Answer :
please make me a brainlist answer
Answer:
Sure, here are some interesting Python code examples that demonstrate various capabilities of the language:
### 1. Web Scraping with BeautifulSoup
```python
import requests
from bs4 import BeautifulSoup
url = 'https://example.com'
response = requests.get(url)
soup = BeautifulSoup(response.content, 'html.parser')
for link in soup.find_all('a'):
print(link.get('href'))
```
### 2. Basic Data Analysis with Pandas
```python
import pandas as pd
data = {'Name': ['John', 'Anna', 'Peter', 'Linda'],
'Age': [28, 24, 35, 32],
'City': ['New York', 'Paris', 'Berlin', 'London']}
df = pd.DataFrame(data)
print(df.describe())
```
### 3. Creating a Simple REST API with Flask
```python
from flask import Flask, jsonify, request
app = Flask(__name__)
data = [{'id': 1, 'name': 'John'}, {'id': 2, 'name': 'Anna'}]
@app.route('/api/data', methods=['GET'])
def get_data():
return jsonify(data)
@app.route('/api/data', methods=['POST'])
def add_data():
new_data = request.json
data.append(new_data)
return jsonify(new_data), 201
if __name__ == '__main__':
app.run(debug=True)
```
### 4. Data Visualization with Matplotlib
```python
import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5]
y = [2, 3, 5, 7, 11]
plt.plot(x, y, marker='o')
plt.title('Simple Line Plot')
plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.show()
```
### 5. Machine Learning with Scikit-Learn
```python
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
# Load dataset
iris = load_iris()
X, y = iris.data, iris.target
# Split the dataset
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
# Train the model
clf = RandomForestClassifier(n_estimators=100)
clf.fit(X_train, y_train)
# Predict and evaluate
y_pred = clf.predict(X_test)
print(f'Accuracy: {accuracy_score(y_test, y_pred):.2f}')
```
### 6. Asynchronous Programming with Asyncio
```python
import asyncio
async def say_hello(delay, message):
await asyncio.sleep(delay)
print(message)
async def main():
task1 = asyncio.create_task(say_hello(1, 'Hello'))
task2 = asyncio.create_task(say_hello(2, 'World'))
await task1
await task2
asyncio.run(main())
```
### 7. Reading and Writing Files
```python
# Writing to a file
with open('example.txt', 'w') as file:
file.write('Hello, world!')
# Reading from a file
with open('example.txt', 'r') as file:
content = file.read()
print(content)
```
These examples cover a range of applications from web scraping, data analysis, creating REST APIs, data visualization, machine learning, asynchronous programming, to file handling. Each example demonstrates a different facet of Python's versatility and utility.