As an IT expert, interviewing is one of the challenges that every programmer must face. In Python interviews, interviewers usually ask questions about Python basics, common libraries and frameworks, algorithms and data structures, etc. In order to help you better prepare for Python interviews, this article will introduce these questions in detail and provide corresponding answers and sample code.
1. Basic knowledge of Python
1. Features of Python
Python is an interpreted, object-oriented, dynamic data type high-level programming language. Its design philosophy emphasizes code readability and concise syntax (especially the use of space indentation to delimit code blocks instead of using braces or keywords). Python supports multiple programming paradigms, including object-oriented, imperative, functional, and procedural programming. The Python interpreter is usually installed on UNIX and other large operating systems, and there are versions for Windows, Macintosh, and Linux.
2. Python’s basic data types
Python has five basic data types: integer (int), floating point number (float), string (str), list (list) and dictionary (dict). These data types can be nested within each other to form complex data structures.
3. Python’s control structure
Python provides control structures such as if-elif-else, for loop and while loop to implement conditional judgment and loop operations. In addition, Python also supports break and continue statements, which are used to break out of the current loop or skip the remaining part of this loop.
4. Python functions
Python uses the def keyword to define functions. Functions can have parameters or no parameters. A function can return a value or no value. The function body consists of indented blocks of code.
5. Python modules and packages
Python uses the import keyword to import other modules or packages. Specific parts of a module can be imported using the from...import... statement. A module is a file containing Python code, and the file name is the module name. A package is a directory containing multiple modules. There needs to be an __init__.py file in the directory (can be empty).
Example:
```python
# Import the sqrt function in the math module
from math import sqrt
# Use the sqrt function to calculate the square root of 9
result = sqrt(9)
print(result) # Output 3.0
````
2. Python common libraries and frameworks
1. NumPy
NumPy is an open source numerical computing extension library for Python that provides multi-dimensional array objects, matrix operations and other functions. The core of NumPy is the ndarray object, which represents an n-dimensional array and supports vectorization operations.
Example:
```python
import numpy as np
# Create a 2x3 two-dimensional array
arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr) # Output [[1 2 3] [4 5 6]]
```
2. Pandas
Pandas is a data processing library based on NumPy, which provides data structures such as DataFrame and Series, as well as various data processing and analysis functions. Pandas makes working with structured data easier.
Example:
```python
import pandas as pd
# Create a DataFrame object
data = {'Name': ['Tom', 'Jerry', 'Mike'], 'Age': [20, 18, 19]} df = pd.DataFrame(data) print(
df
) # Output Name Age
0 Tom 20
1 Jerry 18
2 Mike 19
```
3. Matplotlib
Matplotlib is a Python plotting library that provides a variety of plotting, visualization, and graphics processing functions. Matplotlib can draw various static, dynamic, and interactive charts.
Example:
```python
import matplotlib.pyplot as plt
import numpy as np
#Create data
x = np.linspace(0, 10, 100)
y = np.sin(x)
# Draw a sine curve
plt.plot(x, y)
plt.xlabel('x')
plt.ylabel('y')
plt.title('Sine Wave')
plt.show() # Display the image window and wait for the user After closing, continue executing subsequent
code```
3. Algorithms and data structures
1. Sorting algorithm (bubble sort, selection sort, insertion sort, quick sort, etc.)