* in `ModelTree.hh` creates `dynamic_set_auxiliary_series()` that manipulates time series with `lag` and `lead` functions. We need to choose a time series representation in Python.
* in `ModelTree.hh` creates `dynamic_set_auxiliary_series()` that manipulates time series with `lag` and `lead` functions. We need to choose a time series representation in Python.
#### calling the bytecode library generated by the preprocessor
#### calling the bytecode library generated by the preprocessor
- the code for `bytecode``mex` file needs to separated between a `mex` wrapper and a standard `C`library
- the code for `bytecode``mex` file needs to separated between a `mex` wrapper and a standard `C` library
### Parse the JSON file `<modfilename>/model/json/modfile.json`
- This file contains `statementName` keys that describe computing tasks requested by the user
- See function `parse_statements!()` in `DynareJulia/src/DynareParser.jl`
### Decide about the distribution of Dynare Preprocessor for Python (should be transparent to the Python user who installs the Dynare Python package)
### Decide about the distribution of Dynare Preprocessor for Python (should be transparent to the Python user who installs the Dynare Python package)
- Ideally, installing the Dynare Python package should automatically download the binary Preprocessor adapted to the user's platform (as in Julia)
- Ideally, installing the Dynare Python package should automatically download the binary Preprocessor adapted to the user's platform (as in Julia)
### Check that a Python package can call Python code that it generated itself
- In Julia, this raise a `world age issue`
### Use JuliaCall to call DynareJulia
### Use JuliaCall to call DynareJulia
- See [JuliaCall](https://juliapy.github.io/PythonCall.jl/stable/juliacall/)
- See [JuliaCall](https://juliapy.github.io/PythonCall.jl/stable/juliacall/)
