7 Fun Python Projects: Web Scraping, Chatbots, Poetry Classification and More

There is a well‑known saying about Python: "Don't reinvent the wheel." The article points out three common problems: not knowing existing libraries, duplicating effort on tasks already solved by mature tools, and collecting data without a clear purpose.

Seven Python Projects

1. Scrape Zhihu Images (≈30 lines)

from selenium import webdriver
import time
import urllib.request
import re

driver = webdriver.Chrome()
driver.maximize_window()
driver.get("https://www.zhihu.com/question/29134042")
i = 0
while i < 10:
    driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
    time.sleep(2)
    try:
        driver.find_element_by_css_selector('button.QuestionMainAction').click()
        print("page" + str(i))
        time.sleep(1)
    except:
        break
result_raw = driver.page_source
content_list = re.findall("img src=\"(.+?)\" ", str(result_raw))
n = 0
while n < len(content_list):
    i = time.time()
    local = r"%s.jpg" % (i)
    urllib.request.urlretrieve(content_list[n], local)
    print("编号：" + str(i))
    n = n + 1

2. Chat Between Two Bots

from time import sleep
import requests
s = input("请主人输入话题：")
while True:
    resp = requests.post("http://www.tuling123.com/openapi/api", data={"key":"4fede3c4384846b9a7d0456a5e1e2943", "info": s})
    resp = resp.json()
    sleep(1)
    print('小鱼：', resp['text'])
    s = resp['text']
    resp = requests.get("http://api.qingyunke.com/api.php", {"key":"free", "appid":0, "msg": s})
    resp.encoding = 'utf8'
    resp = resp.json()
    sleep(1)
    print('菲菲：', resp['content'])
    # Additional example using 小i robot omitted for brevity

3. Identify Poem Author (Li Bai or Du Fu) Using Naive Bayes

import jieba
from nltk.classify import NaiveBayesClassifier

# Load poems
text1 = open(r"libai.txt", "rb").read()
list1 = jieba.cut(text1)
result1 = " ".join(list1)
text2 = open(r"dufu.txt", "rb").read()
list2 = jieba.cut(text2)
result2 = " ".join(list2)

def word_feats(words):
    return {word: True for word in words}

libai_features = [(word_feats(lb), 'lb') for lb in result1]
dufu_features = [(word_feats(df), 'df') for df in result2]
train_set = libai_features + dufu_features
classifier = NaiveBayesClassifier.train(train_set)

sentence = input("请输入一句你喜欢的诗：")
seg_list = jieba.cut(sentence)
words = " ".join(seg_list).split()
lb = df = 0
for word in words:
    classResult = classifier.classify(word_feats(word))
    if classResult == 'lb':
        lb += 1
    if classResult == 'df':
        df += 1
x = float(lb) / len(words)
y = float(df) / len(words)
print('李白的可能性：%.2f%%' % (x * 100))
print('杜甫的可能性：%.2f%%' % (y * 100))

4. Generate Random 35‑choose‑7 Lottery Numbers

import random

temp = [i + 1 for i in range(35)]
random.shuffle(temp)
i = 0
lst = []
while i < 7:
    lst.append(temp[i])
    i = i + 1
lst.sort()
print('\033[0;31;;1m')
print(*lst[0:6], end="")
print('\033[0;34;;1m', end=" ")
print(lst[-1])

5. Auto‑Generate an Apology Letter

import random
import xlrd

ExcelFile = xlrd.open_workbook(r'test.xlsx')
sheet = ExcelFile.sheet_by_name('Sheet1')
i = []
x = input("请输入具体事件：")
y = int(input("老师要求的字数："))
while len(str(i)) < y * 1.2:
    s = random.randint(1, 60)
    rows = sheet.row_values(s)
    i.append(*rows)
print("    " * 8 + "检讨书
" + "老师：")
print("我不应该" + str(x) + "，", *i)
print("再次请老师原谅！")

6. Screen Capture Recorder

from time import sleep
from PIL import ImageGrab

m = int(input("请输入想抓屏几分钟："))
m = m * 60
n = 1
while n < m:
    sleep(0.02)
    im = ImageGrab.grab()
    local = r"%s.jpg" % (n)
    im.save(local, 'jpeg')
    n = n + 1

7. Create an Animated GIF

from PIL import Image

im = Image.open("1.jpg")
images = []
images.append(Image.open('2.jpg'))
images.append(Image.open('3.jpg'))
im.save('gif.gif', save_all=True, append_images=images, loop=1, duration=1, comment=b"aaabb")

The collection demonstrates how Python can quickly automate diverse tasks, encouraging developers to explore existing libraries before writing new code.