Eight Fun Python Mini‑Projects Implemented in Ten Lines or Less

Python's concise syntax enables quick creation of useful mini‑projects; this article demonstrates eight examples that can be implemented with ten lines or fewer of code.

1. QR Code Generation

Install the qrcode library and generate a QR code with just two lines of code.

pip install qrcode

import qrcode

text = input('输入文字或URL：')
img = qrcode.make(text)
img.save('qr.png')
img.show()

2. Word Cloud Creation

Using wordcloud, jieba, and matplotlib, a word cloud can be produced from a text file in about ten lines.

pip install wordcloud
pip install jieba
pip install matplotlib
import matplotlib.pyplot as plt
from wordcloud import WordCloud
import jieba

text = open('/Users/hecom/23tips.txt').read()
words = ' '.join(jieba.cut(text, cut_all=True))
wc = WordCloud().generate(words)
plt.imshow(wc)
plt.axis('off')
plt.show()

3. Batch Image Segmentation (Background Removal)

Leverage PaddlePaddle and PaddleHub to remove backgrounds from a folder of images with only five lines of code.

python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
pip install -i https://mirror.baidu.com/pypi/simple paddlehub
import os, paddlehub as hub
humanseg = hub.Module(name='deeplabv3p_xception65_humanseg')
path = 'D:/CodeField/Workplace/PythonWorkplace/GrapImage/'
files = [path + i for i in os.listdir(path)]
results = humanseg.segmentation(data={'image': files})

4. Text Sentiment Recognition

Using PaddleHub's senta_lstm model, sentiment of a list of Chinese sentences is classified.

import paddlehub as hub
senta = hub.Module(name='senta_lstm')
sentence = ['你真美','你真丑','我好难过','我不开心','这个游戏好好玩','什么垃圾游戏']
results = senta.sentiment_classify(data={text:sentence})
for r in results:
    print(r)

5. Mask Detection in Images

Load the pyramidbox_lite_mobile_mask model from PaddleHub to detect whether faces wear masks.

import paddlehub as hub
module = hub.Module(name='pyramidbox_lite_mobile_mask')
image_list = ['face.jpg']
input_dict = {'image': image_list}
module.face_detection(data=input_dict)

6. Simple Information Bombing

Using pynput, automate mouse clicks and keyboard typing to repeatedly send a message.

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple/ pynput
from pynput import mouse, keyboard
import time
m_mouse = mouse.Controller()
m_keyboard = keyboard.Controller()
m_mouse.position = (850, 670)
m_mouse.click(mouse.Button.left)
while True:
    m_keyboard.type('你好')
    m_keyboard.press(keyboard.Key.enter)
    m_keyboard.release(keyboard.Key.enter)
    time.sleep(0.5)

7. OCR – Recognizing Text in Images

With pytesseract and Pillow, extract text from an image file.

import pytesseract
from PIL import Image
img = Image.open('text.jpg')
text = pytesseract.image_to_string(img)
print(text)

8. Simple Number‑Guessing Game

A classic 1‑100 guessing game written in about ten lines.

import random
print('1-100数字猜谜游戏！')
num = random.randint(1,100)
guess = None
while guess != num:
    guess = int(input('请输入你猜的数字：'))
    if guess == num:
        print('恭喜，你猜对了！')
    elif guess < num:
        print('你猜的数小了...')
    else:
        print('你猜的数大了...')
print('游戏结束')

Each snippet demonstrates how Python can accomplish diverse tasks—ranging from data visualization and computer vision to natural‑language processing—using minimal code, highlighting its suitability for rapid prototyping in AI applications.