## Understanding the Concepts
### Strategy Pattern
The Strategy Pattern is a behavioral design pattern that encapsulates algorithms into separate classes with a common interface, enabling interchangeability within the original context object. This approach enhances flexibility by allowing the switching of algorithms or logic at runtime.
### Dependency Injection
Dependency Injection is a technique that promotes Inversion of Control (IoC) - an object obtains its dependencies from an external source rather than creating them itself. DI is instrumental in developing code that is more manageable, modular, and testable.
## Bridging Strategy Pattern with Dependency Injection
When combined, these two concepts can provide exceptional benefits. `Dependency Injection` can be used to inject different Strategy objects into a class, thus promoting flexible behavior that varies with the injected strategy.
## A Practical Example
Let's consider a simple example: a `TextFormatter` class that formats a given text in different ways, such as lower case, upper case, or capitalized. We'll use a Python-esque pseudo-code for our demonstration.
Firstly, we define the strategy interface and the concrete strategies.
```python
class TextFormatStrategy:
def format_text(self, text):
pass
class LowerCaseStrategy(TextFormatStrategy):
def format_text(self, text):
return text.lower()
class UpperCaseStrategy(TextFormatStrategy):
def format_text(self, text):
return text.upper()
class CapitalizeStrategy(TextFormatStrategy):
def format_text(self, text):
return text.capitalize()
```
Next, we define the `TextFormatter` class which will use `Dependency Injection` to accept a `TextFormatStrategy` object.
```python
class TextFormatter:
def __init__(self, strategy: TextFormatStrategy):
self._strategy = strategy
def format(self, text):
return self._strategy.format_text(text)
```
Now we can change the behavior of the `TextFormatter` class at runtime by injecting different strategies.
```python
formatter = TextFormatter(LowerCaseStrategy())
print(formatter.format("Hello World")) # Output: "hello world"
formatter = TextFormatter(UpperCaseStrategy())
print(formatter.format("Hello World")) # Output: "HELLO WORLD"
formatter = TextFormatter(CapitalizeStrategy())
print(formatter.format("hello world")) # Output: "Hello world"
```
This example demonstrates how **Dependency Injection** can inject different **strategies** into a class, resulting in dynamic behavior changes based on the provided strategy.
Cheers! 🍺
Understanding the Concepts
Strategy Pattern
The Strategy Pattern is a behavioral design pattern that encapsulates algorithms into separate classes with a common interface, enabling interchangeability within the original context object. This approach enhances flexibility by allowing the switching of algorithms or logic at runtime.
Dependency Injection
Dependency Injection is a technique that promotes Inversion of Control (IoC) - an object obtains its dependencies from an external source rather than creating them itself. DI is instrumental in developing code that is more manageable, modular, and testable.
Bridging Strategy Pattern with Dependency Injection
When combined, these two concepts can provide exceptional benefits. Dependency Injection can be used to inject different Strategy objects into a class, thus promoting flexible behavior that varies with the injected strategy.
A Practical Example
Let’s consider a simple example: a TextFormatter class that formats a given text in different ways, such as lower case, upper case, or capitalized. We’ll use a Python-esque pseudo-code for our demonstration.
Firstly, we define the strategy interface and the concrete strategies.
This example demonstrates how Dependency Injection can inject different strategies into a class, resulting in dynamic behavior changes based on the provided strategy.