Re: [PR] fix(csv upload): Correctly casting to string numbers with floating points (e+) [superset]

Thu, 09 Oct 2025 12:03:49 -0700 


korbit-ai[bot] commented on code in PR #35586:
URL: https://github.com/apache/superset/pull/35586#discussion_r2417710259


##########
superset/commands/database/uploaders/csv_reader.py:
##########
@@ -357,7 +357,28 @@ def _read_csv(  # noqa: C901
         kwargs["low_memory"] = False
 
         try:
-            types = kwargs.pop("dtype", None)
+            # Only pop types that are not str or object
+            original_types = kwargs.get("dtype", None)
+            types = None
+            if original_types:
+                # keep str/object in kwargs, extract others for custom casting
+                pandas_types = {}
+                custom_types = {}

Review Comment:
   ### Missing type handling encapsulation <sub>![category 
Design](https://img.shields.io/badge/Design-0d9488)</sub>
   
   <details>
     <summary>Tell me more</summary>
   
   ###### What is the issue?
   Type handling logic is embedded within the _read_csv method instead of being 
encapsulated in a dedicated type handling class or method.
   
   
   ###### Why this matters
   Mixing type handling with CSV reading logic reduces code reusability and 
makes it harder to modify type handling behavior independently.
   
   ###### Suggested change ∙ *Feature Preview*
   Create a dedicated TypeHandler class:
   ```python
   class CSVTypeHandler:
       def split_types(self, types: dict[str, str]) -> tuple[dict[str, str], 
dict[str, str]]:
           pandas_types = {col: dtype for col, dtype in types.items() if dtype 
in ('str', 'object', 'string')}
           custom_types = {col: dtype for col, dtype in types.items() if dtype 
not in ('str', 'object', 'string')}
           return pandas_types, custom_types
   ```
   
   
   ###### Provide feedback to improve future suggestions
   [![Nice 
Catch](https://img.shields.io/badge/👍%20Nice%20Catch-71BC78)](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a736bb38-bf95-47ff-9369-3b100dbe7f46/upvote)
 
[![Incorrect](https://img.shields.io/badge/👎%20Incorrect-white)](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a736bb38-bf95-47ff-9369-3b100dbe7f46?what_not_true=true)
  [![Not in 
Scope](https://img.shields.io/badge/👎%20Out%20of%20PR%20scope-white)](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a736bb38-bf95-47ff-9369-3b100dbe7f46?what_out_of_scope=true)
 [![Not in coding 
standard](https://img.shields.io/badge/👎%20Not%20in%20our%20standards-white)](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a736bb38-bf95-47ff-9369-3b100dbe7f46?what_not_in_standard=true)
 
[![Other](https://img.shields.io/badge/👎%20Other-white)](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a736bb38-bf95-47ff-9369-3b100dbe7f46)
   </details>
   
   <sub>
   
   💬 Looking for more details? Reply to this comment to chat with Korbit.
   </sub>
   
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   [](f8dd1a16-addf-4635-8e47-17617b73a291)



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