numnom

PyPI

A fast MPS file parser for Python, powered by Rust.

  • Fast: 745 MB/s throughput on raw MPS text (4.2× faster than SCIP on MIPLIB 2017)
  • Zero-copy numpy arrays: model data lands directly in numpy with no extra copies
  • Compressed files: reads .mps.gz with SIMD-accelerated decompression
  • Well-tested: 0 failures across all 1065 MIPLIB 2017 instances

Install

pip install numnom

# Optional: scipy.sparse integration
pip install "numnom[scipy]"

Usage

import numnom

model = numnom.parse_file("problem.mps.gz")

print(model.name, model.num_row, "rows,", model.num_col, "cols")
print("Nonzeros:", model.a_matrix.value.size)

# Numpy arrays — zero-copy from Rust
model.col_cost      # np.ndarray[float64], shape (num_col,)
model.col_lower     # np.ndarray[float64]
model.col_upper     # np.ndarray[float64]
model.row_lower     # np.ndarray[float64]
model.row_upper     # np.ndarray[float64]
model.col_integrality  # np.ndarray[uint8] — see numnom.{CONTINUOUS,INTEGER,...}

# CSC sparse matrix
A = model.a_matrix
A.start    # np.ndarray[uint32], shape (num_col + 1,)
A.index    # np.ndarray[uint32], shape (nnz,)
A.value    # np.ndarray[float64], shape (nnz,)

# Names
model.col_names    # list[str]
model.row_names    # list[str]

scipy.sparse integration

import numnom

model = numnom.parse_file("problem.mps")
A = numnom.to_scipy(model)   # scipy.sparse.csc_matrix, shape (num_row, num_col)

Parse from string

mps_text = open("problem.mps").read()
model = numnom.parse_str(mps_text)

Write MPS

numnom.write_file(model, "out.mps")
mps_text = numnom.write_str(model)

Variable type codes

model.col_integrality is a uint8 array; values map to:

Code Constant Meaning
0 numnom.CONTINUOUS Continuous
1 numnom.INTEGER Integer
2 numnom.SEMI_CONTINUOUS Semi-continuous
3 numnom.SEMI_INTEGER Semi-integer

License

Apache-2.0

Project links

Data verified by PyPI on Apr 19, 2026
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Key dates

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  • Released:
Latest release

1 maintainer

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Avatar for mmghannam from gravatar.com mmghannam

Credits

Author: Mohammed Ghannam

GitHub Statistics

Data verified by PyPI on Apr 19, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

Apache Software License (Apache-2.0)

Requires

Python >=3.8

Provides Extra

scipy

Tags

mps parser optimization linear-programming mip

Classifiers

Report project as malware

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