Table of Contents
1. Import the installed library
2. Use PyCharm’s auto-completion function
3. Example
4. Summary
Home Backend Development Python Tutorial Learn quickly using PyCharm: how to import libraries in your project

Learn quickly using PyCharm: how to import libraries in your project

Feb 25, 2024 pm 11:39 PM
project pycharm import

PyCharm 快速入门:如何在项目中导入库

PyCharm is a powerful Python integrated development environment that is widely used by Python developers for code writing, debugging and project management. During the development of Python projects, it is often necessary to import various libraries to extend the functions of Python. This article will focus on how to quickly import libraries in PyCharm and provide specific code examples.

1. Import the installed library

First, we need to ensure that the Python library we need to use has been installed. In PyCharm, we can import installed libraries by following these steps:

  1. Open PyCharm and open your Python project.
  2. In the code editing area, find the location where the library needs to be imported.
  3. Where you need to import the library, enter the code to import the library, for example: import numpy as np.

2. Use PyCharm’s auto-completion function

PyCharm provides a powerful auto-completion function that can help us quickly import libraries and reduce errors. When entering the name of a library, PyCharm will automatically prompt possible library names, and you only need to press the Tab key to complete the automatic completion.

3. Example

Next, we use a specific example to demonstrate how to import the library in PyCharm. Suppose we need to use the numpy library in our project for scientific calculations.

# 导入numpy库
import numpy as np

# 创建一个数组
arr = np.array([1, 2, 3, 4, 5])

# 输出数组的元素个数
print("数组元素个数:", len(arr))

# 计算数组元素的平均值
print("数组元素平均值:", np.mean(arr))
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In the above example, we first imported the numpy library and used np as an alias to reference the library. We then created an array of 5 elements and calculated the mean of the array elements using the np.mean method.

4. Summary

Through the introduction of this article, we have learned how to quickly import installed libraries in PyCharm, and demonstrated how to use numpy through specific examples. Library for scientific computing. In actual development, correctly importing libraries is the basis for code writing and a key factor in improving code efficiency and accuracy. I hope this article can help readers become more proficient in importing libraries into PyCharm and improve the efficiency and quality of Python project development.

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