Is "from matplotlib import pyplot as plt" == "import matplotlib.pyplot as plt"?

Understanding Python Imports: 'from X import Y' vs 'import X.Y'

Explore the subtle yet significant differences between from matplotlib import pyplot as plt and import matplotlib.pyplot as plt in Python, and learn how each impacts your code's readability, namespace, and execution.

In Python, importing modules is a fundamental operation, but the syntax can sometimes lead to confusion. A common point of inquiry for new and experienced developers alike revolves around the two primary ways to import submodules or specific objects: from module import object and import module.object. While both achieve a similar goal of making code available, they operate differently regarding how they populate your current namespace and how you subsequently refer to the imported elements. This article will dissect these differences using matplotlib.pyplot as a practical example, providing clarity on when to use each approach.

The 'import module.submodule as alias' Approach

When you use import matplotlib.pyplot as plt, you are importing the entire pyplot submodule directly into your current namespace, but it's nested under the matplotlib module. The as plt part is an alias, making it convenient to refer to matplotlib.pyplot simply as plt.

How it Works:

1. matplotlib is loaded: Python first finds and loads the top-level matplotlib package.
2. pyplot is loaded: Then, it finds and loads the pyplot submodule within matplotlib.
3. Namespace Entry: A single entry, plt, is added to your current namespace. This plt object is a direct reference to the matplotlib.pyplot module.
4. Accessing Functions: To call functions from pyplot, you must prefix them with plt., for example, plt.plot() or plt.show().

import matplotlib.pyplot as plt

# Now you can use plt directly
plt.plot([1, 2, 3], [4, 5, 6])
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Example Plot')
plt.show()

Using import matplotlib.pyplot as plt

The 'from module import object as alias' Approach

The statement from matplotlib import pyplot as plt works differently. Here, you are specifically telling Python to go into the matplotlib package, find the pyplot submodule, and then directly import that submodule into your current namespace under the alias plt.

How it Works:

1. matplotlib is loaded: Python first finds and loads the top-level matplotlib package.
2. pyplot is loaded: It then finds and loads the pyplot submodule within matplotlib.
3. Namespace Entry: A single entry, plt, is added to your current namespace. This plt object is a direct reference to the matplotlib.pyplot module.
4. Accessing Functions: Similar to the previous method, you access functions using plt., e.g., plt.plot().

from matplotlib import pyplot as plt

# Now you can use plt directly
plt.plot([1, 2, 3], [4, 5, 6])
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Example Plot')
plt.show()

Using from matplotlib import pyplot as plt

Are They Equivalent for matplotlib.pyplot?

For the specific case of matplotlib.pyplot, the two statements import matplotlib.pyplot as plt and from matplotlib import pyplot as plt are functionally equivalent in terms of how you interact with plt afterwards. Both result in the matplotlib.pyplot module being bound to the name plt in your current namespace.

Let's visualize the import process and its outcome in the namespace.

flowchart TD
    A[Start Import Process]
    subgraph "import matplotlib.pyplot as plt"
        B1[Load 'matplotlib' package]
        B2[Load 'pyplot' submodule within 'matplotlib']
        B3["Bind 'matplotlib.pyplot' to 'plt' in current namespace"]
    end
    subgraph "from matplotlib import pyplot as plt"
        C1[Load 'matplotlib' package]
        C2[Load 'pyplot' submodule within 'matplotlib']
        C3["Bind 'pyplot' (from 'matplotlib') to 'plt' in current namespace"]
    end
    A --> B1
    B1 --> B2
    B2 --> B3
    A --> C1
    C1 --> C2
    C2 --> C3
    B3 --> D["Result: 'plt' refers to 'matplotlib.pyplot'"]
    C3 --> D

Comparison of import mechanisms for matplotlib.pyplot

As the diagram illustrates, for this specific scenario, the end result is the same: plt becomes an alias for the matplotlib.pyplot module. The difference lies more in the general principle of how import and from ... import work, which becomes more apparent when importing individual functions or classes.

Consider if you were importing a specific function, say plot, directly:

• from matplotlib.pyplot import plot would make plot() available directly.
• import matplotlib.pyplot as plt would require plt.plot().

General Differences and Best Practices

While the matplotlib.pyplot case is a bit unique due to the common aliasing, understanding the general implications of each import style is crucial.

import module.submodule (or import module.submodule as alias)

• Namespace: Adds only module (or alias) to the namespace. You access submodules/functions via module.submodule.function or alias.function.
• Clarity: Explicitly shows the origin of the imported object, reducing naming conflicts.
• Control: Gives you full control over the module's structure.

from module import object (or from module import object as alias)

• Namespace: Adds object (or alias) directly to the namespace. You access it directly as object() or alias().
• Conciseness: Can make code shorter, especially for frequently used functions.
• Potential for Conflicts: Can lead to naming collisions if multiple modules export objects with the same name. It also makes it harder to trace the origin of a function without looking at the import statements.

For matplotlib.pyplot, the as plt alias makes both forms effectively identical in usage because you're always referring to the module pyplot via its alias plt, not individual functions directly into your namespace.

In conclusion, for matplotlib.pyplot, both import matplotlib.pyplot as plt and from matplotlib import pyplot as plt achieve the same practical outcome due to the as plt alias. However, understanding the underlying mechanics of Python's import system is vital for writing clean, maintainable, and conflict-free code in other contexts.