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https://github.com/vgilabert94/execution-timer

Provides a decorator to easily measure and optionally save the execution times.
https://github.com/vgilabert94/execution-timer

decorators-python execution-time measure-time python timer

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Provides a decorator to easily measure and optionally save the execution times.

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# ExecutionTimer



ExecutionTimer is a utility class for measuring execution times of functions or methods in Python. It provides a **decorator** to easily measure and optionally save the execution times.



## Installation



- Install via pip:



```bash

pip install timer-decorator

```



- Install via git clone:

```bash

git clone https://github.com/vgilabert94/execution-timer

```



## Documentation



### Function: `time_execution`



#### Parameters

- `return_measure` (bool, optional): Whether to return the measured time along with the function result (default is False).

- `nanoseconds` (bool, optional): Whether to use nanoseconds resolution for timing measurements (default is False).

- `n_iter` (int, optional): The number of iterations to execute the function/method (default is 1). If n_iter > 1 and return_measure=True: result of the function will be the last execution.

- `return_average` (bool, optional): Whether to return the average time when measuring over multiple iterations (default is True). Only is used when n_iter > 1.



#### Notes

- If `return_measure`=False and `return_average`=False: a message will be printed for each iteration.

- If `n_iter` > 1 and `return_measure`=True: the result will be the last function result.

- If `n_iter` > 1 and `return_measure`=True and `return_average`=False: the result will be the last function result with a list of times for each iteration.



### Class: `ExecutionTimer`



#### Parameters



- `save_measure` (bool, optional): Flag to determine if measurement results should be saved (default is True).

- `nanoseconds` (bool, optional): Flag to use nanoseconds resolution for timing measurements (default is False).

- `n_iter` : (int, optional): Number of iterations to execute the function/method (default is 1).



#### Notes

- If `n_iter` > 1 and `return_measure`=True: the result will be the last function result.

- If `n_iter` > 1 and `return_measure`=False: the time printed will be the last execution result.



#### Methods



#### `time_execution`



Decorator method to measure the execution time of a function or method.



- `func` (callable, optional): Function or method to be timed. If None, returns a decorator function.

- `return_measure` (bool, optional): Flag to indicate if the measured time should be returned along with the function result.

- `print_measure` (bool, optional): Flag to indicate if the measured time should be printed.



Returns:

- `wrapper` (callable): Decorated function that measures the execution time of `func`.



#### `get_measured_time`



Retrieve the recorded execution times.



Returns:

- `dict`: Dictionary containing the measured execution times. Keys are function or method names, and values are lists of measured times.



#### `reset_measured_time`

Reset the recorded execution times.



#### `average_measured_time`

Calculate the average execution times for all recorded functions or methods.



Returns:

- `dict`: A dictionary where keys are function or class names, and values are the average execution times in seconds. If no times are recorded, the value will be None.



## Examples



You can access a comprehensive examples notebook at the following link: [examples/notebook.ipynb](examples/notebook.ipynb)



Load packages: 

```python

import time

from execution_timer import ExecutionTimer, time_execution

```



### Example 1: Measuring a function with the default settings.



```python

timer = ExecutionTimer()



@timer.time_execution

def sample_function(n):

    time.sleep(n)



print(sample_function(n=1))

print(timer.get_measured_time())

```

Output

```bash

None

{'sample_function': [1.0000783540003795]}

```



```python

@time_execution

def sample_function(n):

    time.sleep(n)



print(sample_function(n=1))

```

Output

```bash

The 'sample_function' function was executed in 1.00085 seconds.

None

```



### Example 2: Measuring N iterations



```python

timer = ExecutionTimer(n_iter=5)



@timer.time_execution

def sample_function(n):

    time.sleep(n)



print(sample_function(n=1))

print(timer.get_measured_time())

print(timer.average_measured_time())

```

Output

```bash

The 'sample_function' function was executed in 1.00098 seconds.

None

{'sample_function': [1.0010039510007118, 1.001013477000015, 1.001078371999938, 1.0008607439995103, 1.0009819289998632]}

{'sample_function': 1.0009876946000076}

```



```python

@time_execution(n_iter=5)

def sample_function(n):

    time.sleep(n)



print(sample_function(n=1))

```

Output

```bash

The 'sample_function' function was executed in 1.00030 seconds.

None

```



### Example 8: Measuring a Method from a class



```python

timer = ExecutionTimer()



class SampleClass:

    def __init__(self):

        pass



    @timer.time_execution(return_measure=True)

    def sample_method(self, n):

        time.sleep(n)



    @timer.time_execution

    def sample_method_x2(self, n):

        time.sleep(2*n)



sample = SampleClass()

print(sample.sample_method(n=1))

print(sample.sample_method_x2(n=1))

print(timer.get_measured_time())

```

Output

```bash

(None, 1.0002362490004089)

The 'sample_method_x2' function was executed in 2.00203 seconds.

None

{'SampleClass': {'sample_method': [1.0002362490004089], 'sample_method_x2': [2.0020319710001786]}}

```



## LICENSE 



Distributed under the MIT License. See LICENSE.txt for more information.



## Contact



[Vicent Gilabert](mailto:[email protected])



[Linkedin](https://www.linkedin.com/in/vgilabert/)