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@given(st.lists(st.; min_size=;))

@given(st.lists(st.; min_size=;))

first slot: element generation strategy (e.g., st.integers(), st.text(), st.floats()); second slot: minimum list size (non-negative integer)

• @example for concrete test cases
• Settings to adjust test generation
• assume to filter inputs

• st.sets()
• st.tuples()
• or specifying max_size
• using st.lists(st.integers()) without min_size defaults to 0

Forgetting to import st from hypothesis.strategies; using a non-integer for min_size; using mutable default strategies causing state leakage

@given(st.text()) for generating strings; @given(st.lists(st.integers(), min_size=1)) to forbid empty lists

Coming from unittest: may expect explicit test loops; property-based testing replaces manual iteration with automatic generation

• @given(st.text())
• @given(st.integers())
• @given(st.floats())
• @given(st.tuples(...))

The strategy can be combined with st.one_of() or st.tuples(); large min_size may cause excessive generation time; Hypothesis may shrink failing examples

Automates test data generation, increasing coverage and reducing boilerplate

Think 'given' as 'given some random data'

The min_size parameter must be a non-negative integer; if max_size is set and less than min_size, Hypothesis will raise an InvalidArgument error during test execution.

Add concrete examples with @example alongside @given, or use st.data() to draw more complex strategies during test execution