解决Docker化Flak应用中SQLite数据库无法打开的问题

DE-Project/

│

├── ...

│

├── make_predictions/

│   └── fraud_detection.db  # 数据库文件

│

└── frontend/

    ├── app.py              # Flask应用

    └── ...

# app.py

import os

import sqlite3

from flask import Flask, render_template

app = Flask(__name__)

# ... (模板路径设置)

# 获取当前脚本所在目录的绝对路径，例如：/app/frontend

script_dir = os.path.dirname(os.path.abspath(__file__))

# 尝试构建数据库文件的绝对路径

# 这将导致路径为 /app/frontend/make_predictions/fraud_detection.db

db_file_path = os.path.join(script_dir, make_predictions/fraud_detection.db)

@app.route(/)

def index():

    conn = sqlite3.connect(db_file_path) # 错误发生在这里

    # ...

# Dockerfile.frontend

FROM python:3.8

WORKDIR /app

COPY . /app # 将整个 DE-Project 复制到容器的 /app 目录

# ...

CMD ["python", "frontend/app.py"] # 假设这里是启动命令

/app/

├── make_predictions/

│   └── fraud_detection.db

├── frontend/

│   └── app.py

├── ...

# app.py

import os

import sqlite3

from flask import Flask, render_template

app = Flask(__name__)

# Set the path to the templates folder explicitly

template_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), templates)

app.template_folder = template_path

# --- 数据库路径处理 ---

# 推荐方式：通过环境变量配置，提高灵活性

db_file_path = os.environ.get(DATABASE_PATH)

if db_file_path is None:

    # 备用方案：通过相对路径计算（如果环境变量未设置）

    # 获取当前脚本所在目录的绝对路径 (例如: /app/frontend)

    script_dir = os.path.dirname(os.path.abspath(__file__))

    # 数据库位于 make_predictions 目录，该目录是 frontend 的同级目录

    # 因此，从 script_dir (/app/frontend) 需要先向上退一级 (..) 再进入 make_predictions

    db_file_path = os.path.join(script_dir, .., make_predictions, fraud_detection.db)

# 打印路径用于调试，在生产环境中可以移除

print(f"Attempting to connect to database at: {db_file_path}")

@app.route(/)

def index():

    conn = None # 初始化 conn

    try:

        conn = sqlite3.connect(db_file_path)

        cur = conn.cursor()

        sqlite_select_Query = "SELECT * FROM potential_fraud LIMIT 10;"

        cur.execute(sqlite_select_Query)

        record = cur.fetchall()

        return render_template(index.html, entries=record)

    except sqlite3.OperationalError as e:

        print(f"Error connecting to database: {e}")

        # 返回一个错误页面或信息给用户

        return render_template(error.html, message=f"Database error: {e}"), 500

    finally:

        if conn:

            conn.close()

if __name__ == __main__:

    app.run(host=0.0.0.0, port=5000)

# docker-compose.yaml

version: 3.8

services:

  # Flask 前端服务

  frontend:

    build:

      context: . # Dockerfile.frontend 所在的目录

      dockerfile: Dockerfile.frontend # 指定用于构建前端服务的 Dockerfile

    ports:

      - "5000:5000" # 将容器的 5000 端口映射到宿主机的 5000 端口

    volumes:

      # 将宿主机上的 make_predictions 目录挂载到容器内部的 /app/make_predictions

      # 这样，容器内部 /app/make_predictions 目录下的文件会与宿主机的 make_predictions 目录同步

      - ./make_predictions:/app/make_predictions

    depends_on:

      - consumer # 确保前端服务在消费者服务启动后才启动

      - producer # 如果生产者也需要生成或修改数据库，也依赖它

    environment:

      # 通过环境变量将数据库路径传递给 Flask 应用

      DATABASE_PATH: /app/make_predictions/fraud_detection.db

  # 消费者服务 (示例)

  consumer:

    build:

      context: .

      dockerfile: Dockerfile.consumer

    volumes:

      # 消费者服务也需要访问同一个 make_predictions 目录

      - ./make_predictions:/app/make_predictions

    # command: python make_predictions/consumer.py # 示例启动命令

  # 生产者服务 (示例)

  producer:

    build:

      context: .

      dockerfile: Dockerfile.producer

    volumes:

      # 生产者服务也需要访问同一个 make_predictions 目录

      - ./make_predictions:/app/make_predictions

    # command: python make_predictions/producer.py # 示例启动命令

  # 训练模型服务 (示例)

  train_model:

    build:

      context: .

      dockerfile: Dockerfile.train_model

    volumes:

      # 如果训练模型也需要访问或输出到 make_predictions 目录

      - ./make_predictions:/app/make_predictions

    # command: python train_model/train_model.py # 示例启动命令

# Dockerfile.frontend (示例)

FROM python:3.8

WORKDIR /app

COPY ./shared /app/shared # 复制共享依赖

COPY ./frontend /app/frontend # 复制前端应用

COPY ./make_predictions /app/make_predictions # 复制 make_predictions 目录，尽管会被 volume 覆盖，但可以作为 Fallback

# 确保 requirements.txt 被正确处理，如果 shared/requirements.txt 是通用的

RUN pip install --no-cache-dir -r /app/shared/requirements.txt

EXPOSE 5000

CMD ["python", "frontend/app.py"] # 启动 Flask 应用

# Dockerfile.consumer (示例)

FROM python:3.8

WORKDIR /app

COPY ./shared /app/shared

COPY ./make_predictions /app/make_predictions

RUN pip install --no-cache-dir -r /app/shared/requirements.txt

CMD ["python", "make_predictions/consumer.py"] # 启动消费者

# Dockerfile.producer (示例)

FROM python:3.8

WORKDIR /app

COPY ./shared /app/shared

COPY ./make_predictions /app/make_predictions

RUN pip install --no-cache-dir -r /app/shared/requirements.txt

CMD ["python", "make_predictions/producer.py"] # 启动生产者

docker-compose up --build