Do tests of deprecated functions

pysr/deprecated.py

@@ -1,12 +1,15 @@
 """Various functions to deprecate features."""
 import warnings
 
+from .julia_import import jl
+
 
 def install(*args, **kwargs):
     del args, kwargs
     warnings.warn(
         "The `install` function has been removed. "
-        "PySR now uses the `juliacall` package to install its dependencies automatically at import time. "
+        "PySR now uses the `juliacall` package to install its dependencies automatically at import time. ",
+        FutureWarning,
     )
 
 
@@ -14,8 +17,10 @@ def init_julia(*args, **kwargs):
     del args, kwargs
     warnings.warn(
         "The `init_julia` function has been removed. "
-        "Julia is now initialized automatically at import time."
+        "Julia is now initialized automatically at import time.",
+        FutureWarning,
     )
+    return jl
 
 
 def pysr(X, y, weights=None, **kwargs):  # pragma: no cover

pysr/sr.py

@@ -870,12 +870,14 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
                     warnings.warn(
                         "The `julia_project` parameter has been deprecated. To use a custom "
                         "julia project, please see `https://astroautomata.com/PySR/backend`.",
+                        FutureWarning,
                     )
                 elif k == "julia_kwargs":
                     warnings.warn(
                         "The `julia_kwargs` parameter has been deprecated. To pass custom "
                         "keyword arguments to the julia backend, you should use environment variables. "
                         "See the Julia documentation for more information.",
+                        FutureWarning,
                     )
                 else:
                     raise TypeError(

pysr/test/test.py

@@ -11,9 +11,10 @@ import pandas as pd
 import sympy
 from sklearn.utils.estimator_checks import check_estimator
 
-from .. import PySRRegressor
+from .. import PySRRegressor, install, jl
 from ..export_latex import sympy2latex
 from ..feature_selection import _handle_feature_selection, run_feature_selection
+from ..julia_helpers import init_julia
 from ..sr import _check_assertions, _process_constraints, idx_model_selection
 from ..utils import _csv_filename_to_pkl_filename
 from .params import (
@@ -106,7 +107,6 @@ class TestPipeline(unittest.TestCase):
             warm_start=True,
         )
         model.fit(self.X, y)
-        from pysr.sr import jl
 
         # We should have that the model state is now a Float64 hof:
         jl.test_state = model.raw_julia_state_
@@ -228,8 +228,6 @@ class TestPipeline(unittest.TestCase):
             warm_start=True,
             early_stop_condition=None,
         )
-        # Check that the the julia state is saved:
-        from pysr import jl
 
         # We should have that the model state is now a Float32 hof:
         jl.test_state = regressor.raw_julia_state_
@@ -548,6 +546,17 @@ class TestMiscellaneous(unittest.TestCase):
         # The correct value should be set:
         self.assertEqual(model.fraction_replaced, 0.2)
 
+    def test_deprecated_functions(self):
+        with self.assertWarns(FutureWarning):
+            install()
+
+        _jl = None
+
+        with self.assertWarns(FutureWarning):
+            _jl = init_julia()
+
+        self.assertEqual(_jl, jl)
+
     def test_power_law_warning(self):
         """Ensure that a warning is given for a power law operator."""
         with self.assertWarns(UserWarning):