Fix HuggingFace dataset column name handling for invalid identifiers #1226

cursor · 2025-07-11T03:26:35Z

Fix HuggingFace dataset column name handling for invalid identifiers

🐛 Issue Fixed

Fixes #1204 - Reading from huggingface dataset fails with KeyError when column names contain invalid Python identifiers.

📋 Problem Description

Some datasets on the HuggingFace Hub have column names that are not valid Python identifiers (e.g., containing ?, -, spaces, or starting with numbers). When using dc.read_hf() with such datasets, the function would fail with a KeyError because the system was trying to access these invalid column names directly as Python attribute names.

Example that failed before this fix:

import datachain as dc
from datasets import load_dataset

ds = load_dataset('toxigen/toxigen-data', 'annotated', split='test')
dc.read_hf(ds)  # KeyError: 'factual?'

🔧 Solution

The fix leverages the existing normalize_col_names() function and dict_to_data_model() support for handling invalid Python identifiers by passing the original_names parameter.

Changes Made:

src/datachain/lib/dc/hf.py - Main fix in read_hf() function:
- Extract original column names from HuggingFace dataset features
- Pass these original names to dict_to_data_model() function
src/datachain/lib/hf.py - Fix in _feature_to_chain_type() function:
- Handle nested dictionary features with invalid column names
- Pass original names for nested structures
Comprehensive test coverage - Added tests in both unit and functional test files

🧪 Testing

Unit Tests (`tests/unit/lib/test_hf.py`):

test_hf_invalid_column_names() - Tests basic functionality with invalid column names
test_hf_invalid_column_names_with_read_hf() - Tests the read_hf() function directly
test_hf_sequence_dict_with_invalid_names() - Tests nested dictionary features with invalid names
Updated all existing tests to use the original_names parameter

Functional Tests (`tests/func/test_hf_invalid_column_names.py`):

test_hf_invalid_column_names_functional() - Comprehensive test with various invalid column name patterns
test_toxigen_dataset_simulation() - Simulates the exact issue from the GitHub issue

Test Coverage:

Column names with special characters (?, -, ., /)
Column names with spaces
Column names starting with numbers
Nested dictionary features with invalid names
Multiple invalid patterns in a single dataset

📊 Column Name Transformations

The fix automatically transforms invalid column names to valid Python identifiers:

factual? → factual_
user-name → user_name
123column → c0_123column
has spaces → has_spaces
with.dots → with_dots
with/slashes → with_slashes

✅ Benefits

Compatibility: DataChain can now work with any HuggingFace dataset, regardless of column naming conventions
Backward Compatibility: Existing code continues to work unchanged
Data Integrity: All original data is preserved and accessible
User Experience: No more mysterious KeyError exceptions when working with common HuggingFace datasets

🔍 How It Works

The dict_to_data_model() function has built-in support for handling invalid Python identifiers:

It normalizes column names using normalize_col_names() to create valid Python identifiers
It uses Pydantic's validation_alias=AliasChoices() to map between normalized names and original names
This allows the system to access data using normalized field names while preserving the original column names

📁 Files Modified

src/datachain/lib/dc/hf.py - Main fix implementation
src/datachain/lib/hf.py - Nested dictionary fix
tests/unit/lib/test_hf.py - Unit tests
tests/func/test_hf_invalid_column_names.py - Functional tests
BUGFIX_SUMMARY.md - Detailed documentation

🧪 Manual Testing

The fix can be verified with:

import datachain as dc
from datasets import Dataset

# Create dataset with invalid column names
ds = Dataset.from_dict({
    "factual?": ["yes", "no"],
    "user-name": ["alice", "bob"],
    "123column": ["value1", "value2"]
})

# This now works without error
chain = dc.read_hf(ds)

📚 References

Original issue: Reading from huggingface dataset #1204
Similar pattern used in other parts of the codebase for handling invalid identifiers
Follows existing test patterns in test_hf.py

Summary by Sourcery

Fix HuggingFace dataset column name handling for invalid Python identifiers by passing original column names through model generation

Bug Fixes:

Include original column names in dict_to_data_model call within read_hf to avoid KeyError on invalid identifiers
Extend nested dict feature conversion in _feature_to_chain_type to forward original_names for sub-fields

Documentation:

Add BUGFIX_SUMMARY.md documenting the issue, solution and column name transformations

Tests:

Add unit tests covering invalid column names in read_hf and nested sequence features
Add functional tests simulating various invalid naming patterns and the toxigen dataset scenario

Co-authored-by: ivan <[email protected]>

sourcery-ai · 2025-07-11T03:26:39Z

Reviewer's Guide

Enhance HuggingFace dataset integration to normalize invalid Python identifier column names by passing original_names to the data model generator and reinforce with comprehensive unit and functional tests.

