path given in POSIX (e.g. forward slashes)
+# format, relative to the token %(here)s which refers to the location of this
+# ini file
+script_location = %(here)s
+
+# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
+# Uncomment the line below if you want the files to be prepended with date and time
+# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
+# for all available tokens
+# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
+
+# sys.path path, will be prepended to sys.path if present.
+# defaults to the current working directory.  for multiple paths, the path separator
+# is defined by "path_separator" below.
+prepend_sys_path = .
+
+
+# timezone to use when rendering the date within the migration file
+# as well as the filename.
+# If specified, requires the python>=3.9 or backports.zoneinfo library and tzdata library.
+# Any required deps can installed by adding `alembic[tz]` to the pip requirements
+# string value is passed to ZoneInfo()
+# leave blank for localtime
+# timezone =
+
+# max length of characters to apply to the "slug" field
+# truncate_slug_length = 40
+
+# set to 'true' to run the environment during
+# the 'revision' command, regardless of autogenerate
+# revision_environment = false
+
+# set to 'true' to allow .pyc and .pyo files without
+# a source .py file to be detected as revisions in the
+# versions/ directory
+# sourceless = false
+
+# version location specification; This defaults
+# to <script_location>/versions.  When using multiple version
+# directories, initial revisions must be specified with --version-path.
+# The path separator used here should be the separator specified by "path_separator"
+# below.
+# version_locations = %(here)s/bar:%(here)s/bat:%(here)s/alembic/versions
+
+# path_separator; This indicates what character is used to split lists of file
+# paths, including version_locations and prepend_sys_path within configparser
+# files such as alembic.ini.
+# The default rendered in new alembic.ini files is "os", which uses os.pathsep
+# to provide os-dependent path splitting.
+#
+# Note that in order to support legacy alembic.ini files, this default does NOT
+# take place if path_separator is not present in alembic.ini.  If this
+# option is omitted entirely, fallback logic is as follows:
+#
+# 1. Parsing of the version_locations option falls back to using the legacy
+#    "version_path_separator" key, which if absent then falls back to the legacy
+#    behavior of splitting on spaces and/or commas.
+# 2. Parsing of the prepend_sys_path option falls back to the legacy
+#    behavior of splitting on spaces, commas, or colons.
+#
+# Valid values for path_separator are:
+#
+# path_separator = :
+# path_separator = ;
+# path_separator = space
+# path_separator = newline
+#
+# Use os.pathsep. Default configuration used for new projects.
+path_separator = os
+
+# set to 'true' to search source files recursively
+# in each "version_locations" directory
+# new in Alembic version 1.10
+# recursive_version_locations = false
+
+# the output encoding used when revision files
+# are written from script.py.mako
+# output_encoding = utf-8
+
+# database URL.  This is consumed by the user-maintained env.py script only.
+# other means of configuring database URLs may be customized within the env.py
+# file.
+sqlalchemy.url = driver://user:pass@localhost/dbname
+
+
+[post_write_hooks]
+# post_write_hooks defines scripts or Python functions that are run
+# on newly generated revision scripts.  See the documentation for further
+# detail and examples
+
+# format using "black" - use the console_scripts runner, against the "black" entrypoint
+# hooks = black
+# black.type = console_scripts
+# black.entrypoint = black
+# black.options = -l 79 REVISION_SCRIPT_FILENAME
+
+# lint with attempts to fix using "ruff" - use the module runner, against the "ruff" module
+# hooks = ruff
+# ruff.type = module
+# ruff.module = ruff
+# ruff.options = check --fix REVISION_SCRIPT_FILENAME
+
+# Alternatively, use the exec runner to execute a binary found on your PATH
+# hooks = ruff
+# ruff.type = exec
+# ruff.executable = ruff
+# ruff.options = check --fix REVISION_SCRIPT_FILENAME
+
+# Logging configuration.  This is also consumed by the user-maintained
+# env.py script only.
+[loggers]
+keys = root,sqlalchemy,alembic
+
+[handlers]
+keys = console
+
+[formatters]
+keys = generic
+
+[logger_root]
+level = WARNING
+handlers = console
+qualname =
+
+[logger_sqlalchemy]
+level = WARNING
+handlers =
+qualname = sqlalchemy.engine
+
+[logger_alembic]
+level = INFO
+handlers =
+qualname = alembic
+
+[handler_console]
+class = StreamHandler
+args = (sys.stderr,)
+level = NOTSET
+formatter = generic
+
+[formatter_generic]
+format = %(levelname)-5.5s [%(name)s] %(message)s
+datefmt = %H:%M:%S
--- a/src/sqlalchemy/migrations/stockdb/env.py
+++ b/src/sqlalchemy/migrations/stockdb/env.py
@ -0,0 +1,99 @@
+from logging.config import fileConfig
+
+from sqlalchemy import engine_from_config
+from sqlalchemy import pool
+
+from alembic import context
+
+# this is the Alembic Config object, which provides
+# access to the values within the .ini file in use.
+config = context.config
+
+# Interpret the config file for Python logging.
+# This line sets up loggers basically.
+if config.config_file_name is not None:
+    fileConfig(config.config_file_name)
+
+# add your model's MetaData object here
+# for 'autogenerate' support
+# from myapp import mymodel
+# target_metadata = mymodel.Base.metadata
+target_metadata = None
+
+# other values from the config, defined by the needs of env.py,
+# can be acquired:
+# my_important_option = config.get_main_option("my_important_option")
+# ... etc.
+
+
+def run_migrations_offline() -> None:
+    """Run migrations in 'offline' mode.
+
+    This configures the context with just a URL
+    and not an Engine, though an Engine is acceptable
+    here as well.  By skipping the Engine creation
+    we don't even need a DBAPI to be available.
+
+    Calls to context.execute() here emit the given string to the
+    script output.
+
+    """
+    url = config.get_main_option("sqlalchemy.url")
+    context.configure(
+        url=url,
+        target_metadata=target_metadata,
+        literal_binds=True,
+        dialect_opts={"paramstyle": "named"},
+    )
+
+    with context.begin_transaction():
+        context.run_migrations()
+
+
+''' 修改点
+from models.modelclass_b import Base
+target_metadata = Base.metadata
+
+def run_migrations_online():
+    url = "sqlite:///../databases/db_b.db"
+    connectable = create_engine(url)
+    # 保持其他代码不变
+'''
+
+import os
+from alembic import context
+from sqlalchemy import create_engine
+from logging.config import fileConfig
+from models.stockdb import Base
+target_metadata = Base.metadata
+from config import db_config
+
+def run_migrations_online() -> None:
+    """Run migrations in 'online' mode.
+
+    In this scenario we need to create an Engine
+    and associate a connection with the context.
+
+    connectable = engine_from_config(
+        config.get_section(config.config_ini_section, {}),
+        prefix="sqlalchemy.",
+        poolclass=pool.NullPool,
+    )
+    """
+
+    url = f"mysql+pymysql://{db_config['user']}:{db_config['password']}@{db_config['host']}:3306/{db_config['database']}?charset=utf8mb4"
+    connectable = create_engine(url)
+
+    with connectable.connect() as connection:
+        context.configure(
+            connection=connection, target_metadata=target_metadata
+        )
+
+        with context.begin_transaction():
+            context.run_migrations()
+
+
+if context.is_offline_mode():
+    run_migrations_offline()
+else:
+    run_migrations_online()
--- a/src/sqlalchemy/migrations/stockdb/script.py.mako
+++ b/src/sqlalchemy/migrations/stockdb/script.py.mako
@ -0,0 +1,28 @@
+"""${message}
+
+Revision ID: ${up_revision}
+Revises: ${down_revision | comma,n}
+Create Date: ${create_date}
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+${imports if imports else ""}
+
+# revision identifiers, used by Alembic.
