System Prompt Tool
This tool uses the win10toast library to trigger system notifications and can be used to prompt important things.
#定时通知脚本 from win10toast import ToastNotifier import time #构建通知对象实例 toaster = ToastNotifier() title = input("请输入事件标题:") content = input("请输入事件提要") time_min = float(input("请输入提醒时间(分钟):")) #time_min = time_min * 60 print("设置完成!") time.sleep(1) print("开始运行..") time.sleep(time_min) toaster.show_toast(f"{title}", f"{content}", duration=10, threaded=True) while toaster.notification_active(): time.sleep(0.005)
Folder cleaning tool
import os import threading import time def get_file_list(file_path): #文件按最后修改时间排序 dir_list = os.listdir(file_path) if not dir_list: return else: dir_list = sorted(dir_list, key=lambda x: os.path.getmtime(os.path.join(file_path, x))) return dir_list def get_size(file_path): """[summary] Args: file_path ([type]): [目录] Returns: [type]: 返回目录大小,MB """ totalsize=0 for filename in os.listdir(file_path): totalsize=totalsize+os.path.getsize(os.path.join(file_path, filename)) #print(totalsize / 1024 / 1024) return totalsize / 1024 / 1024 def detect_file_size(file_path, size_Max, size_Del): """[summary] Args: file_path ([type]): [文件目录] size_Max ([type]): [文件夹最大大小] size_Del ([type]): [超过size_Max时要删除的大小] """ print(get_size(file_path)) if get_size(file_path) > size_Max: fileList = get_file_list(file_path) for i in range(len(fileList)): if get_size(file_path) > (size_Max - size_Del): print ("del :%d %s" % (i + 1, fileList[i])) #os.remove(file_path + fileList[i]) def detectFileSize(): #检测线程,每个5秒检测一次 while True: print('======detect============') detect_file_size("/Users/aaron/Downloads/", 100, 30) time.sleep(5) if __name__ == "__main__": #创建检测线程 detect_thread = threading.Thread(target = detectFileSize) detect_thread.start()
Convert PDF files to audio
import pyttsx3 import pyPDF2 book = open('路径/book.pdf',rb) pdfreader = pyPDF2.PdfFileReader(book) pages = pdfreader.numPages print(pages) voice = pyttsx3.init() page = pdfreader.getpage(3) text = page.extractText() speaker.say(text) speaker.runAndWait()
Batch compressed files
import zipfile # zipfile库 压缩文件 import os import time def batch_zip(start_dir): start_dir = start_dir #文件路径 file_news = start_dir + '.zip' # 压缩后文件夹的名字 z = zipfile.ZipFile(file_news, 'w', zipfile.ZIP_DEFLATED) for dir_path, dir_names, file_names in os.walk(start_dir): #避免从根目录复制 f_path = dir_path.replace(start_dir, '') #压缩所有文件 f_path = f_path and f_path + os.sep for filename in file_names: z.write(os.path.join(dir_path, filename), f_path + filename) z.close() return file_news batch_zip('./data/ziptest')
Send by email
# 1、导入模块 import yagmail # 2、设置smtp服务信息 yag = yagmail.SMTP(user="改成自己的邮箱账号@126.com", password="改成自己的邮箱密码", host='smtp.126.com') # 3、设置邮件主题与邮件内容 subject = 'Python邮件测试' content = ['Python邮件测试 -- 邮件来自黑马程序员Python+大数据'] # 4、发送邮件 yag.send('gocndws@126.com', subject, content)
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Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.