MC++: Toolkit for Construction, Manipulation and Evaluation of Factorable Functions
MC++ provides a collection of classes to support the construction and manipulation of factorable functions and
their evaluation using a range of arithmetics. It is primarily written in C++ to promote execution speed, while the
library PyMC++ provides Python binders through pybind11 (the module
is imported as pymcpp).
Expression trees in MC++ can comprise any finite combination of unary and binary operations from a default library and are described by directed acyclic graphs (DAGs). MC++ also features a mechanism to extend DAGs with external operations, currently including affine and polynomial subexpressions, multi-layer perceptrons (MLP) and nested DAGs. Through the library CRONOS, MC++ can also be extended with systems of algebraic and differential equations. Expression trees generated with MC++ are used by the library CANON for local and global numerical optimization, and by the library MAGNUS for the development and analysis of mathematical models.
Capabilities
Version 5 of MC++ supports:
- Expression trees: construction of factorable functions as DAGs, with common-subexpression elimination; differentiation in both forward and reverse accumulation modes; evaluation in any of the arithmetics below; vectorized and multi-threaded evaluation over many points.
- Decomposition: recursive decomposition of factorable expressions into linear/polynomial subexpressions and transcendental operations, the basis for tailored relaxation and reformulation strategies.
- Nested expression trees: a DAG as an operation of another DAG, to enable tailored bounding strategies.
- External operations: user-defined operations with their own evaluation and differentiation rules -- the mechanism CRONOS uses to embed differential-equation solvers.
The bounding arithmetics, each a header that can be used on its own or through the DAGs:
| arithmetic | purpose |
|---|---|
| Interval arithmetic | rigorous enclosures (Boost, PROFIL/BIAS or FILIB++ as backend) |
| Eigenvalue arithmetic | spectral bounds of Hessians |
| Ellipsoidal arithmetic | ellipsoidal enclosures of multivariate systems |
| McCormick relaxations | convex/concave relaxations and their subgradients |
| Taylor and Chebyshev models | polynomial models with rigorous remainder bounds |
| Polyhedral relaxations | linear relaxations for use in LP/MILP solvers |
| Superposition relaxations | relaxation via separable estimators |
A range of Python scripts and notebooks in notebook/ illustrate these capabilities.
Setting up MC++
PyMC++ installs from PyPI, with pre-built wheels for Python 3.10 to 3.14 on Linux, macOS and Windows:
pip install pymcpp
To use the C++ headers, a different interval backend, or the HSL and Torch options, build from source with CMake; refer to INSTALL.md for the requirements, options and instructions.
Layout
src/mc/ the MC++ headers (header-only library)
src/3rdparty/ bundled third-party headers (FADBAD++, used only with MC__USE_FADBAD)
src/pymcpp/ the Python binders (PyMC++, module `pymcpp`)
test/ C++ test and example programs
notebook/ Python scripts and Jupyter notebooks
Contacts
- Repo owner: Benoit C. Chachuat
- OMEGA Research Group, Imperial College London
References
Methods implemented in MC++:
- Mitsos, A., B. Chachuat, P.I. Barton, McCormick-based relaxations of algorithms, SIAM Journal on Optimization, 20(2):573-601, 2009
- Bompadre, A., A. Mitsos, Convergence rate of McCormick relaxations, Journal of Global Optimization 52(1), 1-28, 2012
- Bompadre, A., A. Mitsos, B. Chachuat, Convergence analysis of Taylor models and McCormick-Taylor models, Journal of Global Optimization, 57(1), 75-114, 2013
- Tsoukalas, A., A. Mitsos, Multi-variate McCormick relaxations, Journal of Global Optimization, 59(2), 633-662, 2014
- Wechsung, A., P.I. Barton, Global optimization of bounded factorable functions with discontinuities, Journal of Global Optimization, 58(1), 1-30, 2014
- Villanueva, M.E., J. Rajyaguru, B. Houska, B. Chachuat, Ellipsoidal arithmetic for multivariate systems, Computer Aided Chemical Engineering, 37, 767-772, 2015
- Chachuat, B, B. Houska, R. Paulen, N. Peric, J. Rajyaguru, M.E. Villanueva, Set-theoretic approaches in analysis, estimation and control of nonlinear systems, IFAC-PapersOnLine, 48(8), 981-995, 2015
- Villanueva, M.E., Set-Theoretic Methods for Analysis, Estimation and Control of Nonlinear Systems, PhD Thesis, Department of Chemical Engineering, Imperial College London, 2016
- Rajyaguru, J., Villanueva M.E., Houska B., Chachuat B., Chebyshev model arithmetic for factorable functions, Journal of Global Optimization, 68, 413-438, 2017
- Karia, T., C.S. Adjiman, B. Chachuat, Assessment of a two-step approach for global optimization of mixed-integer polynomial programs using quadratic reformulation, Computers & Chemical Engineering, 165, 107909, 2022
- Zha, Y., M.E. Villanueva, B. Houska, B. Chachuat, Relaxation via separable estimators: Arithmetic and implementation, Journal of Global Optimization, in press, 2026
Software building on MC++:
- Bongartz, D., J. Najman, S. Sass, A. Mitsos, MAiNGO -- McCormick-based Algorithm for mixed-integer Nonlinear Global Optimization, Technical Report, Process Systems Engineering (AVT.SVT), RWTH Aachen University, 2018
- Pyomo, whose MC++ interface bounds factorable functions with McCormick relaxations (built on an earlier MC++ release)
License
MC++ is published under the Eclipse Public License 2.0, with the GNU General Public License, version 2 or later,
as a Secondary License (see LICENSE). The bundled FADBAD++ (MC__USE_FADBAD, off by default) is
a separate work distributed for non-commercial use only: commercial use requires a license from its authors.
