[wip] Pandas Dataframe in Dataclass #3116

Future-Outlier · 2025-02-07T03:03:54Z

Tracking issue

Why are the changes needed?

we want to improve UX.

import flytekit
from flytekit import task, workflow
from dataclasses import dataclass, field
import pandas as pd
# from pydantic import BaseModel
from flytekit.types.structured.structured_dataset import (
    PARQUET,
    StructuredDataset,
    StructuredDatasetDecoder,
    StructuredDatasetEncoder,
    StructuredDatasetTransformerEngine,
)

@dataclass
class smallDC:
    df: pd.DataFrame = field(default_factory=lambda: pd.DataFrame([[1, 2, 3], [4, 5, 6]]))

@dataclass
class DC:
    dc: smallDC
    df: pd.DataFrame = field(default_factory=lambda: pd.DataFrame([[1, 2, 3], [4, 5, 6]]))

@task
def t1() -> DC:
    return DC(dc=smallDC())

if __name__ == "__main__":
    print(t1())

What changes were proposed in this pull request?

How was this patch tested?

Setup process

Screenshots

Check all the applicable boxes

I updated the documentation accordingly.
All new and existing tests passed.
All commits are signed-off.

Related PRs

Docs link

Summary by Bito

This PR enhances Flytekit's functionality in multiple areas: 1) Improves the DataclassTransformer with automatic Pandas DataFrame to StructuredDataset conversion and better type handling, 2) Enhances error handling and validation for msgpack data, authentication, and secret mount management, 3) Implements recursive transformation capabilities and improved JSON decoding, 4) Introduces configurable caching policies and strengthens type validation features.

Unit tests added: True

Estimated effort to review (1-5, lower is better): 5

Signed-off-by: Future-Outlier <[email protected]>

flyte-bot · 2025-02-07T03:04:08Z

Code Review Agent Run #fedbf7

Actionable Suggestions - 2

flytekit/core/type_engine.py - 2
- Consider dedicated transformer for DataFrame conversion · Line 882-884
- Consider caching decoder with original type · Line 1028-1029

Review Details

Files reviewed - 2 · Commit Range: 28db576..28db576
- flytekit/core/type_engine.py
- flytekit/types/structured/structured_dataset.py
Files skipped - 0
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flyte-bot · 2025-02-07T03:07:17Z

Changelist by Bito

This pull request implements the following key changes.

Key Change	Files Impacted
Feature Improvement - Enhanced Dataclass Type Handling with Pandas Support	- `type_engine.py` - Added support for Pandas DataFrame in dataclasses with automatic conversion to StructuredDataset and improved type transformation logic

flyte-bot · 2025-02-07T03:07:18Z

flytekit/core/type_engine.py

+            import pandas as pd
+            if isinstance(python_val, pd.DataFrame):
+                python_val = StructuredDataset(dataframe=python_val, file_format="parquet")


Consider dedicated transformer for DataFrame conversion

Consider moving the pandas DataFrame conversion logic to a dedicated transformer class instead of handling it in the _make_dataclass_serializable method. This would improve code organization and maintainability.

Code suggestion

Check the AI-generated fix before applying

Suggested change

import pandas as pd

if isinstance(python_val, pd.DataFrame):

python_val = StructuredDataset(dataframe=python_val, file_format="parquet")

Code Review Run #fedbf7

Is this a valid issue, or was it incorrectly flagged by the Agent?

it was incorrectly flagged

flyte-bot · 2025-02-07T03:07:19Z

flytekit/core/type_engine.py

+                decoder = JSONDecoder(new_expected_python_type)
+                self._json_decoder[new_expected_python_type] = decoder


Consider caching decoder with original type

Consider storing the decoder in the original expected_python_type key instead of new_expected_python_type to avoid potential memory leaks from storing multiple decoders for the same logical type.

