# Copyright 2006-2024 by Peter Cock.  All rights reserved.
# This file is part of the Biopython distribution and governed by your
# choice of the "Biopython License Agreement" or the "BSD 3-Clause License".
# Please see the LICENSE file that should have been included as part of this
# package.
r"""Sequence input/output as SeqRecord objects.

Bio.SeqIO is also documented at SeqIO_ and by a whole chapter in our Tutorial_:

.. _SeqIO: http://biopython.org/wiki/SeqIO
.. _Tutorial: https://biopython.org/docs/latest/Tutorial/index.html

Input
-----
The main function is Bio.SeqIO.parse(...) which takes an input file handle
(or in recent versions of Biopython alternatively a filename as a string),
and format string.  This returns an iterator giving SeqRecord objects:

>>> from Bio import SeqIO
>>> for record in SeqIO.parse("Fasta/f002", "fasta"):
...     print("%s %i" % (record.id, len(record)))
gi|1348912|gb|G26680|G26680 633
gi|1348917|gb|G26685|G26685 413
gi|1592936|gb|G29385|G29385 471

Note that the parse() function will invoke the relevant parser for the
format with its default settings.  You may want more control, in which case
you need to create a format specific sequence iterator directly.

Some of these parsers are wrappers around low-level parsers which build up
SeqRecord objects for the consistent SeqIO interface. In cases where the
run-time is critical, such as large FASTA or FASTQ files, calling these
underlying parsers will be much faster - in this case these generator
functions which return tuples of strings:

>>> from Bio.SeqIO.FastaIO import SimpleFastaParser
>>> from Bio.SeqIO.QualityIO import FastqGeneralIterator


Input - Single Records
----------------------
If you expect your file to contain one-and-only-one record, then we provide
the following 'helper' function which will return a single SeqRecord, or
raise an exception if there are no records or more than one record:

>>> from Bio import SeqIO
>>> record = SeqIO.read("Fasta/f001", "fasta")
>>> print("%s %i" % (record.id, len(record)))
gi|3318709|pdb|1A91| 79

This style is useful when you expect a single record only (and would
consider multiple records an error).  For example, when dealing with GenBank
files for bacterial genomes or chromosomes, there is normally only a single
record.  Alternatively, use this with a handle when downloading a single
record from the internet.

However, if you just want the first record from a file containing multiple
record, use the next() function on the iterator:

>>> from Bio import SeqIO
>>> record = next(SeqIO.parse("Fasta/f002", "fasta"))
>>> print("%s %i" % (record.id, len(record)))
gi|1348912|gb|G26680|G26680 633

The above code will work as long as the file contains at least one record.
Note that if there is more than one record, the remaining records will be
silently ignored.


Input - Multiple Records
------------------------
For non-interlaced files (e.g. Fasta, GenBank, EMBL) with multiple records
using a sequence iterator can save you a lot of memory (RAM).  There is
less benefit for interlaced file formats (e.g. most multiple alignment file
formats).  However, an iterator only lets you access the records one by one.

If you want random access to the records by number, turn this into a list:

>>> from Bio import SeqIO
>>> records = list(SeqIO.parse("Fasta/f002", "fasta"))
>>> len(records)
3
>>> print(records[1].id)
gi|1348917|gb|G26685|G26685

If you want random access to the records by a key such as the record id,
turn the iterator into a dictionary:

>>> from Bio import SeqIO
>>> record_dict = SeqIO.to_dict(SeqIO.parse("Fasta/f002", "fasta"))
>>> len(record_dict)
3
>>> print(len(record_dict["gi|1348917|gb|G26685|G26685"]))
413

However, using list() or the to_dict() function will load all the records
into memory at once, and therefore is not possible on very large files.
Instead, for *some* file formats Bio.SeqIO provides an indexing approach
providing dictionary like access to any record. For example,

>>> from Bio import SeqIO
>>> record_dict = SeqIO.index("Fasta/f002", "fasta")
>>> len(record_dict)
3
>>> print(len(record_dict["gi|1348917|gb|G26685|G26685"]))
413
>>> record_dict.close()

Many but not all of the supported input file formats can be indexed like
this. For example "fasta", "fastq", "qual" and even the binary format "sff"
work, but alignment formats like "phylip", "clustalw" and "nexus" will not.

