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docs: Add comprehensive test coverage analysis
Analyzed the test coverage of the datafusion-python codebase and identified critical gaps in aggregation functions, window functions, object store modules, and error handling. The analysis includes specific recommendations for new test files and estimated effort. Key findings: - Aggregation functions: ~29% coverage (CRITICAL) - Window functions: ~0% coverage (CRITICAL) - Object store: ~5% coverage (HIGH) - UDF/UDAF/UDWF: ~40% coverage (HIGH) - Error handling: ~5% coverage (HIGH) https://claude.ai/code/session_016efnBof74LCPbyVrWkeGAf
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TEST_COVERAGE_ANALYSIS.md

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# Test Coverage Analysis for DataFusion Python
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This document analyzes the current test coverage of the datafusion-python codebase and identifies areas that need improvement.
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## Executive Summary
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The datafusion-python project has approximately **192 test functions** across **20 test files** (~5,935 lines of test code). While core functionality is reasonably well-tested, there are significant gaps in several critical areas.
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### Key Findings
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| Area | Current Coverage | Priority |
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|------|-----------------|----------|
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| Math Functions | ~97% | Low (well covered) |
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| String Functions | ~84% | Medium |
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| Array/List Functions | ~100% | Low (well covered) |
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| Hash Functions | ~100% | Low (well covered) |
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| **Aggregation Functions** | **~29%** | **CRITICAL** |
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| **Window Functions** | **~0%** | **CRITICAL** |
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| User-Defined Functions | ~40% | High |
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| Object Store | ~5% | High |
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| Common Types | ~5% | Medium |
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| Error Handling | ~5% | High |
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---
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## Critical Coverage Gaps
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### 1. Aggregation Functions (CRITICAL)
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**Location**: `python/datafusion/functions.py`
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**Test File**: `python/tests/test_functions.py`
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The basic SQL aggregation functions have almost no dedicated tests:
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**NOT TESTED (22 functions):**
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- **Basic Aggregates**: `avg()`, `count()`, `count_star()`, `max()`, `min()`, `sum()`
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- **Statistical**: `corr()`, `covar()`, `covar_pop()`, `covar_samp()`, `median()`, `stddev()`, `stddev_pop()`, `stddev_samp()`, `var()`, `var_pop()`, `var_samp()`, `var_sample()`
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- **Bitwise**: `bit_and()`, `bit_or()`, `bit_xor()`, `bool_and()`, `bool_or()`
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- **Approximate**: `approx_distinct()`, `approx_median()`, `approx_percentile_cont()`, `approx_percentile_cont_with_weight()`
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- **String**: `string_agg()`
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**Recommendation**: Create `python/tests/test_aggregation_functions.py` with comprehensive tests for all aggregation functions.
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### 2. Window Functions (CRITICAL)
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**Location**: `python/datafusion/functions.py`
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**Test File**: None dedicated
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**ZERO COVERAGE for these functions:**
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- `row_number()`
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- `rank()`
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- `dense_rank()`
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- `lag()`
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- `lead()`
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- `first_value()`
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- `last_value()`
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- `nth_value()`
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- `cume_dist()`
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- `percent_rank()`
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- `ntile()`
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**Recommendation**: Create `python/tests/test_window_functions.py` with tests covering:
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- Basic window function usage
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- PARTITION BY clauses
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- ORDER BY clauses
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- Window frame specifications (ROWS, RANGE)
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- Combinations of partition/order/frame
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---
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## High Priority Coverage Gaps
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### 3. Object Store Module
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**Location**: `python/datafusion/object_store.py`
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**Test File**: `python/tests/test_store.py` (minimal)
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| Object Store | Test Coverage |
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|--------------|---------------|
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| `LocalFileSystem` | NOT TESTED |
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| `AmazonS3` | NOT TESTED |
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| `GoogleCloud` | NOT TESTED |
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| `MicrosoftAzure` | NOT TESTED |
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| `Http` | Minimal (1 test) |
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**Recommendation**: Add tests for:
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- Object store instantiation with various configurations
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- Registration with SessionContext
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- Reading files from each store type
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- Error handling for invalid credentials/endpoints
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### 4. User-Defined Functions (UDF/UDAF/UDWF)
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**Location**: `python/datafusion/udf.py`
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**Test Files**: `test_udf.py`, `test_udaf.py`, `test_udwf.py`
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#### Missing Coverage:
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| Feature | ScalarUDF | UDAF | UDWF |
