merge style and docs fixes from stable-0.8

Author: basnijholt

README.rst

@@ -113,7 +113,7 @@ please setup the git filter by executing
 
 in the repository.
 
-We implement several other checks in order to maintain a consistent code style. We do this using [pre-commit`](https://pre-commit.com), execute
+We implement several other checks in order to maintain a consistent code style. We do this using `pre-commit <https://pre-commit.com>`_, execute
 
 .. code:: bash
 

adaptive/learner/integrator_learner.py

@@ -390,7 +390,7 @@ def approximating_intervals(self):
 
     def tell(self, point, value):
         if point not in self.x_mapping:
-            raise ValueError("Point {} doesn't belong to any interval".format(point))
+            raise ValueError(f"Point {point} doesn't belong to any interval")
         self.done_points[point] = value
         self.pending_points.discard(point)
 

adaptive/runner.py

@@ -751,4 +751,4 @@ def _get_ncores(ex):
         ex.bootup()  # wait until all workers are up and running
         return ex._pool.size  # not public API!
     else:
-        raise TypeError("Cannot get number of cores for {}".format(ex.__class__))
+        raise TypeError(f"Cannot get number of cores for {ex.__class__}")

adaptive/tests/test_cquad.py

@@ -204,9 +204,7 @@ def test_tell_in_random_order(first_add_33=False):
         assert all(ival.a == other_ival.a for ival, other_ival in zip(*ivals))
 
         # Test if the approximating_intervals are the same
-        ivals = [
-            {(i.a, i.b) for i in learner.approximating_intervals} for l in learners
-        ]
+        ivals = [{(i.a, i.b) for i in l.approximating_intervals} for l in learners]
         assert ivals[0] == ivals[1]
 
         # Test whether the igral is identical

adaptive/tests/test_learners.py

@@ -75,7 +75,7 @@ def generate_random_parametrization(f):
     _, *params = inspect.signature(f).parameters.items()
     if any(not callable(v.annotation) for (p, v) in params):
         raise TypeError(
-            "All parameters to {} must be annotated with functions.".format(f.__name__)
+            f"All parameters to {f.__name__} must be annotated with functions."
         )
     realization = {p: v.annotation() for (p, v) in params}
     return ft.partial(f, **realization)

docs/environment.yml

@@ -1,18 +1,18 @@
 name: adaptive
 
 channels:
-- conda-forge
+  - conda-forge
 
 dependencies:
-  - python=3.7
+  - python=3.7.3
+  - sortedcollections=1.1.2
+  - scikit-optimize=0.5.2
+  - scipy=1.2.1
+  - holoviews=1.11.3
+  - bokeh=1.0.4
+  - plotly=3.9.0
+  - ipywidgets=7.4.2
   - pip:
-    - sortedcollections
-    - scipy
-    - holoviews==1.12*
-    - bokeh==1.1*
-    - plotly
-    - ipywidgets
-    - scikit-optimize
     - git+https://github.com/basnijholt/jupyter-sphinx.git@widgets_execute
-    - sphinx_fontawesome
-    - m2r
+    - sphinx_fontawesome==0.0.6
+    - m2r==0.2.1