An atomic type provides indivisible supported accesses and defined synchronization semantics during concurrent execution. A numeric dtype answers a different question: how values are represented. Choosing NumPy uint8 affects image arithmetic and overflow; choosing pandas column types affects memory use and precision. Neither example establishes atomic access, and no atomic API or synchronization rule is specified here. section 4.2.3 section 7.1.2 section 7.1.3
Atomic type
An atomic type is a type whose supported accesses and operations are indivisible with respect to concurrent execution and provide defined synchronization semantics.
How Fast Python: High performance techniques for large datasets covers it
- How deep it goes
- Works through width conversion and precision checks, but does not define atomic operations or synchronization.
- Examples
- Tests uint8 grayscale overflow and float32 taxi-fare error; neither example tests concurrent access.
- How it connects
- Connects numeric types to NumPy arrays, pandas columns, and Cython universal functions, not to a concurrency model.
Also explained in
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Modern C, Third EditionA type specifies the kind of values an entity can represent and the operations applicable to those values.
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Modern CA type is a C specification that determines the representation and permitted values or operations of an entity.
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Get Programming: Learn to code with PythonAn object type treated as indivisible because it cannot be separated into smaller object types.
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API Design PatternsA data type is a classification that specifies the kind of value a field can contain and how that value is represented.
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C++ Concurrency in Action, Second EditionAn atomic type is a type whose operations provide atomic access to an object and support synchronization between threads.
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Kotlin in Action, 2EA type is a classification that specifies the values an expression or variable can represent and the operations allowed on them.
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The Design of Web APIs, Second EditionA data type is a classification that specifies the kind of value a data element can contain and how it may be represented or processed.
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Learn PowerShell in a Month of Lunches: Fourth Edition, Covers Windows, Linux, and macOSA data type defines the kind of value represented and the operations applicable to that value.
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Code Like a Pro in RustA type is a compile-time classification that determines the values a program element can represent and the operations permitted on them.
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PostgreSQL Mistakes and How to Avoid ThemA data type defines the kind of value a database can store and the operations permitted on that value.
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Python Workout, Second EditionA type is a classification of Python objects that determines their values, behavior, and supported operations.
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100 Java Mistakes and How to Avoid ThemAn atomic variable is a Java concurrency object that supports indivisible access and updates to a stored value.
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Functional Design and Architecture: Examples in HaskellA data type is a type that defines a set of possible values together with the constructors used to build those values.
Compare how 17 books explain atomic type →
Related concepts
- classincludes · A class is a programming-language construct that defines a type’s structure or behavior and provides a basis for creating or representing objects.
- atomic_flagincludes · An atomic flag is a standard atomic type representing a flag and providing indivisible operations to set or clear it for synchronization.
- unit typeincludes · A unit type is a type with exactly one value, commonly written (), that represents the absence of meaningful information or a meaningful result.
- integerused by · An integer is a whole-number value with no fractional part, including negative numbers, zero, and positive numbers.
- primitive data typeincludes · A primitive data type is a fundamental, language-provided type for representing a basic value, rather than a composite of multiple values.
- race conditionaddresses · A race condition is a concurrency defect in which program behavior or results depend on the relative timing or ordering of interacting operations.
This explainer was generated by Manning's knowledge graph from the text of Fast Python: High performance techniques for large datasets. The section links point to the parts of the book it draws on.