PHP and Python are two widely used programming languages. While both support multiple development scenarios, they differ significantly in syntax style, usability, and application focus.
Feature | PHP | Python |
---|---|---|
Syntax Style | Similar to C, structured | Close to natural language, concise and intuitive |
Type System | Dynamically and loosely typed | Dynamically and strongly typed |
Execution Mode | Interpreted | Interpreted |
Community Support | Extensive and stable | Active and diverse |
Each language has its unique strengths and commonly targeted domains.
The following examples illustrate how each language is used in practical projects.
<?php // Connect to database $conn = new mysqli("localhost", "root", "", "database_name"); // INSERT operation $stmt = $conn->prepare("INSERT INTO table_name (name, age) VALUES (?, ?)"); $stmt->bind_param("ss", $name, $age); $stmt->execute(); // SELECT operation $stmt = $conn->prepare("SELECT * FROM table_name"); $stmt->execute(); $result = $stmt->get_result(); while ($row = $result->fetch_assoc()) { echo $row['name'] . " is " . $row['age'] . " years old.<br>"; } // UPDATE operation $stmt = $conn->prepare("UPDATE table_name SET age = ? WHERE name = ?"); $stmt->bind_param("is", $age, $name); $stmt->execute(); // DELETE operation $stmt = $conn->prepare("DELETE FROM table_name WHERE name = ?"); $stmt->bind_param("s", $name); $stmt->execute(); ?>
import pandas as pd import matplotlib.pyplot as plt # Read data data = pd.read_csv("data.csv") # Text preprocessing data['text'] = data['text'].str.lower() data['text'] = data['text'].str.replace('[^\w\s]', '') # Generate word frequency distribution freq_dist = data['text'].str.split().apply(lambda x: pd.Series(x).value_counts()) # Visualize results plt.figure(figsize=(20,10)) freq_dist.sum().sort_values(ascending=False).head(20).plot.bar() plt.title("Most Frequent Words in the Text") plt.xlabel("Word") plt.ylabel("Frequency") plt.show()
Both PHP and Python offer unique advantages: PHP excels in building dynamic websites and is ideal for rapidly deployed web projects, while Python dominates in data analysis, scientific computing, and AI thanks to its strong ecosystem. Choosing the right language based on your project requirements can significantly enhance development efficiency and success.