+revision: str = ${repr(up_revision)}
+down_revision: Union[str, Sequence[str], None] = ${repr(down_revision)}
+branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
+depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    ${upgrades if upgrades else "pass"}
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    ${downgrades if downgrades else "pass"}
--- a/src/sqlalchemy/migrations/stockdb/versions/0a39f1baab38_auto_update_from_stockdb.py
+++ b/src/sqlalchemy/migrations/stockdb/versions/0a39f1baab38_auto_update_from_stockdb.py
@ -0,0 +1,79 @@
+"""Auto update from stockdb
+
+Revision ID: 0a39f1baab38
+Revises: df56ac7669f2
+Create Date: 2025-07-31 16:05:20.579725
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '0a39f1baab38'
+down_revision: Union[str, Sequence[str], None] = 'df56ac7669f2'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('daily_snap',
+    sa.Column('code', sa.String(length=20), nullable=False, comment='股票代码'),
+    sa.Column('curr_date', sa.String(length=20), nullable=False, comment='交易日期'),
+    sa.Column('name', sa.String(length=50), nullable=True, comment='股票名称'),
+    sa.Column('market_id', sa.String(length=50), nullable=True, comment='市场名称'),
+    sa.Column('code_prefix', sa.Integer(), nullable=True, comment='代码前缀'),
+    sa.Column('industry', sa.String(length=50), nullable=True, comment='所处行业'),
+    sa.Column('listing_date', sa.Date(), nullable=True, comment='上市时间'),
+    sa.Column('latest_price', sa.Float(), nullable=True, comment='最新价'),
+    sa.Column('price_change_percent', sa.Float(), nullable=True, comment='涨跌幅(%)'),
+    sa.Column('price_change', sa.Float(), nullable=True, comment='涨跌额'),
+    sa.Column('volume', sa.Float(), nullable=True, comment='成交量'),
+    sa.Column('turnover', sa.Float(), nullable=True, comment='成交额'),
+    sa.Column('amplitude', sa.Float(), nullable=True, comment='振幅(%)'),
+    sa.Column('turnover_rate', sa.Float(), nullable=True, comment='换手率(%)'),
+    sa.Column('pe_dynamic', sa.Float(), nullable=True, comment='市盈率动'),
+    sa.Column('volume_ratio', sa.Float(), nullable=True, comment='量比'),
+    sa.Column('change_5min', sa.Float(), nullable=True, comment='5分钟涨跌(%)'),
+    sa.Column('highest', sa.Float(), nullable=True, comment='最高'),
+    sa.Column('lowest', sa.Float(), nullable=True, comment='最低'),
+    sa.Column('opening', sa.Float(), nullable=True, comment='今开'),
+    sa.Column('previous_close', sa.Float(), nullable=True, comment='昨收'),
+    sa.Column('price_speed', sa.Float(), nullable=True, comment='涨速(%)'),
+    sa.Column('total_market_cap', sa.Float(), nullable=True, comment='总市值'),
+    sa.Column('circulating_market_cap', sa.Float(), nullable=True, comment='流通市值'),
+    sa.Column('pb_ratio', sa.Float(), nullable=True, comment='市净率'),
+    sa.Column('change_60d', sa.Float(), nullable=True, comment='60日涨跌幅(%)'),
+    sa.Column('change_ytd', sa.Float(), nullable=True, comment='年初至今涨跌幅(%)'),
+    sa.Column('weighted_roe', sa.Float(), nullable=True, comment='加权净资产收益率(%)'),
+    sa.Column('total_shares', sa.Float(), nullable=True, comment='总股本'),
+    sa.Column('circulating_shares', sa.Float(), nullable=True, comment='已流通股份'),
+    sa.Column('operating_revenue', sa.Float(), nullable=True, comment='营业收入'),
+    sa.Column('revenue_growth', sa.Float(), nullable=True, comment='营业收入同比增长(%)'),
+    sa.Column('net_profit', sa.Float(), nullable=True, comment='归属净利润'),
+    sa.Column('net_profit_growth', sa.Float(), nullable=True, comment='归属净利润同比增长(%)'),
+    sa.Column('undistributed_profit_per_share', sa.Float(), nullable=True, comment='每股未分配利润'),
+    sa.Column('gross_margin', sa.Float(), nullable=True, comment='毛利率(%)'),
+    sa.Column('asset_liability_ratio', sa.Float(), nullable=True, comment='资产负债率(%)'),
+    sa.Column('reserve_per_share', sa.Float(), nullable=True, comment='每股公积金'),
+    sa.Column('earnings_per_share', sa.Float(), nullable=True, comment='每股收益'),
+    sa.Column('net_asset_per_share', sa.Float(), nullable=True, comment='每股净资产'),
+    sa.Column('pe_static', sa.Float(), nullable=True, comment='市盈率静'),
+    sa.Column('pe_ttm', sa.Float(), nullable=True, comment='市盈率TTM'),
+    sa.Column('report_period', sa.String(length=20), nullable=True, comment='报告期'),
+    sa.Column('created_at', sa.DateTime(), nullable=False, comment='记录创建时间'),
+    sa.PrimaryKeyConstraint('code', 'curr_date'),
+    comment='股票交易数据表'
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table('daily_snap')
+    # ### end Alembic commands ###
--- a/src/sqlalchemy/migrations/stockdb/versions/838eec3adc23_auto_update_from_stockdb.py
+++ b/src/sqlalchemy/migrations/stockdb/versions/838eec3adc23_auto_update_from_stockdb.py
@ -0,0 +1,38 @@
+"""Auto update from stockdb
+
+Revision ID: 838eec3adc23
+Revises: 0a39f1baab38
+Create Date: 2025-07-31 16:56:37.635401
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '838eec3adc23'
+down_revision: Union[str, Sequence[str], None] = '0a39f1baab38'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('futu_trading_days',
+    sa.Column('market', sa.String(length=20), nullable=False, comment='市场标识'),
+    sa.Column('trade_date', sa.Date(), nullable=False, comment='交易日日期'),
+    sa.Column('trade_date_type', sa.String(length=20), nullable=False, comment='交易日类型'),
+    sa.PrimaryKeyConstraint('market', 'trade_date'),
+    comment='富途证券交易日历表'
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table('futu_trading_days')
+    # ### end Alembic commands ###
--- a/src/sqlalchemy/migrations/stockdb/versions/9680e7b8e29b_auto_update_from_stockdb.py
+++ b/src/sqlalchemy/migrations/stockdb/versions/9680e7b8e29b_auto_update_from_stockdb.py
@ -0,0 +1,87 @@
+"""Auto update from stockdb
+
+Revision ID: 9680e7b8e29b
+Revises: 838eec3adc23
+Create Date: 2025-07-31 17:35:37.108765
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '9680e7b8e29b'
+down_revision: Union[str, Sequence[str], None] = '838eec3adc23'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('daily_snap',
+    sa.Column('code', sa.String(length=20), nullable=False, comment='股票代码'),
+    sa.Column('curr_date', sa.String(length=20), nullable=False, comment='交易日期'),
+    sa.Column('name', sa.String(length=50), nullable=True, comment='股票名称'),
+    sa.Column('market_id', sa.String(length=50), nullable=True, comment='市场名称'),
+    sa.Column('code_prefix', sa.Integer(), nullable=True, comment='代码前缀'),
+    sa.Column('industry', sa.String(length=50), nullable=True, comment='所处行业'),
+    sa.Column('listing_date', sa.Date(), nullable=True, comment='上市时间'),
+    sa.Column('latest_price', sa.Float(), nullable=True, comment='最新价'),
+    sa.Column('price_change_percent', sa.Float(), nullable=True, comment='涨跌幅(%)'),
+    sa.Column('price_change', sa.Float(), nullable=True, comment='涨跌额'),
+    sa.Column('volume', sa.Float(), nullable=True, comment='成交量'),
+    sa.Column('turnover', sa.Float(), nullable=True, comment='成交额'),
+    sa.Column('amplitude', sa.Float(), nullable=True, comment='振幅(%)'),
+    sa.Column('turnover_rate', sa.Float(), nullable=True, comment='换手率(%)'),
+    sa.Column('pe_dynamic', sa.Float(), nullable=True, comment='市盈率动'),
+    sa.Column('volume_ratio', sa.Float(), nullable=True, comment='量比'),
+    sa.Column('change_5min', sa.Float(), nullable=True, comment='5分钟涨跌(%)'),
+    sa.Column('highest', sa.Float(), nullable=True, comment='最高'),
+    sa.Column('lowest', sa.Float(), nullable=True, comment='最低'),
+    sa.Column('opening', sa.Float(), nullable=True, comment='今开'),
+    sa.Column('previous_close', sa.Float(), nullable=True, comment='昨收'),
+    sa.Column('price_speed', sa.Float(), nullable=True, comment='涨速(%)'),
+    sa.Column('total_market_cap', sa.Float(), nullable=True, comment='总市值'),
+    sa.Column('circulating_market_cap', sa.Float(), nullable=True, comment='流通市值'),
+    sa.Column('pb_ratio', sa.Float(), nullable=True, comment='市净率'),
+    sa.Column('change_60d', sa.Float(), nullable=True, comment='60日涨跌幅(%)'),
+    sa.Column('change_ytd', sa.Float(), nullable=True, comment='年初至今涨跌幅(%)'),
+    sa.Column('weighted_roe', sa.Float(), nullable=True, comment='加权净资产收益率(%)'),
+    sa.Column('total_shares', sa.Float(), nullable=True, comment='总股本'),
+    sa.Column('circulating_shares', sa.Float(), nullable=True, comment='已流通股份'),
+    sa.Column('operating_revenue', sa.Float(), nullable=True, comment='营业收入'),
+    sa.Column('revenue_growth', sa.Float(), nullable=True, comment='营业收入同比增长(%)'),
+    sa.Column('net_profit', sa.Float(), nullable=True, comment='归属净利润'),
+    sa.Column('net_profit_growth', sa.Float(), nullable=True, comment='归属净利润同比增长(%)'),
