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FERS_core

FERS_core is an open-source Finite Element Method (FEM) library written in Rust with a Python interface. It provides the foundational tools and components necessary for performing FEM analysis. This core package is designed for users who need a reliable and efficient FEM solver.

Features

  • Basic Finite Element Method (FEM) solvers
  • Mesh generation and manipulation tools
  • Support for various types of finite elements
  • Easy-to-use Python interface for integration with existing workflows
  • Designed for high performance with Rust

Installation

You can install FERS_core via pip:

pip install FERS

Solving a model

from fers_core.builders import create_beam

model = create_beam(5.0, "IPE180", udl=-5000.0)   # 5 m span, 5 kN/m downward
model.run_analysis()
print(model.resultsbundle)

Use run_analysis_to_file(path, ...) instead when the result is large — it streams the JSON straight to disk rather than through the Python heap.

Premium solves and timeouts

Without an API key the solver runs at Free-tier limits (100 members) and makes no network call at all. Passing api_key raises those limits:

model.run_analysis(api_key=KEY)

A key means each solve first verifies the licence with ferscloud.com, so that handshake is bounded. If the licence server does not answer within license_timeout seconds (default 30) the call raises FersTimeoutError before the solve starts — so retrying is always safe:

import fers_calculations

try:
    model.run_analysis(api_key=KEY, license_timeout=60)
except fers_calculations.FersTimeoutError:
    ...   # transient stall — retry or skip this model
except RuntimeError:
    ...   # definitive — bad key, non-premium account, or a rejected model

Keeping those two arms apart is the point: retrying a RuntimeError fails identically, while collapsing both into except Exception turns a retryable blip into a lost result. See fers_core/examples/203_Premium_Batch_Solve.py for the full unattended-batch pattern.

FersTimeoutError subclasses the built-in TimeoutError, so a plain except TimeoutError catches it too.

Set FERS_LICENSE_TIMEOUT (seconds) to change the default without editing any call sites. It must be a real environment variable — .env files are not read by the engine.

license_timeout bounds the licence handshake, not the solve. A solve is native code with no cancellation point, so no in-process timeout can interrupt it. For a hard ceiling on total wall time per model, run each solve in a killable subprocess — that also reclaims its memory.

Requires engine fers_calculations >= 0.2.53.

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