Mip

- ability to read and write LP optimal basis files (.bas extension)
- speedup gurobi initialization, thanks jurasofish
- fix for querying column contents in callbacks, thanks rodoufu
- fix for mip gap, thanks nick-gorman
- fix for cbc in dense conflict graphs

- Two additional parameters, three depth and pass number, are now informed to the generage_constrs method in ConstrsGenerator class (which is used for cut/lazy constraints callbacks). Thus, strategies that generate more/less cuts at a given depth can use this information. See [here](https://python-mip.readthedocs.io/en/latest/classes.html#mip.ConstrsGenerator) .

- Cut generators: additional cut generators can now be called at the root node in customized cutting planes algorithms, see [here](https://python-mip.readthedocs.io/en/latest/classes.html#cuttype) .

- Instance features: it is now possible to query a vector of instance features. These features can be used in machine learning algorithms, for example, to decide the best parameter settings. Basic features are just the problems dimensions, e.g.: columns, rows, non-zeros. The current implementation extracts 208 instance features. To see an implementation of algorithm selection that is used in the COIN-OR Linear Programming Solver (CLP) check: Vilas Boas, M.G., Santos, H.G., Merschmann, L.H.C. and Vanden Berghe, G. [Optimal Decision Trees for the Algorithm Selection Problem: Integer Programming Based Approaches](https://arxiv.org/abs/1907.02211). International Transactions in Operational Research, DOI 10.1111/itor.12724. 2019.

This release release adds a new model method: clique_merge, which merges constraints of conflicting variables (usually set packing) to produce a more compact and stronger formulation.

Two new stopping criteria were added: max nodes/seconds without improving the incumbent solution.

We also added more tests and fixed some bugs in the Cbc C Interface.

- fix for loading MIPStart from a file
- test for support for .gz and .bz2
- remove mutable default arguments 93
- tests now in github actions

Additions
- Possible to query solution value of a variable v with float(v), besides the traditional v.x, tks to jurasofish
Fixes:
- for models with only continuous variables and SOS, branch and bound should be executed
Documentation
- Much improved documentation for Special Ordered Sets - SOS
- Example including SOS of types 1 and 2

- The conflict graph of a MIP, indicading conflicting assignments for binary variables, can now be queried
- Initial (optional) support for numpy tensors
- Compatibility fixes for the MacOS binaries
- Speedup for querying solutions in the callbacks
- Documentation improvements