taxprofiler/bin/check_samplesheet.py

#!/usr/bin/env python


"""Provide a command line tool to validate and transform tabular samplesheets."""


import argparse
import csv
import logging
import sys
from collections import Counter
from pathlib import Path


logger = logging.getLogger()


class RowChecker:
    """
    Define a service that can validate and transform each given row.

    Attributes:
        modified (list): A list of dicts, where each dict corresponds to a previously
            validated and transformed row. The order of rows is maintained.

    """

    VALID_FORMATS = (
        ".fq.gz",
        ".fastq.gz",
    )

    def __init__(
        self,
        sample_col="sample",
        first_col="fastq_1",
        second_col="fastq_2",
        single_col="single_end",
        **kwargs,
    ):
        """
        Initialize the row checker with the expected column names.

        Args:
            sample_col (str): The name of the column that contains the sample name
                (default "sample").
            first_col (str): The name of the column that contains the first (or only)
                FASTQ file path (default "fastq_1").
            second_col (str): The name of the column that contains the second (if any)
                FASTQ file path (default "fastq_2").
            single_col (str): The name of the new column that will be inserted and
                records whether the sample contains single- or paired-end sequencing
                reads (default "single_end").

        """
        super().__init__(**kwargs)
        self._sample_col = sample_col
        self._first_col = first_col
        self._second_col = second_col
        self._single_col = single_col
        self._seen = set()
        self.modified = []

    def validate_and_transform(self, row):
        """
        Perform all validations on the given row and insert the read pairing status.

        Args:
            row (dict): A mapping from column headers (keys) to elements of that row
                (values).

        """
        self._validate_sample(row)
        self._validate_first(row)
        self._validate_second(row)
        self._validate_pair(row)
        self._seen.add((row[self._sample_col], row[self._first_col]))
        self.modified.append(row)

    def _validate_sample(self, row):
        """Assert that the sample name exists and convert spaces to underscores."""
        assert len(row[self._sample_col]) > 0, "Sample input is required."
        # Sanitize samples slightly.
        row[self._sample_col] = row[self._sample_col].replace(" ", "_")

    def _validate_first(self, row):
        """Assert that the first FASTQ entry is non-empty and has the right format."""
        assert len(row[self._first_col]) > 0, "At least the first FASTQ file is required."
        self._validate_fastq_format(row[self._first_col])

    def _validate_second(self, row):
        """Assert that the second FASTQ entry has the right format if it exists."""
        if len(row[self._second_col]) > 0:
            self._validate_fastq_format(row[self._second_col])

    def _validate_pair(self, row):
        """Assert that read pairs have the same file extension. Report pair status."""
        if row[self._first_col] and row[self._second_col]:
            row[self._single_col] = False
            assert (
                Path(row[self._first_col]).suffixes[-2:] == Path(row[self._second_col]).suffixes[-2:]
            ), "FASTQ pairs must have the same file extensions."
        else:
            row[self._single_col] = True

    def _validate_fastq_format(self, filename):
        """Assert that a given filename has one of the expected FASTQ extensions."""
        assert any(filename.endswith(extension) for extension in self.VALID_FORMATS), (
            f"The FASTQ file has an unrecognized extension: {filename}\n"
            f"It should be one of: {', '.join(self.VALID_FORMATS)}"
        )

    def validate_unique_samples(self):
        """
        Assert that the combination of sample name and FASTQ filename is unique.

        In addition to the validation, also rename the sample if more than one sample,
        FASTQ file combination exists.

        """
        assert len(self._seen) == len(self.modified), "The pair of sample name and FASTQ must be unique."
        if len({pair[0] for pair in self._seen}) < len(self._seen):
            counts = Counter(pair[0] for pair in self._seen)
            seen = Counter()
            for row in self.modified:
                sample = row[self._sample_col]
                seen[sample] += 1
                if counts[sample] > 1:
                    row[self._sample_col] = f"{sample}_T{seen[sample]}"


def read_head(handle, num_lines=10):
    """Read the specified number of lines from the current position in the file."""
    lines = []
    for idx, line in enumerate(handle):
        if idx == num_lines:
            break
        lines.append(line)
    return "".join(lines)


def sniff_format(handle):
    """
    Detect the tabular format.

