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FERS_calculations

FERS_calculations is a high-performance library for Rust-backed calculations in mechanical engineering. It can process JSON input files to deliver fast and accurate results. While it can be run as a standalone tool, integration with FERS_core simplifies input creation and workflow management.

Features

  • Standalone Functionality: Run directly by providing a valid JSON input file.
  • Rust-Powered Performance: Designed for speed and reliability in computational tasks.
  • Python Integration: Seamless integration with FERS_core for easy preprocessing and result handling.
  • Engineer-Friendly Design: Minimal coding effort required for complex structural engineering calculations.

Installation

pip install fers_calculations

This installs the pre-built Rust bindings -- no Rust toolchain required.

Usage

Standalone (Python)

You can call fers_calculations directly from Python without FERS_core:

import fers_calculations

# Load your JSON input
with open("001_cantilever_with_end_load.json") as f:
    json_data = f.read()

# Run the analysis
results_json = fers_calculations.calculate_from_json(json_data)

# Save the results
with open("results.json", "w") as f:
    f.write(results_json)

Premium licensing and timeouts

Passing api_key unlocks Premium model limits. That is the only thing that makes the library contact the network — omit it and no request is ever sent.

Because a licence check is a network call, it is bounded. If ferscloud.com does not answer within license_timeout seconds (default 30) the call raises fers_calculations.FersTimeoutError before the solve starts, so retrying is always safe:

import fers_calculations

try:
    fers_calculations.calculate_to_file(
        json_data, "results.json", api_key=KEY, license_timeout=60
    )
except fers_calculations.FersTimeoutError:
    ...  # transient — retry or skip this model

FersTimeoutError subclasses the built-in TimeoutError, so except TimeoutError catches it too. A definitive failure — an invalid key, a non-premium account, an unreachable host — raises RuntimeError instead, since retrying those is pointless.

license_timeout bounds the licence handshake only, not the solve. To put a hard ceiling on a whole solve, run it in a killable subprocess.

Two environment variables are read (real process environment only — .env files are loaded by the CLI binary, never by this extension module):

Variable Purpose Default
FERS_LICENSE_TIMEOUT Default license_timeout, in seconds 30
FERS_CLOUD_URL Base URL of the licence API https://ferscloud.com

With FERS_core (recommended)

For a more ergonomic workflow, install FERS_core which handles model creation, calling the Rust engine, and post-processing / visualisation:

pip install fers-core
from fers_core import FERS

model = FERS.from_json("001_cantilever_with_end_load.json")
model.calculate()
model.plot_results_3d()

See FERS_core on PyPI for full documentation.

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