python-bio-error-handling

name	python-bio-error-handling
description	Handle malformed FASTA/GFF via try/except/else/finally, custom exceptions, raise-from chaining. Use for parsers crashing on bad input, strict vs lenient FASTA parsing, KeyError/IndexError/ValueError, or batches skipping bad records.
tool_type	python
primary_tool	Python

Error Handling for Bioinformatics

When to Use

• A parser (FASTA/GFF/VCF/GenBank) needs to fail loudly on malformed records instead of silently producing wrong results.
• You want to distinguish "file not found" from "no permission" from "file exists but is corrupt" with different recovery paths.
• A batch job over thousands of sequences/records should skip bad entries and report them, rather than dying on the first one.
• You are debugging a KeyError, IndexError, ValueError, or UnicodeDecodeError raised while parsing a bioinformatics file format.
• You need to preserve the original traceback when re-raising a more specific, domain-level exception.

Version Compatibility

Pure standard library — Python ≥3.10 (uses dict[str, str] / str | None type hints natively). No third-party dependencies.

Prerequisites

• Comfortable with Python functions, dict/set, and basic file I/O (open, with).
• Familiarity with a sequence file format (FASTA/GFF) helps but isn't required — see bio-sequence-io-read-sequences for parsing basics.

Custom Exception Hierarchy

Goal: give callers a way to catch "any bioinformatics error" or a specific failure mode, instead of bare Exception. Approach: one base class, subclasses carry structured context (which chars, which line) so error messages are actionable.

class BioinformaticsError(Exception):
    """Base for all pipeline errors."""

class InvalidSequenceError(BioinformaticsError):
    """Raised when a sequence contains characters outside the expected alphabet."""
    def __init__(self, invalid_chars, seq_type="DNA"):
        self.invalid_chars = invalid_chars
        super().__init__(f"Invalid {seq_type} characters: {invalid_chars}")

class SequenceLengthError(BioinformaticsError):
    """Raised when a sequence violates a minimum/maximum length constraint."""
    def __init__(self, actual, minimum=None, maximum=None):
        if minimum and actual < minimum:
            msg = f"Sequence too short: {actual} < {minimum}"
        elif maximum and actual > maximum:
            msg = f"Sequence too long: {actual} > {maximum}"
        else:
            msg = f"Invalid sequence length: {actual}"
        super().__init__(msg)

class FastaParseError(BioinformaticsError):
    """Raised on FASTA/GFF format violations, with file/line context for debugging."""
     ():
        parts = [message]
         filename:
            parts.append()
         line_number:
            parts.append()
         line_content:
            parts.append()
        ().__init__(.join(parts))

 ():
    
    

try/except/else/finally Pattern

Goal: open a file, distinguishing recoverable errors (missing file) from real failures, and always clean up. Approach: except handles specific failure classes, else runs only on success, finally always runs (cleanup).

def read_fasta(filename: str) -> dict[str, str]:
    """Read a FASTA file into {id: sequence}, with per-failure-mode handling."""
    sequences: dict[str, str] = {}
    current_id = None
    f = None
    try:
        f = open(filename, 'r')
    except FileNotFoundError:
        raise  # let caller decide how to handle a missing file
    except PermissionError as e:
        raise FastaParseError(f"Cannot read '{filename}'") from e
    else:
        # Only runs if open() succeeded
        for line in f:
            line = line.strip()
            if line.startswith('>'):
                current_id = line[1:].split()[0]
                sequences[current_id] = []
            elif current_id:
                sequences[current_id].append(line)
        sequences = {k: ''.join(v) for k, v in sequences.items()}
    finally:
        if f:
            f.close()  # always runs, even if the loop above raised
    return sequences

Exception Chaining for Format Parsing

Goal: convert a low-level ValueError (e.g. from int()) into a domain-specific error without losing the original cause. Approach: raise NewError(...) from e attaches e as __cause__, visible in the traceback and via e.__cause__.

def parse_gff_line(line: str, line_number: int | None = None) -> dict:
    """Parse a single tab-separated GFF3 line into a field dict."""
    fields = line.strip().split('\t')
    if len(fields) != 9:
        raise FastaParseError(
            f"Expected 9 fields, got {len(fields)}",
            line_number=line_number, line_content=line.strip()
        )
    try:
        return {
            'seqid': fields[0], 'source': fields[1], 'type': fields[2],
            'start': int(fields[3]), 'end': int(fields[4]),
            'score': fields[5], 'strand': fields[6],
            'phase': fields[7], 'attributes': fields[8],
        }
    except ValueError as e:
        raise FastaParseError(
            "Cannot parse coordinates",
            line_number=line_number, line_content=line.strip()
        ) from e   # preserves the original ValueError traceback

