# How Do Electrical Engineers Use Python? Source: https://ordergroup.co/blog/python-electrical-engineering/ Last updated: 2023-10-30 > In this piece, we'll share three ways factories use Python to make things run faster, more efficiently, and safer in modern manufacturing facilities. ![How Do Electrical Engineers Use Python?](https://ordergroup.co/media/images/Wind_turbines600_ikOC4DO.width-2850.format-webp.webp) How Do Electrical Engineers Use Python? [Łukasz Menclewicz](https://ordergroup.co/authors/lukasz-menclewicz/), Senior Back-end Developer | October 30, 2023 | 4 min read Table of Contents The brief Python in Automation & Control Python in Maintenance & Operations Optimizing Electrical Measurements with Python Is Python Always Worth It, though? The brief Every modern factory is filled with electromechanical gears and machines, but the top ones have something more: smart systems that control data, production devices, and the entire manufacturing process. These systems allow machines to talk to each other and people instantly. They gather all the data and make easy-to-read reports from it. In many cases, these systems run on Python. It's grown in popularity in the IoT industry because of its simplicity, versatility, and extensive library support. In this piece, I'll share three ways factories use Python to make things run faster, more efficiently, and safer in modern manufacturing facilities. Python in Automation & Control Communicating between different devices in a factory setting is challenging because **machines and devices often speak different languages**, with a mix of protocols like GPIB, RS232, USB, and Ethernet.This is where Python tools like pyVISA come in handy. They make it easier to control devices, whatever their interface. Picture a machine designed for PCB testing. When you slot in the PCB, on the reverse side, two types of pins come into play: power pins that ensure the correct power supply is delivered to corresponding points on the PCB,measurement pins, connected to the measuring device, that detect changes in the PCB's electrical signals.With the right power supply secured at one location via the power pins, the machine then uses the measurement pins to take readings on the PCB, capturing variances in current or voltage. This allows you to review and confirm the efficiency of electrical flows and voltage maintenance. Such processes or switches might occur multiple times during a single test cycle, so the assessment is thorough.In such a machine, **Python acts as the middleman**, facilitating dialogues between devices. It sends a message, waits for an answer, and when the data comes in, it processes and archives it, making it ready for immediate distribution.On top of that, Python**automates the whole testing process** and controls at least three devices: a relay card that connects the appropriate points to the input/output of the corresponding measuring/power supply device, a power supply on which it sets the appropriate voltage value and outputs it, and a measuring device that sets it to the suitable measuring range and takes the reading. Why does this matter?First, Python **minimizes human mistakes**, such as misentries, imprecise measurements, or incorrect pin placements that can lead to false readings.Second, a fully automatic process **saves a lot of time** on manually setting power supplies and connecting to points on the PCB. Finally, combined with API integrations, Python's continuous oversight **keeps the team updated in real time**, alerting them when measurements stray from the norm.But that's not all. Python in Maintenance & Operations Overseeing a factory means always knowing the state of your machines. Without real-time insights, things can slip.Traditionally, if a machine faced an issue, the operator would notice and report it. But this method has its pitfalls.An operator might **miss the issue or spot it too late**, risking damage to the machine and the batch of products. And even if they do notice, the message might get lost or delayed, especially if the manager isn't immediately available.That's where Python shines. With tools like Django and Flask, Python can set up a **direct communication line between machines** connected to the network. It collects real-time data, so the right people get instant updates, like whether machines are online and working as they should.So, when something goes wrong, the information is visible in the API interface (Django/Flask) but can also be sent by email/SMS/notification directly to a technician.**The team knows instantly. This quick response reduces downtime and speeds up repairs.**Take PCB testing, for instance. Using Python, you can continuously measure and validate test results. If the system notices a recurring error across several PCBs, it will hint at a possible tester issue, like a bent pin. Such subtle issues might escape the naked eye, but Python flags them immediately. This prevents production hiccups and**saves the company from time and material losses.** Optimizing Electrical Measurements with Python Machines routinely gather and store measurements in databases. Engineers then extract this data to compile reports.Imagine you're tasked with assessing the voltage stability, either the DC voltage or the RMS value of the AC voltage of a device over a set duration. Ideally, the voltage-time graph should show a steady line without oscillations.Traditionally, a machine takes readings at certain intervals, and then an operator tediously transfers this data to an Excel sheet to create a graph. This manual method works, but it is time-consuming and prone to errors.With Python libraries like Pandas for data analysis and Matplotlib for visual representation, it's possible to **gather data and construct diverse charts automatically.** These can range from histograms, medians, and averages to maximum and minimum values.But Python doesn't stop there. It can collate this data into daily, monthly, or yearly reports and convert them to accessible formats like doc or pdf. These reports can then be sent quickly to the relevant personnel.Compared with the traditional manual method, the automated Python approach has clear benefits. A single Python command can**execute a series of tasks reliably and consistently.**Plus, the likelihood of errors drops substantially, because a well-designed script is precise in a way manual processes are not. Is Python Always Worth It, though? In summary, systems built with Python automate tasks traditionally done by humans, allowing faster and more reliable information exchange between devices. Reports and analyses that take an engineer anywhere from several minutes to several hours can, with a single script, be available in real time or be done in just a few seconds.So, is it worth investing in advanced measurement and reporting systems?From my experience, the answer is yes. Of course, there might be exceptions, such as small businesses with limited production scales, where the cost of implementing a complex system might outweigh its benefits.However, in most situations, particularly in primary industrial settings, Python-based tools pay off. They provide substantial financial benefits and priceless **peace of mind****for engineers, operators, and management staff.** Work with high-tech specialists [Let's talk about your project!](https://ordergroup.co/estimate-project/) Explore this topic further Domain hub [Software Development](https://ordergroup.co/services/software-development/) Service [Web Development Services](https://ordergroup.co/services/software-development/web-app-development/) More articles about Software engineering [Software engineering | September 12, 2024 | 4 min read Next.js 15. 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