ChatGPT可以帮忙自动生成python代码

生成图表

ChatGPT可以帮助我们轻松返回生成图标的python代码。

image.png

import matplotlib.pyplot as plt
import numpy as np

# Generate some random data
x = np.random.rand(100)
y = x + np.random.normal(0, 0.1, size=100)

# Fit a linear regression to the data
m, b = np.polyfit(x, y, 1)

# Plot the data and the fitted line
plt.plot(x, y, 'o')
plt.plot(x, m*x + b, '-')
plt.show()

发送信息

chatgpt可以帮助我们生成发送信息的python代码。

import pywhatkit

# Set the time in 24-hour format (HH:MM:SS) when you want the message to be sent
time = "HH:MM:SS"
# Set the phone number that you want to send the message to
phone_number = "1234567890"
# Set the message that you want to send
message = "Your message goes here"
# Use the sendwhatmsg method to send the message at the specified time
pywhatkit.sendwhatmsg(time, phone_number, message)

发送邮件

chatgpt也可以发送给我们发送邮件的python代码。

python_send_email-1024x512.png

import smtplib

# create an SMTP object
smtp_obj = smtplib.SMTP('smtp.gmail.com', 587)

# start TLS encryption
smtp_obj.starttls()

# login to the email account
smtp_obj.login('codelessearnmore@gmail.com', 'YOUR_PASSWORD')

# construct the email message
message = "Subject: Email sent by ChatGPT\n\nChatGPT rocks!"

# send the email
smtp_obj.sendmail('codelessearnmore@gmail.com', 'frank@codelessearnmore.com', message)

# close the SMTP connection
smtp_obj.quit()

抓取数据

chatgpt也可以帮我们生成抓取网页信息的代码。

import requests
from bs4 import BeautifulSoup

# Make a GET request to the website
response = requests.get("https://books.toscrape.com/")

# Parse the HTML content of the website
soup = BeautifulSoup(response.text, "html.parser")

# Extract the data you want using Beautiful Soup's various methods and attributes
titles = soup.find_all("h3")
prices = soup.find_all(class_="price_color")

# Save the extracted data to a file or database, or use it for some other purpose
with open("book_data.txt", "w") as file:
    for title, price in zip(titles, prices):
        file.write(f"{title.text}: {price.text}\n")

导出数据

同样，chatgpt也可以帮我们生成从excel导出数据的代码。

image.png

# Import the `openpyxl` library
import openpyxl
# Create a new Excel workbook
workbook = openpyxl.Workbook()
# Get the active sheet in the workbook (which will be the only sheet at this point)
sheet = workbook.active
# Add some data to the sheet
sheet["A1"] = "Product"
sheet["B1"] = "Sales"
# Add some more data to the sheet
products = ["Product A", "Product B", "Product C"]
sales = [100, 200, 300]
for i in range(len(products)):
    sheet.cell(row=i+2, column=1).value = products[i]
    sheet.cell(row=i+2, column=2).value = sales[i]
# Save the workbook to a file
workbook.save("sales_report.xlsx")