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@ -17,7 +17,9 @@ from sqlalchemy.exc import OperationalError |
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import json |
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import json |
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import re |
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import re |
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from decimal import Decimal |
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from decimal import Decimal |
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import sqlparse |
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from sqlparse.sql import Identifier, IdentifierList, Function, Token |
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from sqlparse.tokens import Keyword, DML |
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class MetaSecurityService: |
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class MetaSecurityService: |
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""" |
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""" |
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数据源安全管理模块服务层 |
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数据源安全管理模块服务层 |
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@ -304,7 +306,7 @@ class MetaSecurityService: |
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dbConnent= cls.get_db_engine(dsDataResource["type"],dsDataResource["connectionParams"]) |
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dbConnent= cls.get_db_engine(dsDataResource["type"],dsDataResource["connectionParams"]) |
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# await test_connection(dbConnent) |
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# await test_connection(dbConnent) |
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#3获取sql中涉及的表名 |
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#3获取sql中涉及的表名 |
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sqlScheamAndTable =await cls.get_tables_from_sql(page_object.sqlStr) |
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sqlScheamAndTable =await get_tables_from_sql(page_object.sqlStr) |
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oldStrSql=generate_pagination_sql(page_object,dsDataResource["type"]) |
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oldStrSql=generate_pagination_sql(page_object,dsDataResource["type"]) |
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#4.执行原始sql |
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#4.执行原始sql |
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result = await cls.execute_sql(dbConnent, oldStrSql,"原始") |
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result = await cls.execute_sql(dbConnent, oldStrSql,"原始") |
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@ -405,74 +407,6 @@ class MetaSecurityService: |
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except SQLAlchemyError as e: |
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except SQLAlchemyError as e: |
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raise RuntimeError(f"{sql_type}执行 SQL 查询时发生错误: {e}") |
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raise RuntimeError(f"{sql_type}执行 SQL 查询时发生错误: {e}") |
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# async def get_tables_from_sql(sql_query: str): |
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# """ |
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# 解析 SQL 查询，提取所有 Schema 和 Table 名称，并确保表名包含模式名（schema.table）。 |
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# :param sql_query: SQL 查询字符串 |
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# :return: {'schemas': [...], 'table_names': [...]} |
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# :raises ServiceException: 如果 SQL 未使用 schema.table 结构，则抛出异常 |
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# """ |
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# # ✅ 改进正则：支持 `FROM a.o, b.x JOIN c.y` |
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# table_section_pattern = r"(?i)(?:FROM|JOIN|INTO|UPDATE)\s+([\w\.\s,]+)" |
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# table_sections = re.findall(table_section_pattern, sql_query, re.DOTALL) |
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# if not table_sections: |
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# raise ServiceException(data='', message='SQL 解析失败，未找到表名') |
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# # 解析多个表（用 `,` 和 `JOIN` 拆分） |
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# for section in table_sections: |
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# tables = re.split(r"\s*,\s*|\s+JOIN\s+", section, flags=re.IGNORECASE) |
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# for table in tables: |
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# table = table.strip().split()[0] # 取 `schema.table`，忽略别名 |
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# if "." not in table: |
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# raise ServiceException( |
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# data='', |
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# message=f"SQL 中的表名必须携带模式名（schema.table），但发现了无模式的表：{table}" |
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# ) |
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# return table_sections |
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async def get_tables_from_sql(sql_query: str): |
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""" |
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解析 SQL 查询，提取所有 schema.table 名称（支持嵌套子查询、别名、JOIN、INTO、UPDATE）。 |
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自动排除字段引用与无模式表。 |
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""" |
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# 1️⃣ 清理注释与多余空白 |
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sql_query = re.sub(r"--.*?$", "", sql_query, flags=re.MULTILINE) |
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sql_query = re.sub(r"/\*.*?\*/", "", sql_query, flags=re.DOTALL) |
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sql_query = " ".join(sql_query.split()) |
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# 2️⃣ 匹配 FROM/JOIN/INTO/UPDATE 后面的 schema.table |
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pattern = re.compile( |
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r"""(?ix) |
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(?:FROM|JOIN|INTO|UPDATE)\s+ # SQL 关键字 |
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(?!\() # 排除子查询 |