Code suggestion

Check the AI-generated fix before applying

Suggested change

decoder = JSONDecoder(new_expected_python_type)

self._json_decoder[new_expected_python_type] = decoder

decoder = JSONDecoder(new_expected_python_type)

self._json_decoder[expected_python_type] = decoder

Code Review Run #fedbf7

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it was incorrectly flagged

Signed-off-by: Future-Outlier <[email protected]>

flyte-bot · 2025-02-07T05:18:00Z

Code Review Agent Run #6cea0d

Actionable Suggestions - 0

Review Details

Files reviewed - 2 · Commit Range: 28db576..fc506fe
- flytekit/core/type_engine.py
- flytekit/types/structured/structured_dataset.py
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flyte-bot · 2025-02-07T08:41:41Z

Code Review Agent Run #b16268

Actionable Suggestions - 2

flytekit/core/type_engine.py - 2
- Consider adding type hints to function · Line 972-972
- Consider validating dataclass field compatibility · Line 1032-1032

Review Details

Files reviewed - 1 · Commit Range: fc506fe..de150b1
- flytekit/core/type_engine.py
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flyte-bot · 2025-02-07T08:44:44Z

flytekit/core/type_engine.py

+        from flytekit.types.structured.structured_dataset import StructuredDataset
+        from typing import get_type_hints, Type, Dict
+
+        def convert_dataclass(instance, target_cls):


Consider adding type hints to function

The convert_dataclass function could benefit from type hints for better code maintainability and IDE support. Consider adding type annotations for instance and target_cls parameters.

Code suggestion

Check the AI-generated fix before applying

Suggested change

def convert_dataclass(instance, target_cls):

def convert_dataclass(instance: Any, target_cls: Type[T]) -> T:

Code Review Run #b16268

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it was incorrectly flagged

flyte-bot · 2025-02-07T08:44:45Z

flytekit/core/type_engine.py


            dc = decoder.decode(json_str)

-        return self._fix_dataclass_int(expected_python_type, dc)
+        return convert_dataclass(self._fix_dataclass_int(new_expected_python_type, dc), expected_python_type)


Consider validating dataclass field compatibility

The conversion from new_expected_python_type to expected_python_type may lose data if the types have different field structures. Consider validating field compatibility before conversion.

Code suggestion

Check the AI-generated fix before applying

Suggested change

return convert_dataclass(self._fix_dataclass_int(new_expected_python_type, dc), expected_python_type)

fixed_dc = self._fix_dataclass_int(new_expected_python_type, dc)

# Validate field compatibility

if not all(f.name in [ef.name for ef in fields(expected_python_type)] for f in fields(fixed_dc.__class__)):

raise ValueError(f"Incompatible field structure between {new_expected_python_type.__name__} and {expected_python_type.__name__}")

return convert_dataclass(fixed_dc, expected_python_type)

Code Review Run #b16268

Is this a valid issue, or was it incorrectly flagged by the Agent?

it was incorrectly flagged

Signed-off-by: Future-Outlier <[email protected]>

flyte-bot · 2025-02-10T15:32:25Z

Code Review Agent Run #9c627a

Actionable Suggestions - 1

flytekit/core/type_engine.py - 1
- Consider extracting duplicated transform_dataclass function · Line 689-710

Review Details

Files reviewed - 1 · Commit Range: de150b1..2a3bffe
- flytekit/core/type_engine.py
Files skipped - 0
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flyte-bot · 2025-02-10T15:35:43Z

flytekit/core/type_engine.py

+        def transform_dataclass(cls, memo=None):
+            if memo is None:
+                memo = {}
+
+            if cls in memo:
+                return memo[cls]
+
+            cls_hints = get_type_hints(cls)
+            new_field_defs = []
+            for field in fields(cls):
+                orig_type = cls_hints[field.name]
+                if orig_type == pd.DataFrame:
+                    new_type = StructuredDataset
+                elif is_dataclass(orig_type):
+                    new_type = transform_dataclass(orig_type, memo)
+                else:
+                    new_type = orig_type
+                new_field_defs.append((field.name, new_type))
+
+            new_cls = make_dataclass("FlyteModified" + cls.__name__, new_field_defs)
+            memo[cls] = new_cls
+            return new_cls


Consider extracting duplicated transform_dataclass function

Consider extracting the transform_dataclass function to avoid code duplication. This function appears multiple times in the codebase (lines 689-710, 764-785, and 1014-1035) with identical functionality.