+    sa.Column('undistributed_profit_per_share', sa.Float(), nullable=True, comment='每股未分配利润'),
+    sa.Column('gross_margin', sa.Float(), nullable=True, comment='毛利率(%)'),
+    sa.Column('asset_liability_ratio', sa.Float(), nullable=True, comment='资产负债率(%)'),
+    sa.Column('reserve_per_share', sa.Float(), nullable=True, comment='每股公积金'),
+    sa.Column('earnings_per_share', sa.Float(), nullable=True, comment='每股收益'),
+    sa.Column('net_asset_per_share', sa.Float(), nullable=True, comment='每股净资产'),
+    sa.Column('pe_static', sa.Float(), nullable=True, comment='市盈率静'),
+    sa.Column('pe_ttm', sa.Float(), nullable=True, comment='市盈率TTM'),
+    sa.Column('report_period', sa.String(length=20), nullable=True, comment='报告期'),
+    sa.Column('created_at', sa.DateTime(), nullable=False, comment='记录创建时间'),
+    sa.PrimaryKeyConstraint('code', 'curr_date'),
+    comment='股票交易数据表'
+    )
+    op.create_table('futu_trading_days',
+    sa.Column('market', sa.String(length=20), nullable=False, comment='市场标识'),
+    sa.Column('trade_date', sa.Date(), nullable=False, comment='交易日日期'),
+    sa.Column('trade_date_type', sa.String(length=20), nullable=False, comment='交易日类型'),
+    sa.PrimaryKeyConstraint('market', 'trade_date'),
+    comment='富途证券交易日历表'
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table('futu_trading_days')
+    op.drop_table('daily_snap')
+    # ### end Alembic commands ###
--- a/src/sqlalchemy/migrations/stockdb/versions/df56ac7669f2_auto_update_from_stockdb.py
+++ b/src/sqlalchemy/migrations/stockdb/versions/df56ac7669f2_auto_update_from_stockdb.py
@ -0,0 +1,32 @@
+"""Auto update from stockdb
+
+Revision ID: df56ac7669f2
+Revises: 
+Create Date: 2025-07-31 16:04:32.216988
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = 'df56ac7669f2'
+down_revision: Union[str, Sequence[str], None] = None
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column('daily_snap', sa.Column('market_id', sa.String(length=50), nullable=True, comment='市场名称'))
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column('daily_snap', 'market_id')
+    # ### end Alembic commands ###
--- a/src/sqlalchemy/models/base.py
+++ b/src/sqlalchemy/models/base.py
@ -0,0 +1,23 @@
+from sqlalchemy import Column, Integer, DateTime
+from sqlalchemy.ext.declarative import declarative_base
+from datetime import datetime
+
+# 所有模型的基类
+Base = declarative_base()
+
+class BaseModel(Base):
+    __abstract__ = True  # 抽象类，不生成实际表
+    
+    # 通用字段
+    id = Column(Integer, primary_key=True, autoincrement=True, comment="主键ID")
+    created_at = Column(DateTime, default=datetime.now, comment="创建时间")
+    updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now, comment="更新时间")
+    
+    # 通用方法：将模型实例转为字典（方便JSON序列化）
+    def to_dict(self, exclude=None):
+        exclude = exclude or []
+        return {
+            c.name: getattr(self, c.name)
+            for c in self.__table__.columns
+            if c.name not in exclude
+        }
--- a/src/sqlalchemy/models/stockdb.py
+++ b/src/sqlalchemy/models/stockdb.py
@ -0,0 +1,448 @@
+from sqlalchemy import BigInteger, Date, DateTime, Double, Float, Integer, String, text, Numeric
+from sqlalchemy.dialects.mysql import TINYINT, VARCHAR
+from typing import Optional
+
+from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
+import datetime
+import decimal
+
+class Base(DeclarativeBase):
+    pass
+
+
+class FutuMarketSnapshot(Base):
+    __tablename__ = 'futu_market_snapshot'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"), comment='股票代码')
+    name: Mapped[str] = mapped_column(String(255), server_default=text("''"), comment='股票名称')
+    update_time: Mapped[datetime.datetime] = mapped_column(DateTime, primary_key=True, comment='当前价更新时间')
+    last_price: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='最新价格')
+    open_price: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='今日开盘价')
+    high_price: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='最高价格')
+    low_price: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='最低价格')
+    prev_close_price: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='昨收盘价格')
+    volume: Mapped[int] = mapped_column(BigInteger, server_default=text("'0'"), comment='成交数量')
+    turnover: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='成交金额')
+    turnover_rate: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='换手率')
+    suspension: Mapped[int] = mapped_column(TINYINT(1), server_default=text("'0'"), comment='是否停牌')
+    listing_date: Mapped[datetime.date] = mapped_column(Date, server_default=text("'1970-01-01'"), comment='上市日期')
+    equity_valid: Mapped[int] = mapped_column(TINYINT(1), server_default=text("'0'"), comment='是否正股')
+    issued_shares: Mapped[int] = mapped_column(BigInteger, server_default=text("'0'"), comment='总股本')
+    total_market_val: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='总市值')
+    net_asset: Mapped[int] = mapped_column(BigInteger, server_default=text("'0'"), comment='资产净值')
+    net_profit: Mapped[int] = mapped_column(BigInteger, server_default=text("'0'"), comment='净利润')
+    earning_per_share: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='每股盈利')
+    outstanding_shares: Mapped[int] = mapped_column(BigInteger, server_default=text("'0'"), comment='流通股本')
+    net_asset_per_share: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='每股净资产')
+    circular_market_val: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='流通市值')
+    ey_ratio: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='收益率')
+    pe_ratio: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='市盈率')
+    pb_ratio: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='市净率')
+    pe_ttm_ratio: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='市盈率 TTM')
+    dividend_ttm: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='股息 TTM')
+    dividend_ratio_ttm: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='股息率 TTM')
+    dividend_lfy: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='股息 LFY')
+    dividend_lfy_ratio: Mapped[float] = mapped_column(Float, server_default=text("'0'"), comment='股息率 LFY')
+
+
+class FutuPlatList(Base):
+    __tablename__ = 'futu_plat_list'
+
+    up_date: Mapped[datetime.date] = mapped_column(Date, primary_key=True)
+    market: Mapped[str] = mapped_column(String(50))
+    plat: Mapped[str] = mapped_column(String(50), primary_key=True, server_default=text("'INDUSTRY'"))
+    code: Mapped[str] = mapped_column(String(50), primary_key=True)
+    plate_id: Mapped[str] = mapped_column(String(50))
+    plate_name: Mapped[str] = mapped_column(String(255))
+
+
+class FutuRehab(Base):
+    __tablename__ = 'futu_rehab'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    ex_div_date: Mapped[datetime.date] = mapped_column(Date, primary_key=True)
+    forward_adj_factorA: Mapped[float] = mapped_column(Float)
+    forward_adj_factorB: Mapped[float] = mapped_column(Float)
+    backward_adj_factorA: Mapped[float] = mapped_column(Float)
+    backward_adj_factorB: Mapped[float] = mapped_column(Float)
+
+
+class Hs300(Base):
+    __tablename__ = 'hs300'
+
+    up_date: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    index_code: Mapped[str] = mapped_column(String(100), server_default=text("'000300'"))
+    index_name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    index_name_eng: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code_inner: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    code_name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code_name_eng: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    exchange: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    exchange_eng: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+
+
+class Hs3003yearsYieldStats2410(Base):
+    __tablename__ = 'hs300_3years_yield_stats_2410'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    year_diff: Mapped[int] = mapped_column(Integer, primary_key=True)
+    max_yield_rate: Mapped[float] = mapped_column(Float)
+    max_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    max_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    min_yield_rate: Mapped[float] = mapped_column(Float)
+    min_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    min_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    avg_yield_rate: Mapped[float] = mapped_column(Float)
+    median_yield_rate: Mapped[float] = mapped_column(Float)
+    win_rate: Mapped[float] = mapped_column(Float)
