Add some types to printing.py

pytensor/printing.py

@@ -1200,18 +1200,18 @@ def __call__(self, *args):
 
 def pydotprint(
     fct,
-    outfile=None,
-    compact=True,
-    format="png",
-    with_ids=False,
-    high_contrast=True,
+    outfile: str | None = None,
+    compact: bool = True,
+    format: str = "png",
+    with_ids: bool = False,
+    high_contrast: bool = True,
     cond_highlight=None,
-    colorCodes=None,
-    max_label_size=70,
-    scan_graphs=False,
-    var_with_name_simple=False,
-    print_output_file=True,
-    return_image=False,
+    colorCodes: dict | None = None,
+    max_label_size: int = 70,
+    scan_graphs: bool = False,
+    var_with_name_simple: bool = False,
+    print_output_file: bool = True,
+    return_image: bool = False,
 ):
     """Print to a file the graph of a compiled pytensor function's ops. Supports
     all pydot output formats, including png and svg.
@@ -1676,7 +1676,9 @@ def get_tag(self):
         return rval
 
 
-def min_informative_str(obj, indent_level=0, _prev_obs=None, _tag_generator=None):
+def min_informative_str(
+    obj, indent_level: int = 0, _prev_obs: dict | None = None, _tag_generator=None
+) -> str:
     """
     Returns a string specifying to the user what obj is
     The string will print out as much of the graph as is needed
@@ -1776,7 +1778,7 @@ def min_informative_str(obj, indent_level=0, _prev_obs=None, _tag_generator=None
     return rval
 
 
-def var_descriptor(obj, _prev_obs=None, _tag_generator=None):
+def var_descriptor(obj, _prev_obs: dict | None = None, _tag_generator=None) -> str:
     """
     Returns a string, with no endlines, fully specifying
     how a variable is computed. Does not include any memory
@@ -1832,7 +1834,7 @@ def var_descriptor(obj, _prev_obs=None, _tag_generator=None):
     return rval
 
 
-def position_independent_str(obj):
+def position_independent_str(obj) -> str:
     if isinstance(obj, Variable):
         rval = "pytensor_var"
         rval += "{type=" + str(obj.type) + "}"
@@ -1842,7 +1844,7 @@ def position_independent_str(obj):
     return rval
 
 
-def hex_digest(x):
+def hex_digest(x: np.ndarray) -> str:
     """
     Returns a short, mostly hexadecimal hash of a numpy ndarray
     """
@@ -1852,8 +1854,8 @@ def hex_digest(x):
     # because the buffer interface only exposes the raw data, not
     # any info about the semantics of how that data should be arranged
     # into a tensor
-    rval = rval + "|strides=[" + ",".join(str(stride) for stride in x.strides) + "]"
-    rval = rval + "|shape=[" + ",".join(str(s) for s in x.shape) + "]"
+    rval += "|strides=[" + ",".join(str(stride) for stride in x.strides) + "]"
+    rval += "|shape=[" + ",".join(str(s) for s in x.shape) + "]"
     return rval