The decorator "cache" is created, tested and ready to work #745
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Bohdan-Salamakha
suggested changes
Sep 30, 2023
app/main.py
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| if func_key in cached_data[func.__name__]: | ||
| print("Getting from cache") | ||
| return cached_data[func.__name__][func_key] | ||
| else: |
app/main.py
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| func_result = func(*args) | ||
| cached_data[func.__name__][func_key] = func_result | ||
| return func_result | ||
| else: |
app/main.py
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| """ | ||
| Decorator for caching results of functions with immutable arguments. | ||
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| The `cache` function is designed to automatically cache results of | ||
| functions with immutable (unchangeable) arguments. Each function | ||
| decorated with this decorator gets its own cache to store results. | ||
| In this decorator, the cache is reset with each new test suite. | ||
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| Args: | ||
| func (Callable): The function to be decorated. | ||
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| Returns: | ||
| Callable: The modified function that caches results based on | ||
| arguments. | ||
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| Examples: | ||
| @cache | ||
| def long_time_func(a: int, b: int, c: int) -> int: | ||
| return (a ** b ** c) % (a * c) | ||
| result = long_time_func(2, 3, 4) # Computation is performed | ||
| # and result is cached | ||
| result = long_time_func(2, 3, 4) # Result is retrieved from | ||
| # cache, computation is not | ||
| # repeated | ||
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| Note: | ||
| This decorator supports caching results for functions with | ||
| arguments that are immutable types, such as int, float, str, | ||
| tuple, bool, and NoneType. The results are stored in memory | ||
| and used for subsequent calls to the function with the same | ||
| arguments. | ||
| """ |
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docstring is super redundant here
remove it
pavlejviki
suggested changes
Sep 30, 2023
app/main.py
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| immutable_type = (int, float, str, tuple, bool, type(None)) | ||
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| def argument_based_cacher(*args) -> Any: | ||
| nonlocal cached_data |
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you're modifying the dictionary that cached_data points to (by adding keys and values). Since you're not re-assigning the variable, you don't need nonlocal.
app/main.py
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| def argument_based_cacher(*args) -> Any: | ||
| nonlocal cached_data | ||
| if all([isinstance(variable, immutable_type) for variable in args]): | ||
| func_key = tuple(args) |
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args is already a tuple, and there's no need to convert it again using tuple(args).
| func_result = func(*args) | ||
| cached_data[func.__name__][func_key] = func_result | ||
| return func_result | ||
| print("Calculating new result") |
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Decorator cache is supposed to decorate only functions that take immutable arguments.
Dimosphen1
approved these changes
Oct 2, 2023
| pass | ||
| cached_data = {} | ||
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| def argument_based_cacher(*args) -> Any: |
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You could use decorator from functools to preserve the wrapped function naming and docstring.
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Decorator for caching results of functions with immutable arguments.
The
cachefunction is designed to automatically cache the results of functions with immutable (unchangeable) arguments.Each function decorated with this decorator gets its own cache to store results.
In this decorator, the cache is reset with each new test suite.
Args:
func (Callable): The function to be decorated.
Returns:
Callable: The modified function that caches results based on arguments.
Examples:
@cache
def long_time_func(a: int, b: int, c: int) -> int:
return (a ** b ** c) % (a * c)
result = long_time_func(2, 3, 4) # Computation is performed and result is cached
result = long_time_func(2, 3, 4) # Result is retrieved from cache, computation is not repeated
Note:
This decorator supports caching results for functions with arguments that are immutable types,
such as int, float, str, tuple, bool, and NoneType. The results are stored in memory
and used for subsequent calls to the function with the same arguments.