The `pydantic` library is used for data validation and settings management using Python type annotations.
Example:
from pydantic import BaseModel
class User(BaseModel):
name: str
age: int
user = User(name='John', age=30)
print(user)
The `pydantic` library is used for data validation and settings management using Python type annotations.
Example:
from pydantic import BaseModel
class User(BaseModel):
name: str
age: int
user = User(name='John', age=30)
print(user)
The `itertools` module provides efficient looping constructs. It includes tools for creating iterators for efficient looping.
Example:
import itertools
for item in itertools.count(start=10, step=2):
if item > 20:
break
print(item)
Writing thread-safe code involves using synchronization mechanisms like locks and ensuring data consistency.
Example:
import threading
lock = threading.Lock()
def thread_safe_function():
with lock:
# critical section
pass
`async` and `await` enable asynchronous programming in Python. They help manage tasks that can run concurrently.
Example:
import asyncio
async def fetch_data():
await asyncio.sleep(1)
return 'data'
async def main():
data = await fetch_data()
print(data)
asyncio.run(main())
Data classes simplify the creation of classes used primarily to store values. They automatically generate special methods like `__init__` and `__repr__`.
Example:
from dataclasses import dataclass
@dataclass
class Person:
name: str
age: int
p = Person(name='John', age=30)
print(p)
Optimizing Python code can significantly improve performance. Techniques include using efficient data structures, minimizing I/O operations, and leveraging libraries like NumPy.
Example optimization:
import time
start_time = time.time()
result = [i**2 for i in range(10000)]
print('Time taken:', time.time() - start_time)
The Optional class in Java helps handle null values safely without null checks.
Optional allows avoiding NullPointerExceptions by providing a cleaner way to deal with nulls.
Optional name = Optional.ofNullable(null);
name.ifPresentOrElse(
System.out::println,
() -> System.out.println("Name is not present")
);
This example shows how to use Optional for safer null handling in Java.
Garbage Collection in Java automatically reclaims memory, but performance can be optimized.
To optimize garbage collection, you can tweak JVM parameters like heap size and GC algorithms.
java -Xms1024m -Xmx2048m -XX:+UseG1GC MyApp
This example shows how to use JVM parameters to optimize garbage collection.
The `new` keyword creates new objects, while constructor chaining calls other constructors.
In constructor chaining, one constructor calls another to reuse code.
class Person {
String name;
Person() {
this("Unknown");
}
Person(String name) {
this.name = name;
}
}
This example shows how constructor chaining can initialize different constructors in a class.
Java’s module system allows developers to group related packages into modules.
With modules, you can control which parts of your code are accessible from outside.
module com.example.myapp {
requires java.base;
exports com.example.myapp.core;
}
This example shows how to define a module and export packages.