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Reporters

Reporter classes for different output formats and destinations.

This module provides formatters for converting benchmark results to various formats and reporters for sending formatted results to different destinations.

CSVFormatter

Bases: Formatter

Format results as CSV.

Source code in easybench/reporters.py 
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class CSVFormatter(Formatter):
    """Format results as CSV."""

    def format(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> str:
        """Format results as CSV."""
        _ = results  # unused but avoids ARG002
        output = StringIO()
        writer = csv.writer(output)

        # Write header row
        header = self._create_header_row(config)
        writer.writerow(header)

        # Write data rows
        for method_name in self.sort_keys(stats, config):
            row = self._create_data_row(method_name, stats[method_name], config)
            writer.writerow(row)

        return output.getvalue()

    def _create_header_row(self, config: BenchConfig) -> list[str]:
        """Create the CSV header row based on configuration."""
        memory_unit = MemoryUnit.from_config(config)
        time_unit = TimeUnit.from_config(config)

        header = ["Function"]

        if config.trials == 1:
            if config.time:
                header.append(f"Time ({time_unit})")
            if config.memory:
                header.append(f"Memory ({memory_unit})")
        else:
            if config.time:
                header.extend(
                    [
                        f"Avg Time ({time_unit})",
                        f"Min Time ({time_unit})",
                        f"Max Time ({time_unit})",
                    ],
                )
            if config.memory:
                header.extend(
                    [
                        f"Avg Memory ({memory_unit})",
                        f"Max Memory ({memory_unit})",
                    ],
                )

        return header

    def _create_data_row(
        self,
        method_name: str,
        stat: StatType,
        config: BenchConfig,
    ) -> list[str | float]:
        """Create a data row for the given method."""
        memory_unit = MemoryUnit.from_config(config)
        time_unit = TimeUnit.from_config(config)

        if config.trials == 1:
            row: list[str | float] = [method_name]
            if config.time:
                row.append(time_unit.convert_seconds(stat["avg"]))
            if config.memory:
                row.append(memory_unit.convert_bytes(stat["avg_memory"]))
        else:
            row = [method_name]
            if config.time:
                row.extend(
                    [
                        time_unit.convert_seconds(stat["avg"]),
                        time_unit.convert_seconds(stat["min"]),
                        time_unit.convert_seconds(stat["max"]),
                    ],
                )
            if config.memory:
                row.extend(
                    [
                        memory_unit.convert_bytes(stat["avg_memory"]),
                        memory_unit.convert_bytes(stat["max_memory"]),
                    ],
                )

        return row

format(results, stats, config)

Format results as CSV.

Source code in easybench/reporters.py 
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def format(
    self,
    results: ResultsType,
    stats: StatsType,
    config: BenchConfig,
) -> str:
    """Format results as CSV."""
    _ = results  # unused but avoids ARG002
    output = StringIO()
    writer = csv.writer(output)

    # Write header row
    header = self._create_header_row(config)
    writer.writerow(header)

    # Write data rows
    for method_name in self.sort_keys(stats, config):
        row = self._create_data_row(method_name, stats[method_name], config)
        writer.writerow(row)

    return output.getvalue()

CallbackReporter

Bases: Reporter

Reporter that sends output to a callback function.

Source code in easybench/reporters.py 
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class CallbackReporter(Reporter):
    """Reporter that sends output to a callback function."""

    def __init__(
        self,
        callback: Callable[[Formatted], None],
        formatter: Formatter | None = None,
    ) -> None:
        """
        Initialize callback reporter.

        Args:
            callback: Function to call with formatted output
            formatter: Formatter to use (defaults to DataFrameFormatter)

        """
        super().__init__(formatter or DataFrameFormatter())
        self.callback = callback

    def report_formatted(self, formatted_output: Formatted) -> None:
        """
        Send formatted output to callback.

        Args:
            formatted_output: The formatted output to send

        """
        self.callback(formatted_output)

__init__(callback, formatter=None)

Initialize callback reporter.

Parameters:

Name Type Description Default
callback Callable[[Formatted], None]

Function to call with formatted output

 required
formatter Formatter | None

Formatter to use (defaults to DataFrameFormatter)

 None
Source code in easybench/reporters.py 
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def __init__(
    self,
    callback: Callable[[Formatted], None],
    formatter: Formatter | None = None,
) -> None:
    """
    Initialize callback reporter.

    Args:
        callback: Function to call with formatted output
        formatter: Formatter to use (defaults to DataFrameFormatter)

    """
    super().__init__(formatter or DataFrameFormatter())
    self.callback = callback

report_formatted(formatted_output)

Send formatted output to callback.

Parameters:

Name Type Description Default
formatted_output Formatted

The formatted output to send

 required
Source code in easybench/reporters.py 
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def report_formatted(self, formatted_output: Formatted) -> None:
    """
    Send formatted output to callback.

    Args:
        formatted_output: The formatted output to send

    """
    self.callback(formatted_output)

ConsoleReporter

Bases: StreamReporter

Reporter that sends output to the console (stdout).

Source code in easybench/reporters.py 
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class ConsoleReporter(StreamReporter):
    """Reporter that sends output to the console (stdout)."""

    def __init__(self, formatter: Formatter | None = None) -> None:
        """
        Initialize console reporter.

        Args:
            formatter: Formatter to use (defaults to TableFormatter)

        """
        super().__init__(formatter=formatter, file=None)

__init__(formatter=None)

Initialize console reporter.

Parameters:

Name Type Description Default
formatter Formatter | None

Formatter to use (defaults to TableFormatter)

 None
Source code in easybench/reporters.py 
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def __init__(self, formatter: Formatter | None = None) -> None:
    """
    Initialize console reporter.

    Args:
        formatter: Formatter to use (defaults to TableFormatter)

    """
    super().__init__(formatter=formatter, file=None)

DataFrameFormatter

Bases: Formatter

Format results as pandas DataFrame.

Source code in easybench/reporters.py 
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class DataFrameFormatter(Formatter):
    """Format results as pandas DataFrame."""

    def format(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> pd.DataFrame:
        """
        Format results as DataFrame.