Code suggestion

Check the AI-generated fix before applying

Suggested change

def transform_dataclass(cls, memo=None):

if memo is None:

memo = {}

if cls in memo:

return memo[cls]

cls_hints = get_type_hints(cls)

new_field_defs = []

for field in fields(cls):

orig_type = cls_hints[field.name]

if orig_type == pd.DataFrame:

new_type = StructuredDataset

elif is_dataclass(orig_type):

new_type = transform_dataclass(orig_type, memo)

else:

new_type = orig_type

new_field_defs.append((field.name, new_type))

new_cls = make_dataclass("FlyteModified" + cls.__name__, new_field_defs)

memo[cls] = new_cls

return new_cls

from flytekit.core.utils import transform_dataclass

Code Review Run #9c627a

Is this a valid issue, or was it incorrectly flagged by the Agent?

it was incorrectly flagged

Signed-off-by: Future-Outlier <[email protected]>

codecov · 2025-02-14T04:09:08Z

Codecov Report

Attention: Patch coverage is 1.69492% with 116 lines in your changes missing coverage. Please review.

Project coverage is 41.34%. Comparing base (66d4aed) to head (b5f2a6f).

Files with missing lines	Patch %	Lines
flytekit/core/type_engine.py	1.69%	116 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##           master    #3116       +/-   ##
===========================================
- Coverage   76.85%   41.34%   -35.52%     
===========================================
  Files         206      206               
  Lines       21851    21955      +104     
  Branches     2837     2860       +23     
===========================================
- Hits        16794     9077     -7717     
- Misses       4269    12729     +8460     
+ Partials      788      149      -639

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

flyte-bot · 2025-02-14T05:33:47Z

Code Review Agent Run #e17dbe

Actionable Suggestions - 3

flytekit/core/type_engine.py - 3
- Consider moving constant to module level · Line 776-778
- Consider moving constant to module level · Line 776-778
- Consider using immutable type for constants · Line 776-778

Review Details

Files reviewed - 1 · Commit Range: 2a3bffe..1625381
- flytekit/core/type_engine.py
Files skipped - 0
Tools
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flyte-bot · 2025-02-14T05:36:50Z

flytekit/core/type_engine.py

+            FLYTE_TYPES = [FlyteFile, FlyteDirectory, StructuredDataset, FlyteSchema]
+            if cls in FLYTE_TYPES:
+                return cls


Consider moving constant to module level

Consider moving the FLYTE_TYPES list to a module-level constant since it's used in multiple places within the same file. This would improve maintainability and reduce duplication.

Code suggestion

Check the AI-generated fix before applying

Suggested change

FLYTE_TYPES = [FlyteFile, FlyteDirectory, StructuredDataset, FlyteSchema]

if cls in FLYTE_TYPES:

return cls

FLYTE_TYPES = [FlyteFile, FlyteDirectory, StructuredDataset, FlyteSchema]

if cls in FLYTE_TYPES: return cls

Code Review Run #e17dbe

Is this a valid issue, or was it incorrectly flagged by the Agent?

it was incorrectly flagged

flyte-bot · 2025-02-14T05:36:51Z

flytekit/core/type_engine.py

+            FLYTE_TYPES = [FlyteFile, FlyteDirectory, StructuredDataset, FlyteSchema]
+            if cls in FLYTE_TYPES:
+                return cls


Consider using immutable type for constants

Consider using a tuple or frozenset instead of list for FLYTE_TYPES since it appears to be a constant collection that won't be modified. This provides better performance for lookups and makes the intent clearer.