    Args:
        handle (text file): A handle to a `text file`_ object. The read position is
        expected to be at the beginning (index 0).

    Returns:
        csv.Dialect: The detected tabular format.

    .. _text file:
        https://docs.python.org/3/glossary.html#term-text-file

    """
    peek = read_head(handle)
    handle.seek(0)
    sniffer = csv.Sniffer()
    if not sniffer.has_header(peek):
        logger.critical(f"The given sample sheet does not appear to contain a header.")
        sys.exit(1)
    dialect = sniffer.sniff(peek)
    return dialect


def check_samplesheet(file_in, file_out):
    """
    Check that the tabular samplesheet has the structure expected by nf-core pipelines.

    Validate the general shape of the table, expected columns, and each row. Also add
    an additional column which records whether one or two FASTQ reads were found.

    Args:
        file_in (pathlib.Path): The given tabular samplesheet. The format can be either
            CSV, TSV, or any other format automatically recognized by ``csv.Sniffer``.
        file_out (pathlib.Path): Where the validated and transformed samplesheet should
            be created; always in CSV format.

    Example:
        This function checks that the samplesheet follows the following structure,
        see also the `viral recon samplesheet`_::

            sample,fastq_1,fastq_2
            SAMPLE_PE,SAMPLE_PE_RUN1_1.fastq.gz,SAMPLE_PE_RUN1_2.fastq.gz
            SAMPLE_PE,SAMPLE_PE_RUN2_1.fastq.gz,SAMPLE_PE_RUN2_2.fastq.gz
            SAMPLE_SE,SAMPLE_SE_RUN1_1.fastq.gz,

    .. _viral recon samplesheet:
        https://raw.githubusercontent.com/nf-core/test-datasets/viralrecon/samplesheet/samplesheet_test_illumina_amplicon.csv

    """
    required_columns = {"sample", "fastq_1", "fastq_2"}
    # See https://docs.python.org/3.9/library/csv.html#id3 to read up on `newline=""`.
    with file_in.open(newline="") as in_handle:
        reader = csv.DictReader(in_handle, dialect=sniff_format(in_handle))
        # Validate the existence of the expected header columns.
        if not required_columns.issubset(reader.fieldnames):
            logger.critical(f"The sample sheet **must** contain the column headers: {', '.join(required_columns)}.")
            sys.exit(1)
        # Validate each row.
        checker = RowChecker()
        for i, row in enumerate(reader):
            try:
                checker.validate_and_transform(row)
            except AssertionError as error:
                logger.critical(f"{str(error)} On line {i + 2}.")
                sys.exit(1)
        checker.validate_unique_samples()
    header = list(reader.fieldnames)
    header.insert(1, "single_end")
    # See https://docs.python.org/3.9/library/csv.html#id3 to read up on `newline=""`.
    with file_out.open(mode="w", newline="") as out_handle:
        writer = csv.DictWriter(out_handle, header, delimiter=",")
        writer.writeheader()
        for row in checker.modified:
            writer.writerow(row)


def parse_args(argv=None):
    """Define and immediately parse command line arguments."""
    parser = argparse.ArgumentParser(
        description="Validate and transform a tabular samplesheet.",
        epilog="Example: python check_samplesheet.py samplesheet.csv samplesheet.valid.csv",
    )
    parser.add_argument(
        "file_in",
        metavar="FILE_IN",
        type=Path,
        help="Tabular input samplesheet in CSV or TSV format.",
    )
    parser.add_argument(
        "file_out",
        metavar="FILE_OUT",
        type=Path,
        help="Transformed output samplesheet in CSV format.",
    )
    parser.add_argument(
        "-l",
        "--log-level",
        help="The desired log level (default WARNING).",
        choices=("CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG"),
        default="WARNING",
    )
    return parser.parse_args(argv)


def main(argv=None):
    """Coordinate argument parsing and program execution."""
    args = parse_args(argv)
    logging.basicConfig(level=args.log_level, format="[%(levelname)s] %(message)s")
    if not args.file_in.is_file():
        logger.error(f"The given input file {args.file_in} was not found!")
        sys.exit(2)
    args.file_out.parent.mkdir(parents=True, exist_ok=True)
    check_samplesheet(args.file_in, args.file_out)


if __name__ == "__main__":
    sys.exit(main())