Dynamic type checking verifies at runtime that a value supports the operation a program is about to perform. Unlike static type checking, which examines code before execution, dynamic checking can reveal a type error only when execution reaches the relevant operation. Languages and programs can combine both approaches.
What dynamic type checking means
The Python typing documentation defines a dynamically typed language as one that “does not run a type checker before running a program” and instead checks values before operations at runtime. In practice, the program examines the value involved in an operation—such as attribute access or arithmetic—and follows the language’s runtime rules. Python typing documentation
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Dynamic checking does not mean that values have no types. Python values have types; the distinction is that Python does not require a separate static type check before the program runs. For example, whether a value supports an attribute access or arithmetic operation can be determined when that operation is executed.
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| Approach | When checking occurs | What that means for errors |
|---|---|---|
| Static | Before execution | A checker can identify some type-rule violations before the program runs. |
| Dynamic | During execution | A type-related failure may appear when the program reaches the invalid operation. |
| Hybrid or gradual | Some checks before execution and others at runtime | Static analysis and runtime checks can cover different parts of a program or different kinds of uncertainty. |
Static checking can provide earlier feedback, but it does not guarantee that every defect will be found. Dynamic checking can allow code to proceed until a particular operation is reached; if the value does not support that operation, the failure becomes visible then. Rascal’s type-checker documentation describes hybrid checking as performing checks before execution where possible and leaving other checks to execution. Rascal documentation
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Examples in Python and C#
Python: runtime rules with optional static analysis
Python is dynamically typed: normal program execution checks values as operations occur. Python also supports type annotations that external static type checkers can use. This is gradual typing: selected code can receive static analysis while ordinary runtime checks remain in place. For example, a checker may analyze a dictionary’s key type statically while its value type is still subject to runtime checking. The annotation Any signals that a type is not known statically to a checker; it does not remove Python’s runtime rules. Python typing documentation
C#: a dynamic feature in a statically typed language
C# uses the keyword dynamic for expressions whose operations bypass static type checking and are resolved at runtime. Microsoft describes dynamic as a static type, while noting that an object of that type bypasses static checking. This feature does not make C# as a whole a dynamically typed language; it makes runtime resolution available for particular expressions. Microsoft Learn: Using type dynamic
Other language examples
Oracle’s Java documentation identifies JavaScript and Ruby as dynamically typed languages, defining dynamic typing by the fact that type checking occurs at runtime. Oracle documentation
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Why languages use dynamic checking
Runtime checking lets a program evaluate operations against values available during execution, which can be useful when an operation’s validity depends on runtime data. The trade-off is timing: a type-related problem might not become apparent until the execution path reaches the operation. Static rules can catch some violations earlier, while hybrid and gradual approaches distribute checks across pre-execution analysis and runtime. These approaches differ in where and when checks happen; the distinction alone does not establish that one is universally safer or better.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Dynamic type checking in one sentence
Dynamic type checking is runtime verification that a value is compatible with an operation, with any resulting type error becoming visible when execution reaches that operation.
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