Code suggestion

Check the AI-generated fix before applying

Suggested change

FLYTE_TYPES = [FlyteFile, FlyteDirectory, StructuredDataset, FlyteSchema]

if cls in FLYTE_TYPES:

return cls

FLYTE_TYPES = (FlyteFile, FlyteDirectory, StructuredDataset, FlyteSchema)

if cls in FLYTE_TYPES:

return cls

Code Review Run #e17dbe

Is this a valid issue, or was it incorrectly flagged by the Agent?

it was incorrectly flagged

Signed-off-by: Future-Outlier <[email protected]>

flyte-bot · 2025-02-14T15:21:53Z

Code Review Agent Run #c4bd83

Actionable Suggestions - 1

flytekit/core/type_engine.py - 1
- Potential encoder type mismatch issue · Line 740-740

Review Details

Files reviewed - 1 · Commit Range: 1625381..d9d438e
- flytekit/core/type_engine.py
Files skipped - 0
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flyte-bot · 2025-02-14T15:24:50Z

flytekit/core/type_engine.py

@@ -702,7 +737,7 @@ def to_generic_literal(
                encoder = self._json_encoder[python_type]
            except KeyError:
                encoder = JSONEncoder(python_type)
-                self._json_encoder[python_type] = encoder
+                self._json_encoder[new_python_type] = encoder


Potential encoder type mismatch issue

Consider using python_type instead of new_python_type when storing the encoder in self._json_encoder. The encoder is created using python_type but stored with new_python_type, which could lead to inconsistencies in encoder lookup.

Code suggestion

Check the AI-generated fix before applying

Suggested change

self._json_encoder[new_python_type] = encoder

self._json_encoder[python_type] = encoder

Code Review Run #c4bd83

Is this a valid issue, or was it incorrectly flagged by the Agent?

it was incorrectly flagged

Signed-off-by: Future-Outlier <[email protected]>

flyte-bot · 2025-02-17T08:32:42Z

Code Review Agent Run #8760de

Actionable Suggestions - 0

Additional Suggestions - 10

flytekit/core/python_auto_container.py - 1
- Consider adding shared memory param validation · Line 55-55
flytekit/core/python_function_task.py - 1
- Consider using context for signal handlers · Line 631-634
tests/flytekit/unit/utils/test_rate_limiter.py - 2
- Consider consolidating duplicate rate limiter tests · Line 27-31
- Consider adding edge case tests · Line 27-31
flytekit/configuration/plugin.py - 1
- Consider default implementation for cache policies · Line 58-59
flytekit/remote/remote.py - 5
- Consider adding interruptible parameter validation · Line 1993-1993
- Consider adding interruptible parameter validation · Line 1944-1944
- Consider splitting version resolution logic · Line 811-825
- Consider adding interruptible parameter validation · Line 2056-2056
- Consider refactoring array node handling logic · Line 2555-2633

