Add type-hints to adaptive/notebook_integration.py

Author: basnijholt

adaptive/notebook_integration.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import asyncio
 import datetime
 import importlib
@@ -76,7 +78,7 @@ def ensure_plotly():
         raise RuntimeError("plotly is not installed; plotting is disabled.")
 
 
-def in_ipynb():
+def in_ipynb() -> bool:
     try:
         # If we are running in IPython, then `get_ipython()` is always a global
         return get_ipython().__class__.__name__ == "ZMQInteractiveShell"

adaptive/tests/test_average_learner1d.py

@@ -1,6 +1,6 @@
+from itertools import chain
+
 import numpy as np
-import pandas as pd
-from pandas.testing import assert_series_equal
 
 from adaptive import AverageLearner1D
 from adaptive.tests.test_learners import (
@@ -11,13 +11,27 @@
 
 
 def almost_equal_dicts(a, b):
-    assert_series_equal(pd.Series(sorted(a.items())), pd.Series(sorted(b.items())))
+    assert a.keys() == b.keys()
+    for k, v1 in a.items():
+        v2 = b[k]
+        if (
+            v1 is None
+            or v2 is None
+            or isinstance(v1, (tuple, list))
+            and any(x is None for x in chain(v1, v2))
+        ):
+            assert v1 == v2
+        else:
+            try:
+                np.testing.assert_almost_equal(v1, v2)
+            except TypeError:
+                raise AssertionError(f"{v1} != {v2}")
 
 
 def test_tell_many_at_point():
     f = generate_random_parametrization(noisy_peak)
     learner = AverageLearner1D(f, bounds=(-2, 2))
-    control = AverageLearner1D(f, bounds=(-2, 2))
+    control = learner.new()
     learner._recompute_losses_factor = 1
     control._recompute_losses_factor = 1
     simple_run(learner, 100)

adaptive/tests/test_learners.py

@@ -12,7 +12,6 @@
 
 import flaky
 import numpy as np
-import pandas
 import pytest
 import scipy.spatial
 
@@ -28,6 +27,7 @@
     LearnerND,
     SequenceLearner,
 )
+from adaptive.learner.learner1D import with_pandas
 from adaptive.runner import simple
 
 try:
@@ -708,6 +708,7 @@ def wrapper(*args, **kwargs):
     return wrapper
 
 
+@pytest.mark.skipif(not with_pandas, reason="pandas is not installed")
 @run_with(
     Learner1D,
     Learner2D,
@@ -719,6 +720,8 @@ def wrapper(*args, **kwargs):
     with_all_loss_functions=False,
 )
 def test_to_dataframe(learner_type, f, learner_kwargs):
+    import pandas
+
     if learner_type is LearnerND:
         kw = {"point_names": tuple("xyz")[: len(learner_kwargs["bounds"])]}
     else:

adaptive/utils.py

@@ -45,7 +45,7 @@ def wrapper(*args, **kwargs):
     return wrapper
 
 
-def save(fname: str, data: Any, compress: bool = True) -> None:
+def save(fname: str, data: Any, compress: bool = True) -> bool:
     fname = os.path.expanduser(fname)
     dirname = os.path.dirname(fname)
     if dirname:
@@ -74,7 +74,7 @@ def save(fname: str, data: Any, compress: bool = True) -> None:
     return True
 
 
-def load(fname: str, compress: bool = True):
+def load(fname: str, compress: bool = True) -> Any:
     fname = os.path.expanduser(fname)
     _open = gzip.open if compress else open
     with _open(fname, "rb") as f:

setup.py

@@ -42,6 +42,7 @@ def get_version_and_cmdclass(package_name):
         "holoviews>=1.9.1",
         "ipywidgets",
         "bokeh",
+        "pandas",
         "matplotlib",
         "plotly",
     ],
@@ -52,7 +53,6 @@ def get_version_and_cmdclass(package_name):
         "pytest-randomly",
         "pytest-timeout",
         "pre_commit",
-        "pandas",
         "typeguard",
     ],
     "other": [