Strict FASTA Parser

Goal: reject malformed FASTA (empty IDs, sequence before header, illegal IUPAC codes) with precise line-level errors. Approach: track the current record while scanning; validate on every header switch and at EOF for the last record.

def strict_fasta_parser(filename: str) -> dict[str, str]:
    """Parse FASTA with strict validation; raises FastaParseError on any violation."""
    sequences: dict[str, str] = {}
    current_id: str | None = None
    current_seq: list[str] = []
    VALID = set('ATGCNRYSWKMBDHV.-')  # IUPAC nucleotide codes + gap chars

    with open(filename, 'r') as f:
        for line_num, line in enumerate(f, 1):
            line = line.strip()
            if not line:
                continue
            if line.startswith('>'):
                if current_id is not None:
                    seq = ''.join(current_seq)
                    if not seq:
                        raise FastaParseError("Empty sequence", filename, line_num, f">{current_id}")
                    sequences[current_id] = seq
                if len(line) == 1:
                    raise FastaParseError("Empty sequence ID", filename, line_num, line)
                current_id = line[:].split()[]
                current_seq = []
            :
                 current_id  :
                     FastaParseError(, filename, line_num, line)
                invalid = (line.upper()) - VALID
                 invalid:
                     FastaParseError(, filename, line_num, line)
                current_seq.append(line.upper())

     current_id   :
        seq = .join(current_seq)
          seq:
             FastaParseError(, filename)
        sequences[current_id] = seq

     sequences

Batch Processing with Graceful Degradation

Goal: run an analysis over thousands of records without one bad record aborting the whole batch. Approach: catch the base BioinformaticsError, collect failures alongside results, and expose a strict switch for fail-fast use.

def batch_gc_analysis(sequences: dict[str, str], strict: bool = False):
    """Compute GC% per sequence. strict=True raises on first bad record;
    strict=False skips bad records and returns (results, errors)."""
    results, errors = {}, []
    for seq_id, seq in sequences.items():
        try:
            if not seq:
                raise SequenceLengthError(0, minimum=1)
            invalid = set(seq.upper()) - set('ATGCN')
            if invalid:
                raise InvalidSequenceError(invalid)
            s = seq.upper()
            results[seq_id] = round((s.count('G') + s.count('C')) / len(s) * 100, 2)
        except BioinformaticsError as e:
            if strict:
                raise
            errors.append((seq_id, str(e)))
    return results, errors

Common Built-in Exceptions in Parsing Code

• KeyError: looking up a gene/sample ID missing from a dict (gene_info['TP53']) — catch and report the missing key, or use .get() with a default.
• IndexError: a GFF/BED/VCF line has fewer tab-separated fields than expected — validate len(fields) before indexing.
• ValueError: int()/float() on a malformed coordinate (e.g. "12,345") — catch and chain into a domain error (see above).
• UnicodeDecodeError: reading a binary file (e.g. BAM, gzip) as text — open with the correct mode/encoding, or errors='replace' for lossy recovery.

Pitfalls

• Bare except:: catches KeyboardInterrupt and SystemExit — impossible to stop the script with Ctrl+C. Always name the exception.
• assert for input validation: disabled with python -O, so invalid input silently passes in production. Use if not condition: raise ValueError(...) for anything that must always be checked.
• raise NewError(...) from original: omitting from original hides the root cause in tracebacks (or worse, shows a misleading "during handling of the above exception" chain).
• else on try: runs only when no exception occurred — separates "might fail" from "should only run on success". Commonly forgotten, leading to code that runs even when the risky operation failed.
• finally runs even on return: useful for cleanup (file close, temp removal), but mutating results in finally can mask real errors.
• Catching BioinformaticsError too broadly: catch the most specific subclass first (InvalidSequenceError, SequenceLengthError, ...); put the base-class catch last as a fallback.

See Also

• bio-sequence-io-read-sequences — parsing FASTA/FASTQ/GenBank without reinventing the wrapped parsers here.
• bio-variant-calling-vcf-basics — VCF-specific parsing/validation where similar exception-chaining patterns apply.
• bio-genome-intervals-gtf-gff-handling — robust GFF/GTF field parsing beyond the single-line example above.