Using Aliases Import Method

Common aliases: numpy → np, pandas → pd, math → m, datetime → dt

Console Output
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Alias Import Visualization
Click "Generate Alias Import" button in the left panel to see the visualization
Alias Import Flow
Module with custom name for better readability
math module
Original module name
Alias: alias
Custom module name
alias.sqrt(16)
Function call with alias
Alias Import Demo:
Current Alias Configuration
math • sqrt • alias
import math as alias
result = alias.sqrt()
Selected function: sqrt
Common Alias Examples:
numpy → np
import numpy as np → np.array([1,2,3])
pandas → pd
import pandas as pd → pd.DataFrame()
matplotlib.pyplot → plt
import matplotlib.pyplot as plt → plt.plot()
math → m
import math as m → m.sqrt(16)
datetime → dt
import datetime as dt → dt.datetime.now()
random → rand
import random as rand → rand.randint(1,10)
Benefits of Using Aliases:
Shorter Code
np.array() vs numpy.array()
Prevents Conflicts
Avoid naming collisions
Better Readability
Clear and concise syntax
Community Standard
Follows Python conventions
Consistency
Uniform across projects
Module-Specific Alias Tips:
math Module Alias Tips
• Use 'm' as alias for shorter math operations
• Example: m.sqrt(16) instead of math.sqrt(16)
• Common in scientific computing
Alias Best Practices
• Use short, meaningful aliases (np, pd, plt)
• Follow community conventions for popular libraries
• Avoid single letters except for common cases
• Be consistent across your entire project
• Document non-standard aliases in your code
• Don't use aliases that could cause confusion