+    annual_max_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_max_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_max_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_min_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_min_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_min_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_avg_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_median_yield_rate: Mapped[float] = mapped_column(Float)
+    max_deficit_days: Mapped[int] = mapped_column(Integer)
+    max_deficit_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    max_deficit_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_yield_variance: Mapped[float] = mapped_column(Float)
+
+
+class Hs3005yearsYieldStats2410(Base):
+    __tablename__ = 'hs300_5years_yield_stats_2410'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    year_diff: Mapped[int] = mapped_column(Integer, primary_key=True)
+    max_yield_rate: Mapped[float] = mapped_column(Float)
+    max_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    max_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    min_yield_rate: Mapped[float] = mapped_column(Float)
+    min_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    min_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    avg_yield_rate: Mapped[float] = mapped_column(Float)
+    median_yield_rate: Mapped[float] = mapped_column(Float)
+    win_rate: Mapped[float] = mapped_column(Float)
+    annual_max_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_max_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_max_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_min_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_min_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_min_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_avg_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_median_yield_rate: Mapped[float] = mapped_column(Float)
+    max_deficit_days: Mapped[int] = mapped_column(Integer)
+    max_deficit_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    max_deficit_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_yield_variance: Mapped[float] = mapped_column(Float)
+
+
+class Hs300AjustKline202410(Base):
+    __tablename__ = 'hs300_ajust_kline_202410'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    time_key: Mapped[datetime.datetime] = mapped_column(DateTime, primary_key=True)
+    hfq_open: Mapped[float] = mapped_column(Float)
+    hfq_close: Mapped[float] = mapped_column(Float)
+    qfq_open: Mapped[float] = mapped_column(Float)
+    qfq_close: Mapped[float] = mapped_column(Float)
+    none_open: Mapped[float] = mapped_column(Float)
+    none_close: Mapped[float] = mapped_column(Float)
+
+
+class Hs300HisKlineHfq(Base):
+    __tablename__ = 'hs300_his_kline_hfq'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    time_key: Mapped[datetime.datetime] = mapped_column(DateTime, primary_key=True)
+    open: Mapped[float] = mapped_column(Float)
+    close: Mapped[float] = mapped_column(Float)
+    high: Mapped[float] = mapped_column(Float)
+    low: Mapped[float] = mapped_column(Float)
+    pe_ratio: Mapped[Optional[float]] = mapped_column(Float)
+    turnover_rate: Mapped[Optional[float]] = mapped_column(Float)
+    volume: Mapped[Optional[int]] = mapped_column(BigInteger)
+    turnover: Mapped[Optional[decimal.Decimal]] = mapped_column(Double(asdecimal=True))
+    change_rate: Mapped[Optional[float]] = mapped_column(Float)
+    last_close: Mapped[Optional[float]] = mapped_column(Float)
+
+
+class Hs300HisKlineNone(Base):
+    __tablename__ = 'hs300_his_kline_none'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    time_key: Mapped[datetime.datetime] = mapped_column(DateTime, primary_key=True)
+    open: Mapped[float] = mapped_column(Float)
+    close: Mapped[float] = mapped_column(Float)
+    high: Mapped[float] = mapped_column(Float)
+    low: Mapped[float] = mapped_column(Float)
+    pe_ratio: Mapped[Optional[float]] = mapped_column(Float)
+    turnover_rate: Mapped[Optional[float]] = mapped_column(Float)
+    volume: Mapped[Optional[int]] = mapped_column(BigInteger)
+    turnover: Mapped[Optional[decimal.Decimal]] = mapped_column(Double(asdecimal=True))
+    change_rate: Mapped[Optional[float]] = mapped_column(Float)
+    last_close: Mapped[Optional[float]] = mapped_column(Float)
+
+
+class Hs300QfqHis(Base):
+    __tablename__ = 'hs300_qfq_his'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    time_key: Mapped[datetime.datetime] = mapped_column(DateTime, primary_key=True)
+    open: Mapped[float] = mapped_column(Float)
+    close: Mapped[float] = mapped_column(Float)
+    high: Mapped[float] = mapped_column(Float)
+    low: Mapped[float] = mapped_column(Float)
+    pe_ratio: Mapped[Optional[float]] = mapped_column(Float)
+    turnover_rate: Mapped[Optional[float]] = mapped_column(Float)
+    volume: Mapped[Optional[int]] = mapped_column(BigInteger)
+    turnover: Mapped[Optional[decimal.Decimal]] = mapped_column(Double(asdecimal=True))
+    change_rate: Mapped[Optional[float]] = mapped_column(Float)
+    last_close: Mapped[Optional[float]] = mapped_column(Float)
+
+
+class IndexHk(Base):
+    __tablename__ = 'index_hk'
+
+    up_date: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    index_code: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("'000300'"))
+    index_name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code_inner: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    code_name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    weight: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+
+
+class IndexHs(Base):
+    __tablename__ = 'index_hs'
+
+    up_date: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    index_code: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("'000300'"))
+    index_name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    index_name_eng: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code_inner: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    code_name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code_name_eng: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    exchange: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    exchange_eng: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+
+
+class IndexUs(Base):
+    __tablename__ = 'index_us'
+
+    up_date: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    index_code: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("'000300'"))
+    index_name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code_inner: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    code_name: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    weight: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+
+
+class Sp500(Base):
+    __tablename__ = 'sp500'
+
+    sp_no: Mapped[int] = mapped_column(Integer, server_default=text("'0'"))
+    code_name: Mapped[str] = mapped_column(VARCHAR(100), server_default=text("''"))
+    code_inner: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("''"))
+    sector: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    code: Mapped[str] = mapped_column(String(100), server_default=text("''"))
+    up_date: Mapped[str] = mapped_column(String(100), primary_key=True, server_default=text("'2024-10-02'"))
+
+
+class Sp5003yearsYieldStats2410(Base):
+    __tablename__ = 'sp500_3years_yield_stats_2410'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    year_diff: Mapped[int] = mapped_column(Integer, primary_key=True)
+    max_yield_rate: Mapped[float] = mapped_column(Float)
+    max_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    max_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    min_yield_rate: Mapped[float] = mapped_column(Float)
+    min_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    min_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    avg_yield_rate: Mapped[float] = mapped_column(Float)
+    median_yield_rate: Mapped[float] = mapped_column(Float)
+    win_rate: Mapped[float] = mapped_column(Float)
+    annual_max_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_max_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_max_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_min_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_min_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_min_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_avg_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_median_yield_rate: Mapped[float] = mapped_column(Float)
+    max_deficit_days: Mapped[int] = mapped_column(Integer)
