Python导出PostgreSQL数据库的表结构（使用SSH隧道）

 1、安装依赖

pip install sshtunnel psycopg2  openpyxl  pandas 

 

2、实现代码：

import pandas as pd
import psycopg2
from openpyxl import load_workbook
from openpyxl.styles import Border, Side, PatternFill, Font, Alignment
from openpyxl.utils import get_column_letter
from sshtunnel import SSHTunnelForwarder


def apply_formatting(excel_path):
    """应用格式设置"""
    wb = load_workbook(excel_path)

    # 定义样式
    blue_fill = PatternFill(
        start_color="0070C0",
        end_color="0070C0",
        fill_type="solid"
    )
    thin_border = Border(
        left=Side(style='thin'),
        right=Side(style='thin'),
        top=Side(style='thin'),
        bottom=Side(style='thin')
    )

    for sheet in wb.worksheets:
        # 设置标题行样式
        for cell in sheet[1]:
            cell.fill = blue_fill
            cell.font = Font(color="FFFFFF", bold=True)

        # 设置边框
        for row in sheet.iter_rows(min_row=1):
            for cell in row:
                cell.border = thin_border

        # 自适应列宽
        for column in sheet.columns:
            max_length = max(
                len(str(cell.value)) for cell in column
            )
            adjusted_width = (max_length + 2) * 1.2
            sheet.column_dimensions[
                get_column_letter(column[0].column)
            ].width = adjusted_width

        # 定义居中对齐样式（水平居中 + 垂直居中）
        alignment = Alignment(
            horizontal='center',  # 水平居中：'left', 'center', 'right', 'justify'
            vertical='center'  # 垂直居中：'top', 'center', 'bottom'
        )
        # 对指定的列设置居中
        columns_to_center = ['A', 'H']     # 将A列和H列设置居中
        for col in columns_to_center:
            for cell in sheet[col]:
                cell.alignment = alignment

    wb.save(excel_path)


def add_hyperlinks(excel_path):
    """添加双向超链接"""
    wb = load_workbook(excel_path)
    ws_summary = wb["首页总览"]

    # 总览表到分表
    for row in ws_summary.iter_rows(min_row=2):
        table_name = row[1].value
        sheet_name = table_name[:30]
        hyperlink = f"#'{sheet_name}'!A1"
        row[1].hyperlink = hyperlink
        row[1].style = "Hyperlink"

    # 分表到总览表
    for sheet_name in wb.sheetnames[1:]:
        ws = wb[sheet_name]
        last_row = ws.max_row + 1
        ws.cell(row=last_row, column=1, value="返回\"首页总览\"")
        ws.cell(row=last_row, column=1).hyperlink = "#'首页总览'!A1"
        ws.cell(row=last_row, column=1).style = "Hyperlink"

    wb.save(excel_path)


def sql_to_dataframe(cursor):
    """将 pyodbc cursor 结果转换为 DataFrame"""
    # 获取列名
    columns = [column[0] for column in cursor.description]
    # 获取数据并创建DataFrame
    data = cursor.fetchall()
    return pd.DataFrame.from_records(data, columns=columns)


def get_tables_info(cursor, db_user):
    """获取所有表信息"""
    query = f"""
            SELECT
                c.relname AS table_name,
                obj_description(c.oid, 'pg_class') AS table_comment
            FROM  pg_class c
            JOIN  pg_namespace n ON n.oid = c.relnamespace
            WHERE
                c.relkind = 'r'               
                AND n.nspname = 'public'      
                AND NOT EXISTS (
                    SELECT 1
                    FROM pg_inherits i
                    WHERE i.inhrelid = c.oid   
                )
            ORDER BY table_name
    """
    # 执行查询
    cursor.execute(query)
    return sql_to_dataframe(cursor)