In most cases you can also use SeqIO.index to get the record from the file
as a raw string (not a SeqRecord). This can be useful for example to extract
a sub-set of records from a file where SeqIO cannot output the file format
(e.g. the plain text SwissProt format, "swiss") or where it is important to
keep the output 100% identical to the input). For example,

>>> from Bio import SeqIO
>>> record_dict = SeqIO.index("Fasta/f002", "fasta")
>>> len(record_dict)
3
>>> print(record_dict.get_raw("gi|1348917|gb|G26685|G26685").decode())
>gi|1348917|gb|G26685|G26685 human STS STS_D11734.
CGGAGCCAGCGAGCATATGCTGCATGAGGACCTTTCTATCTTACATTATGGCTGGGAATCTTACTCTTTC
ATCTGATACCTTGTTCAGATTTCAAAATAGTTGTAGCCTTATCCTGGTTTTACAGATGTGAAACTTTCAA
GAGATTTACTGACTTTCCTAGAATAGTTTCTCTACTGGAAACCTGATGCTTTTATAAGCCATTGTGATTA
GGATGACTGTTACAGGCTTAGCTTTGTGTGAAANCCAGTCACCTTTCTCCTAGGTAATGAGTAGTGCTGT
TCATATTACTNTAAGTTCTATAGCATACTTGCNATCCTTTANCCATGCTTATCATANGTACCATTTGAGG
AATTGNTTTGCCCTTTTGGGTTTNTTNTTGGTAAANNNTTCCCGGGTGGGGGNGGTNNNGAAA
<BLANKLINE>
>>> print(record_dict["gi|1348917|gb|G26685|G26685"].format("fasta"))
>gi|1348917|gb|G26685|G26685 human STS STS_D11734.
CGGAGCCAGCGAGCATATGCTGCATGAGGACCTTTCTATCTTACATTATGGCTGGGAATC
TTACTCTTTCATCTGATACCTTGTTCAGATTTCAAAATAGTTGTAGCCTTATCCTGGTTT
TACAGATGTGAAACTTTCAAGAGATTTACTGACTTTCCTAGAATAGTTTCTCTACTGGAA
ACCTGATGCTTTTATAAGCCATTGTGATTAGGATGACTGTTACAGGCTTAGCTTTGTGTG
AAANCCAGTCACCTTTCTCCTAGGTAATGAGTAGTGCTGTTCATATTACTNTAAGTTCTA
TAGCATACTTGCNATCCTTTANCCATGCTTATCATANGTACCATTTGAGGAATTGNTTTG
CCCTTTTGGGTTTNTTNTTGGTAAANNNTTCCCGGGTGGGGGNGGTNNNGAAA
<BLANKLINE>
>>> record_dict.close()

Here the original file and what Biopython would output differ in the line
wrapping. Also note that the get_raw method will return a bytes object,
hence the use of decode to turn it into a string.

Also note that the get_raw method will preserve the newline endings. This
example FASTQ file uses Unix style endings (b"\n" only),

>>> from Bio import SeqIO
>>> fastq_dict = SeqIO.index("Quality/example.fastq", "fastq")
>>> len(fastq_dict)
3
>>> raw = fastq_dict.get_raw("EAS54_6_R1_2_1_540_792")
>>> raw.count(b"\n")
4
>>> raw.count(b"\r\n")
0
>>> b"\r" in raw
False
>>> len(raw)
78
>>> fastq_dict.close()

Here is the same file but using DOS/Windows new lines (b"\r\n" instead),

>>> from Bio import SeqIO
>>> fastq_dict = SeqIO.index("Quality/example_dos.fastq", "fastq")
>>> len(fastq_dict)
3
>>> raw = fastq_dict.get_raw("EAS54_6_R1_2_1_540_792")
>>> raw.count(b"\n")
4
>>> raw.count(b"\r\n")
4
>>> b"\r\n" in raw
True
>>> len(raw)
82
>>> fastq_dict.close()

Because this uses two bytes for each new line, the file is longer than
the Unix equivalent with only one byte.