+    max_deficit_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    max_deficit_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_yield_variance: Mapped[float] = mapped_column(Float)
+
+
+class Sp5005yearsYieldStats2410(Base):
+    __tablename__ = 'sp500_5years_yield_stats_2410'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    year_diff: Mapped[int] = mapped_column(Integer, primary_key=True)
+    max_yield_rate: Mapped[float] = mapped_column(Float)
+    max_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    max_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    min_yield_rate: Mapped[float] = mapped_column(Float)
+    min_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    min_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    avg_yield_rate: Mapped[float] = mapped_column(Float)
+    median_yield_rate: Mapped[float] = mapped_column(Float)
+    win_rate: Mapped[float] = mapped_column(Float)
+    annual_max_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_max_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_max_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_min_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_min_yield_rate_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_min_yield_rate_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_avg_yield_rate: Mapped[float] = mapped_column(Float)
+    annual_median_yield_rate: Mapped[float] = mapped_column(Float)
+    max_deficit_days: Mapped[int] = mapped_column(Integer)
+    max_deficit_start: Mapped[datetime.datetime] = mapped_column(DateTime)
+    max_deficit_end: Mapped[datetime.datetime] = mapped_column(DateTime)
+    annual_yield_variance: Mapped[float] = mapped_column(Float)
+
+
+class Sp500AjustKline202410(Base):
+    __tablename__ = 'sp500_ajust_kline_202410'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    time_key: Mapped[datetime.datetime] = mapped_column(DateTime, primary_key=True)
+    hfq_open: Mapped[float] = mapped_column(Float)
+    hfq_close: Mapped[float] = mapped_column(Float)
+    qfq_open: Mapped[float] = mapped_column(Float)
+    qfq_close: Mapped[float] = mapped_column(Float)
+    none_open: Mapped[float] = mapped_column(Float)
+    none_close: Mapped[float] = mapped_column(Float)
+
+
+class Sp500HisKlineNone(Base):
+    __tablename__ = 'sp500_his_kline_none'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    time_key: Mapped[datetime.datetime] = mapped_column(DateTime, primary_key=True)
+    open: Mapped[float] = mapped_column(Float)
+    high: Mapped[float] = mapped_column(Float)
+    low: Mapped[float] = mapped_column(Float)
+    close: Mapped[float] = mapped_column(Float)
+    volume: Mapped[int] = mapped_column(BigInteger)
+    dividends: Mapped[float] = mapped_column(Float)
+    stock_splits: Mapped[float] = mapped_column(Float)
+    adj_close: Mapped[float] = mapped_column(Float)
+
+
+class Sp500QfqHis202410(Base):
+    __tablename__ = 'sp500_qfq_his_202410'
+
+    code: Mapped[str] = mapped_column(String(100), primary_key=True)
+    name: Mapped[str] = mapped_column(String(100))
+    time_key: Mapped[datetime.datetime] = mapped_column(DateTime, primary_key=True)
+    open: Mapped[float] = mapped_column(Float)
+    high: Mapped[float] = mapped_column(Float)
+    low: Mapped[float] = mapped_column(Float)
+    close: Mapped[float] = mapped_column(Float)
+    volume: Mapped[int] = mapped_column(BigInteger)
+    dividends: Mapped[float] = mapped_column(Float)
+    stock_splits: Mapped[float] = mapped_column(Float)
+    adj_close: Mapped[float] = mapped_column(Float)
+
+
+
+class DailySanpModel(Base):
+    """股票数据模型类（使用mapped_column风格）"""
+    __tablename__ = 'daily_snap'
+    __table_args__ = {"comment": "股票交易数据表"}
+    
+    # 联合主键：股票代码+报告期
+    code: Mapped[str] = mapped_column(String(20), primary_key=True, comment='股票代码')
+    curr_date: Mapped[str] = mapped_column(String(20), primary_key=True, comment='交易日期')
+    
+    # 基本信息字段
+    name: Mapped[str | None] = mapped_column(String(50), comment='股票名称')
+    market_id: Mapped[str | None] = mapped_column(String(50), comment='市场名称')
+    code_prefix: Mapped[int | None] = mapped_column(Integer, comment='代码前缀')
+    industry: Mapped[str | None] = mapped_column(String(50), comment='所处行业')
+    listing_date: Mapped[datetime.date | None] = mapped_column(Date, comment='上市时间')
+    
+    # 交易数据字段
+    latest_price: Mapped[float | None] = mapped_column(Float, comment='最新价')
+    price_change_percent: Mapped[float | None] = mapped_column(Float, comment='涨跌幅(%)')
+    price_change: Mapped[float | None] = mapped_column(Float, comment='涨跌额')
+    volume: Mapped[float | None] = mapped_column(Float, comment='成交量')
+    turnover: Mapped[float | None] = mapped_column(Float, comment='成交额')
+    amplitude: Mapped[float | None] = mapped_column(Float, comment='振幅(%)')
+    turnover_rate: Mapped[float | None] = mapped_column(Float, comment='换手率(%)')
+    pe_dynamic: Mapped[float | None] = mapped_column(Float, comment='市盈率动')
+    volume_ratio: Mapped[float | None] = mapped_column(Float, comment='量比')
+    change_5min: Mapped[float | None] = mapped_column(Float, comment='5分钟涨跌(%)')
+    highest: Mapped[float | None] = mapped_column(Float, comment='最高')
+    lowest: Mapped[float | None] = mapped_column(Float, comment='最低')
+    opening: Mapped[float | None] = mapped_column(Float, comment='今开')
+    previous_close: Mapped[float | None] = mapped_column(Float, comment='昨收')
+    price_speed: Mapped[float | None] = mapped_column(Float, comment='涨速(%)')
+    
+    # 市值数据字段
+    total_market_cap: Mapped[float | None] = mapped_column(Float, comment='总市值')
+    circulating_market_cap: Mapped[float | None] = mapped_column(Float, comment='流通市值')
+    pb_ratio: Mapped[float | None] = mapped_column(Float, comment='市净率')
+    change_60d: Mapped[float | None] = mapped_column(Float, comment='60日涨跌幅(%)')
+    change_ytd: Mapped[float | None] = mapped_column(Float, comment='年初至今涨跌幅(%)')
+    
+    # 财务数据字段
+    weighted_roe: Mapped[float | None] = mapped_column(Float, comment='加权净资产收益率(%)')
+    total_shares: Mapped[float | None] = mapped_column(Float, comment='总股本')
+    circulating_shares: Mapped[float | None] = mapped_column(Float, comment='已流通股份')
+    operating_revenue: Mapped[float | None] = mapped_column(Float, comment='营业收入')
+    revenue_growth: Mapped[float | None] = mapped_column(Float, comment='营业收入同比增长(%)')
+    net_profit: Mapped[float | None] = mapped_column(Float, comment='归属净利润')
+    net_profit_growth: Mapped[float | None] = mapped_column(Float, comment='归属净利润同比增长(%)')
+    undistributed_profit_per_share: Mapped[float | None] = mapped_column(Float, comment='每股未分配利润')
+    gross_margin: Mapped[float | None] = mapped_column(Float, comment='毛利率(%)')
+    asset_liability_ratio: Mapped[float | None] = mapped_column(Float, comment='资产负债率(%)')
+    reserve_per_share: Mapped[float | None] = mapped_column(Float, comment='每股公积金')
+    earnings_per_share: Mapped[float | None] = mapped_column(Float, comment='每股收益')
+    net_asset_per_share: Mapped[float | None] = mapped_column(Float, comment='每股净资产')
+    pe_static: Mapped[float | None] = mapped_column(Float, comment='市盈率静')
+    pe_ttm: Mapped[float | None] = mapped_column(Float, comment='市盈率TTM')
+    report_period: Mapped[str | None] = mapped_column(String(20), comment='报告期')
+    
+    # 记录创建时间
+    created_at: Mapped[datetime.datetime] = mapped_column(DateTime, default=datetime.datetime.now, comment='记录创建时间')
+
+
+class FutuTradingDayModel(Base):
+    """富途交易日历模型类"""
+    __tablename__ = "futu_trading_days"
+    __table_args__ = {"comment": "富途证券交易日历表"}
+    
+    # 联合主键：market + trade_date
+    market: Mapped[str] = mapped_column(
+        String(20), 
+        primary_key=True, 
+        comment="市场标识"
+    )
+    trade_date: Mapped[datetime.date] = mapped_column(
+        Date, 
+        primary_key=True, 
+        comment="交易日日期"
+    )
+    trade_date_type: Mapped[str] = mapped_column(
+        String(20), 
+        comment="交易日类型"
+    )
--- a/src/sqlalchemy/readme.txt
+++ b/src/sqlalchemy/readme.txt
@ -0,0 +1,13 @@
+
+# 从数据库生成模型类
+sqlacodegen --outfile=models/stockdb.py "mysql+pymysql://root:mysqlpw@testdb:3306/stockdb?charset=utf8mb4"
+
+# 初始化
+mkdir migrations
+alembic init migrations/stockdb
+# 修改 alembic.ini 脚本，以及 env.py 导入 models
+
+# 同步修改到数据库（读取 models/shared.py ）
+./scripts/sync_stockdb.sh
+
+### 对视图支持不好，主要是视图的字段没有类型，所以在导入导出时会出错，慎用！
--- a/src/sqlalchemy/scripts/sync_stockdb.sh
+++ b/src/sqlalchemy/scripts/sync_stockdb.sh
@ -0,0 +1,7 @@
+#!/bin/bash
+cd $(dirname $0)/..