def get_columns_info(cursor, table_name):
    """获取指定表结构详情"""
    query = f"""
             SELECT
                        c.relname  AS  table_name,
                        a.attname  AS  column_name,
                        col_description(a.attrelid, a.attnum) AS  column_comment,
                        CASE 
                            WHEN t.typcategory = 'A' THEN REPLACE(t.typname, '_', '') || '[]'
                            ELSE t.typname 
                        END AS  column_type,
                        CASE 
                                WHEN t.typname IN ('varchar','bpchar') THEN a.atttypmod -4
                                WHEN t.typname = 'numeric' THEN (a.atttypmod -4) >> 16 & 65535
                                ELSE NULL 
                        END AS  type_length,
                        CASE 
                                WHEN t.typname = 'numeric' THEN (a.atttypmod -4) & 65535 
                                ELSE NULL 
                        END AS  type_scale,                       
                        CASE WHEN a.attnotnull THEN '[√]' ELSE '[]' END  AS  isnotnull
                FROM  pg_class c
                JOIN  pg_attribute a ON a.attrelid = c.oid
                JOIN  pg_type t ON a.atttypid = t.oid
                WHERE
                        c.relkind = 'r' 
                        AND a.attnum > 0  
                        AND NOT a.attisdropped   
                        AND c.relname = '{table_name}'
                        AND c.relnamespace = 'public'::regnamespace  
                ORDER BY  c.relname, a.attnum
    """

    # 执行查询
    cursor.execute(query)
    return sql_to_dataframe(cursor)


if __name__ == '__main__':

    # ================== 配置信息 ==================
    # SSH 隧道配置
    ssh_host = "100.100.10.10"  # SSH跳板机IP
    ssh_port = 22               # SSH端口（默认22）
    ssh_user = "root"           # SSH用户名
    ssh_password = "Root@1234"  # SSH密码

    # 数据库参数
    db_host = "100.100.20.20"  # 数据库服务器实际IP（SSH隧道目标）
    db_port = 5432             # 数据库默认端口
    db_name = "mydb"           # 数据库
    db_user = "postgres"       # 数据库用户
    db_password = "postgres"   # 数据库用户的密码

    # 本地绑定端口（随机可用端口）
    local_bind_port = 9090

    # ================== 建立SSH隧道 ==================
    try:
        with SSHTunnelForwarder(
                (ssh_host, ssh_port),
                ssh_username=ssh_user,
                ssh_password=ssh_password,
                remote_bind_address=(db_host, db_port),
                local_bind_address=("0.0.0.0", local_bind_port),
                set_keepalive=15         # 保持连接活跃
        ) as tunnel:
            print(f"SSH隧道建立成功，本地端口：{tunnel.local_bind_port}")

            # ================== 连接数据库 ==================
            conn = psycopg2.connect(
                host='localhost',             # 关键！必须使用localhost
                port=tunnel.local_bind_port,  # 映射的本地端口
                database=db_name,
                user=db_user,
                password=db_password
            )
            cursor = conn.cursor()
            print("数据库连接成功！")

            # 获取所有表的信息
            df_summary = get_tables_info(cursor, db_user.upper())
            df_summary.insert(0, '序号', range(1, len(df_summary) + 1))

            # 写入的Excel名称
            output_file = f"数据库{db_name}表结构.xlsx"

            # 创建Excel写入对象
            with pd.ExcelWriter(output_file, engine='openpyxl') as writer:
                # 写入总览页
                df_summary.to_excel(
                    writer,
                    sheet_name='首页总览',
                    index=False,
                    header=['序号', '表名', '表注释']
                )

                # 遍历写入各表结构
                for _, row in df_summary.iterrows():
                    table_name = row['table_name']

                    print("正在导出表", table_name, "的表结构")

                    df_columns = get_columns_info(cursor, table_name)
                    df_columns.insert(0, '序号', range(1, len(df_columns) + 1))
                    df_columns.to_excel(
                        writer,
                        sheet_name=table_name[:30],  # Excel表名最长31字符
                        index=False,
                        header=["序号", "表名", "字段名称", "字段注释", "字段类型", "长度", "小数点", "非空"]
                    )

            # 应用格式和超链接
            print("正在设置超链接和边框......")
            add_hyperlinks(output_file)    # 设置超链接
            apply_formatting(output_file)   # 设置边框

            print(f"表结构已成功导出至 {output_file}")

    except Exception as e:
        print(f"连接失败: {str(e)}")
    finally:
        if 'conn' in locals():
            conn.close()