What’s New in GNPy Release 2.14: improved accuracy, multi-vendor equipment library, and YANG model support

GNPy has become a cornerstone tool for optical network engineers, planning, simulating, and optimizing open DWDM networks. Built based on a Gaussian-Noise (GN) mathematical model, GNPy enables accurate end-to-end optical signals’ propagation calculations, supports multiband operation, and integrates into automated planning workflows used by operators, vendors, and researchers worldwide. Its design philosophy—open source development, equipment-model transparency, and reproducible results—has made it a reference implementation for route-planning engines in modern mesh optical networks.

With the 2.14 release, published on February 5, 2026, the Telecom Infra Project’s OOPT community introduced a significant set of improvements that enhance modeling accuracy, simplify the equipment modelling and path request handling , and make troubleshooting easier for operators and tool builders. Below is a breakdown of the most relevant enhancements:

Sharper Physical Modeling: Accuracy Improvements

Release 2.14 introduces two main changes that improve the precision and stability of propagation results:

More Realistic Power Calculations: The fiber model now uses total channel power (Signal + ASE + NLI) instead of just signal power to compute propagation. This produces more realistic span-loading behavior and slightly shifts results (typically <0.1 dB) because ASE and nonlinear noise are now explicitly included in injected power calculations.
Stable Multiband Sorting: In earlier releases, multiband operation (e.g., C+L) could exhibit small inconsistencies depending on how band definitions were ordered. GNPy now sorts channels strictly by increasing optical frequency, ensuring stable, order-independent initialization of spectral information.
Richer Exported Metrics: Troubleshooting optical networks often requires analyzing more than SNR. In this new release, GNPy now exports Maximum SNR, Minimum required OSNR, Propagated GSNR, and specific penalties (PDL, PMD, and CD). These additional indicators are particularly valuable in cases where GSNR may look acceptable, but penalties or OSNR thresholds still cause a service to fail—allowing deeper root-cause analysis from within GNPy’s native output formats.

These changes collectively yield a more robust GN-model evaluation and reduce subtle edge cases in wideband and L-band planning.

Enhanced Equipment Library Management

To facilitate the integration of GNPy across different vendor systems, GNPy’s equipment library has been significantly improved:

Vendor Aliases (other_name keyword): allows multiple identifiers for the same physical component (e.g., vendor-specific aliases), preventing duplication and making it easier to maintain unified equipment libraries across multiple topology sources.
Library metadata support: Equipment files can now include metadata such as supplier references, creation dates, or contact details. This makes library management more transparent and helps operators maintain audit trails and provenance information within their planning toolchain.
YANG Model Support: Release 2.14 introduces a YANG model for API requests, making it much faster to integrate GNPy with SDN controllers and standard multi-vendor network management pipelines.

Improved Path Requests & CLI Usability

This new release introduces several workflow improvements to make life easier for engineers and PCE (Path Computation Element) developers:

Direct Pathing via CLI: The CLI now supports a --path option that lets users explicitly list ROADM nodes, using a pipe-separated notation (e.g., A|B|C|D).
Smarter Service Requests: A complementary --service argument allows service files to be used directly together with a --route_id. Source/destination nodes are automatically inferred, streamlining the invocation of complex service requests.
Clearer Terminal Output: The CLI now provides enhanced path-request result displays, giving engineers deeper visibility into how each network element behaves under a given service specification.
New Spectrum Assignment Policy: A new spectrum-assignment policy option, currently implementing a last-fit strategy, expands GNPy’s suitability for automated spectrum-management tools used in large mesh networks.

Conclusion

GNPy 2.14 is a focused but impactful release: it improves physical accuracy, reduces edge-case behavior, enhances path-definition flexibility, extends diagnostics, and strengthens tooling around equipment libraries and automation.

For engineers building PCE components, for researchers exploring new modulation formats or multiband strategies, and for operators validating vendor planning results, this release advances GNPy's role as the open, transparent baseline for DWDM route planning.