+
+alembic -c migrations/stockdb/alembic.ini revision --autogenerate -m "Auto update from stockdb"
+alembic -c migrations/stockdb/alembic.ini upgrade head
+
+echo "数据库 stockdb 同步完成"
--- a/src/static/daily_snap_em.py
+++ b/src/static/daily_snap_em.py
@ -0,0 +1,231 @@
+"""
+Script Name: 
+Description: 获取沪深300成分股的最新股价, 并计算年内涨幅, 924以来的涨幅, 市盈率, 股息率等。
+    调用em历史数据接口。
+
+Author: [Your Name]
+Created Date: YYYY-MM-DD
+Last Modified: YYYY-MM-DD
+Version: 1.0
+
+Modification History:
+    - YYYY-MM-DD [Your Name]: 
+    - YYYY-MM-DD [Your Name]: 
+    - YYYY-MM-DD [Your Name]: 
+"""
+
+import pymysql
+import logging
+import csv
+import os
+import re
+import time
+import pandas as pd
+import numpy as np
+from datetime import datetime
+import argparse
+import src.crawling.stock_hist_em as his_em
+import src.logger.logger as logger
+from src.config.config import global_stock_data_dir
+from src.crawler.zixuan.xueqiu_zixuan import XueQiuStockFetcher
+from src.sqlalchemy.models.stockdb import DailySanpModel, Base
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+from src.sqlalchemy.config import global_db_url
+
+# 配置日志
+logger.setup_logging()
+
+current_date = datetime.now().strftime("%Y%m%d")
+current_year = datetime.now().strftime("%Y")
+
+res_dir = global_stock_data_dir
+
+# 刷新代码列表，并返回
+def flush_code_map():
+    code_id_map_em_df = his_em.code_id_map_em()
+    print(code_id_map_em_df)
+    return code_id_map_em_df
+
+# 获取所有市场的当年股价快照，带重试机制。
+def fetch_snap_all(max_retries: int = 3) -> pd.DataFrame:
+    # 检查文件是否存在
+    file_name = f'{res_dir}/snapshot_em_{current_date}.csv'
+    if os.path.exists(file_name):
+        try:
+            # 读取本地文件
+            snap_data = pd.read_csv(file_name, encoding='utf-8')
+            logging.info(f"load snapshot data from local: {file_name}\n\n")
+            return snap_data
+        except Exception as e:
+            logging.warning(f"读取本地文件失败: {e}，将重新拉取数据\n\n")
+
+    # 拉取数据
+    market_fs = {"cn":      "m:0 t:6,m:0 t:80,m:1 t:2,m:1 t:23,m:0 t:81 s:2048",
+                 "hk":      "m:128 t:3,m:128 t:4,m:128 t:1,m:128 t:2",
+                 "us":      "m:105,m:106,m:107"}
+    
+    result = pd.DataFrame()
+    for market_id, fs in market_fs.items():
+        df = his_em.stock_zh_a_spot_em(fs, fs_desc=market_id)
+        if df.empty:
+            logging.warning(f'{market_id} empty data. please check.')
+            return pd.DataFrame()
+        else:
+            logging.info(f'get {market_id} stock snapshot. stock count: {len(df)}')
+            # 关键步骤：添加market_id列，值为当前市场标识
+            df['market_id'] = market_id  # 新增一列，记录数据所属市场
+            result = pd.concat([result, df], ignore_index=True)
+
+    result.to_csv(file_name, index=False, encoding='utf-8')
+    logging.info(f"get snapshot data and write to file: {file_name}\n\n")
+
+    return result
+
+
+def load_xueqiu_codes():
+    # 替换为你的实际cookie
+    USER_COOKIES = "u=5682299253; HMACCOUNT=AA6F9D2598CE96D7; xq_is_login=1; snbim_minify=true; _c_WBKFRo=BuebJX5KAbPh1PGBVFDvQTV7x7VF8W2cvWtaC99v; _nb_ioWEgULi=; cookiesu=661740133906455; device_id=fbe0630e603f726742fec4f9a82eb5fb; s=b312165egu; bid=1f3e6ffcb97fd2d9b4ddda47551d4226_m7fv1brw; Hm_lvt_1db88642e346389874251b5a1eded6e3=1751852390; xq_a_token=a0fd17a76966314ab80c960412f08e3fffb3ec0f; xqat=a0fd17a76966314ab80c960412f08e3fffb3ec0f; xq_id_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJ1aWQiOjU2ODIyOTkyNTMsImlzcyI6InVjIiwiZXhwIjoxNzU0NzAzMjk5LCJjdG0iOjE3NTIxMTEyOTkyODYsImNpZCI6ImQ5ZDBuNEFadXAifQ.Vbs-LDgB4bCJI2N644DwfeptdcamKsAm2hbXxlPnJ_0fnTJhXp6T-2Gc6b6jmhTjXJIsWta8IuS0rQBB1L-9fKpUliNFHkv4lr7FW2x7QhrZ1D4lrvjihgBxKHq8yQl31uO6lmUOJkoRaS4LM1pmkSL_UOVyw8aUeuVjETFcJR1HFDHwWpHCLM8kY55fk6n1gEgDZnYNh1_FACqlm6LU4Vq14wfQgyF9sfrGzF8rxXX0nns_j-Dq2k8vN3mknh8yUHyzCyq6Sfqn6NeVdR0vPOciylyTtNq5kOUBFb8uJe48aV2uLGww3dYV8HbsgqW4k0zam3r3QDErfSRVIg-Usw; xq_r_token=1b73cbfb47fcbd8e2055ca4a6dc7a08905dacd7d; Hm_lpvt_1db88642e346389874251b5a1eded6e3=1752714700; is_overseas=0; ssxmod_itna=QqfxBD2D9DRQPY5i7YYxiwS4GhDYu0D0dGMD3qiQGglDFqAPKDHKm=lerDUhGr5h044VYmkTtDlxWeDZDG9dDqx0orXU7BB411D+iENYYe2GG+=3X0xOguYo7I=xmAkwKhSSIXNG2A+DnmeDQKDoxGkDivoD0IYwDiiTx0rD0eDPxDYDG4mDDvvQ84DjmEmFfoGImAeQIoDbORhz74DROdDS73A+IoGqW3Da1A3z8RGDmKDIhjozmoDFOL3Yq0k54i3Y=Ocaq0OZ+BGR0gvh849m1xkHYRr/oRCYQD4KDx5qAxOx20Z3isrfDxRvt70KGitCH4N4DGbh5gYH7x+GksdC58CNR3sx=1mt2qxkGd+QmoC5ZGYdixKG52q4iiqPj53js4D; ssxmod_itna2=QqfxBD2D9DRQPY5i7YYxiwS4GhDYu0D0dGMD3qiQGglDFqAPKDHKm=lerDUhGr5h044VYmkwYDioSBbrtN4=Htz/DUihxz=w4aD"
+        
+    # 初始化获取器