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(?P<schema>["'`]?[A-Za-z_][\w\$]*["'`]?) # schema |
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\. # . |
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(?P<table>["'`]?[A-Za-z_][\w\$]*["'`]?) # table |
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\b |
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""", |
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re.VERBOSE |
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) |
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# 3️⃣ 使用 finditer，逐个安全提取匹配项 |
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table_names = set() |
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for m in pattern.finditer(sql_query): |
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schema_raw = m.group("schema") |
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table_raw = m.group("table") |
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if not schema_raw or not table_raw: |
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continue |
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schema =unquote_ident(schema_raw) |
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table = unquote_ident(table_raw) |
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table_names.add(f"{schema}.{table}") |
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# 4️⃣ 检查结果 |
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if not table_names: |
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raise ServiceException(data='', message="SQL 解析失败，未找到任何 schema.table 结构") |
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return list(table_names) |
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@classmethod |
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@classmethod |
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async def get_columns_from_tables(cls, dbConnent, table_names, db_type: str): |
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async def get_columns_from_tables(cls, dbConnent, table_names, db_type: str): |
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@ -734,13 +668,6 @@ async def replace_table_with_subquery(ctrSqlDict, oldStrSql): |
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original_table = match.group(2) |
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original_table = match.group(2) |
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alias_part = match.group(3) # " AS xxx" 或 " xxx" |
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alias_part = match.group(3) # " AS xxx" 或 " xxx" |
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alias_name = match.group(4) # xxx |
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alias_name = match.group(4) # xxx |
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# 动态获取子查询 |
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if original_table in ctrSqlDict: |
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# 使用 ctrSqlDict 中的子查询替换表名 |
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replaced = f"{keyword} ({ctrSqlDict[original_table]}) {alias_part}" |
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else: |
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# 默认处理逻辑：判断 alias 是否为关键字 |
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sql_keywords = { |
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sql_keywords = { |
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"SELECT", "INSERT", "UPDATE", "DELETE", "MERGE", "TRUNCATE", |
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"SELECT", "INSERT", "UPDATE", "DELETE", "MERGE", "TRUNCATE", |
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"VALUES", "RETURNING", "FROM", "WHERE", "GROUP", "HAVING", "ORDER", |
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"VALUES", "RETURNING", "FROM", "WHERE", "GROUP", "HAVING", "ORDER", |
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@ -753,6 +680,13 @@ async def replace_table_with_subquery(ctrSqlDict, oldStrSql): |
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"ALL", "SOME", "FETCH", "NEXT", "ONLY", "ASC", "DESC", "GRANT", "REVOKE", "ROLE", |
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"ALL", "SOME", "FETCH", "NEXT", "ONLY", "ASC", "DESC", "GRANT", "REVOKE", "ROLE", |
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"USER", "CURRENT_DATE", "CURRENT_TIME", "CURRENT_TIMESTAMP", |
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"USER", "CURRENT_DATE", "CURRENT_TIME", "CURRENT_TIMESTAMP", |
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} |
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} |
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# 动态获取子查询 |
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if original_table in ctrSqlDict and alias_name not in sql_keywords: |
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# 使用 ctrSqlDict 中的子查询替换表名 |
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replaced = f"{keyword} ({ctrSqlDict[original_table]}) {alias_part}" |
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else: |
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# 默认处理逻辑：判断 alias 是否为关键字 |
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if alias_name and alias_name.upper().split()[0] not in sql_keywords: |
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if alias_name and alias_name.upper().split()[0] not in sql_keywords: |
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replaced = f"{keyword} ({subquery}) {alias_part}" |
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replaced = f"{keyword} ({subquery}) {alias_part}" |
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@ -835,3 +769,93 @@ def generate_pagination_sql(page_object: MetaSecurityApiModel, db_type: str) -> |
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raise ValueError(f"不支持的数据库类型: {db_type}") |
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raise ValueError(f"不支持的数据库类型: {db_type}") |
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return newStrSql |
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return newStrSql |
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def _extract_identifiers(token): |
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""" |
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从 Identifier 或 IdentifierList 中抽取 (schema, table) 对。 |
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返回格式为 'schema.table'（如果有 schema），否则 None。 |
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""" |
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if isinstance(token, Identifier): |
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real_name = token.get_real_name() # table |