        Memory values are converted to the specified unit.
        """
        memory_unit = MemoryUnit.from_config(config)
        time_unit = TimeUnit.from_config(config)
        try:
            import pandas as pd  # noqa: PLC0415
        except ImportError as err:
            error_msg = (
                "pandas is required for DataFrame output. "
                "Install with pip install pandas."
            )
            raise ImportError(error_msg) from err

        data = []
        for method_name in self.sort_keys(stats, config):
            stat = stats[method_name]
            row: dict[str, Any] = {"Function": method_name}

            # Add stats based on number of trials
            if config.trials == 1:
                if config.time:
                    row[f"Time ({time_unit})"] = time_unit.convert_seconds(stat["avg"])
                if config.memory:
                    row[f"Memory ({memory_unit})"] = memory_unit.convert_bytes(
                        stat["avg_memory"],
                    )
            else:
                if config.time:
                    row.update(
                        {
                            f"Avg Time ({time_unit})": time_unit.convert_seconds(
                                stat["avg"],
                            ),
                            f"Min Time ({time_unit})": time_unit.convert_seconds(
                                stat["min"],
                            ),
                            f"Max Time ({time_unit})": time_unit.convert_seconds(
                                stat["max"],
                            ),
                        },
                    )
                if config.memory:
                    row.update(
                        {
                            f"Avg Memory ({memory_unit})": (
                                memory_unit.convert_bytes(stat["avg_memory"])
                            ),
                            f"Max Memory ({memory_unit})": (
                                memory_unit.convert_bytes(stat["max_memory"])
                            ),
                        },
                    )

            # Add output if requested
            if config.show_output and "output" in results[method_name]:
                # Just take first output
                row["Output"] = results[method_name]["output"][0]

            data.append(row)

        return pd.DataFrame(data)

format(results, stats, config)

Format results as DataFrame.

Memory values are converted to the specified unit.

Source code in easybench/reporters.py 
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def format(
    self,
    results: ResultsType,
    stats: StatsType,
    config: BenchConfig,
) -> pd.DataFrame:
    """
    Format results as DataFrame.

    Memory values are converted to the specified unit.
    """
    memory_unit = MemoryUnit.from_config(config)
    time_unit = TimeUnit.from_config(config)
    try:
        import pandas as pd  # noqa: PLC0415
    except ImportError as err:
        error_msg = (
            "pandas is required for DataFrame output. "
            "Install with pip install pandas."
        )
        raise ImportError(error_msg) from err

    data = []
    for method_name in self.sort_keys(stats, config):
        stat = stats[method_name]
        row: dict[str, Any] = {"Function": method_name}

        # Add stats based on number of trials
        if config.trials == 1:
            if config.time:
                row[f"Time ({time_unit})"] = time_unit.convert_seconds(stat["avg"])
            if config.memory:
                row[f"Memory ({memory_unit})"] = memory_unit.convert_bytes(
                    stat["avg_memory"],
                )
        else:
            if config.time:
                row.update(
                    {
                        f"Avg Time ({time_unit})": time_unit.convert_seconds(
                            stat["avg"],
                        ),
                        f"Min Time ({time_unit})": time_unit.convert_seconds(
                            stat["min"],
                        ),
                        f"Max Time ({time_unit})": time_unit.convert_seconds(
                            stat["max"],
                        ),
                    },
                )
            if config.memory:
                row.update(
                    {
                        f"Avg Memory ({memory_unit})": (
                            memory_unit.convert_bytes(stat["avg_memory"])
                        ),
                        f"Max Memory ({memory_unit})": (
                            memory_unit.convert_bytes(stat["max_memory"])
                        ),
                    },
                )

        # Add output if requested
        if config.show_output and "output" in results[method_name]:
            # Just take first output
            row["Output"] = results[method_name]["output"][0]

        data.append(row)

    return pd.DataFrame(data)

FileReporter

Bases: Reporter

Reporter that sends output to a file.

Source code in easybench/reporters.py 
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class FileReporter(Reporter):
    """Reporter that sends output to a file."""

    def __init__(
        self,
        path: str | Path,
        formatter: Formatter | None = None,
        mode: str = "w",
        encoding: str = "utf-8",
    ) -> None:
        """
        Initialize file reporter.

        Args:
            path: Path to the output file
            formatter: Formatter to use (defaults based on file extension)
            mode: File open mode ('w' for write, 'a' for append)
            encoding: File encoding

        """
        if formatter is None:
            # Infer formatter from file extension
            path_obj = Path(path)
            ext = path_obj.suffix.lower()
            if ext == ".csv":
                formatter = CSVFormatter()
            elif ext == ".json":
                formatter = JSONFormatter()
            else:
                formatter = TableFormatter()

        super().__init__(formatter)
        self.path = Path(path)
        self.mode = mode
        self.encoding = encoding

    def report_formatted(self, formatted_output: Formatted) -> None:
        """
        Write formatted output to file.

        Args:
            formatted_output: The formatted output to write

        """
        with self.path.open(self.mode, encoding=self.encoding) as f:
            f.write(formatted_output)

__init__(path, formatter=None, mode='w', encoding='utf-8')

Initialize file reporter.

Parameters:

Name Type Description Default
path str | Path

Path to the output file

 required
formatter Formatter | None

Formatter to use (defaults based on file extension)

 None
mode str

File open mode ('w' for write, 'a' for append)

 'w'
encoding str

File encoding

 'utf-8'
Source code in easybench/reporters.py 
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def __init__(
    self,
    path: str | Path,
    formatter: Formatter | None = None,
    mode: str = "w",
    encoding: str = "utf-8",
) -> None:
    """
    Initialize file reporter.

    Args:
        path: Path to the output file
        formatter: Formatter to use (defaults based on file extension)
        mode: File open mode ('w' for write, 'a' for append)
        encoding: File encoding

    """
    if formatter is None:
        # Infer formatter from file extension
        path_obj = Path(path)
        ext = path_obj.suffix.lower()
        if ext == ".csv":
            formatter = CSVFormatter()
        elif ext == ".json":
            formatter = JSONFormatter()
        else:
            formatter = TableFormatter()

    super().__init__(formatter)
    self.path = Path(path)
    self.mode = mode
    self.encoding = encoding

report_formatted(formatted_output)

Write formatted output to file.

Parameters:

Name Type Description Default
formatted_output Formatted

The formatted output to write

 required
Source code in easybench/reporters.py 
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def report_formatted(self, formatted_output: Formatted) -> None:
    """
    Write formatted output to file.

    Args:
        formatted_output: The formatted output to write

    """
    with self.path.open(self.mode, encoding=self.encoding) as f:
        f.write(formatted_output)

Formatter

Bases: ABC

Base class for all result formatters.

Source code in easybench/reporters.py 
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class Formatter(ABC):
    """Base class for all result formatters."""

    def format_(
        self,
        results: ResultsType,
        stats: StatsType | None = None,
        config: BenchConfig | None = None,
    ) -> Formatted:
        """
        Format benchmark results.

        Args:
            results: Dictionary mapping benchmark names to result data.
            stats: Dictionary of calculated statistics.
                If None, stats will be calculated from results.
            config: Benchmark configuration. Required.

        Returns:
            Formatted results in the appropriate format

        """
        if stats is None:
            stats = calculate_statistics(results)

        if config is None:
            msg = "The 'config' option is required."
            raise TypeError(msg)

        return self.format(results, stats, config)

    @abstractmethod
    def format(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> Formatted:
        """
        Format benchmark results.

        Args:
            results: Dictionary mapping benchmark names to result data.
            stats: Dictionary of calculated statistics.
            config: Benchmark configuration

        Returns:
            Formatted results in the appropriate format

        """

    def sort_keys(
        self,
        stats: StatsType,
        config: BenchConfig,
    ) -> list[str]:
        """
        Sort stats keys based on the config.