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|---------|:---------:|:----:|:----:|
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| Multi-argument functions ||||
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| Null array handling ||||
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| Empty array handling ||||
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| Volatility=Stable ||||
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| Volatility=Volatile ||||
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| Enum volatility values ||||
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| Multiple return types ||||
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| Name auto-generation ||| ⚠️ |
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| Error propagation ||| ⚠️ |
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**Legend**: ✅ Tested, ⚠️ Partially tested, ❌ Not tested
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**Specific Gaps**:
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**ScalarUDF (`test_udf.py`):**
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- Only tests `pa.bool_()` return type - missing int, float, string, complex types
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- No multi-argument UDF tests
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- No volatility variations tested
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- No error handling tests
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**UDAF (`test_udaf.py`):**
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- Only tests `pa.float64()` return type
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- Known bug: code breaks on None (line 37 comment) - not tested
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- No multi-state accumulator tests
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- Limited merge operation testing
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**UDWF (`test_udwf.py`):**
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- Missing tests for `memoize()`, `is_causal()` methods
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- Only 2 window frame types tested
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- No tests for flag combinations
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### 5. Error Handling
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**Current State**: Only ~24 error handling tests across entire test suite
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**Missing Error Cases**:
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- Invalid SQL queries (malformed syntax)
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- Schema mismatch errors
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- Type coercion failures
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- Resource exhaustion scenarios
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- Invalid configuration options
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- Invalid UDF return types
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- Stream operation errors
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- File not found scenarios
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- Permission errors
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**Recommendation**: Add error handling tests to each module's test file.
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---
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## Medium Priority Coverage Gaps
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### 6. SessionContext Methods
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**Location**: `python/datafusion/context.py`
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**Test File**: `python/tests/test_context.py`
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**Untested Methods**:
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- `session_id()` - Returns unique session identifier
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- `empty_table()` - Creates empty DataFrame
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- `enable_url_table()` - Enables querying local files as tables
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- `register_table_provider()` - Advanced table provider registration
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**SessionConfig Untested Methods**:
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- `with_batch_size()`
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- `with_repartition_sorts()`
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- `with_repartition_file_scans()`
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- `with_repartition_file_min_size()`
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**RuntimeEnvBuilder Untested Methods**:
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- `with_disk_manager_disabled()`
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- `with_unbounded_memory_pool()`
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- `with_greedy_memory_pool()`
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### 7. Expression Methods
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**Location**: `python/datafusion/expr.py`
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**Test File**: `python/tests/test_expr.py`
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**Untested Methods**:
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- `canonical_name()` - Complete string representation
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- `variant_name()` - Returns Expr variant name
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- `rex_type()` - Returns RexType classification
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- `types()` - Returns DataTypeMap
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- `python_value()` - Extracts value from literal
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- `rex_call_operands()` - Returns operands
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- `rex_call_operator()` - Extracts operator
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- `column_name()` - Compute output column name
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### 8. Plan Methods
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**Location**: `python/datafusion/plan.py`
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**Test File**: `python/tests/test_plans.py`
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**LogicalPlan Untested Methods**:
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- `display_indent_schema()` - Print indented schema
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- `display_graphviz()` - GraphViz visualization
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**ExecutionPlan Untested Methods**:
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- `children()` - Get list of child plans
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- `display_indent()` - Indented physical plan display
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### 9. Common Module Types
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**Location**: `python/datafusion/common.py`
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**Test File**: None dedicated
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**Untested Types**:
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- `DFSchema` - No functional tests
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- `DataType` - No tests
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- `DataTypeMap` - No tests