Release files for pymcpp 5.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pymcpp-5.0.3.tar.gz | 8.4 MB | With provenance | Details for pymcpp-5.0.3.tar.gz |
Built distributions (wheels)
Total release size: 193.7 MB
Release files / pymcpp-5.0.3.tar.gz
| Download URL | pymcpp-5.0.3.tar.gz |
|---|---|
| Size | 8.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3d1322efe47fa45ec36a503a3428865441fdd4465a1b6d03f824a2ccef056cd4
|
|
BLAKE2b-256 checksum How to use checksums |
ea96bd2713804aa191b4674f86354243b17c12da6718a4d3551e9886cece766e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp314-cp314-win_amd64.whl
| Download URL | pymcpp-5.0.3-cp314-cp314-win_amd64.whl |
|---|---|
| Size | 17.6 MB |
| Tags | CPython 3.14 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
f681e481fbad042e63ed0344b7db50245bdbbada0276674b34be0fe63217f81a
|
|
BLAKE2b-256 checksum How to use checksums |
e6cdd1e826d6b889e555305b24771706a6b27623d14682117b132f165bcd8b7d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | pymcpp-5.0.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 16.0 MB |
| Tags | CPython 3.14 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
|
SHA-256 checksum How to use checksums |
d350dbace1495f5731b011524092471875a861f5e185e707f1af576f2a6d9126
|
|
BLAKE2b-256 checksum How to use checksums |
5aefc5347d942e741ccdb30a047244b5599b24f9418aad37e170e9a87cb417a0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp314-cp314-macosx_14_0_arm64.whl
| Download URL | pymcpp-5.0.3-cp314-cp314-macosx_14_0_arm64.whl |
|---|---|
| Size | 3.7 MB |
| Tags | CPython 3.14 macOS 14.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
c8370a8167a6acc49db09240a2e717b5cab0b3f7d382894ec24b9b4fa161c19f
|
|
BLAKE2b-256 checksum How to use checksums |
0a51d49acb7346eb60080d3d744537e57dab23109dbf4d3b145e24a0dc78c0b2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp313-cp313-win_amd64.whl
| Download URL | pymcpp-5.0.3-cp313-cp313-win_amd64.whl |
|---|---|
| Size | 17.2 MB |
| Tags | CPython 3.13 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
827e0f1bd04d2200e2610cf1bcd3f3134dfbee50a7bcae3edb8a59f53ca2dda5
|
|
BLAKE2b-256 checksum How to use checksums |
a90ed6de575090ce3df56fcebe1c973bbfebc9b1e0d7a9d676f3e0b77c440baf
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | pymcpp-5.0.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 16.0 MB |
| Tags | CPython 3.13 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
|
SHA-256 checksum How to use checksums |
1b276eaaea30ee931e8a3b27105c8a7313959e0e39e90343f13614c75b944479
|
|
BLAKE2b-256 checksum How to use checksums |
9a4af3ea0bb5f368265ef994898271dce0d520afd36eb3f6cfa5dd8ab0f10b79
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp313-cp313-macosx_14_0_arm64.whl
| Download URL | pymcpp-5.0.3-cp313-cp313-macosx_14_0_arm64.whl |
|---|---|
| Size | 3.7 MB |
| Tags | CPython 3.13 macOS 14.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
d4197417ba5f07491a2fdecd5afb958081668870282c08d2bf4fc6bf998be755
|
|
BLAKE2b-256 checksum How to use checksums |
94aa846141176873d96afb9d28a79e613d5e46a6db9aca0733259f0e8b9b0b95
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp312-cp312-win_amd64.whl
| Download URL | pymcpp-5.0.3-cp312-cp312-win_amd64.whl |
|---|---|
| Size | 17.2 MB |
| Tags | CPython 3.12 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
c665523e6d9e472435fe94b5d7765206b24905994a9a7f169d23794ec3ae3870
|
|
BLAKE2b-256 checksum How to use checksums |
6ca914c0f762211367eed2dd33f00e6537c3f603dd1f4aa3295a34db06cfaf81
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | pymcpp-5.0.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 16.0 MB |