        Args:
            stats: Dictionary of precomputed statistics for each benchmark
            config: Benchmark config

        Returns:
            Sorted list of stats keys

        """
        if config.sort_by in get_args(MetricType):
            metric: MetricType = config.sort_by  # type: ignore [assignment]
            return sorted(
                stats.keys(),
                key=lambda method_name: stats[method_name][metric],
                reverse=config.reverse,
            )

        if config.reverse:
            return list(stats.keys())[::-1]

        return list(stats.keys())

    def shrink_data(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> None:
        """
        Modify the given results and stats in place by removing any unnecessary entries.

        This operation mutates the input data structures directly.

        Args:
            results (ResultsType): The benchmark results to be pruned.
            stats (StatsType): The corresponding statistical data to be pruned.
            config (BenchConfig): Configuration specifying which data to keep or remove.

        Returns:
            None

        """
        self._shrink_time_data(results, stats, config)
        self._shrink_memory_data(results, stats, config)

    def _shrink_time_data(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> None:
        """
        Modify the given results and stats by removing any unnecessary time entries.

        This operation mutates the input data structures directly.

        Args:
            results (ResultsType): The benchmark results to be pruned.
            stats (StatsType): The corresponding statistical data to be pruned.
            config (BenchConfig): Configuration specifying which data to keep or remove.

        Returns:
            None

        """
        if not config.time:
            for result in results.values():
                if "times" in result:
                    del result["times"]
            for stat in stats.values():
                if "avg" in stat:
                    del stat["avg"]
                if "max" in stat:
                    del stat["max"]
                if "min" in stat:
                    del stat["min"]

    def _shrink_memory_data(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> None:
        """
        Modify the given results and stats by removing any unnecessary memory entries.

        This operation mutates the input data structures directly.

        Args:
            results (ResultsType): The benchmark results to be pruned.
            stats (StatsType): The corresponding statistical data to be pruned.
            config (BenchConfig): Configuration specifying which data to keep or remove.

        Returns:
            None

        """
        if not config.memory:
            for result in results.values():
                if "memory" in result:
                    del result["memory"]
            for stat in stats.values():
                if "avg_memory" in stat:
                    del stat["avg_memory"]
                if "max_memory" in stat:
                    del stat["max_memory"]

format(results, stats, config) abstractmethod

Format benchmark results.

Parameters:

Name Type Description Default
results ResultsType

Dictionary mapping benchmark names to result data.

 required
stats StatsType

Dictionary of calculated statistics.

 required
config BenchConfig

Benchmark configuration

 required

Returns:

Type Description
Formatted

Formatted results in the appropriate format
Source code in easybench/reporters.py 
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@abstractmethod
def format(
    self,
    results: ResultsType,
    stats: StatsType,
    config: BenchConfig,
) -> Formatted:
    """
    Format benchmark results.

    Args:
        results: Dictionary mapping benchmark names to result data.
        stats: Dictionary of calculated statistics.
        config: Benchmark configuration

    Returns:
        Formatted results in the appropriate format

    """

format_(results, stats=None, config=None)

Format benchmark results.

Parameters:

Name Type Description Default
results ResultsType

Dictionary mapping benchmark names to result data.

 required
stats StatsType | None

Dictionary of calculated statistics. If None, stats will be calculated from results.

 None
config BenchConfig | None

Benchmark configuration. Required.

 None

Returns:

Type Description
Formatted

Formatted results in the appropriate format
Source code in easybench/reporters.py 
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def format_(
    self,
    results: ResultsType,
    stats: StatsType | None = None,
    config: BenchConfig | None = None,
) -> Formatted:
    """
    Format benchmark results.

    Args:
        results: Dictionary mapping benchmark names to result data.
        stats: Dictionary of calculated statistics.
            If None, stats will be calculated from results.
        config: Benchmark configuration. Required.

    Returns:
        Formatted results in the appropriate format

    """
    if stats is None:
        stats = calculate_statistics(results)

    if config is None:
        msg = "The 'config' option is required."
        raise TypeError(msg)

    return self.format(results, stats, config)

shrink_data(results, stats, config)

Modify the given results and stats in place by removing any unnecessary entries.

This operation mutates the input data structures directly.

Parameters:

Name Type Description Default
results ResultsType

The benchmark results to be pruned.

 required
stats StatsType

The corresponding statistical data to be pruned.

 required
config BenchConfig

Configuration specifying which data to keep or remove.

 required

Returns:

Type Description
None

None
Source code in easybench/reporters.py 
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def shrink_data(
    self,
    results: ResultsType,
    stats: StatsType,
    config: BenchConfig,
) -> None:
    """
    Modify the given results and stats in place by removing any unnecessary entries.

    This operation mutates the input data structures directly.

    Args:
        results (ResultsType): The benchmark results to be pruned.
        stats (StatsType): The corresponding statistical data to be pruned.
        config (BenchConfig): Configuration specifying which data to keep or remove.

    Returns:
        None

    """
    self._shrink_time_data(results, stats, config)
    self._shrink_memory_data(results, stats, config)

sort_keys(stats, config)

Sort stats keys based on the config.

Parameters:

Name Type Description Default
stats StatsType

Dictionary of precomputed statistics for each benchmark

 required
config BenchConfig

Benchmark config

 required

Returns:

Type Description
list[str]

Sorted list of stats keys
Source code in easybench/reporters.py 
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def sort_keys(
    self,
    stats: StatsType,
    config: BenchConfig,
) -> list[str]:
    """
    Sort stats keys based on the config.

    Args:
        stats: Dictionary of precomputed statistics for each benchmark
        config: Benchmark config

    Returns:
        Sorted list of stats keys

    """
    if config.sort_by in get_args(MetricType):
        metric: MetricType = config.sort_by  # type: ignore [assignment]
        return sorted(
            stats.keys(),
            key=lambda method_name: stats[method_name][metric],
            reverse=config.reverse,
        )

    if config.reverse:
        return list(stats.keys())[::-1]

    return list(stats.keys())

JSONFormatter

Bases: Formatter

Format results as JSON.

Source code in easybench/reporters.py 
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class JSONFormatter(Formatter):
    """Format results as JSON."""

    def __init__(self, output_mode: Literal["all", "no_results"] = "all") -> None:
        """
        Initialize.

