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decoratorutilities-1.0.2
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مشاهده بیشترتوضیحات
Python library to user type guard utilities to check parameters and return type, allow function overloading and function mocking at runtime
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | decoratorutilities-1.0.2 |
| نام | decoratorutilities |
| نسخه کتابخانه | 1.0.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Scalamandrè Simone, Giovanni Cardamone |
| ایمیل نویسنده | simone.scalamandre@sourcesense.com, giovanni.cardamone@sourcesense.com |
| آدرس صفحه اصلی | https://github.com/Symone95/decoratorutilities |
| آدرس اینترنتی | https://pypi.org/project/decoratorutilities/ |
| مجوز | - |
# DecoratorUtilities
### Readthedocs Reference
Please read our documentation here: [Readthedocs Reference](https://decoratorutilities.readthedocs.io/en/dev/)
### Package Reference
Our package reference link is: https://pypi.org/project/decoratorutilities
## Menu
- [Intro](#intro)
- [Installation](#installation)
- [Decorators](#decorators)
- [Check Type Decorator](#check_type_decorator)
- [Overloading Decorator](#overloading_decorator)
- [Mocking Decorator](#mocking-decorator)
- [Memoized Decorator](#memoized-decorator)
- [Timeit Decorator](#timeit-decorator)
- [Singleton Decorator](#singleton-decorator)
## Intro
DecoratorUtilities is a python library that provides different utilities for functions and class methods such as
to check parameters and return type, allow overloading, to cache results to speed up them, instantiate a Singleton object
and mocking at runtime
## Installation
```bash
pip install decoratorutilities
```
## Decorators
### Check Type Decorator
Decorate your own functions with **@checktype** decorator to check parameters type and return type too
**Example:**
```python
from decoratorutilities import checktype
import pytest
@checktype
def my_functon(a: int, b: int) -> int:
return 1
# Valid usage: Integer parameters and return type
my_functon(5, 6) # return 1
assert my_functon(5, 6) == 1 # True
# Invalid usage: String parameters and return type
with pytest.raises(TypeError):
my_functon("5", "6") # Raises TypeError Exception
with pytest.raises(TypeError):
my_functon("invalid", b="Invalid") # Raises TypeError Exception
with pytest.raises(TypeError):
my_functon(a="invalid", b="Invalid") # Raises TypeError Exception
with pytest.raises(TypeError):
assert my_functon(5, 6) == "1" # Raises TypeError Exception
```
Decorate your own class methods with **@checktype** decorator to check parameters type and return type too
**Example:**
```python
from decoratorutilities import checktype
import pytest
class X(object):
@checktype # checktype decorator for classes methods
def my_function(self, value: int):
return value
# Valid usage: Integer parameters and return type
assert X().my_function(1) == 1 # True
# Invalid usage: String parameters and return type
with pytest.raises(TypeError):
X().my_function('1') # Raises TypeError Exception
with pytest.raises(TypeError):
X().my_function(1) == "1" # Raises TypeError Exception
```
### Overloading Decorator
Decorate your own function with **@overload** decorator to define multiple functions with same name but with different parameters
**Example:**
```python
from decoratorutilities import overload
@overload
def my_functon(a:int):
return 1
@overload
def my_functon(a:str):
return 2
# Invoke first my_functon and return 1
my_functon(1)
# Invoke second my_functon and return 2
my_functon('1')
```
Decorate your own class method with **@overload** decorator to define multiple class methods with same name but with different parameters
**Example:**
```python
from decoratorutilities import overload
class X(object):
@overload
def x(self, x: int):
return int
@overload
def x(self, x: str):
return str
assert X().x(1) == int # True
assert X().x('1') == str # True
```
### Mocking Decorator
Decorate your own function with **@mocking** decorator to mock that function adding args in a tuple, kwargs in a dict and return value
**Example:**
```python
from decoratorutilities import mocking
# Define args tuple, kwargs dict and return value
@mocking([
((1, 2, 3), {"a": 1}, 1),
((4, 5, 6), {"b": 2}, 2)
])
def a():
pass
# Valid usage
assert a(1, 2, 3, a=1) == 1 # return 1