Input - Alignments
------------------
You can read in alignment files as alignment objects using Bio.AlignIO.
Alternatively, reading in an alignment file format via Bio.SeqIO will give
you a SeqRecord for each row of each alignment:

>>> from Bio import SeqIO
>>> for record in SeqIO.parse("Clustalw/hedgehog.aln", "clustal"):
...     print("%s %i" % (record.id, len(record)))
gi|167877390|gb|EDS40773.1| 447
gi|167234445|ref|NP_001107837. 447
gi|74100009|gb|AAZ99217.1| 447
gi|13990994|dbj|BAA33523.2| 447
gi|56122354|gb|AAV74328.1| 447


Output
------
Use the function Bio.SeqIO.write(...), which takes a complete set of
SeqRecord objects (either as a list, or an iterator), an output file handle
(or in recent versions of Biopython an output filename as a string) and of
course the file format::

  from Bio import SeqIO
  records = ...
  SeqIO.write(records, "example.faa", "fasta")

Or, using a handle::

    from Bio import SeqIO
    records = ...
    with open("example.faa", "w") as handle:
      SeqIO.write(records, handle, "fasta")

You are expected to call this function once (with all your records) and if
using a handle, make sure you close it to flush the data to the hard disk.


Output - Advanced
-----------------
The effect of calling write() multiple times on a single file will vary
depending on the file format, and is best avoided unless you have a strong
reason to do so.

If you give a filename, then each time you call write() the existing file
will be overwritten. For sequential files formats (e.g. fasta, genbank) each
"record block" holds a single sequence.  For these files it would probably
be safe to call write() multiple times by re-using the same handle.

However, trying this for certain alignment formats (e.g. phylip, clustal,
stockholm) would have the effect of concatenating several multiple sequence
alignments together.  Such files are created by the PHYLIP suite of programs
for bootstrap analysis, but it is clearer to do this via Bio.AlignIO instead.

Worse, many fileformats have an explicit header and/or footer structure
(e.g. any XMl format, and most binary file formats like SFF). Here making
multiple calls to write() will result in an invalid file.


Conversion
----------
The Bio.SeqIO.convert(...) function allows an easy interface for simple
file format conversions. Additionally, it may use file format specific
optimisations so this should be the fastest way too.

In general however, you can combine the Bio.SeqIO.parse(...) function with
the Bio.SeqIO.write(...) function for sequence file conversion. Using
generator expressions or generator functions provides a memory efficient way
to perform filtering or other extra operations as part of the process.


File Formats
------------
When specifying the file format, use lowercase strings.  The same format
names are also used in Bio.AlignIO and include the following:

    - abi     - Applied Biosystem's sequencing trace format
    - abi-trim - Same as "abi" but with quality trimming with Mott's algorithm
    - ace     - Reads the contig sequences from an ACE assembly file.
    - cif-atom - Uses Bio.PDB.MMCIFParser to determine the (partial) protein
      sequence as it appears in the structure based on the atomic coordinates.
    - cif-seqres - Reads a macromolecular Crystallographic Information File
      (mmCIF) file to determine the complete protein sequence as defined by the
      _pdbx_poly_seq_scheme records.
    - embl    - The EMBL flat file format. Uses Bio.GenBank internally.
    - fasta   - The generic sequence file format where each record starts with
      an identifier line starting with a ">" character, followed by
      lines of sequence.
    - fasta-2line - Stricter interpretation of the FASTA format using exactly
      two lines per record (no line wrapping).
    - fastq   - A "FASTA like" format used by Sanger which also stores PHRED
      sequence quality values (with an ASCII offset of 33).
    - fastq-sanger - An alias for "fastq" for consistency with BioPerl and EMBOSS
    - fastq-solexa - Original Solexa/Illumnia variant of the FASTQ format which
      encodes Solexa quality scores (not PHRED quality scores) with an
      ASCII offset of 64.
    - fastq-illumina - Solexa/Illumina 1.3 to 1.7 variant of the FASTQ format
      which encodes PHRED quality scores with an ASCII offset of 64
      (not 33). Note as of version 1.8 of the CASAVA pipeline Illumina
      will produce FASTQ files using the standard Sanger encoding.
    - gck     - Gene Construction Kit's format.
    - genbank - The GenBank or GenPept flat file format.
    - gb      - An alias for "genbank", for consistency with NCBI Entrez Utilities
    - gfa1     - Graphical Fragment Assemblyv versions 1.x. Only segment lines
      are parsed and all linkage information is ignored.
    - gfa2    - Graphical Fragment Assembly version 2.0. Only segment lines are
      parsed and all linkage information is ignored.
    - ig      - The IntelliGenetics file format, apparently the same as the
      MASE alignment format.
    - imgt    - An EMBL like format from IMGT where the feature tables are more
      indented to allow for longer feature types.
    - nib     - UCSC's nib file format for nucleotide sequences, which uses one
      nibble (4 bits) to represent each nucleotide, and stores two nucleotides in
      one byte.
    - pdb-seqres -  Reads a Protein Data Bank (PDB) file to determine the
      complete protein sequence as it appears in the header (no dependencies).
    - pdb-atom - Uses Bio.PDB to determine the (partial) protein sequence as
      it appears in the structure based on the atom coordinate section of the
      file (requires NumPy for Bio.PDB).
    - phd     - Output from PHRED, used by PHRAP and CONSED for input.
    - pir     - A "FASTA like" format introduced by the National Biomedical
      Research Foundation (NBRF) for the Protein Information Resource
      (PIR) database, now part of UniProt.
    - seqxml  - SeqXML, simple XML format described in Schmitt et al (2011).
    - sff     - Standard Flowgram Format (SFF), typical output from Roche 454.
    - sff-trim - Standard Flowgram Format (SFF) with given trimming applied.
    - snapgene - SnapGene's native format.
    - swiss   - Plain text Swiss-Prot aka UniProt format.
    - tab     - Simple two column tab separated sequence files, where each
      line holds a record's identifier and sequence. For example,
      this is used as by Aligent's eArray software when saving
      microarray probes in a minimal tab delimited text file.
    - qual    - A "FASTA like" format holding PHRED quality values from
      sequencing DNA, but no actual sequences (usually provided
      in separate FASTA files).
    - uniprot-xml - The UniProt XML format (replacement for the SwissProt plain
      text format which we call "swiss")
    - xdna        - DNA Strider's and SerialCloner's native format.

Note that while Bio.SeqIO can read all the above file formats, it cannot
write to all of them.

You can also use any file format supported by Bio.AlignIO, such as "nexus",
"phylip" and "stockholm", which gives you access to the individual sequences
making up each alignment as SeqRecords.
"""
# TODO
# - define policy on reading aligned sequences with more than
#   one gap character (see also AlignIO)
#
# - How best to handle unique/non unique record.id when writing.
#   For most file formats reading such files is fine; The stockholm
#   parser would fail.
#
# - MSF multiple alignment format, aka GCG, aka PileUp format (*.msf)
#   http://www.bioperl.org/wiki/MSF_multiple_alignment_format
#
# FAO BioPython Developers
# ------------------------
# The way I envision this SeqIO system working as that for any sequence file
# format we have an iterator that returns SeqRecord objects.
#
# This also applies to interlaced file formats (like clustal - although that
# is now handled via Bio.AlignIO instead) where the file cannot be read record
# by record.  You should still return an iterator, even if the implementation
# could just as easily return a list.
#
# These file format specific sequence iterators may be implemented as:
#    - Classes which take a handle for __init__ and provide the __iter__ method
#    - Functions that take a handle, and return an iterator object
#    - Generator functions that take a handle, and yield SeqRecord objects
#
# It is then trivial to turn this iterator into a list of SeqRecord objects,
# an in memory dictionary, or a multiple sequence alignment object.
#
# For building the dictionary by default the id property of each SeqRecord is
# used as the key.  You should always populate the id property, and it should
# be unique in most cases. For some file formats the accession number is a good
# choice.  If the file itself contains ambiguous identifiers, don't try and
# dis-ambiguate them - return them as is.
#
# When adding a new file format, please use the same lower case format name
# as BioPerl, or if they have not defined one, try the names used by EMBOSS.
#
# See also http://biopython.org/wiki/SeqIO_dev
#
# --Peter