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- `PythonType` - No tests
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- `RexType` - No tests
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- `SqlFunction`, `SqlSchema`, `SqlStatistics`, `SqlTable`, `SqlType`, `SqlView` - No tests
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### 10. Temporal Functions
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**Location**: `python/datafusion/functions.py`
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**Untested (6 functions)**:
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- `current_date()` - Returns current UTC date
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- `current_time()` - Returns current UTC time
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- `make_date()` - Construct date from year, month, day
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- `now()` - Returns current timestamp
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- `to_unixtime()` - Convert to Unix time
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- `to_hex()` - Integer to hex string
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### 11. String Functions
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**Location**: `python/datafusion/functions.py`
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**Untested (7 functions)**:
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- `char_length()` - Alias for length
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- `find_in_set()` - Find string in comma-separated list
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- `instr()` - Alias for strpos
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- `levenshtein()` - Edit distance calculation
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- `position()` - Alias for strpos
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- `substr_index()` - Substring before N occurrences
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- `substring()` - With explicit position and length
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---
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## Edge Cases Requiring Tests
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### Empty DataFrames
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- Current: Partially tested for `to_pandas()`, `to_polars()`, `to_arrow_table()`
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- Missing: Empty record batch streams, empty aggregation results
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### Null Value Handling
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- Current: Used in various tests but not dedicated testing
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- Missing: All-null batches, null in multi-argument functions, null handling in UDFs
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### Type Coercion
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- Current: Basic `cast()` test exists
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- Missing: Invalid cast operations, implicit type conversions, cross-type comparisons
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### Large Datasets
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- Current: No performance tests
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- Missing: Tests with millions of rows, memory efficiency tests, large batch handling
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---
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## Recommended New Test Files
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1. **`test_aggregation_functions.py`** - All aggregation functions (~22 tests)
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2. **`test_window_functions.py`** - All window functions (~15 tests)
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3. **`test_object_store.py`** (expand) - All object store types (~20 tests)
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4. **`test_expression_builders.py`** - coalesce, nullif, in_list, struct (~15 tests)
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5. **`test_common_types.py`** - DFSchema, DataType, etc. (~15 tests)
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6. **`test_error_handling.py`** - Cross-module error cases (~30 tests)
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7. **`test_edge_cases.py`** - Empty, null, large datasets (~25 tests)
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---
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## Summary of Test Improvements Needed
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| Priority | Area | Estimated Tests Needed |
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|----------|------|----------------------|
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| CRITICAL | Aggregation Functions | 25+ |
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| CRITICAL | Window Functions | 20+ |
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| HIGH | Object Store | 20+ |
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| HIGH | UDF/UDAF/UDWF Gaps | 30+ |
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| HIGH | Error Handling | 30+ |
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| MEDIUM | SessionContext Methods | 15+ |
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| MEDIUM | Expression Methods | 10+ |
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| MEDIUM | Common Types | 15+ |
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| MEDIUM | Temporal Functions | 10+ |
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| LOW | String Function Aliases | 5+ |
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| LOW | Edge Cases | 25+ |
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| **TOTAL** | | **~200+ tests** |
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---
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## Quick Wins
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These tests can be added with minimal effort:
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1. **Aggregation basics**: Add tests for `sum()`, `count()`, `avg()`, `min()`, `max()` - these are one-liners
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2. **Window function basics**: Add tests for `row_number()`, `rank()`, `dense_rank()`
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3. **SessionContext.session_id()**: Simple property access test
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4. **UDF with multiple arguments**: Extend existing test patterns
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5. **Volatility enum values**: Add parametrized tests to existing UDF tests
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---
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## Conclusion
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While the datafusion-python test suite provides good coverage for many core features, there are critical gaps in:
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1. **SQL aggregation functions** - The most commonly used SQL operations
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2. **Window functions** - Entire category with zero coverage
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3. **Object stores** - Critical for cloud deployments
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4. **Error handling** - Essential for production reliability
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Addressing these gaps would significantly improve the reliability and maintainability of the project.

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