Optimize code for performance and load times #2
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Co-authored-by: sjf1998112 <sjf1998112@gmail.com>
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WalkthroughA performance optimization PR introducing lazy-loading for CLI imports and object creation, plus batch-wise data processing in output generation. The changes defer initialization of formatters and readers until needed and replace in-memory data collection with PyArrow batch streaming for reduced startup time and memory usage. Changes
Sequence DiagramsequenceDiagram
autonumber
participant CLI as CLI Command
participant Lazy as Lazy Loader
participant Formatter as Formatter
participant Reader as ParquetReader
participant Output as output.print_table()
participant PyArrow as PyArrow Batch Iterator
participant Rich as Rich Table
CLI->>Lazy: _get_formatter()
Lazy->>Formatter: instantiate OutputFormatter
Formatter-->>Lazy: formatter instance
Lazy-->>CLI: formatter
CLI->>Lazy: _get_reader(file_path)
Lazy->>Reader: instantiate ParquetReader
Reader-->>Lazy: reader instance
Lazy-->>CLI: reader
CLI->>Reader: read_table()
Reader-->>CLI: PyArrow Table
CLI->>Output: print_table(table, formatter)
Output->>PyArrow: to_batches()
loop per batch
PyArrow-->>Output: batch
Output->>Rich: append rows from batch
end
Rich-->>Output: rendered table
Output-->>CLI: (memory efficient)
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~25 minutes
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Actionable comments posted: 1
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⚠️ Outside diff range comments (5)
parq/cli.py (5)
62-72: Fix potential UnboundLocalError in exception handlers.If
FileNotFoundErroris raised on line 63 beforeformatteris assigned on line 65, the exception handler on line 68 will fail withUnboundLocalError: local variable 'formatter' referenced before assignment.Apply this diff to fix all exception handlers in the
metacommand:try: reader = _get_reader(str(file)) metadata = reader.get_metadata_dict() formatter = _get_formatter() formatter.print_metadata(metadata) except FileNotFoundError as e: + formatter = _get_formatter() formatter.print_error(str(e)) raise typer.Exit(code=1) except Exception as e: + formatter = _get_formatter() formatter.print_error(f"Failed to read Parquet file: {e}") raise typer.Exit(code=1)
86-96: Fix potential UnboundLocalError in exception handlers.Same issue as in the
metacommand -formattermay not be defined if an exception occurs before line 89.Apply this diff:
try: reader = _get_reader(str(file)) schema_info = reader.get_schema_info() formatter = _get_formatter() formatter.print_schema(schema_info) except FileNotFoundError as e: + formatter = _get_formatter() formatter.print_error(str(e)) raise typer.Exit(code=1) except Exception as e: + formatter = _get_formatter() formatter.print_error(f"Failed to read Parquet file: {e}") raise typer.Exit(code=1)
115-125: Fix potential UnboundLocalError in exception handlers.Same issue -
formatterused in exception handlers before it's defined.Apply this diff:
try: reader = _get_reader(str(file)) table = reader.read_head(n) formatter = _get_formatter() formatter.print_table(table, f"First {n} Rows") except FileNotFoundError as e: + formatter = _get_formatter() formatter.print_error(str(e)) raise typer.Exit(code=1) except Exception as e: + formatter = _get_formatter() formatter.print_error(f"Failed to read Parquet file: {e}") raise typer.Exit(code=1)
144-154: Fix potential UnboundLocalError in exception handlers.Same issue in the
tailcommand.Apply this diff:
try: reader = _get_reader(str(file)) table = reader.read_tail(n) formatter = _get_formatter() formatter.print_table(table, f"Last {n} Rows") except FileNotFoundError as e: + formatter = _get_formatter() formatter.print_error(str(e)) raise typer.Exit(code=1) except Exception as e: + formatter = _get_formatter() formatter.print_error(f"Failed to read Parquet file: {e}") raise typer.Exit(code=1)
168-177: Fix potential UnboundLocalError in exception handlers.Same issue in the
countcommand.Apply this diff:
try: reader = _get_reader(str(file)) formatter = _get_formatter() formatter.print_count(reader.num_rows) except FileNotFoundError as e: + formatter = _get_formatter() formatter.print_error(str(e)) raise typer.Exit(code=1) except Exception as e: + formatter = _get_formatter() formatter.print_error(f"Failed to read Parquet file: {e}") raise typer.Exit(code=1)
🧹 Nitpick comments (2)
parq/output.py (2)
106-107: Clarify "row-by-row" claim in documentation.The docstring states "converting data row-by-row" but the implementation processes data batch-by-batch, materializing each batch fully into a Python dict before iterating rows. While this is more memory-efficient than loading the entire table at once, it's not truly row-by-row processing.
