Advanced Python programming

 Here's a tutorial on advanced topics in Python:

*Regular Expressions*

1. Introduction

2. Pattern Syntax

3. Matching Functions

4. Groups and Capturing

5. Escaping and Special Characters

Example:

```

import re

text = "Hello, my email is john.doe@example.com"

pattern = r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b"

match = re.search(pattern, text)

if match:

    print("Email found:", match.group())

```

*Web Development with Flask*

1. Introduction to Flask

2. Routing and Views

3. Templates and Static Files

4. Request and Response Objects

5. Database Integration (SQLAlchemy)

Example:

```

from flask import Flask, render_template

from flask_sqlalchemy import SQLAlchemy

app = Flask(__name__)

app.config["SQLALCHEMY_DATABASE_URI"] = "sqlite:///database.db"

db = SQLAlchemy(app)

class User(db.Model):

    id = db.Column(db.Integer, primary_key=True)

    name = db.Column(db.String(100), nullable=False)

@app.route("/")

def index():

    users = User.query.all()

    return render_template("index.html", users=users)

if __name__ == "__main__":

    app.run(debug=True)

```

*Data Analysis with Pandas*

1. Introduction to Pandas

2. DataFrames and Series

3. Data Manipulation (filtering, sorting, grouping)

4. Data Visualization (Matplotlib, Seaborn)

5. Data Cleaning and Preprocessing

Example:

```

import pandas as pd

import matplotlib.pyplot as plt

data = {"Name": ["John", "Mary", "David"], 

        "Age": [25, 31, 42]}

df = pd.DataFrame(data)

df.plot(kind="bar", x="Name", y="Age")

plt.show()

```

*Machine Learning with Scikit-learn*

1. Introduction to Scikit-learn

2. Supervised Learning (Linear Regression, Logistic Regression)

3. Unsupervised Learning (K-Means Clustering)

4. Model Evaluation and Selection

5. Hyperparameter Tuning

Example:

```

from sklearn.datasets import load_iris

from sklearn.model_selection import train_test_split

from sklearn.linear_model import LogisticRegression

iris = load_iris()

X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.2)

logreg = LogisticRegression()

logreg.fit(X_train, y_train)

accuracy = logreg.score(X_test, y_test)

print("Accuracy:", accuracy)

```

*Advanced Topics*

1. Decorators

2. Generators and Iterators

3. Context Managers

4. Asyncio and Concurrent Programming

5. Type Hints and Static Analysis

Example:

```

def timer(func):

    def wrapper(*args, **kwargs):

        start_time = time.time()

        result = func(*args, **kwargs)

        end_time = time.time()

        print(f"Time elapsed: {end_time - start_time} seconds")

        return result

    return wrapper

@timer

def example_function():

    time.sleep(2)

    print("Function executed")

example_function()

```

*Best Practices and Tools*

1. Code Organization and Structure

2. Testing and Debugging

3. Version Control (Git)

4. Continuous Integration and Deployment

5. Code Review and Pair Programming

Resources:

1. Official Python Documentation

2. Python Cookbook by David Beazley and Brian Kernighan

3. Automate the Boring Stuff with Python by Al Sweigart

4. Python Crash Course by Eric Matthes

5. Real Python

Do you have any specific questions about these advanced topics?