+    fetcher = XueQiuStockFetcher(
+        cookies=USER_COOKIES,
+        size=1000,
+        retry_count=3
+    )
+    all_codes = []
+    stocks = fetcher.get_stocks_by_group(
+        category=1,     # 股票
+        pid=-1      # 全部
+    )
+    if stocks:
+        for item in stocks:
+            code = item['symbol']
+            mkt = item['marketplace']   
+
+            if mkt:            
+                if mkt.lower() == 'cn':
+                    code = format_stock_code(code)
+                elif mkt.lower() == 'hk':
+                    code = f"HK.{code}"
+                else:
+                    code = f"US.{code}"
+
+            all_codes.append({'code': code, 'code_name': item['name']})
+
+    return all_codes
+
+
+def insert_stock_data_to_db(dataframe, db_url=global_db_url):
+    """
+    将pandas DataFrame中的股票数据插入到MySQL数据库
+    
+    参数:
+        dataframe: 包含股票数据的pandas DataFrame
+        db_url: 数据库连接字符串，格式如'mysql+mysqldb://user:password@host:port/dbname?charset=utf8mb4'
+    """
+    # 创建数据库引擎
+    engine = create_engine(db_url)
+    
+    # 创建数据表（如果不存在）
+    Base.metadata.create_all(engine)
+    
+    # 创建会话
+    Session = sessionmaker(bind=engine)
+    session = Session()
+
+    # 注意：pandas中NaN在数值列用np.nan，字符串列用pd.NA，统一替换为None
+    dataframe = dataframe.replace({np.nan: None, pd.NA: None})
+    try:
+        count_insert = 0
+        count_update = 0
+        # 遍历DataFrame的每一行
+        for _, row in dataframe.iterrows():
+            # 先检查 code 是否存在且有效
+            if not row.get('代码'):
+                logging.warning(f"警告：发现无效的 code 值，跳过该行数据。行数据：{row['名称']}")
+                continue  # 跳过无效行
+
+            # 创建股票数据对象
+            stock = DailySanpModel(
+                code=row['代码'],
+                curr_date=current_date,  # TODO: 怎么判断当前的数据是哪一天的？ 要看当前时间是否已经开盘，还是在盘前，还是前一个交易日的？
+                name=row['名称'],
+                market_id=row['market_id'],
+                code_prefix=row['代码前缀'],
+                industry=row['所处行业'],
+                listing_date=pd.to_datetime(row['上市时间']).date() if row['上市时间'] else None,
+                
+                latest_price=row['最新价'],
+                price_change_percent=row['涨跌幅'],
+                price_change=row['涨跌额'],
+                volume=row['成交量'],
+                turnover=row['成交额'],
+                amplitude=row['振幅'],
+                turnover_rate=row['换手率'],
+                pe_dynamic=row['市盈率动'],
+                volume_ratio=row['量比'],
+                change_5min=row['5分钟涨跌'],
+                highest=row['最高'],
+                lowest=row['最低'],
+                opening=row['今开'],
+                previous_close=row['昨收'],
+                price_speed=row['涨速'],
+                
+                total_market_cap=row['总市值'],
+                circulating_market_cap=row['流通市值'],
+                pb_ratio=row['市净率'],
+                change_60d=row['60日涨跌幅'],
+                change_ytd=row['年初至今涨跌幅'],
+                
+                weighted_roe=row['加权净资产收益率'],
+                total_shares=row['总股本'],
+                circulating_shares=row['已流通股份'],
+                operating_revenue=row['营业收入'],
+                revenue_growth=row['营业收入同比增长'],
+                net_profit=row['归属净利润'],
+                net_profit_growth=row['归属净利润同比增长'],
+                undistributed_profit_per_share=row['每股未分配利润'],
+                gross_margin=row['毛利率'],
+                asset_liability_ratio=row['资产负债率'],
+                reserve_per_share=row['每股公积金'],
+                earnings_per_share=row['每股收益'],
+                net_asset_per_share=row['每股净资产'],
+                pe_static=row['市盈率静'],
+                pe_ttm=row['市盈率TTM'],
+                report_period=row['报告期']
+            )
+            # 2. 执行merge：存在则更新，不存在则插入
+            merged_stock = session.merge(stock)
+            
+            # 3. 统计插入/更新数量
+            if merged_stock in session.new:  # 新插入
+                count_insert += 1
+            elif merged_stock in session.dirty:  # 已更新
+                count_update += 1     
+        
+        # 提交事务
+        session.commit()
+        logging.info(f"成功插入 {count_insert} 条，更新 {count_update} 条数据")
+        
+    except Exception as e:
+        # 发生错误时回滚
+        session.rollback()
+        logging.warning(f"插入数据失败: {str(e)}")
+    finally:
+        # 关闭会话
+        session.close()
+    
+
+def main():
+    # 获取快照数据
+    snap_data = fetch_snap_all()
+    if snap_data.empty:
+        logging.error(f"fetching snapshot data error!")
