diff --git a/parq/cli.py b/parq/cli.py index 36f9b7b..f79fc5b 100644 --- a/parq/cli.py +++ b/parq/cli.py @@ -202,12 +202,6 @@ def split( # Split into subdirectory parq split data.parquet -f 3 -n "output/part-%02d.parquet" """ - # {{CHENGQI: - # Action: Added; Timestamp: 2025-10-14 21:32:00 +08:00; - # Reason: Add CLI command for split functionality; - # Principle_Applied: Consistent error handling pattern, User-friendly output - # }} - # {{START MODIFICATIONS}} try: # Validate mutually exclusive parameters if file_count is None and record_count is None: @@ -226,14 +220,41 @@ def split( # Start timer start_time = time.time() - # Create reader and perform split + # Create reader reader = ParquetReader(str(file)) - output_files = reader.split_file( - output_pattern=name_format, - file_count=file_count, - record_count=record_count, + + # Setup progress bar + from rich.progress import ( + BarColumn, + Progress, + SpinnerColumn, + TextColumn, + TimeRemainingColumn, ) + from parq.output import console + + with Progress( + SpinnerColumn(), + TextColumn("[bold blue]{task.description}"), + BarColumn(), + TextColumn("[progress.percentage]{task.percentage:>3.0f}%"), + TimeRemainingColumn(), + console=console, + ) as progress: + task = progress.add_task(f"[cyan]Splitting {file.name}...", total=reader.num_rows) + + def update_progress(current: int, total: int): + progress.update(task, completed=current) + + # Perform split with progress callback + output_files = reader.split_file( + output_pattern=name_format, + file_count=file_count, + record_count=record_count, + progress_callback=update_progress, + ) + # Calculate elapsed time elapsed_time = time.time() - start_time @@ -255,8 +276,6 @@ def split( formatter.print_error(f"Failed to split Parquet file: {e}") raise typer.Exit(code=1) - # {{END MODIFICATIONS}} - if __name__ == "__main__": app() diff --git a/parq/output.py b/parq/output.py index 83d4a15..038bf45 100644 --- a/parq/output.py +++ b/parq/output.py @@ -103,27 +103,36 @@ def print_table(arrow_table: pa.Table, title: str = "Data Preview") -> None: """ Print PyArrow table as a Rich table. + Optimized to avoid pandas conversion, directly reading from PyArrow table + for better performance and reduced memory usage. + Args: arrow_table: PyArrow table to display title: Title for the table """ - # Convert to pandas for easier display - df = arrow_table.to_pandas() - table = Table( title=f"[bold blue]📄 {title}[/bold blue]", box=box.ROUNDED, show_header=True, header_style="bold magenta", + padding=(0, 1), + show_lines=True, ) - # Add columns - for col in df.columns: - table.add_column(str(col), style="cyan") + # Add columns directly from PyArrow schema + for col_name in arrow_table.column_names: + table.add_column(str(col_name), style="cyan") - # Add rows - for _, row in df.iterrows(): - table.add_row(*[str(val) for val in row]) + # Add rows using columnar access for better performance + # Convert columns to Python lists first, leveraging PyArrow's optimized operations + columns_data = [arrow_table[col_name].to_pylist() for col_name in arrow_table.column_names] + + # Transpose and iterate over rows + for row_idx in range(arrow_table.num_rows): + row_values = [ + str(columns_data[col_idx][row_idx]) for col_idx in range(len(columns_data)) + ] + table.add_row(*row_values) console.print(table) @@ -179,12 +188,6 @@ def print_split_result( total_rows: Total number of rows in source file elapsed_time: Time taken to split in seconds """ - # {{CHENGQI: - # Action: Added; Timestamp: 2025-10-14 21:35:00 +08:00; - # Reason: Add output formatter for split command results; - # Principle_Applied: Consistent output formatting, User-friendly display - # }} - # {{START MODIFICATIONS}} # Calculate statistics num_files = len(output_files) @@ -233,5 +236,3 @@ def print_split_result( table.add_row(str(idx), str(file_path), size) console.print(table) - - # {{END MODIFICATIONS}} diff --git a/parq/reader.py b/parq/reader.py index 24345c7..0a992af 100644 --- a/parq/reader.py +++ b/parq/reader.py @@ -9,6 +9,11 @@ import pyarrow as pa import pyarrow.parquet as pq +# Heuristic multiplier for determining when to use fast path vs optimized path +# Files with <= n * FAST_PATH_ROWS_MULTIPLIER rows use full read + slice (simpler) +# Larger files use row group optimization to reduce I/O +FAST_PATH_ROWS_MULTIPLIER = 10 + class ParquetReader: """Parquet file reader with metadata inspection capabilities.""" @@ -116,27 +121,87 @@ def read_head(self, n: int = 5) -> pa.Table: """ Read first n rows. + Optimized to only read necessary row groups for large files, + significantly reducing memory usage and improving performance. + Args: - n: Number of rows to read + n: Number of rows to read (must be >= 0) Returns: PyArrow table with first n rows + + Raises: + ValueError: If n < 0 """ - table = self._parquet_file.read() - return table.slice(0, min(n, self.num_rows)) + # Input validation + if n < 0: + raise ValueError(f"n must be non-negative, got {n}") + + # Guard: zero rows requested - return empty table with correct schema + if n == 0: + return pa.table({field.name: pa.array([], type=field.type) for field in self.schema}) + + # Fast path: small files or single row group + # Avoids overhead of row group calculation + if self.num_rows <= n * FAST_PATH_ROWS_MULTIPLIER or self.num_row_groups == 1: + table = self._parquet_file.read() + return table.slice(0, min(n, self.num_rows)) + + # Optimized path: only read necessary row groups + # For large files, this can reduce I/O by 10-100x + rows_read = 0 + row_groups = [] + for i in range(self.num_row_groups): + row_groups.append(i) + rows_read += self.metadata.row_group(i).num_rows + if rows_read >= n: + break + + table = self._parquet_file.read_row_groups(row_groups) + return table.slice(0, n) def read_tail(self, n: int = 5) -> pa.Table: """ Read last n rows. + Optimized to only read necessary row groups from the end of the file, + significantly reducing memory usage and improving performance for large files. + Args: - n: Number of rows to read + n: Number of rows to read (must be >= 0) Returns: PyArrow table with last n rows + + Raises: + ValueError: If n < 0 """ - table = self._parquet_file.read() - start = max(0, self.num_rows - n) + # Input validation + if n < 0: + raise ValueError(f"n must be non-negative, got {n}") + + # Guard: zero rows requested - return empty table with correct schema + if n == 0: + return pa.table({field.name: pa.array([], type=field.type) for field in self.schema}) + + # Fast path: small files or single row group + if self.num_rows <= n * FAST_PATH_ROWS_MULTIPLIER or self.num_row_groups == 1: + table = self._parquet_file.read() + start = max(0, self.num_rows - n) + return table.slice(start, n) + + # Optimized path: read from end, only necessary row groups + # Start from last row group and work backwards + rows_needed = n + row_groups = [] + for i in range(self.num_row_groups - 1, -1, -1): + row_groups.insert(0, i) # Maintain order + rows_needed -= self.metadata.row_group(i).num_rows + if rows_needed <= 0: + break + + table = self._parquet_file.read_row_groups(row_groups) + start = max(0, len(table) - n) return table.slice(start, n) def read_columns(self, columns: Optional[List[str]] = None) -> pa.Table: @@ -156,6 +221,7 @@ def split_file( output_pattern: str, file_count: Optional[int] = None, record_count: Optional[int] = None, + progress_callback: Optional[callable] = None, ) -> List[Path]: """ Split parquet file into multiple files. @@ -164,6 +230,7 @@ def split_file( output_pattern: Output file name pattern (e.g., 'result-%06d.parquet') file_count: Number of output files (mutually exclusive with record_count) record_count: Number of records per file (mutually exclusive with file_count) + progress_callback: Optional callback function(current, total) for progress updates Returns: List of created file paths @@ -172,12 +239,6 @@ def split_file( ValueError: If both or neither of file_count/record_count are provided IOError: If file write fails """ - # {{CHENGQI: - # Action: Added; Timestamp: 2025-10-14 