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35 lines
1.6 KiB
Markdown
35 lines
1.6 KiB
Markdown
---
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layout: default
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title: "NumPy Core"
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nav_order: 15
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has_children: true
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---
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# Tutorial: NumPy Core
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NumPy provides the powerful **ndarray** object, a *multi-dimensional grid* optimized for numerical computations on large datasets. It uses **dtypes** (data type objects) to precisely define the *kind of data* (like integers or floating-point numbers) stored within an array, ensuring memory efficiency and enabling optimized low-level operations. NumPy also features **ufuncs** (universal functions), which are functions like `add` or `sin` designed to operate *element-wise* on entire arrays very quickly, leveraging compiled code. Together, these components form the foundation for high-performance scientific computing in Python.
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**Source Repository:** [https://github.com/numpy/numpy/tree/3b377854e8b1a55f15bda6f1166fe9954828231b/numpy/_core](https://github.com/numpy/numpy/tree/3b377854e8b1a55f15bda6f1166fe9954828231b/numpy/_core)
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```mermaid
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flowchart TD
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A0["ndarray (N-dimensional array)"]
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A1["dtype (Data Type Object)"]
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A2["ufunc (Universal Function)"]
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A3["multiarray Module"]
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A4["umath Module"]
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A5["Numeric Types"]
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A6["Array Printing"]
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A7["__array_function__ Protocol / Overrides"]
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A0 -- "Has data type" --> A1
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A2 -- "Operates element-wise on" --> A0
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A3 -- "Provides implementation for" --> A0
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A4 -- "Provides implementation for" --> A2
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A5 -- "Defines scalar types for" --> A1
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A6 -- "Formats for display" --> A0
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A6 -- "Uses for formatting info" --> A1
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A7 -- "Overrides functions from" --> A3
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A7 -- "Overrides functions from" --> A4
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A1 -- "References type hierarchy" --> A5
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``` |