+        return
+    em_code_map = {row['代码']: row['代码前缀'] for _, row in snap_data.iterrows()}
+
+    insert_stock_data_to_db(dataframe=snap_data)
+
+if __name__ == "__main__":
+    main()
--- a/src/static/get_futu_trading_days.py
+++ b/src/static/get_futu_trading_days.py
@ -0,0 +1,140 @@
+from futu import *
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+from src.sqlalchemy.models.stockdb import Base, FutuTradingDayModel
+import datetime
+import logging
+import numpy as np
+import src.logger.logger as logger
+from src.sqlalchemy.config import global_db_url
+
+# 配置日志
+logger.setup_logging()
+
+def get_current_year():
+    """获取当前年份"""
+    return datetime.datetime.now().year
+
+def get_year_date_range(year):
+    """获取指定年份的年初和年末日期"""
+    start_date = f"{year}-01-01"
+    end_date = f"{year}-12-31"
+    return start_date, end_date
+
+def init_db(db_url=global_db_url):
+    """初始化数据库连接和表结构"""
+    engine = create_engine(db_url)
+    # 创建表（如果不存在）
+    Base.metadata.create_all(engine)
+    return sessionmaker(bind=engine)
+
+def save_trading_days_to_db(session, market, trading_days):
+    """
+    将交易日历数据保存到数据库
+    存在则更新，不存在则插入
+    """
+    count_insert = 0
+    count_update = 0
+    
+    for day in trading_days:
+        # 转换日期字符串为date对象
+        trade_date = datetime.datetime.strptime(day['time'], '%Y-%m-%d').date()
+        
+        # 查询是否已存在
+        existing = session.query(FutuTradingDayModel).filter(
+            FutuTradingDayModel.market == market,
+            FutuTradingDayModel.trade_date == trade_date
+        ).first()
+        
+        if existing:
+            # 存在则更新类型
+            if existing.trade_date_type != day['trade_date_type']:
+                existing.trade_date_type = day['trade_date_type']
+                count_update += 1
+        else:
+            # 不存在则插入新记录
+            new_day = FutuTradingDayModel(
+                market=market,
+                trade_date=trade_date,
+                trade_date_type=day['trade_date_type']
+            )
+            session.add(new_day)
+            count_insert += 1
+    
+    return count_insert, count_update
+
+def get_futu_trading_days(market, desc, db_url=global_db_url, year=None):
+    """
+    获取指定市场的交易日历并保存到数据库
+    :param market: 市场类型（如TradeDateMarket.HK）
+    :param db_url: 数据库连接字符串
+    :param year: 年份，默认当前年
+    """
+    # 确定年份
+    target_year = year or get_current_year()
+    start_date, end_date = get_year_date_range(target_year)
+    logging.info(f"开始获取 {market} 市场 {target_year} 年的交易日历（{start_date} 至 {end_date}）")
+    
+    # 初始化富途连接
+    quote_ctx = None
+    try:
+        quote_ctx = OpenQuoteContext(host='127.0.0.1', port=11111)
+        
+        # 请求交易日历
+        ret, data = quote_ctx.request_trading_days(
+            market=market,
+            start=start_date,
+            end=end_date
+        )
+        
+        if ret != RET_OK:
+            logging.error(f"获取交易日历失败: {data}")
+            return False
+        
+        logging.info(f"成功获取 {len(data)} 条交易日数据")
+        
+        # 初始化数据库会话
+        Session = init_db(db_url)
+        session = Session()
+        
+        try:
+            # 保存到数据库
+            count_insert, count_update = save_trading_days_to_db(
+                session=session,
+                market=desc,  # 存储枚举值（如'HK'）
+                trading_days=data
+            )
+            session.commit()
+            logging.info(f"数据库操作完成：新增 {count_insert} 条，更新 {count_update} 条")
+            return True
+            
+        except Exception as e:
+            session.rollback()
+            logging.error(f"数据库操作失败: {str(e)}")
+            return False
+        finally:
+            session.close()
+            
+    except Exception as e:
+        logging.error(f"连接富途API失败: {str(e)}")
+        return False
+    finally:
+        # 确保连接关闭
+        if quote_ctx:
+            quote_ctx.close()
+
+if __name__ == "__main__":    
+    # 示例：获取港股（HK）和美股（US）的当前年交易日历
+    markets = {
+        'CN' : TradeDateMarket.CN,  # 港股
+        'HK' : TradeDateMarket.HK,  # 港股
+        'US' : TradeDateMarket.US   # 美股
+    }
+    
+    for desc, market in markets.items():
+        get_futu_trading_days(
+            market=market,
+            desc=desc,
+            # db_url=DB_URL,
+            # year=2024  # 可选：指定年份，默认当前年
+        )
--- a/src/static/trading_day.py
+++ b/src/static/trading_day.py
@ -0,0 +1,122 @@
+from datetime import datetime, time, date, timedelta
+from zoneinfo import ZoneInfo
+from sqlalchemy.orm import Session
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+from src.sqlalchemy.models.stockdb import FutuTradingDayModel
+from src.sqlalchemy.config import global_db_url
+
+
+# 市场时间配置（东八区 Asia/Shanghai）
+# 新增盘前开始时间（pre_market_start）作为判断临界点
+MARKET_HOURS = {
+    # A股（沪深）：盘前集合竞价9:15开始，实际交易9:30-15:00
+    "CN": {
+        "pre_market_start": time(9, 15),  # 盘前开始时间（集合竞价）
+        "morning_start": time(9, 30),
+        "morning_end": time(11, 30),
+        "afternoon_start": time(13, 0),
+        "afternoon_end": time(15, 0)
+    },
+    # 港股：盘前竞价9:00开始，实际交易9:30-16:00
+    "HK": {
+        "pre_market_start": time(9, 0),   # 盘前开始时间
+        "morning_start": time(9, 30),
+        "morning_end": time(12, 0),
+        "afternoon_start": time(13, 0),
+        "afternoon_end": time(16, 0)
+    },
+    # 美股：盘前交易4:00-9:30（纽约时间），对应东八区夏令时16:00-21:30，冬令时17:00-22:30
+    "US": {
+        # 东八区盘前开始时间（夏令时/冬令时）
+        "dst_pre_start": time(16, 0),    # 夏令时盘前开始
+        "std_pre_start": time(17, 0),    # 冬令时盘前开始
+        # 东八区交易时间（同之前）
+        "dst_start": time(21, 30),
+        "dst_end": time(4, 0),
+        "std_start": time(22, 30),
+        "std_end": time(5, 0)
+    }
+}
+
+def get_trading_date(market: str, db_session: Session) -> str:
+    """
+    根据新逻辑返回交易日期：
+    1. 若当前日期是交易日，且当前时间 >= 盘前开始时间 → 取当前交易日
+    2. 否则（非交易日，或交易日但未到盘前时间） → 取前一交易日
+    
+    参数:
+        market: 市场标识（CN=A股, HK=港股, US=美股）
+        db_session: SQLAlchemy数据库会话对象
+    返回:
+        交易日期字符串（YYYY-MM-DD）
+    """
+    # 1. 获取东八区当前时间和日期
+    tz_sh = ZoneInfo("Asia/Shanghai")
+    now = datetime.now(tz_sh)  # 含时区的当前时间
+    current_date: date = now.date()  # 东八区当前日期（仅日期）
+    current_time: time = now.time()  # 东八区当前时间（仅时间）
+
+
+    # 2. 判断当前日期是否为该市场的交易日
+    def is_trading_day(market: str, date: date, session: Session) -> bool:
+        """检查指定日期是否为该市场的交易日"""
+        return session.query(FutuTradingDayModel).filter(
+            FutuTradingDayModel.market == market,
+            FutuTradingDayModel.trade_date == date
+        ).first() is not None
+
+
+    # 3. 获取该市场的盘前开始时间（东八区）
+    def get_pre_market_start(market: str, now: datetime) -> time:
+        """根据市场和当前时间（判断夏令时）返回盘前开始时间"""
+        if market == "US":
+            # 美股需根据纽约时区判断夏令时
+            tz_ny = ZoneInfo("America/New_York")
+            now_ny = now.astimezone(tz_ny)
+            is_dst = now_ny.dst() != timedelta(0)  # 夏令时判断
+            return MARKET_HOURS["US"]["dst_pre_start"] if is_dst else MARKET_HOURS["US"]["std_pre_start"]
+        else:
+            # A股/港股直接返回配置的盘前时间
+            return MARKET_HOURS[market]["pre_market_start"]
+
+
+    # 4. 核心逻辑判断
+    current_is_trading_day = is_trading_day(market, current_date, db_session)
+    pre_market_start = get_pre_market_start(market, now)
+    is_after_pre_market = current_time >= pre_market_start  # 当前时间是否过了盘前开始时间
+
+
+    # 5. 确定查询条件
+    if current_is_trading_day and is_after_pre_market:
+        # 情况1：当前是交易日，且已过盘前时间 → 取当前交易日
+        target_date = current_date
+    else:
+        # 情况2：非交易日，或未到盘前时间 → 取前一交易日
+        # 查询小于当前日期的最大交易日
+        prev_trading_day = db_session.query(FutuTradingDayModel.trade_date).filter(
+            FutuTradingDayModel.market == market,
+            FutuTradingDayModel.trade_date < current_date
+        ).order_by(FutuTradingDayModel.trade_date.desc()).first()
+        
+        if not prev_trading_day:
+            raise ValueError(f"未查询到{market}市场的前一交易日数据")
+        target_date = prev_trading_day.trade_date
+
+
+    return target_date.strftime("%Y-%m-%d")
+
+# 示例：获取各市场的目标交易日期
+
+if __name__ == "__main__":
+    engine = create_engine(global_db_url)
+    Session = sessionmaker(bind=engine)
+    db_session = Session()
+
+    try:
+        # 分别获取三个市场的交易日期
+        print(f"A股目标交易日期：{get_trading_date('CN', db_session)}")
+        print(f"港股目标交易日期：{get_trading_date('HK', db_session)}")
+        print(f"美股目标交易日期：{get_trading_date('US', db_session)}")
+    finally:
+        db_session.close()