        Args:
            output_mode: Output mode, either "all" (include results) or "no_results"

        """
        super().__init__()
        self.output_mode = output_mode

    def format(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> str:
        """Format results as JSON."""
        memory_unit = MemoryUnit.from_config(config)
        time_unit = TimeUnit.from_config(config)
        self.shrink_data(results, stats, config)
        output_data: dict[str, Any] = {
            "config": config.model_dump(exclude={"reporters", "progress"}),
            "stats": {},
        }

        # Only include results if output_mode is "all"
        if self.output_mode == "all":
            output_data["results"] = results

        for method_name in self.sort_keys(stats, config):
            stat = stats[method_name].copy()

            # Convert time values to the specified unit
            if config.time:
                for key in ["avg", "min", "max"]:
                    if key in stat:
                        stat[key] = time_unit.convert_seconds(stat[key])  # type: ignore [literal-required]

            # Convert memory values to the specified unit
            if config.memory:
                if "avg_memory" in stat:
                    stat["avg_memory"] = memory_unit.convert_bytes(stat["avg_memory"])
                if "max_memory" in stat:
                    stat["max_memory"] = memory_unit.convert_bytes(stat["max_memory"])

            output_data["stats"][method_name] = stat

        return json.dumps(output_data, indent=2)

__init__(output_mode='all')

Initialize.

Parameters:

Name Type Description Default
output_mode Literal['all', 'no_results']

Output mode, either "all" (include results) or "no_results"

 'all'
Source code in easybench/reporters.py 
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def __init__(self, output_mode: Literal["all", "no_results"] = "all") -> None:
    """
    Initialize.

    Args:
        output_mode: Output mode, either "all" (include results) or "no_results"

    """
    super().__init__()
    self.output_mode = output_mode

format(results, stats, config)

Format results as JSON.

Source code in easybench/reporters.py 
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def format(
    self,
    results: ResultsType,
    stats: StatsType,
    config: BenchConfig,
) -> str:
    """Format results as JSON."""
    memory_unit = MemoryUnit.from_config(config)
    time_unit = TimeUnit.from_config(config)
    self.shrink_data(results, stats, config)
    output_data: dict[str, Any] = {
        "config": config.model_dump(exclude={"reporters", "progress"}),
        "stats": {},
    }

    # Only include results if output_mode is "all"
    if self.output_mode == "all":
        output_data["results"] = results

    for method_name in self.sort_keys(stats, config):
        stat = stats[method_name].copy()

        # Convert time values to the specified unit
        if config.time:
            for key in ["avg", "min", "max"]:
                if key in stat:
                    stat[key] = time_unit.convert_seconds(stat[key])  # type: ignore [literal-required]

        # Convert memory values to the specified unit
        if config.memory:
            if "avg_memory" in stat:
                stat["avg_memory"] = memory_unit.convert_bytes(stat["avg_memory"])
            if "max_memory" in stat:
                stat["max_memory"] = memory_unit.convert_bytes(stat["max_memory"])

        output_data["stats"][method_name] = stat

    return json.dumps(output_data, indent=2)

MemoryUnit

Bases: str, Enum

Memory unit options for display.

Source code in easybench/reporters.py 
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class MemoryUnit(str, Enum):
    """Memory unit options for display."""

    BYTES = "B"
    KILOBYTES = "KB"
    MEGABYTES = "MB"
    GIGABYTES = "GB"

    def __str__(self) -> str:
        """Convert unit to string."""
        return self.value

    def convert_bytes(self, byte_size: float) -> float:
        """
        Convert byte size to this memory unit.

        Args:
            byte_size (float): The size in bytes.

        Returns:
            float: The converted size in this memory unit.

        """
        unit_divisors = {
            MemoryUnit.BYTES: 1,
            MemoryUnit.KILOBYTES: 1024,
            MemoryUnit.MEGABYTES: 1024**2,
            MemoryUnit.GIGABYTES: 1024**3,
        }

        divisor = unit_divisors[self]
        return byte_size / divisor

    @classmethod
    def from_config(cls, config: BenchConfig) -> MemoryUnit:
        """Get memory unit from config."""
        unit = MemoryUnit.KILOBYTES

        if isinstance(config.memory, str):
            unit = MemoryUnit(config.memory.upper())
        elif isinstance(config.memory, MemoryUnit):
            unit = config.memory

        return unit

__str__()

Convert unit to string.

Source code in easybench/reporters.py 
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def __str__(self) -> str:
    """Convert unit to string."""
    return self.value

convert_bytes(byte_size)

Convert byte size to this memory unit.

Parameters:

Name Type Description Default
byte_size float

The size in bytes.

 required

Returns:

Name Type Description
float float

The converted size in this memory unit.
Source code in easybench/reporters.py 
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def convert_bytes(self, byte_size: float) -> float:
    """
    Convert byte size to this memory unit.

    Args:
        byte_size (float): The size in bytes.

    Returns:
        float: The converted size in this memory unit.

    """
    unit_divisors = {
        MemoryUnit.BYTES: 1,
        MemoryUnit.KILOBYTES: 1024,
        MemoryUnit.MEGABYTES: 1024**2,
        MemoryUnit.GIGABYTES: 1024**3,
    }

    divisor = unit_divisors[self]
    return byte_size / divisor

from_config(config) classmethod

Get memory unit from config.

Source code in easybench/reporters.py 
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@classmethod
def from_config(cls, config: BenchConfig) -> MemoryUnit:
    """Get memory unit from config."""
    unit = MemoryUnit.KILOBYTES

    if isinstance(config.memory, str):
        unit = MemoryUnit(config.memory.upper())
    elif isinstance(config.memory, MemoryUnit):
        unit = config.memory

    return unit

Reporter

Base reporter class for sending benchmark results to destinations.

Source code in easybench/reporters.py 
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class Reporter:
    """Base reporter class for sending benchmark results to destinations."""

    def __init__(self, formatter: Formatter) -> None:
        """
        Initialize reporter with a formatter.

        Args:
            formatter: Formatter to use for formatting results

        """
        self.formatter = formatter

    def report(
        self,
        results: ResultsType,
        stats: StatsType | None = None,
        config: BenchConfig | None = None,
    ) -> None:
        """
        Report benchmark results.

        Args:
            results: Dictionary mapping benchmark names to result data
            stats: Dictionary of calculated statistics
            config: Benchmark configuration. Required.

        """
        formatted = self.formatter.format_(
            results=results,
            stats=stats,
            config=config,
        )
        self.report_formatted(formatted)

    @abstractmethod
    def report_formatted(self, formatted_output: Formatted) -> None:
        """
        Send formatted output to the destination.

        Args:
            formatted_output: The formatted output to send

        """

__init__(formatter)

Initialize reporter with a formatter.

Parameters:

Name Type Description Default
formatter Formatter

Formatter to use for formatting results

 required
Source code in easybench/reporters.py 
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def __init__(self, formatter: Formatter) -> None:
    """
    Initialize reporter with a formatter.

    Args:
        formatter: Formatter to use for formatting results

    """
    self.formatter = formatter

report(results, stats=None, config=None)

Report benchmark results.

Parameters:

Name Type Description Default
results ResultsType

Dictionary mapping benchmark names to result data

 required
stats StatsType | None

Dictionary of calculated statistics

 None
config BenchConfig | None

Benchmark configuration. Required.