| Tags | CPython 3.12 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
|
SHA-256 checksum How to use checksums |
c90eaab941e6febb47185d794e7348ca34b7b507889f371ff3cd36e70e04ed1c
|
|
BLAKE2b-256 checksum How to use checksums |
03e569195f132caa4499bb09d6fa696d1932741635b857ff15f9bdaf1e5bed12
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp312-cp312-macosx_14_0_arm64.whl
| Download URL | pymcpp-5.0.3-cp312-cp312-macosx_14_0_arm64.whl |
|---|---|
| Size | 3.7 MB |
| Tags | CPython 3.12 macOS 14.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
a0c64634a5375cff7e7fc9cf9a4eaf78e3180ba23d762546a13f6ec0128effe3
|
|
BLAKE2b-256 checksum How to use checksums |
263b9ece0c082cdf05c086a487b91b28ad1bbcf0508a310d259581025fdc424e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp311-cp311-win_amd64.whl
| Download URL | pymcpp-5.0.3-cp311-cp311-win_amd64.whl |
|---|---|
| Size | 17.4 MB |
| Tags | CPython 3.11 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
5c496d8718eb18bf705c028ecb302f82eb7865e98d502b2103ede69715f1164d
|
|
BLAKE2b-256 checksum How to use checksums |
4248317829c3954f2e32c4f85ecffc32075defa8302426ba8c65683248649b73
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | pymcpp-5.0.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 16.1 MB |
| Tags | CPython 3.11 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
|
SHA-256 checksum How to use checksums |
dfd92a317531190599d2c49b5fc698889a9ad4e90d800495f7ce818be48f08fd
|
|
BLAKE2b-256 checksum How to use checksums |
96273e0122e823f09af0668f8d61b37f9215546edb91ec57cb3a26a21ff23aaa
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp311-cp311-macosx_14_0_arm64.whl
| Download URL | pymcpp-5.0.3-cp311-cp311-macosx_14_0_arm64.whl |
|---|---|
| Size | 3.7 MB |
| Tags | CPython 3.11 macOS 14.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
5ef52fed7084296efae146cf50ee0e0f4b3d90fe7ae4aaf6674446e6a334aa34
|
|
BLAKE2b-256 checksum How to use checksums |
03d54eedee914d32b680e953d61fad6b32e2b1137fe67fd08b7fd971e85e967d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp310-cp310-win_amd64.whl
| Download URL | pymcpp-5.0.3-cp310-cp310-win_amd64.whl |
|---|---|
| Size | 17.4 MB |
| Tags | CPython 3.10 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
db58199305f09b4fca6e3b20a21e4da63f37ab04ae60ac4ef0d23de5a67fcdc4
|
|
BLAKE2b-256 checksum How to use checksums |
06804e6697650309533583854cc533df73d645995377771c1aac1b6bba2d8368
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | pymcpp-5.0.3-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 16.1 MB |
| Tags | CPython 3.10 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
|
SHA-256 checksum How to use checksums |
220e0fa1f9e33d4baa4b6a0e2c5f455daa6c94bffc4b7fcc02b99f856bcd71fb
|
|
BLAKE2b-256 checksum How to use checksums |
c481f7249a372dff6d911fb1c6e76498c17d49b3ceedd0a746c88518ac310a6b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logRelease files / pymcpp-5.0.3-cp310-cp310-macosx_14_0_arm64.whl
| Download URL | pymcpp-5.0.3-cp310-cp310-macosx_14_0_arm64.whl |
|---|---|
| Size | 3.7 MB |
| Tags | CPython 3.10 macOS 14.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
71785c845b97121c80d59732504f38f57dbb700b65f1b22dba5e7778436a3e18
|
|
BLAKE2b-256 checksum How to use checksums |
c5da687c04e8bcc8280c1eec7181bb24a625f3bbc67a3973834fba9fb42f67e7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logSecurity for pymcpp 5.0.3
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 16 files in this release have been uploaded with provenance metadata.
Attestation for pymcpp-5.0.3.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 8, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