Consider updating the docstring to accurately reflect the batch-wise approach:
- Optimized to avoid pandas conversion and minimize memory usage by - converting data row-by-row using PyArrow's record batch iterator. + Optimized to avoid pandas conversion and minimize memory usage by + processing data in batches using PyArrow's record batch iterator.
126-137: Consider optimizing batch-to-dict conversion.While
batch.to_pydict()reduces memory compared to converting the entire table, it still materializes each batch completely as Python objects. For very large tables with wide schemas, individual batches can still be memory-intensive.Consider alternative approaches if memory optimization is critical:
Option 1: Use PyArrow's column iterators directly (more memory-efficient)
# Memory-efficient: Access columns directly without full dict conversion for batch in arrow_table.to_batches(): batch_size = len(batch) for row_idx in range(batch_size): row_values = [ str(batch.column(col_idx)[row_idx].as_py()) for col_idx in range(batch.num_columns) ] table.add_row(*row_values)Option 2: Control batch size for better memory management
# Use smaller batch sizes for tighter memory control for batch in arrow_table.to_batches(max_chunksize=1024): ...
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📒 Files selected for processing (3)
PERFORMANCE_OPTIMIZATIONS.md(1 hunks)parq/cli.py(9 hunks)parq/output.py(2 hunks)
🧰 Additional context used
🧬 Code graph analysis (1)
parq/cli.py (2)
parq/output.py (1)
OutputFormatter(18-240)parq/reader.py (6)
ParquetReader(18-353)metadata(35-37)get_metadata_dict(64-100)get_schema_info(102-118)read_head(120-161)read_tail(163-205)
🔇 Additional comments (3)
parq/cli.py (2)
216-218: Good practice: Early formatter initialization for error handling.Initializing the formatter early ensures it's available for all error paths in the
splitcommand, preventingUnboundLocalErrorissues present in other commands.
235-236: Good practice: Lazy import of time module.Importing
timewithin the function rather than at module level is consistent with the lazy-loading optimization strategy.PERFORMANCE_OPTIMIZATIONS.md (1)
1-190: Well-structured performance documentation.The documentation provides a comprehensive overview of the performance optimizations including lazy loading and batch processing. The examples align well with the actual code changes.
Minor suggestions for accuracy:
Lines 80-92: The code example states "row-by-row" processing, but as noted in the code review, it's actually batch-by-batch processing with
to_pydict()materializing each batch.Lines 95-97: The claim of "streaming processing" (流式处理) is somewhat overstated since
to_pydict()fully materializes each batch. Consider clarifying this as "batch-wise processing" rather than true streaming.Line 122-125: It would be valuable to add actual benchmark numbers rather than relative descriptions like "significantly improved."
| def _get_formatter(): | ||
| """Lazy load formatter to improve CLI startup time.""" | ||
| from parq.output import OutputFormatter | ||
| return OutputFormatter() |
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🛠️ Refactor suggestion | 🟠 Major
Remove unnecessary OutputFormatter instantiation.
OutputFormatter contains only static methods, so instantiation is unnecessary and adds overhead. Return the class itself instead.
Apply this diff:
def _get_formatter():
"""Lazy load formatter to improve CLI startup time."""
from parq.output import OutputFormatter
- return OutputFormatter()
+ return OutputFormatterThen update all usage from formatter.method() to formatter.method() (no change needed since static methods work on both instances and classes).
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def _get_formatter(): | |
| """Lazy load formatter to improve CLI startup time.""" | |
| from parq.output import OutputFormatter | |
| return OutputFormatter() | |
| def _get_formatter(): | |
| """Lazy load formatter to improve CLI startup time.""" | |
| from parq.output import OutputFormatter | |
| return OutputFormatter |
🤖 Prompt for AI Agents
In parq/cli.py around lines 19 to 22, _get_formatter currently instantiates
OutputFormatter even though it only contains static methods; change the function
to return the OutputFormatter class itself (i.e., return OutputFormatter)
instead of OutputFormatter(), and verify callers work with the class (no
call-site changes needed because static methods can be invoked on the class).
This pull request contains changes generated by Cursor background composer.
Summary by CodeRabbit
Performance Improvements
Documentation