 None
Source code in easybench/reporters.py 
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def report(
    self,
    results: ResultsType,
    stats: StatsType | None = None,
    config: BenchConfig | None = None,
) -> None:
    """
    Report benchmark results.

    Args:
        results: Dictionary mapping benchmark names to result data
        stats: Dictionary of calculated statistics
        config: Benchmark configuration. Required.

    """
    formatted = self.formatter.format_(
        results=results,
        stats=stats,
        config=config,
    )
    self.report_formatted(formatted)

report_formatted(formatted_output) abstractmethod

Send formatted output to the destination.

Parameters:

Name Type Description Default
formatted_output Formatted

The formatted output to send

 required
Source code in easybench/reporters.py 
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@abstractmethod
def report_formatted(self, formatted_output: Formatted) -> None:
    """
    Send formatted output to the destination.

    Args:
        formatted_output: The formatted output to send

    """

SimpleConsoleReporter

Bases: SimpleStreamReporter

Reporter that outputs concise metric values to the console (stdout).

Source code in easybench/reporters.py 
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class SimpleConsoleReporter(SimpleStreamReporter):
    """Reporter that outputs concise metric values to the console (stdout)."""

    def __init__(
        self,
        metric: MetricType = "avg",
        item_format: Callable[[str, float], str] | None = None,
        list_format: Callable[[list[str]], str] | None = None,
    ) -> None:
        """
        Initialize simple console reporter.

        Args:
            metric: The metric to output (avg, min, max, avg_memory, max_memory)
            item_format: Optional function to format individual values
                         Takes method_name and value as arguments
            list_format: Optional function to join multiple values

        """
        super().__init__(
            metric=metric,
            item_format=item_format,
            list_format=list_format,
            file=None,
        )

__init__(metric='avg', item_format=None, list_format=None)

Initialize simple console reporter.

Parameters:

Name Type Description Default
metric MetricType

The metric to output (avg, min, max, avg_memory, max_memory)

 'avg'
item_format Callable[[str, float], str] | None

Optional function to format individual values Takes method_name and value as arguments

 None
list_format Callable[[list[str]], str] | None

Optional function to join multiple values

 None
Source code in easybench/reporters.py 
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def __init__(
    self,
    metric: MetricType = "avg",
    item_format: Callable[[str, float], str] | None = None,
    list_format: Callable[[list[str]], str] | None = None,
) -> None:
    """
    Initialize simple console reporter.

    Args:
        metric: The metric to output (avg, min, max, avg_memory, max_memory)
        item_format: Optional function to format individual values
                     Takes method_name and value as arguments
        list_format: Optional function to join multiple values

    """
    super().__init__(
        metric=metric,
        item_format=item_format,
        list_format=list_format,
        file=None,
    )

SimpleFormatter

Bases: Formatter

Format results as concise metric values.

Source code in easybench/reporters.py 
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class SimpleFormatter(Formatter):
    """Format results as concise metric values."""

    def __init__(
        self,
        metric: MetricType = "avg",
        item_format: Callable[[str, float], str] | None = None,
        list_format: Callable[[list[str]], str] | None = None,
    ) -> None:
        """
        Initialize with a metric to output.

        Args:
            metric: The metric to output (avg, min, max, avg_memory, max_memory)
            item_format: Optional function to format individual values
                         Takes method_name and value as arguments
            list_format: Optional function to join multiple values

        """
        self.metric = metric
        if metric not in ("avg", "min", "max", "avg_memory", "max_memory"):
            msg = f"'{metric}' is not a valid metric for Simple formatter"
            raise ValueError(msg)

        # Use provided functions or defaults
        self.item_format = item_format or (lambda _, value: str(value))
        self.list_format = list_format or (lambda values: "\n".join(values) + "\n")

    def format(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> str:
        """
        Format results as concise metric values.

        Args:
            results: Dictionary mapping benchmark names to result data
            stats: Dictionary of calculated statistics (memory values in bytes)
            config: Benchmark configuration

        Returns:
            Simple metrics as a string with memory values converted to specified unit

        """
        memory_unit = MemoryUnit.from_config(config)
        time_unit = TimeUnit.from_config(config)
        values = []
        _ = results

        for method_name in self.sort_keys(stats, config):
            stat = stats[method_name]

            # Get the value for the specified metric
            value: float | None = None
            if self.metric in stat:
                value = stat[self.metric]
                # Convert if it's a memory metric
                if self.metric in ("avg_memory", "max_memory"):
                    value = memory_unit.convert_bytes(value)
                # Convert if it's a time metric
                elif self.metric in ("avg", "min", "max"):
                    value = time_unit.convert_seconds(value)

            if value is not None:
                values.append(self.item_format(method_name, value))
            else:
                values.append("")

        return self.list_format(values)

__init__(metric='avg', item_format=None, list_format=None)

Initialize with a metric to output.

Parameters:

Name Type Description Default
metric MetricType

The metric to output (avg, min, max, avg_memory, max_memory)

 'avg'
item_format Callable[[str, float], str] | None

Optional function to format individual values Takes method_name and value as arguments

 None
list_format Callable[[list[str]], str] | None

Optional function to join multiple values

 None
Source code in easybench/reporters.py 
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def __init__(
    self,
    metric: MetricType = "avg",
    item_format: Callable[[str, float], str] | None = None,
    list_format: Callable[[list[str]], str] | None = None,
) -> None:
    """
    Initialize with a metric to output.

    Args:
        metric: The metric to output (avg, min, max, avg_memory, max_memory)
        item_format: Optional function to format individual values
                     Takes method_name and value as arguments
        list_format: Optional function to join multiple values

    """
    self.metric = metric
    if metric not in ("avg", "min", "max", "avg_memory", "max_memory"):
        msg = f"'{metric}' is not a valid metric for Simple formatter"
        raise ValueError(msg)

    # Use provided functions or defaults
    self.item_format = item_format or (lambda _, value: str(value))
    self.list_format = list_format or (lambda values: "\n".join(values) + "\n")

format(results, stats, config)

Format results as concise metric values.

Parameters:

Name Type Description Default
results ResultsType

Dictionary mapping benchmark names to result data

 required
stats StatsType

Dictionary of calculated statistics (memory values in bytes)

 required
config BenchConfig

Benchmark configuration

 required

Returns:

Type Description
str

Simple metrics as a string with memory values converted to specified unit
Source code in easybench/reporters.py 
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def format(
    self,
    results: ResultsType,
    stats: StatsType,
    config: BenchConfig,
) -> str:
    """
    Format results as concise metric values.

