<p>Pinch analysis provides a systematic approach to targeting the minimum heating and cooling requirements of industrial processes and to designing heat exchanger networks that approach this target. Decades after its introduction, the method remains essential for energy efficiency, decarbonisation, and retrofit studies across sectors such as chemicals, pulp and paper, food, and refining. In addition, numerous papers have proposed extensions to PA but these are often left isolate and unavailable for future development and implementation. In short, tool development has not kept pace with academic progress and today’s industry requirements. Many practitioners rely on bespoke or basic spreadsheets or legacy desktop applications that make it difficult to scale analyses, embed the results in modern workflows, or experiment with emerging pinch techniques. OpenPinch fills this gap with an open-source Python toolkit that implements advanced pinch analysis and total site integration methods. The library offers typed schemas for robust data ingestion, modular analysis routines that span unit operation to process, site and regional scales, and export paths that maintain compatibility with conventional spreadsheet workflows. As illustrated by a survey of current pinch tools, a distinctive contribution is its comprehensive implementation of (unified) total site heat integration combined with multiple utilities, both isothermal and non-isothermal ones, via a combination of problem-table transformations, temperature-interval segmentation, and iterative assignment. The basis of these algorithms were reported in Tarighaleslami et al. (<CitationRef CitationID="CR31">2017a</CitationRef>). This technical note documents the architecture, algorithms, and data flow of OpenPinch, highlighting an end-to-end example of a pulp mill case study as well as key directions for future extension.</p>