replace try with specific ifs

graphistry/ai_utils.py

@@ -1,6 +1,6 @@
 import pandas as pd
 import numpy as np
-
+from inspect import getmodule
 import graphistry
 
 from .constants import DISTANCE, WEIGHT, BATCH
@@ -422,9 +422,9 @@ def infer_self_graph(res,
         assert (
             emb.shape[0] == df.shape[0]
         ), "minibatches emb and X must have same number of rows since h(df) = emb"
-        try:
+        if emb.x is not None:
             df = df.assign(x=emb.x, y=emb.y)  # add x and y to df for graphistry instance
-        except AttributeError:
+        else:
             df = df.assign(x=emb[0], y=emb[1])  # if umap kwargs n_components > 2, take first 2 here 
     else:  # if umap has been fit, but only transforming over features, need to add x and y or breaks plot binds of res
         df['x'] = np.random.random(df.shape[0])
@@ -454,9 +454,9 @@ def infer_self_graph(res,
             diff = np.array(diff, dtype = 'float')
         except TypeError:
             pass
-        try:
+        if 'pandas' in str(getmodule(diff)):
             dist = np.linalg.norm(diff, axis=1)  # Euclidean distance
-        except TypeError:
+        else:
             dist = np.linalg.norm(diff.to_pandas(), axis=1)  # Euclidean distance
         mdists.append(dist)
 

graphistry/dep_manager.py

@@ -19,7 +19,7 @@ def _add_deps(self, pkg:str):
         except:
             pass
 
-    def import_from(self,pkg:str, name:str):
+    def import_from(self, pkg:str, name:str):
         try:
             module = __import__(pkg, fromlist=[name])
             self.pkgs[name] = module