    Args:
        results: Dictionary mapping benchmark names to result data
        stats: Dictionary of calculated statistics (memory values in bytes)
        config: Benchmark configuration

    Returns:
        Simple metrics as a string with memory values converted to specified unit

    """
    memory_unit = MemoryUnit.from_config(config)
    time_unit = TimeUnit.from_config(config)
    values = []
    _ = results

    for method_name in self.sort_keys(stats, config):
        stat = stats[method_name]

        # Get the value for the specified metric
        value: float | None = None
        if self.metric in stat:
            value = stat[self.metric]
            # Convert if it's a memory metric
            if self.metric in ("avg_memory", "max_memory"):
                value = memory_unit.convert_bytes(value)
            # Convert if it's a time metric
            elif self.metric in ("avg", "min", "max"):
                value = time_unit.convert_seconds(value)

        if value is not None:
            values.append(self.item_format(method_name, value))
        else:
            values.append("")

    return self.list_format(values)

SimpleStreamReporter

Bases: StreamReporter

Reporter that outputs concise metric values to a stream.

Source code in easybench/reporters.py 
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class SimpleStreamReporter(StreamReporter):
    """Reporter that outputs concise metric values to a stream."""

    def __init__(
        self,
        metric: MetricType = "avg",
        item_format: Callable[[str, float], str] | None = None,
        list_format: Callable[[list[str]], str] | None = None,
        file: TextIO | None = None,
    ) -> None:
        """
        Initialize simple stream reporter.

        Args:
            metric: The metric to output (avg, min, max, avg_memory, max_memory)
            item_format: Optional function to format individual values
                         Takes method_name and value as arguments
            list_format: Optional function to join multiple values
            file: File object to write to (defaults to sys.stdout)

        """
        formatter = SimpleFormatter(
            metric=metric,
            item_format=item_format,
            list_format=list_format,
        )
        super().__init__(formatter=formatter, file=file)

__init__(metric='avg', item_format=None, list_format=None, file=None)

Initialize simple stream reporter.

Parameters:

Name Type Description Default
metric MetricType

The metric to output (avg, min, max, avg_memory, max_memory)

 'avg'
item_format Callable[[str, float], str] | None

Optional function to format individual values Takes method_name and value as arguments

 None
list_format Callable[[list[str]], str] | None

Optional function to join multiple values

 None
file TextIO | None

File object to write to (defaults to sys.stdout)

 None
Source code in easybench/reporters.py 
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def __init__(
    self,
    metric: MetricType = "avg",
    item_format: Callable[[str, float], str] | None = None,
    list_format: Callable[[list[str]], str] | None = None,
    file: TextIO | None = None,
) -> None:
    """
    Initialize simple stream reporter.

    Args:
        metric: The metric to output (avg, min, max, avg_memory, max_memory)
        item_format: Optional function to format individual values
                     Takes method_name and value as arguments
        list_format: Optional function to join multiple values
        file: File object to write to (defaults to sys.stdout)

    """
    formatter = SimpleFormatter(
        metric=metric,
        item_format=item_format,
        list_format=list_format,
    )
    super().__init__(formatter=formatter, file=file)

StreamReporter

Bases: Reporter

Reporter that sends output to a stream.

Source code in easybench/reporters.py 
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class StreamReporter(Reporter):
    """Reporter that sends output to a stream."""

    def __init__(
        self,
        formatter: Formatter | None = None,
        file: TextIO | None = None,
    ) -> None:
        """
        Initialize stream reporter.

        Args:
            formatter: Formatter to use (defaults to TableFormatter)
            file: File object to write to (defaults to sys.stdout)

        """
        super().__init__(formatter or TableFormatter())
        self.file = file

    def report_formatted(self, formatted_output: Formatted) -> None:
        """
        Print formatted output to stream.

        Args:
            formatted_output: The formatted output to print

        """
        _file = self.file or sys.stdout
        print(formatted_output, file=_file, end="")

__init__(formatter=None, file=None)

Initialize stream reporter.

Parameters:

Name Type Description Default
formatter Formatter | None

Formatter to use (defaults to TableFormatter)

 None
file TextIO | None

File object to write to (defaults to sys.stdout)

 None
Source code in easybench/reporters.py 
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def __init__(
    self,
    formatter: Formatter | None = None,
    file: TextIO | None = None,
) -> None:
    """
    Initialize stream reporter.

    Args:
        formatter: Formatter to use (defaults to TableFormatter)
        file: File object to write to (defaults to sys.stdout)

    """
    super().__init__(formatter or TableFormatter())
    self.file = file

report_formatted(formatted_output)

Print formatted output to stream.

Parameters:

Name Type Description Default
formatted_output Formatted

The formatted output to print

 required
Source code in easybench/reporters.py 
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def report_formatted(self, formatted_output: Formatted) -> None:
    """
    Print formatted output to stream.

    Args:
        formatted_output: The formatted output to print

    """
    _file = self.file or sys.stdout
    print(formatted_output, file=_file, end="")

TableFormatter

Bases: Formatter

Format results as text tables (current default format).

Source code in easybench/reporters.py 
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class TableFormatter(Formatter):
    """Format results as text tables (current default format)."""

    def __init__(self, precision: int = 6) -> None:
        """
        Initialize.

        Args:
            precision: Number of decimal places to display for numeric values

        """
        super().__init__()
        self.precision = precision

    def format(
        self,
        results: ResultsType,
        stats: StatsType,
        config: BenchConfig,
    ) -> str:
        """Format results as text tables."""
        output = []
        self.max_name_len = max(visual_width(name) for name in results)
        self.sorted_methods = self.sort_keys(stats, config)

        # Pre-calculate all formatting data in one go
        self.formatting_data = self._prepare_formatting_data(stats, config)

        # Add title line
        output.append(self._format_title(config))

        # Format header
        header = self._format_header(config)
        output.append(header)

        # Add dash line
        dash_length = self._calculate_dash_length(config)
        output.append("-" * dash_length)

        # Format result lines
        if config.trials == 1:
            self._format_single_trial_results(output, config)
        else:
            self._format_multiple_trial_results(output, config)

        # Add function outputs if requested
        if config.show_output:
            self._format_output_section(output, results)

        return "\n".join(output) + "\n"

    def _prepare_formatting_data(
        self,
        stats: StatsType,
        config: BenchConfig,
    ) -> dict[str, Any]:
        """
        Prepare all formatting data.