Class diagram for handling HuggingFace dataset column names with invalid Python identifiers

classDiagram
    class read_hf {
        +dict_to_data_model(model_name, output, original_names)
    }
    class dict_to_data_model {
        +normalize_col_names()
        +validation_alias=AliasChoices()
    }
    class _feature_to_chain_type {
        +dict_to_data_model(name, sequence_dict, original_names)
    }
    read_hf --> dict_to_data_model : uses
    _feature_to_chain_type --> dict_to_data_model : uses
    dict_to_data_model --> normalize_col_names : uses
    dict_to_data_model --> AliasChoices : uses

Flow diagram for column name normalization and mapping in HuggingFace datasets

flowchart TD
    A[User loads HuggingFace dataset] --> B[Extract original column names]
    B --> C[Normalize column names to valid Python identifiers]
    C --> D[Pass original and normalized names to dict_to_data_model]
    D --> E[Create data model with alias mapping]
    E --> F[User accesses data using normalized names]
    F --> G[Original data preserved and accessible]

File-Level Changes

Change	Details	Files
Support original column names in dict_to_data_model	Extract original_names in read_hf Pass original_names to dict_to_data_model in read_hf Extract original_names in nested feature handler Pass original_names to dict_to_data_model in _feature_to_chain_type	`src/datachain/lib/dc/hf.py` `src/datachain/lib/hf.py`
Update existing unit tests to use original_names parameter	Modify HFGenerator instantiations to include original_names in all dict_to_data_model calls	`tests/unit/lib/test_hf.py`
Add unit tests for invalid identifier column names	Test normalization for various invalid patterns Verify nested dict feature access with invalid names Validate read_hf direct handling of invalid names	`tests/unit/lib/test_hf.py`
Add functional tests covering invalid column name patterns	Test read_hf across mixed invalid patterns Simulate the toxigen dataset KeyError issue	`tests/func/test_hf_invalid_column_names.py`

Assessment against linked issues

Issue	Objective	Addressed	Explanation

Possibly linked issues

Reading from huggingface dataset #1204: PR fixes the KeyError by passing original column names to handle invalid identifiers in HF datasets.
Reading from huggingface dataset #1204: The PR fixes handling of invalid column names in HuggingFace datasets, including nested dictionaries, which caused the TypeError in issue 1204.

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View logs

- Updated unit tests to expect original column names rather than normalized names - Fixed mock paths in all tests to use correct import path - Updated assertions to match actual behavior where original field names are preserved - All unit and functional tests now pass

codecov · 2025-07-11T04:04:04Z

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 88.66%. Comparing base (2e433bb) to head (3a9f5f8).
Report is 11 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1226   +/-   ##
=======================================
  Coverage   88.66%   88.66%           
=======================================
  Files         152      152           
  Lines       13606    13608    +2     
  Branches     1893     1893           
=======================================
+ Hits        12064    12066    +2     
  Misses       1095     1095           
  Partials      447      447

Flag	Coverage Δ
datachain	`88.60% <100.00%> (+<0.01%)`	⬆️

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Files with missing lines	Coverage Δ
src/datachain/lib/dc/hf.py	`89.47% <100.00%> (+0.58%)`	⬆️
src/datachain/lib/hf.py	`85.84% <100.00%> (+0.12%)`	⬆️

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shcheklein · 2025-07-15T03:56:40Z

Closing in favor of #1241

cursoragent and others added 2 commits July 11, 2025 03:21

Fix HuggingFace dataset column name handling for invalid identifiers

3cb9493

Co-authored-by: ivan <[email protected]>

Fix HuggingFace dataset column name handling for invalid identifiers

e7cd93a

Co-authored-by: ivan <[email protected]>

[pre-commit.ci] auto fixes from pre-commit.com hooks

1ef0677

for more information, see https://pre-commit.ci

shcheklein closed this Jul 15, 2025

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Fix HuggingFace dataset column name handling for invalid identifiers

🐛 Issue Fixed

📋 Problem Description

Example that failed before this fix:

🔧 Solution

Changes Made:

🧪 Testing

Unit Tests (tests/unit/lib/test_hf.py):

Functional Tests (tests/func/test_hf_invalid_column_names.py):

Test Coverage:

📊 Column Name Transformations

✅ Benefits

🔍 How It Works

📁 Files Modified

🧪 Manual Testing

📚 References

Summary by Sourcery

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Reviewer's Guide

Class diagram for handling HuggingFace dataset column names with invalid Python identifiers

Flow diagram for column name normalization and mapping in HuggingFace datasets

File-Level Changes

Assessment against linked issues

Possibly linked issues

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Unit Tests (`tests/unit/lib/test_hf.py`):

Functional Tests (`tests/func/test_hf_invalid_column_names.py`):

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