lp_solve | Mirror of lp_solve

I need to minimize a huge linear programming system where all related data (objective function, constraints) are stored in the memory in arrays and structures but not in lp file format or CPLEX

I saw that there are many solvers like here and here but the problem is how can I minimize the model without calling it from a file of a special format?

I did the same work previously in R and Python by solving the model directly after producing it without the need to save it initially in a special file and then call it by the solver. Here is an example in Python:

So I am creating a Docker container with python 3.6 runtime. I need a UX64 version of lp_solver (http://lpsolve.sourceforge.net/5.5/index.htm) for python. The one linked is python 2.7. I have found the following: https://github.com/chandu-atina/lp_solve_python_3x but it does not work either. Tried both approaches. I have really no idea how to get this lp_solver to work on Ubuntu Python 3.6. Is there something like the following: https://www.lfd.uci.edu/~gohlke/pythonlibs/#lp_solve but for Ubuntu?

Also found this, which worked: https://anaconda.org/snorfalorpagus/lpsolve but I cannot import lpsolve. (here is the question linked for importing lpsolve: Conda installation of lpsolve)

EDIT 1:

Here are the steps that I take:

I made a really simple linear problem for lp_solve.