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parent_name = token.get_parent_name() # schema if exists |
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if real_name and parent_name: |
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return f"{parent_name}.{real_name}" |
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# 处理像 schema.table AS alias 这种形式 |
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# token.get_name() 返回 alias 或 table，根据需要可扩展 |
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return None |
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async def get_tables_from_sql(sql_query: str): |
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""" |
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使用 sqlparse 解析 SQL 并返回 schema.table 列表（去重） |
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支持嵌套子查询、函数、别名、JOIN、INTO、UPDATE 等。 |
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只返回包含 schema 的标识符（即有点号的）。 |
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""" |
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parsed = sqlparse.parse(sql_query) |
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tables = set() |
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for stmt in parsed: |
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# 遍历语句的 token 树，寻找顶层的 FROM/JOIN/INTO/UPDATE 子句 |
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for token in stmt.tokens: |
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# 忽略函数、子查询整体（它们会在自己的 stmt 中被处理） |
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# 但我们需要遍历整个树以捕获顶层的 Identifier/IdentifierList |
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if token.is_group: |
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# 递归遍历 group 内的 token |
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for t in token.flatten(): |
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# 跳过在函数内部的 FROM（例如 EXTRACT(... FROM ...)） |
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# 方法：判断最近的父级 group 是否为 Function（我们用了 flatten，故这里检查 parent types is hard） |
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# 简化办法：如果 token 的上层类型是 Function 的一部分，skip（handled by checking surrounding tokens） |
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pass |
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# 更好的做法：直接按 sqlparse 提供的机制遍历并查找 Identifier/IdentifierList |
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for token in stmt.tokens: |
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if token.ttype is DML and token.normalized.upper() in ("UPDATE",): |
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# UPDATE table_name ... |
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# 下一个非空白 token 往往是 Identifier |
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nxt = stmt.token_next(stmt.token_index(token), skip_ws=True, skip_cm=True) |
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if nxt: |
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name = _extract_identifiers(nxt[1]) if isinstance(nxt[1], (Identifier, IdentifierList)) else None |
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if name: |
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tables.add(name) |
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# 使用遍历获取所有 Identifier / IdentifierList 出现在 FROM 或 JOIN 后面的情况 |
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# 这里遍历 token 序列并在遇到 FROM/JOIN/INTO/UPDATE 时提取后续 identifier |
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idx = 0 |
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tokens = list(stmt.tokens) |
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while idx < len(tokens): |
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t = tokens[idx] |
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if t.is_whitespace: |
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idx += 1 |
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continue |
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if t.ttype is Keyword and t.normalized.upper() in ("FROM", "JOIN", "INTO"): |
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# 找下一个有意义的 token（可能是 Identifier 或 IdentifierList 或 Parenthesis 表示子查询） |
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nxt = stmt.token_next(idx, skip_ws=True, skip_cm=True) |
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if nxt: |
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tok = nxt[1] |
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# 如果是 parenthesis -> 子查询，跳过 |
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if tok.is_group and isinstance(tok, Function): |
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# 函数内的 FROM（如 EXTRACT(...)）会被解析为 Function 的一部分 —— 跳过 |
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pass |
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else: |
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# 处理 Identifier 或 IdentifierList |
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if isinstance(tok, Identifier): |
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name = _extract_identifiers(tok) |
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if name: |
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tables.add(name) |
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elif isinstance(tok, IdentifierList): |
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for ident in tok.get_identifiers(): |
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name = _extract_identifiers(ident) |
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if name: |
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tables.add(name) |
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else: |
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# 可能是直接的 Name token 'schema.table'（未被识别为 Identifier） |
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txt = tok.value |
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if "." in txt: |
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parts = txt.strip().strip('`"\'').split(".") |
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if len(parts) == 2: |
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tables.add(f"{parts[0]}.{parts[1]}") |
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idx += 1 |
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continue |
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idx += 1 |
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if not tables: |
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raise ValueError("SQL 解析失败，未找到任何 schema.table 结构") |
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return sorted(tables) |
xueyinfei
4 days ago