Sources and verification record

Research completed 2026-07-23 with parallel-cli search and parallel-cli extract, then checked against an isolated installation of simpy==4.1.2. Versioned documentation is preferred over the latest build, which showed a 4.1.2 development revision during verification.

Release, packaging, and source

• SimPy on PyPI — 4.1.2, released 2026-05-24; Requires-Python >=3.8; classifiers list Python 3.8-3.14, CPython, and PyPy; MIT; no runtime dependencies. Verified 2026-07-23.
• GitLab source project — canonical repository, MIT license, tagged source, tests, and documentation. Accessed 2026-07-23.
• GitLab tag 4.1.2 — protected/verified tag, commit f43816490c6f76f336ad6e457d3cab9f386894af, dated 2026-05-24.
• Tagged CHANGES.rst — 4.1.2 entry dated 2026-05-23: Python 3.13/3.14 support, modern-interpreter test/doc fixes, ConditionValue explicitly unhashable, lint/type cleanup.
• Tagged pyproject.toml — Python requirement/classifiers, no dependencies, setuptools build, pytest, mypy, and ruff configuration. Dated 2026-05-23; accessed 2026-07-23.
• Tagged tox.ini and tagged tests — upstream test matrix and behavior tests. Accessed 2026-07-23.
• Tagged simpy/core.py — authoritative Environment.run(), step(), queue tuple, and StopSimulation implementation. Accessed 2026-07-23.

PyPI file hashes observed 2026-07-23:

• wheel simpy-4.1.2-py3-none-any.whl SHA-256 43071f84b6512c9b4fcb33ef057f240ccb1d1f3b263f9b4f9229d072e310b372;
• sdist simpy-4.1.2.tar.gz SHA-256 76ef36b71e0436ba94e55febc001c78879e493a323f045bbcfbb0b216e9b1fbc.

Use the pinned package command in SKILL.md; hashes are recorded for provenance, not embedded into uv pip install syntax.

Official SimPy 4.1.2 documentation

Entry points

• 4.1.2 documentation contents
• 4.1.2 tutorial
• 4.1.2 topical guides
• 4.1.2 examples
• 4.1.2 API reference
• history/change log
• license

All accessed 2026-07-23. The examples index covers condition events, interrupts, Resource, PreemptiveResource, Container, Store, shared events, and process waiting.

Core topical guides

• SimPy basics
• Environments
• Events
• Process Interaction
• Shared Resources
• Monitoring
• Time and Scheduling
• Real-time simulations

All accessed 2026-07-23.

API pages

• simpy.core — Environment, run, schedule, peek, step, EmptySchedule.
• simpy.events — Event, Timeout, Process, Condition, AnyOf, AllOf, priorities.
• simpy.exceptions — Interrupt.
• simpy.resources — Resource/Priority/Preemptive, Container, Store/Filter/Priority, base events.
• simpy.rt — RealtimeEnvironment.
• simpy.util — helper processes.

All accessed 2026-07-23.

Source-level semantic finding

The 4.1.2 Environments topical guide informally says Event-based run() returns when the Event has been processed. The 4.1.2 API docstring says "triggered." Tagged core.py is decisive:

• run(until=event) appends StopSimulation.callback;
• step() sets callbacks to None, executes them, catches StopSimulation, restores callbacks remaining after the stopping callback, and reschedules that Event at priority -1.

Therefore the target value can be returned while target.processed is still false, until one more step processes the rescheduled empty-callback Event. This was reproduced under the exact PyPI 4.1.2 wheel on Python 3.13 and is covered by tests/test_scripts.py.

Numeric run(until=time) creates an urgent internal stop Event, so normal Events at that exact time are excluded. This was verified from both tagged source and runtime tests.

Primary simulation-method sources

These sources describe simulation-study design and output analysis. They are not SimPy API documentation.

• Averill M. Law, "Statistical Analysis of Simulation Output Data", Proceedings of the 2020 Winter Simulation Conference, 2020. Defines terminating/nonterminating analyses; independent replications; replication/deletion; warm-up/run length; Student-t intervals; and warns against naive single-run IID intervals. Accessed 2026-07-23.
• Pierre L'Ecuyer, "Random Number Generation with Multiple Streams for Sequential and Parallel Computing", Proceedings of the 2015 Winter Simulation Conference, 2015, DOI 10.1109/WSC.2015.7408151. Covers streams/substreams, one stream per random source, replication separation, common random numbers, testing, and exact reproducibility. Accessed 2026-07-23.
• Robert G. Sargent, "Verification and Validation of Simulation Models", Proceedings of the 2010 Winter Simulation Conference, 2010. Defines model verification, conceptual/data/operational validity, intended-purpose/domain framing, sensitivity analysis, and validation evidence. Accessed 2026-07-23.
• Stewart Robinson, "Conceptual Modelling for Simulation Part I: Definition and Requirements", Journal of the Operational Research Society 59, 278-290, 2008. Identifies validity, credibility, utility, feasibility, and simplest-adequate-model requirements. Publisher page accessed 2026-07-23.
• Lee W. Schruben, "Detecting Initialization Bias in Simulation Output", Operations Research 30(3), 569-590, June 1982. Original initialization-bias testing method. Metadata/abstract verified via IDEAS/RePEc on 2026-07-23.
• Stewart Robinson, "A Statistical Process Control Approach to Selecting a Warm-up Period for a Discrete-event Simulation", European Journal of Operational Research 176(1), 332-346, January 2007. Accessed 2026-07-23.
• Kathryn Hoad, Stewart Robinson, Ruth Davies, "Automated Selection of the Number of Replications for a Discrete-event Simulation", Journal of the Operational Research Society 61(11), 1632-1644, November 2010. Replication-count/precision methodology; metadata verified 2026-07-23.
• Thomas Monks et al., "Strengthening the Reporting of Empirical Simulation Studies: Introducing the STRESS Guidelines", Journal of Simulation, 2018/2019 publication record. Reporting checklists for objectives, logic, data, experimentation, implementation, and code access. EQUATOR record last updated 2021-11-19; both accessed 2026-07-23.
• Averill M. Law and W. David Kelton, "Confidence Intervals for Steady-State Simulations: I. A Survey of Fixed Sample Size Procedures", Operations Research 32(6), 1221-1239, December 1984. Surveys replication, batch means, autoregressive, spectral, and regenerative fixed-run methods and cautions that adequate run length is model-dependent. Accessed 2026-07-23.

Research queries used

Parallel searches/extractions covered:

• latest SimPy stable version, Python support, PyPI files, GitLab tags/changelog;
• Environment/Event/Process/Timeout/Condition and scheduling;
• all Resource, Container, and Store variants;
• interrupts, monitoring, stepping, real-time, examples, API, and testing config;
• independent replications, confidence intervals, warm-up/transient bias, random streams, conceptual modeling, V&V, sensitivity, and reproducibility.

No Parallel JSON artifacts were written into the repository.