        Returns:
            Dictionary containing all pre-calculated formatting data

        """
        memory_unit = MemoryUnit.from_config(config)
        time_unit = TimeUnit.from_config(config)

        data: dict[str, Any] = {
            "memory_unit": memory_unit,
            "time_unit": time_unit,
            "converted_stats": {},
            "column_widths": {},
            "extremes": {},
        }

        # Convert all values once and store them
        for method_name in stats:
            stat = stats[method_name]
            if config.time:
                converted = {
                    "avg_time": time_unit.convert_seconds(stat["avg"]),
                    "min_time": time_unit.convert_seconds(stat["min"]),
                    "max_time": time_unit.convert_seconds(stat["max"]),
                }
            else:
                converted = {}

            if config.memory:
                avg_memory = stat.get("avg_memory", 0.0)
                max_memory = stat.get("max_memory", avg_memory)
                converted["avg_memory"] = memory_unit.convert_bytes(avg_memory)
                converted["max_memory"] = memory_unit.convert_bytes(max_memory)

            data["converted_stats"][method_name] = converted

        # Calculate column widths based on converted values
        self._calculate_column_widths(data, config)

        # Calculate extremes for coloring
        self._calculate_extremes(data, config)

        return data

    def _calculate_column_widths(
        self,
        data: dict[str, Any],
        config: BenchConfig,
    ) -> None:
        """Calculate optimal column widths and store in formatting data."""
        converted_stats = data["converted_stats"]
        memory_unit = data["memory_unit"]
        time_unit = data["time_unit"]

        # Calculate time column widths
        if config.time:
            # Collect all time values for width calculation
            time_values = []
            for converted in converted_stats.values():
                time_values.extend(
                    [
                        converted["avg_time"],
                        converted["min_time"],
                        converted["max_time"],
                    ],
                )

            max_time_str_len = max(
                len(f"{val:.{self.precision}f}") for val in time_values
            )

            if config.trials == 1:
                time_header_len = len(f"Time ({time_unit})")
                data["column_widths"]["time"] = (
                    max(max_time_str_len, time_header_len) + 2
                )
            else:
                headers = [
                    f"Avg Time ({time_unit})",
                    f"Min Time ({time_unit})",
                    f"Max Time ({time_unit})",
                ]
                for i, key in enumerate(["avg_time", "min_time", "max_time"]):
                    data["column_widths"][key] = (
                        max(max_time_str_len, len(headers[i])) + 2
                    )

        # Calculate memory column widths if needed
        if config.memory:
            memory_values = []
            for converted in converted_stats.values():
                memory_values.extend([converted["avg_memory"], converted["max_memory"]])

            max_memory_str_len = max(
                len(f"{val:.{self.precision}f}") for val in memory_values
            )

            if config.trials == 1:
                memory_header_len = len(f"Memory ({memory_unit})")
                data["column_widths"]["memory"] = (
                    max(max_memory_str_len, memory_header_len) + 2
                )
            else:
                headers = [f"Avg Mem ({memory_unit})", f"Max Mem ({memory_unit})"]
                for i, key in enumerate(["avg_memory", "max_memory"]):
                    data["column_widths"][key] = (
                        max(max_memory_str_len, len(headers[i])) + 2
                    )

    def _calculate_extremes(self, data: dict[str, Any], config: BenchConfig) -> None:
        """Calculate min/max values for coloring and store in formatting data."""
        converted_stats = data["converted_stats"]

        # Time extremes
        if config.time:
            time_metrics = ["avg_time", "min_time", "max_time"]
            for metric in time_metrics:
                values = [converted[metric] for converted in converted_stats.values()]
                data["extremes"][f"min_{metric}"] = min(values)
                data["extremes"][f"max_{metric}"] = max(values)

        # Memory extremes
        if config.memory:
            memory_metrics = ["avg_memory", "max_memory"]
            for metric in memory_metrics:
                values = [converted[metric] for converted in converted_stats.values()]
                data["extremes"][f"min_{metric}"] = min(values)
                data["extremes"][f"max_{metric}"] = max(values)

    def _format_title(self, config: BenchConfig) -> str:
        """Format the benchmark title."""
        return (
            f"\nBenchmark Results ({config.trials} trial"
            f"{'s' if config.trials > 1 else ''}):\n"
        )

    def _format_header(self, config: BenchConfig) -> str:
        """Format the header row."""
        memory_unit = self.formatting_data["memory_unit"]
        time_unit = self.formatting_data["time_unit"]
        column_widths = self.formatting_data["column_widths"]

        if config.trials == 1:
            header = "Function".ljust(self.max_name_len + 2)
            if config.time:
                header += f"Time ({time_unit})".rjust(column_widths["time"])
            if config.memory:
                header += f"Memory ({memory_unit})".rjust(column_widths["memory"])
        else:
            header = "Function".ljust(self.max_name_len + 2)
            if config.time:
                header += f"Avg Time ({time_unit})".rjust(column_widths["avg_time"])
                header += f"Min Time ({time_unit})".rjust(column_widths["min_time"])
                header += f"Max Time ({time_unit})".rjust(column_widths["max_time"])
            if config.memory:
                header += f"Avg Mem ({memory_unit})".rjust(column_widths["avg_memory"])
                header += f"Max Mem ({memory_unit})".rjust(column_widths["max_memory"])
        return header

    def _calculate_dash_length(self, config: BenchConfig) -> int:
        """Calculate dash line length."""
        column_widths = self.formatting_data["column_widths"]

        total_width = self.max_name_len + 2

        if config.trials == 1:
            if config.time:
                total_width += column_widths["time"]
            if config.memory:
                total_width += column_widths["memory"]
        else:
            if config.time:
                total_width += (
                    column_widths["avg_time"]
                    + column_widths["min_time"]
                    + column_widths["max_time"]
                )
            if config.memory:
                total_width += column_widths["avg_memory"] + column_widths["max_memory"]

        return total_width

    def _format_single_trial_results(
        self,
        output: list[str],
        config: BenchConfig,
    ) -> None:
        """Format results for a single trial benchmark."""
        converted_stats = self.formatting_data["converted_stats"]
        column_widths = self.formatting_data["column_widths"]
        extremes = self.formatting_data["extremes"]

        color = config.color if len(converted_stats) > 1 else False

        for method_name in self.sorted_methods:
            converted = converted_stats[method_name]
            line = visual_ljust(method_name, self.max_name_len + 2)

            if config.time:
                # Format time values with coloring
                time_val = self._format_metric(
                    converted["avg_time"],
                    extremes["min_avg_time"],
                    extremes["max_avg_time"],
                    width=column_widths["time"],
                    color=color,
                )
                line += time_val

            if config.memory:
                # Format memory values with coloring
                mem_val = self._format_metric(
                    converted["avg_memory"],
                    extremes["min_avg_memory"],
                    extremes["max_avg_memory"],
                    width=column_widths["memory"],
                    color=color,
                )
                line += mem_val

            output.append(line)

    def _format_multiple_trial_results(
        self,
        output: list[str],
        config: BenchConfig,
    ) -> None:
        """Format results for multiple trial benchmarks."""
        converted_stats = self.formatting_data["converted_stats"]
        column_widths = self.formatting_data["column_widths"]
        extremes = self.formatting_data["extremes"]

        color = config.color if len(converted_stats) > 1 else False

        for method_name in self.sorted_methods:
            converted = converted_stats[method_name]
            line = visual_ljust(method_name, self.max_name_len + 2)

