Projects: pypi: PuLP
https://packages.ecosyste.ms/registries/pypi.org/packages/PuLP
PuLP is an LP modeler written in python. PuLP can generate MPS or LP files and call GLPK, COIN CLP/CBC, CPLEX, and GUROBI to solve linear problems.
40 versions
Latest release: about 2 years ago
67 dependent packages
838,979 downloads last month
Enhanced Analysis
Educational Contributors:
ted@lehigh.edu
Repository Activity:
Repository Owner:
COIN-OR Foundation (organization)
Computational Infrastructure for Operations Research. Academic
Computational Infrastructure for Operations Research. Academic
README Analysis:
Science Score: 100/100
Starting Score: 100 points
Bonuses:
-
+20
Educational commit emails
1 contributors with educational email addresses -
+20
Academic repository owner
Repository owned by academic institution -
+15
Institutional repository owner
Repository owned by research institution -
+4
Science terms in README
2 scientific terms found in README
Penalties:
-
-10
PyPI ecosystem
General-purpose ecosystem -
-10
No science terms in description
No scientific terms found in description
Very Likely Science (100)
Papers Mentioning PuLP 4
10.1186/s13059-019-1783-3
AlleleAnalyzer: a tool for personalized and allele-specific sgRNA designCited by: 20
Author(s): Kathleen C. Keough, Svetlana Lyalina, Michael P. Olvera, Sean Whalen, Bruce R. Conklin, Katherine S. Pollard
Software Mentions: 14
Published: about 6 years ago
10.1186/s13059-020-02247-1
Uncovering deeply conserved motif combinations in rapidly evolving noncoding sequencesCited by: 22
Author(s): Caroline Jane Ross, Aviv Rom, Amit Spinrad, Dikla Gelbard-Solodkin, Neta Degani, Igor Ulitsky
Software Mentions: 5
Published: over 4 years ago
10.1186/s13015-021-00191-8
Using the longest run subsequence problem within homology-based scaffoldingCited by: 0
Author(s): Sven Schrinner, Manish Goel, Michael Wulfert, Philipp Spohr, Korbinian Schneeberger, Gunnar W. Klau
Software Mentions: 1
Published: about 4 years ago
10.1093/bioinformatics/btaa794
Finding orthologous gene blocks in bacteria: the computational hardness of the problem and novel methods to address itCited by: 1
Author(s): Huy Nguyen, Alexey Markin, Iddo Friedberg, Oliver Eulenstein
Software Mentions: 1
Published: almost 5 years ago