TOP 5 useful Python tools for data engineers and web developer | Big Data Science

TOP 5 useful Python tools for data engineers and web developers
• Requests is an easy-to-use HTTP library for Python that allows you to make requests and interact with the API https://docs.python-requests.org/en/master/
• Advanced Python Scheduler (APScheduler) - a library for deferred execution of Python code once or with periodic repetition. When the tasks are saved in the database, their states and the restart of the scheduler will also be saved. APScheduler can also be used as a cross-platform application-specific replacement for platform-specific schedulers such as the cron daemon or Windows task scheduler. However, APScheduler is not a daemon or service, and therefore does not come with command line tools, but is intended to run inside existing applications. This library provides some ready-made building blocks for creating a scheduler service or for running it in a separate process. https://apscheduler.readthedocs.io/en/stable/userguide.html
• Watchdog - a module for tracking filesystem events through the Python API and shell utilities https://pypi.org/project/watchdog/
• Twilio - a library for automating the sending of text messages and phone calls. It is very convenient for automatic monitoring of events on third-party sites, for example, prompt tracking of discounts on the right products or the appearance of new products https://pypi.org/project/twilio/
• Random User Agent - a library for adding random user agents to requests, which is useful when web parsing data or sending a large number of requests https://pypi.org/project/random-user-agent/