What Are the Most Overlooked Python Libraries That Can Supercharge Your Workflow?

[shreyapatel]

I've been working with Python across a range of projects—from automation and data parsing to API integrations and backend systems. Along the way, I've discovered some lesser-known Python libraries that have made a big difference in performance and productivity.

I’d love to hear from the community:

What underrated or niche Python packages do you use regularly?

Have any saved you hours of coding or simplified complex logic?

Bonus: Share a use-case where it really helped.

Let’s build a list that others can benefit from, especially those who want to level up beyond the usual requests, pandas, and Flask.

[DeaD_EyE]

• snap7 to control PLC (Siemens S7-1200/1500) via S7-Online
  
• freeopcua / asyncua to use OPC-UA for PLC/HMI
  
• pnio-dcp to get/set a name and ip address of a ProfientDevice
  

The real use case was to automate testing of 64 assembled PLC-Racks. All digital/analog IOs were tested. In addition, the MAC-Address, IP-Address and Profinet-Name were checked on an Excel Spreadsheet with the help of openpyxl.

It saved me hours of work. Otherwise, I had to test all 32 digital inputs/outputs, 8 analog inputs and 4 analog outputs manually.

[Plyth]

That's a solid list, thanks for sharing those! I hadn’t come across pnio-dcp before, but that sounds incredibly useful for handling Profinet configurations. Automating the testing of 64 PLC racks is no joke. Using Python to streamline all that hardware validation with openpyxl is a great example of combining industrial protocols with common data tools. Bookmarking this for future reference when working with automation systems.