Comments (7)
Indeed! Testing wasn't done on Windows, sorry for that. I think I have to come up with an alternative approach for checking whether a solver are installed. Do you have the glpk installed?
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No, I just recognized that I actually have not😅 However, I have gurobipy installed, which is not utilized/detected on startup. If glpk is required for linopy to run, maybe add it as a dependency as well?
from linopy.
The solvers are not required, and should be installed by the users, so that's fine. However the command for checking if glpk is installed fails. The error is the same when you write which glpsol
in your console, which fails due to which
not working on Windows. So probably even when you have glpk installed linopy still raises the same error (if I understand correctly).
from linopy.
Ahh, that makes sense. For Windows, the keyword where
is available, which should do the same trick. I will try to fix the issue tomorrow and make a pull-request
from linopy.
Great! I made a first attempt in https://github.com/PyPSA/linopy/tree/windows-compat, where I also added update the CI, let's see how that plays out.
from linopy.
Yes, this one works like a charm so far!
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Thanks for reporting @tburandt
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Related Issues (20)
- Optionally release memory during solving process
- [Feature] Support early stopping for solving such as allowing a relative optimality gap HOT 1
- Add solution values for linear expressions HOT 3
- Enable broadcasting when multiplying with pandas objects HOT 1
- How to add multi-objectives? HOT 6
- Support constant values in objective HOT 1
- Indicate applied masking in string representation of constraints HOT 3
- Change `dims` keyword of sum functions to `dim` HOT 1
- Support for sparse xarrays HOT 23
- show benchmark in readme
- Missing dimension when initializing variable with boundaries of lower dimensions HOT 2
- Improve documentation on overriding coordinates feature HOT 8
- Inconsistent coordinate override in arithmetic expressions HOT 3
- Docstring of `Model.solve()` has wrong return type
- `io_api="mps"` leads to memory overhead
- Error using scip
- Licensed CPLEX not detected HOT 3
- MPS IO changes with highspy >= 1.7
- Re-solving a changed model with "direct" api results in wrong model being solved HOT 1
- add_constraints lhs eats constant HOT 2
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