How to use thinkorm to quickly import and export data from the database

How to use thinkorm to quickly import and export data from the database

Introduction:
In the actual development process, data import and export is a common requirement. thinkorm is an open source Python ORM framework that can easily operate databases. This article will introduce how to use thinkorm to quickly implement the data import and export functions of the database, and provide code examples.

1. Install thinkorm
First, please make sure you have installed the Python environment. Run the following command in the command line to install thinkorm:

pip install thinkorm

2. Connect to the database
Before using thinkorm, we need to connect to the database first. Taking the MySQL database as an example, you can use the following code to connect:

from thinkorm import Database

# 创建数据库连接
db = Database(host='localhost', port=3306, user='root', password='password', database='test')

3. Import data

1. Import data from CSV files
   thinkorm provides bulk_create method can quickly import data. We can first save the data into a CSV file and then use the bulk_create method to import the data into the database.

The following is an example:

from thinkorm import Model, Field

# 创建模型
class User(Model):
    id = Field()
    name = Field()
    age = Field()

# 读取 CSV 文件
data = []
with open('data.csv', 'r') as f:
    lines = f.readlines()
    for line in lines:
        values = line.strip().split(',')
        data.append(User(id=int(values[0]), name=values[1], age=int(values[2])))

# 导入数据
User.bulk_create(data)

2. Import data from Excel file
   If the data is saved in an Excel file, we can use the third-party library pandas to convert the Excel data Read it into a DataFrame, and then convert it into a thinkorm model object for import.

The following is an example:

import pandas as pd
from thinkorm import Model, Field

# 创建模型
class User(Model):
    id = Field()
    name = Field()
    age = Field()

# 读取 Excel 文件
data = pd.read_excel('data.xlsx')

# 转换数据为模型对象
data = [User(id=int(row[0]), name=row[1], age=int(row[2])) for row in data.values]

# 导入数据
User.bulk_create(data)

4. Export data

1. The export data is a CSV file
   thinkorm providesall method can get all the data in the table, and we can export the data to a CSV file.

The following is an example:

# 导出数据
data = User.all()
with open('data.csv', 'w') as f:
    for row in data:
        f.write(f"{row.id},{row.name},{row.age}
")

2. Export data as Excel file
   If you need to export the data as an Excel file, we can use the third-party library pandas to convert the data Convert to DataFrame and save as Excel file.

The following is an example:

import pandas as pd

# 导出数据
data = User.all()

# 转换数据为 DataFrame
data = pd.DataFrame([(row.id, row.name, row.age) for row in data], columns=['id', 'name', 'age'])

# 导出为 Excel 文件
data.to_excel('data.xlsx', index=False)

Summary:
This article introduces how to use thinkorm to quickly implement the data import and export functions of the database. By using the bulk_create method, we can easily import data from a CSV file or Excel file; and by using the all method, we can export the data to a CSV file or Excel file. These methods can help us process data efficiently and improve development efficiency.

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