21:30:00 +08:00; - # Reason: Implement split command functionality; - # Principle_Applied: SOLID-S (Single Responsibility), DRY, Error handling - # }} - # {{START MODIFICATIONS}} # Validate parameters if file_count is None and record_count is None: @@ -236,6 +297,7 @@ def split_file( # Read and distribute data in batches current_file_idx = 0 current_file_rows = 0 + rows_processed = 0 # Use batch reader for memory efficiency batch_size = min(10000, rows_per_file) # Read in chunks @@ -259,6 +321,11 @@ def split_file( batch_offset += rows_to_write current_file_rows += rows_to_write + rows_processed += rows_to_write + + # Report progress + if progress_callback: + progress_callback(rows_processed, total_rows) # Move to next file if current is full if current_file_rows >= rows_per_file and current_file_idx < num_files - 1: @@ -271,8 +338,6 @@ def split_file( if writer: writer.close() - # {{END MODIFICATIONS}} - return output_files def _get_compression_type(self) -> str: @@ -282,11 +347,6 @@ def _get_compression_type(self) -> str: Returns: Compression type string (e.g., 'SNAPPY', 'GZIP', 'NONE') """ - # {{CHENGUI: - # Action: Added; Timestamp: 2025-10-14 21:30:00 +08:00; - # Reason: Helper method to extract compression type for split files; - # Principle_Applied: DRY, Encapsulation - # }} if self.num_row_groups > 0: compression = self.metadata.row_group(0).column(0).compression return compression diff --git a/pyproject.toml b/pyproject.toml index 2abf558..2d67946 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,7 +8,6 @@ dependencies = [ "pyarrow>=18.0.0", "typer>=0.15.0", "rich>=13.0.0", - "pandas>=2.0.0", ] authors = [ {name = "SimonSun", email = "sjf19981112@gmail.com"} diff --git a/tests/test_reader.py b/tests/test_reader.py index d19e960..4645d6d 100644 --- a/tests/test_reader.py +++ b/tests/test_reader.py @@ -63,6 +63,20 @@ def test_read_head(self, sample_parquet_file): table = reader.read_head(10) assert len(table) == 5 + def test_read_head_edge_cases(self, sample_parquet_file): + """Test read_head with edge cases.""" + reader = ParquetReader(str(sample_parquet_file)) + + # Test n=0 returns empty table with correct schema + table = reader.read_head(0) + assert len(table) == 0 + assert table.num_columns == reader.num_columns + assert table.column_names == reader.schema.names + + # Test negative n raises ValueError + with pytest.raises(ValueError, match="must be non-negative"): + reader.read_head(-1) + def test_read_tail(self, sample_parquet_file): """Test reading last N rows.""" reader = ParquetReader(str(sample_parquet_file)) @@ -71,10 +85,24 @@ def test_read_tail(self, sample_parquet_file): table = reader.read_tail(2) assert len(table) == 2 - # Verify it's the last rows - df = table.to_pandas() - assert df.iloc[0]["id"] == 4 - assert df.iloc[1]["id"] == 5 + # Verify it's the last rows (using PyArrow's idiomatic to_pylist method) + id_values = table["id"].to_pylist() + assert id_values[0] == 4 + assert id_values[1] == 5 + + def test_read_tail_edge_cases(self, sample_parquet_file): + """Test read_tail with edge cases.""" + reader = ParquetReader(str(sample_parquet_file)) + + # Test n=0 returns empty table with correct schema + table = reader.read_tail(0) + assert len(table) == 0 + assert table.num_columns == reader.num_columns + assert table.column_names == reader.schema.names + + # Test negative n raises ValueError + with pytest.raises(ValueError, match="must be non-negative"): + reader.read_tail(-5) def test_read_columns(self, sample_parquet_file): """Test reading specific columns.""" diff --git a/uv.lock b/uv.lock index 282b097..ed3a544 100644 --- a/uv.lock +++ b/uv.lock @@ -227,211 +227,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/b3/38/89ba8ad64ae25be8de66a6d463314cf1eb366222074cfda9ee839c56a4b4/mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8", size = 9979 }, ] -[[package]] -name = "numpy" -version = "2.0.2" -source = { registry = "https://pypi.org/simple" } -resolution-markers = [ - 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