Review Details

Files reviewed - 65 · Commit Range: d9d438e..b5f2a6f
- flytekit/__init__.py
- flytekit/clients/auth_helper.py
- flytekit/clients/grpc_utils/auth_interceptor.py
- flytekit/clis/sdk_in_container/init.py
- flytekit/clis/sdk_in_container/run.py
- flytekit/configuration/plugin.py
- flytekit/core/cache.py
- flytekit/core/constants.py
- flytekit/core/node.py
- flytekit/core/promise.py
- flytekit/core/python_auto_container.py
- flytekit/core/python_function_task.py
- flytekit/core/resources.py
- flytekit/core/task.py
- flytekit/core/type_engine.py
- flytekit/core/type_match_checking.py
- flytekit/core/worker_queue.py
- flytekit/core/workflow.py
- flytekit/image_spec/default_builder.py
- flytekit/image_spec/image_spec.py
- flytekit/interaction/click_types.py
- flytekit/interaction/string_literals.py
- flytekit/loggers.py
- flytekit/models/core/workflow.py
- flytekit/models/execution.py
- flytekit/models/security.py
- flytekit/models/task.py
- flytekit/remote/data.py
- flytekit/remote/remote.py
- flytekit/utils/rate_limiter.py
- plugins/flytekit-aws-sagemaker/tests/test_boto3_agent.py
- plugins/flytekit-onnx-pytorch/dev-requirements.txt
- plugins/flytekit-openai/tests/openai_batch/test_agent.py
- plugins/flytekit-pandera/flytekitplugins/pandera/pandas_transformer.py
- plugins/flytekit-pandera/setup.py
- pydoclint-errors-baseline.txt
- pyproject.toml
- tests/flytekit/integration/remote/test_remote.py
- tests/flytekit/integration/remote/workflows/basic/dataclass_wf.py
- tests/flytekit/unit/bin/test_python_entrypoint.py
- tests/flytekit/unit/cli/pyflyte/test_run.py
- tests/flytekit/unit/cli/pyflyte/test_run_lps.py
- tests/flytekit/unit/clients/auth/test_keyring_store.py
- tests/flytekit/unit/clients/test_auth_helper.py
- tests/flytekit/unit/clients/test_friendly.py
- tests/flytekit/unit/clients/test_raw.py
- tests/flytekit/unit/core/image_spec/test_default_builder.py
- tests/flytekit/unit/core/image_spec/test_image_spec.py
- tests/flytekit/unit/core/test_annotated_bindings.py
- tests/flytekit/unit/core/test_array_node_map_task.py
- tests/flytekit/unit/core/test_cache.py
- tests/flytekit/unit/core/test_generice_idl_type_engine.py
- tests/flytekit/unit/core/test_node_creation.py
- tests/flytekit/unit/core/test_resources.py
- tests/flytekit/unit/core/test_type_engine.py
- tests/flytekit/unit/core/test_type_match_checking.py
- tests/flytekit/unit/core/test_worker_queue.py
- tests/flytekit/unit/interaction/test_click_types.py
- tests/flytekit/unit/interaction/test_string_literals.py
- tests/flytekit/unit/models/core/test_security.py
- tests/flytekit/unit/models/core/test_workflow.py
- tests/flytekit/unit/models/test_execution.py
- tests/flytekit/unit/models/test_tasks.py
- tests/flytekit/unit/types/structured_dataset/test_structured_dataset.py
- tests/flytekit/unit/utils/test_rate_limiter.py
Files skipped - 1
- .gitignore - Reason: Filter setting
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Pandas Dataframe in Dataclass

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Signed-off-by: Future-Outlier <[email protected]>

Future-Outlier requested review from wild-endeavor, kumare3, eapolinario, pingsutw, cosmicBboy, samhita-alla and thomasjpfan as code owners February 7, 2025 03:03

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[wip] Pandas Dataframe in Dataclass #3116

[wip] Pandas Dataframe in Dataclass #3116

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	import pandas as pd
	if isinstance(python_val, pd.DataFrame):
	python_val = StructuredDataset(dataframe=python_val, file_format="parquet")

		decoder = JSONDecoder(new_expected_python_type)
		self._json_decoder[new_expected_python_type] = decoder

	def convert_dataclass(instance, target_cls):
	def convert_dataclass(instance: Any, target_cls: Type[T]) -> T:

-        return convert_dataclass(self._fix_dataclass_int(new_expected_python_type, dc), expected_python_type)
+        fixed_dc = self._fix_dataclass_int(new_expected_python_type, dc)
+        # Validate field compatibility
+        if not all(f.name in [ef.name for ef in fields(expected_python_type)] for f in fields(fixed_dc.__class__)):
+            raise ValueError(f"Incompatible field structure between {new_expected_python_type.__name__} and {expected_python_type.__name__}")
+        return convert_dataclass(fixed_dc, expected_python_type)

	self._json_encoder[new_python_type] = encoder
	self._json_encoder[python_type] = encoder

[wip] Pandas Dataframe in Dataclass #3116

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[wip] Pandas Dataframe in Dataclass #3116

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Future-Outlier commented Feb 7, 2025 • edited by flyte-bot Loading

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