What Can You Do With Python Scripting?


Larry Thompson

Python scripting is a powerful tool that can be used for a wide range of tasks. Whether you are a beginner or an experienced programmer, Python scripting can open up a world of possibilities. In this article, we will explore the various things you can do with Python scripting.

Automate Repetitive Tasks

One of the most common uses of Python scripting is to automate repetitive tasks. Whether it’s renaming files, processing large amounts of data, or performing system operations, Python can help you save time and effort. With its simple syntax and extensive library support, Python makes it easy to write scripts that automate these tasks.


import os

for file_name in os.listdir():

   if file_name.endswith(“.txt”):

     new_file_name = “new_” + file_name

     os.rename(file_name, new_file_name)

This script renames all text files in the current directory by adding a prefix “new_” to their names.

Data Analysis and Visualization

Python provides powerful libraries like NumPy, Pandas, and Matplotlib that make it an excellent choice for data analysis and visualization. With these libraries, you can manipulate and analyze data easily. You can perform operations like filtering data, computing statistics, creating plots and charts, and much more.

import pandas as pd

data = pd.read_csv(“data.csv”)

filtered_data = data[data[“age”] > 18]

filtered_data.plot(x=”name”, y=”age”, kind=”bar”)

This script reads data from a CSV file, filters out records where age is less than or equal to 18, and then plots a bar chart of the remaining records.

Web Development

Python offers several frameworks like Django and Flask that make web development a breeze. These frameworks provide tools and libraries to handle different aspects of web development, such as routing, database management, form handling, and authentication. With Python scripting, you can build dynamic websites, web applications, and RESTful APIs.

from flask import Flask, render_template

app = Flask(__name__)


def hello(name):

   return render_template(“hello.html”, name=name)

This script creates a simple Flask web application that takes a name as input in the URL and renders an HTML template with the provided name.

Machine Learning and Artificial Intelligence

Python has become the go-to language for machine learning and artificial intelligence. With libraries like TensorFlow, PyTorch, and Scikit-learn, you can build complex models for tasks like image recognition, natural language processing, and predictive analytics. Python scripting allows you to preprocess data, train models, evaluate performance, and deploy them into production.

import tensorflow as tf

(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()

x_train = x_train / 255.0

model = tf.Sequential([

   tf.layers.Flatten(input_shape=(28, 28)),

   tf.Dense(128, activation=”relu”),

   tf.Dense(10, activation=”softmax”)


This script loads the MNIST dataset, preprocesses the data by scaling it between 0 and 1, and then defines a simple neural network model using TensorFlow.


In this article, we have explored just a few of the many things you can do with Python scripting. Whether you want to automate tasks, analyze data, build web applications, or delve into machine learning and artificial intelligence, Python scripting provides a versatile and powerful toolset. So go ahead and start exploring the endless possibilities of Python scripting!

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