            if config.time:
                # Format time values with coloring
                avg_val = self._format_metric(
                    converted["avg_time"],
                    extremes["min_avg_time"],
                    extremes["max_avg_time"],
                    width=column_widths["avg_time"],
                    color=color,
                )
                min_val = self._format_metric(
                    converted["min_time"],
                    extremes["min_min_time"],
                    extremes["max_min_time"],
                    width=column_widths["min_time"],
                    color=color,
                )
                max_val = self._format_metric(
                    converted["max_time"],
                    extremes["min_max_time"],
                    extremes["max_max_time"],
                    width=column_widths["max_time"],
                    color=color,
                )

                line += (
                    avg_val.rjust(column_widths["avg_time"])
                    + min_val.rjust(column_widths["min_time"])
                    + max_val.rjust(column_widths["max_time"])
                )

            if config.memory:
                # Format memory values with coloring
                avg_mem = self._format_metric(
                    converted["avg_memory"],
                    extremes["min_avg_memory"],
                    extremes["max_avg_memory"],
                    width=column_widths["avg_memory"],
                    color=color,
                )
                peak_mem = self._format_metric(
                    converted["max_memory"],
                    extremes["min_max_memory"],
                    extremes["max_max_memory"],
                    width=column_widths["max_memory"],
                    color=color,
                )
                line += avg_mem.rjust(column_widths["avg_memory"]) + peak_mem.rjust(
                    column_widths["max_memory"],
                )

            output.append(line)

    def _format_output_section(
        self,
        output: list[str],
        results: ResultsType,
    ) -> None:
        """Format the output section."""
        output.append("\nBenchmark Return Values:")
        output.append("-" * max(self.max_name_len + 10, 30))

        for method_name in self.sorted_methods:
            if "output" not in results[method_name]:
                continue

            return_values = results[method_name]["output"]
            if len({str(val) for val in return_values}) == 1:
                output.append(f"{method_name}: {return_values[0]}")
            else:
                output.append(f"{method_name}:")
                for i, val in enumerate(return_values):
                    output.append(f"  Trial {i+1}: {val}")

    def _format_metric(
        self,
        value: float,
        min_value: float,
        max_value: float,
        width: int,
        *,
        color: bool = True,
    ) -> str:
        """
        Format a metric value with appropriate coloring.

        Args:
            value: The value to format
            min_value: The minimum value across all benchmarks
            max_value: The maximum value across all benchmarks
            width: The width to format the value to
            color: Whether to use colored output

        Returns:
            Formatted string with color codes if color is True

        """
        # Define ANSI color codes
        min_color = "\033[32m"  # GREEN
        max_color = "\033[31m"  # RED
        reset = "\033[0m"
        formatted = f"{value:.{self.precision}f}".rjust(width)

        if not color:
            return formatted

        if value == min_value:
            return f"{min_color}{formatted}{reset}"
        if value == max_value:
            return f"{max_color}{formatted}{reset}"
        return formatted

__init__(precision=6)

Initialize.

Parameters:

Name Type Description Default
precision int

Number of decimal places to display for numeric values

 6
Source code in easybench/reporters.py 
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def __init__(self, precision: int = 6) -> None:
    """
    Initialize.

    Args:
        precision: Number of decimal places to display for numeric values

    """
    super().__init__()
    self.precision = precision

format(results, stats, config)

Format results as text tables.

Source code in easybench/reporters.py 
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def format(
    self,
    results: ResultsType,
    stats: StatsType,
    config: BenchConfig,
) -> str:
    """Format results as text tables."""
    output = []
    self.max_name_len = max(visual_width(name) for name in results)
    self.sorted_methods = self.sort_keys(stats, config)

    # Pre-calculate all formatting data in one go
    self.formatting_data = self._prepare_formatting_data(stats, config)

    # Add title line
    output.append(self._format_title(config))

    # Format header
    header = self._format_header(config)
    output.append(header)

    # Add dash line
    dash_length = self._calculate_dash_length(config)
    output.append("-" * dash_length)

    # Format result lines
    if config.trials == 1:
        self._format_single_trial_results(output, config)
    else:
        self._format_multiple_trial_results(output, config)

    # Add function outputs if requested
    if config.show_output:
        self._format_output_section(output, results)

    return "\n".join(output) + "\n"

TimeUnit

Bases: str, Enum

Time unit options for display.

Source code in easybench/reporters.py 
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class TimeUnit(str, Enum):
    """Time unit options for display."""

    NANOSECONDS = "ns"
    MICROSECONDS = "μs"
    MILLISECONDS = "ms"
    SECONDS = "s"
    MINUTES = "m"

    def __str__(self) -> str:
        """Convert unit to string."""
        return self.value

    def convert_seconds(self, seconds: float) -> float:
        """
        Convert seconds to this time unit.

        Args:
            seconds (float): The time in seconds.

        Returns:
            float: The converted time in this time unit.

        """
        unit_multipliers = {
            TimeUnit.NANOSECONDS: 1e9,
            TimeUnit.MICROSECONDS: 1e6,
            TimeUnit.MILLISECONDS: 1e3,
            TimeUnit.SECONDS: 1,
            TimeUnit.MINUTES: 1 / 60,
        }

        multiplier = unit_multipliers[self]
        return seconds * multiplier

    @classmethod
    def from_config(cls, config: BenchConfig) -> TimeUnit:
        """Get time unit from config."""
        unit = TimeUnit.SECONDS

        if isinstance(config.time, str):
            time_str = config.time.lower()
            # Handle 'us' as an alternative for microseconds
            unit = TimeUnit.MICROSECONDS if time_str == "us" else TimeUnit(time_str)

        elif isinstance(config.time, TimeUnit):
            unit = config.time

        return unit

__str__()

Convert unit to string.

Source code in easybench/reporters.py 
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def __str__(self) -> str:
    """Convert unit to string."""
    return self.value

convert_seconds(seconds)

Convert seconds to this time unit.

Parameters:

Name Type Description Default
seconds float

The time in seconds.

 required

Returns:

Name Type Description
float float

The converted time in this time unit.
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def convert_seconds(self, seconds: float) -> float:
    """
    Convert seconds to this time unit.

    Args:
        seconds (float): The time in seconds.

    Returns:
        float: The converted time in this time unit.

    """
    unit_multipliers = {
        TimeUnit.NANOSECONDS: 1e9,
        TimeUnit.MICROSECONDS: 1e6,
        TimeUnit.MILLISECONDS: 1e3,
        TimeUnit.SECONDS: 1,
        TimeUnit.MINUTES: 1 / 60,
    }

    multiplier = unit_multipliers[self]
    return seconds * multiplier

from_config(config) classmethod

Get time unit from config.

Source code in easybench/reporters.py 
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@classmethod
def from_config(cls, config: BenchConfig) -> TimeUnit:
    """Get time unit from config."""
    unit = TimeUnit.SECONDS

    if isinstance(config.time, str):
        time_str = config.time.lower()
        # Handle 'us' as an alternative for microseconds
        unit = TimeUnit.MICROSECONDS if time_str == "us" else TimeUnit(time_str)

    elif isinstance(config.time, TimeUnit):
        unit = config.time

    return unit