PYTHON · VS CODE · pyodbc & pandas · OPC UA / MQTT / REST · EXCEL & PDF REPORTS
A Python course written for automation engineers, not for web developers. Set up VS Code, pip and virtual environments, then learn the language through plant examples with proper exception handling and logging. Connect Python to SQL Server with pyodbc and analyse the data with pandas, pull values straight from the controller over OPC UA, publish through MQTT and exchange data over REST — then automate Excel and PDF reports that email themselves on a schedule.
Classroom day batches · Online 7:30 PM–9:00 PM · Sunday 11:00 AM–5:00 PM
See the tools, libraries and practical topics used at each stage of the Python scripting path. Select a module to view exactly what you will work with.
Training progression: Module 01 sets up the environment and the language, Module 02 connects Python to the plant database and analyses the data, Module 03 talks to the plant directly over OPC UA, MQTT and REST, and Module 04 turns all of it into reports that generate, email and schedule themselves.
View Detailed Python Training Contents →The Python course is organised as four practical modules covering 20 hands-on topics. Every topic below is a written guide with working script you can open before or after the session — from setup and language fundamentals through SQL Server and pandas to OPC UA, MQTT, REST and automated reporting.
Get a clean working environment and the language basics an automation engineer needs — installation, virtual environments, control flow, functions, modules and classes, and the exception handling and logging that keep a plant script from failing silently.
Where Python fits beside PLC and SCADA work, what it is genuinely good for on a plant network, and what it should not be used for.
View training topic →02Install Python and VS Code, add the extensions that matter, and use pip to bring in the libraries the later labs need.
View training topic →03Keep each project isolated with venv and reproduce it anywhere from requirements.txt — the step that prevents “it works on my laptop”.
View training topic →04Control flow and functions written around plant examples: tag checks, shift loops and reusable helpers instead of textbook exercises.
View training topic →05Structure a growing script into modules and classes so a data collector or report generator stays maintainable a year later.
View training topic →06try/except done properly, plus a log file that tells you what a scheduled script did at 06:00 when nobody was watching.
View training topic →Connect Python to the plant database: data type mapping, connection strings, full CRUD with pyodbc, and reading query results into pandas for filtering, cleaning and summarising.
How Python types map to SQL Server columns, and why timestamps, decimals and nulls cause most insert failures.
View training topic →02Drivers, connection strings and authentication, then create the database and tables your scripts will work against.
View training topic →03Parameterised inserts, batch writes and commit behaviour so plant values land reliably and safely.
View training topic →04Ten working scripts covering create, read, update and delete against real plant tables, ready to adapt to your schema.
View training topic →05Pull query results into a DataFrame and handle dates, nulls and large result sets without exhausting memory.
View training topic →06Filter by shift and equipment, clean bad records, resample time series and produce the summary figures a report needs.
View training topic →Talk to the plant directly from Python: subscribe to controller values over OPC UA, publish and subscribe through an MQTT broker, and exchange data with business systems over REST.
Connect, browse node IDs, subscribe to value changes and insert into SQL Server with error handling and reconnection.
View training topic →02Publish and subscribe with paho-mqtt, design JSON payloads and move broker data into the database or a dashboard.
View training topic →03Build and consume REST endpoints so plant data can be exchanged with ERP, MES and web applications, with authentication handled.
View training topic →Deliver the output and make it run without you: formatted Excel workbooks and PDF reports, automatic email distribution, unattended scheduled runs, and a packaged executable for stations without Python.
Generate a formatted shift or production workbook with headers, column widths, number formats and multiple sheets.
View training topic →02Build a print-ready PDF with title block, tables and totals for the reports management signs and files.
View training topic →03Attach the generated report and send it to the shift distribution list, with SMTP settings and send-failure handling.
View training topic →04Run the script unattended at shift end: task setup, working directory, credentials and logging that proves it ran.
View training topic →05Package the script as an executable so a SCADA station can trigger it without a Python installation.
View training topic →Automation, SCADA and maintenance engineers who need to collect plant data, connect systems and produce reports. The examples are built around tags, shifts, alarms and production records rather than generic programming exercises.
No. The first module covers installation, virtual environments, control flow, functions, modules and classes from the beginning, so a PLC or SCADA engineer with no coding background can follow the whole course.
Python 3 with VS Code, pip and venv for environments, then pyodbc and pandas for database work, asyncua and paho-mqtt for plant connectivity, and openpyxl plus a PDF library for reporting. Each library is installed and explained during the sessions.
Yes, through OPC UA in this course. A Python client connects to the controller's OPC UA server, browses node IDs, subscribes to value changes and stores the values, which is the vendor-neutral route used in most Industry 4.0 projects.
Database work is a full module: data type mapping, connection strings and authentication, creating tables, parameterised inserts, full CRUD operations, and reading query results into pandas for filtering, cleaning and summarising.
Yes. Scripts are scheduled with Windows Task Scheduler to run at shift end, generate the Excel or PDF report, email it to a distribution list, and write a log entry so you can prove the run happened.
The course covers packaging a script as a standalone executable so the station can trigger it without a Python installation, which is the usual answer when IT policy blocks installations on a runtime PC.
Yes. Publishing and subscribing with paho-mqtt including topic and JSON payload design, and consuming or building REST endpoints so plant data can be exchanged with ERP, MES and web applications.
Classroom sessions run in the day batches and live online sessions run from 7:30 PM to 9:00 PM on weekdays, with a Sunday batch from 11:00 AM to 5:00 PM. Corporate and in-plant groups can request a different schedule.
Send your requirement for Python scripting training. Mention your current programming level, what you need Python for (data collection, database work, reporting or integration) and whether it can be installed on the target machine, so the labs match your plant. Online batch runs 7:30 PM to 9:00 PM on weekdays and 11:00 AM to 5:00 PM on Sunday.
Explore the four modules, the environment and libraries used in the labs, the reporting output produced and classroom or online batch options.
Content reviewed: 18 September 2026