assert a(4, 5, 6, b=2) == 2 # return 2
# Invalid usage
assert a(7, 8, 9, c=1) == 1 # Raises KeyError Exception
```
### Memoized Decorator
Decorate your own function or class method with **@memoized** decorator to speed up it by storing the results and returning the cached result when the same inputs occur again
**Example:**
```python
from decoratorutilities import memoized
import datetime
def util_run_function_with_time(fn, args, kwargs):
start_time = datetime.datetime.now()
tmp = fn(*args, **kwargs)
end_time = datetime.datetime.now()
return (end_time - start_time), tmp
@memoized
def memoized_fibonacci(x):
if x == 0:
return 0
if x == 1:
return 1
return memoized_fibonacci(x - 1) + memoized_fibonacci(x - 2)
def fibonacci(x):
if x == 0:
return 0
if x == 1:
return 1
return fibonacci(x - 1) + fibonacci(x - 2)
fib_value = 20
memoized_execution_time, memoized_value = util_run_function_with_time(memoized_fibonacci, (fib_value, ), {}) # Return execution time and value for memoized function
unmemoized_execution_time, unmemoized_value = util_run_function_with_time(fibonacci, (fib_value, ), {}) # Return execution time and value for unmemoized function
print(f"memoized_execution_time: {memoized_execution_time} - unmemoized_execution_time: {unmemoized_execution_time}")
assert memoized_execution_time < unmemoized_execution_time # OK
assert memoized_value == unmemoized_value # OK
```
### Timeit Decorator
Decorate your own function with **@timeit** decorator to monitoring execution time
**Example:**
```python
from decoratorutilities import timeit
import time
@timeit
def hello():
time.sleep(0.1)
if __name__ == "__main__":
hello() # print "Execution time: 100.75 ms"
```
### Debug Decorator
Decorate your own function with **@debug** decorator to print in console more Exception details
**Example:**
```python
from decoratorutilities import debug
import pytest
@debug
def a():
message = "Hello " + 5
return message
with pytest.raises(TypeError):
a() # Print in console: Found "<class 'TypeError'>" Exception in file "('../tests', 'test_debug.py')" on line "9"
# Error message: "can only concatenate str (not "int") to str"
```
Decorate your own class methods with **@debug** decorator to print in console more Exception details
**Example:**
```python
from decoratorutilities import debug
import pytest
class A(object):
@debug
def __init__(self):
self.message = "Hello " + 5
with pytest.raises(TypeError):
A() # Raises TypeError Exception
```
### Singleton Decorator
Decorate your own classes with **@singleton()** decorator to ensure that only one instance of the singleton class ever exists.
Never invoke **@singleton()** decorator without brackets otherwise it will cause problems
Define your class method `__init__()` without parameters, pass them to the **@singleton()** decorator
**Example with args and kwargs**
```python
import pytest
from decoratorutilities import singleton
@singleton(10, message="Message to send", email=["simone.scalamandre95@gmail.com"])
class A(object):
def __init__(self):
self.x = 50 # Define constant class attribute
def print_hello(self): # Custom method
return "Hello World"
# Valid usage
assert A[0] == 10 # True -> Get first arg
assert A.x == 50 # True -> Get decorated class attribute
assert A.print_hello() == "Hello World" # True -> Get decorated class method "print_hello()"
assert A.message == "Message to send" # True -> Get kwarg "message" passed to Singleton decorator
assert A.email == ["simone.scalamandre95@gmail.com"] # True
with pytest.raises(TypeError):
# Invalid usage, brackets are missing
@singleton
class B(object):
def __init__(self):
self.x = 10
B() # Raises TypeError Exception
```
We can define our singleton class with or without args and kwargs parameters but we can only instantiate one
**Example**
```python
import pytest
from decoratorutilities import singleton
@singleton()
class A(object):
def __init__(self):
pass
@singleton(x=10)
class B(object):
def __init__(self):
pass
with pytest.raises(TypeError) as e:
A() # Raises TypeError Exception
with pytest.raises(TypeError):
B() # Raises TypeError Exception
```
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl decoratorutilities-1.0.2:
pip install decoratorutilities-1.0.2.whl
نصب پکیج tar.gz decoratorutilities-1.0.2:
pip install decoratorutilities-1.0.2.tar.gz