from abc import ABC, abstractmethod
from collections.abc import Callable
from collections.abc import Iterable
from typing import Union

from Bio import AlignIO
from Bio.SeqIO import AbiIO
from Bio.SeqIO import AceIO
from Bio.SeqIO import FastaIO
from Bio.SeqIO import GckIO
from Bio.SeqIO import GfaIO
from Bio.SeqIO import IgIO  # IntelliGenetics or MASE format
from Bio.SeqIO import InsdcIO  # EMBL and GenBank
from Bio.SeqIO import NibIO
from Bio.SeqIO import PdbIO
from Bio.SeqIO import PhdIO
from Bio.SeqIO import PirIO
from Bio.SeqIO import QualityIO  # FastQ and qual files
from Bio.SeqIO import SeqXmlIO
from Bio.SeqIO import SffIO
from Bio.SeqIO import SnapGeneIO
from Bio.SeqIO import SwissIO
from Bio.SeqIO import TabIO
from Bio.SeqIO import TwoBitIO
from Bio.SeqIO import UniprotIO
from Bio.SeqIO import XdnaIO
from Bio.SeqRecord import SeqRecord

from .Interfaces import _IOSource, _TextIOSource, SequenceIterator, SequenceWriter

# Convention for format names is "mainname-subtype" in lower case.
# Please use the same names as BioPerl or EMBOSS where possible.
#
# Note that this simple system copes with defining
# multiple possible iterators for a given format/extension
# with the -subtype suffix
#
# Most alignment file formats will be handled via Bio.AlignIO

_FormatToIterator = {
    "abi": AbiIO.AbiIterator,
    "abi-trim": AbiIO._AbiTrimIterator,
    "ace": AceIO.AceIterator,
    "fasta": FastaIO.FastaIterator,
    "fasta-2line": FastaIO.FastaTwoLineIterator,
    "fasta-blast": FastaIO.FastaBlastIterator,
    "fasta-pearson": FastaIO.FastaPearsonIterator,
    "ig": IgIO.IgIterator,
    "embl": InsdcIO.EmblIterator,
    "embl-cds": InsdcIO.EmblCdsFeatureIterator,
    "gb": InsdcIO.GenBankIterator,
    "gck": GckIO.GckIterator,
    "genbank": InsdcIO.GenBankIterator,
    "genbank-cds": InsdcIO.GenBankCdsFeatureIterator,
    "gfa1": GfaIO.Gfa1Iterator,
    "gfa2": GfaIO.Gfa2Iterator,
    "imgt": InsdcIO.ImgtIterator,
    "nib": NibIO.NibIterator,
    "cif-seqres": PdbIO.CifSeqresIterator,
    "cif-atom": PdbIO.CifAtomIterator,
    "pdb-atom": PdbIO.PdbAtomIterator,
    "pdb-seqres": PdbIO.PdbSeqresIterator,
    "phd": PhdIO.PhdIterator,
    "pir": PirIO.PirIterator,
    "fastq": QualityIO.FastqPhredIterator,
    "fastq-sanger": QualityIO.FastqPhredIterator,
    "fastq-solexa": QualityIO.FastqSolexaIterator,
    "fastq-illumina": QualityIO.FastqIlluminaIterator,
    "qual": QualityIO.QualPhredIterator,
    "seqxml": SeqXmlIO.SeqXmlIterator,
    "sff": SffIO.SffIterator,
    "snapgene": SnapGeneIO.SnapGeneIterator,
    "sff-trim": SffIO._SffTrimIterator,  # Not sure about this in the long run
    "swiss": SwissIO.SwissIterator,
    "tab": TabIO.TabIterator,
    "twobit": TwoBitIO.TwoBitIterator,
    "uniprot-xml": UniprotIO.UniprotIterator,
    "xdna": XdnaIO.XdnaIterator,
}

# Right now used in the unit tests as proxy for all supported outputs...
_FormatToWriter = {
    "fasta": FastaIO.FastaWriter,
    "fasta-2line": FastaIO.FastaTwoLineWriter,
    "gb": InsdcIO.GenBankWriter,
    "genbank": InsdcIO.GenBankWriter,
    "embl": InsdcIO.EmblWriter,
    "imgt": InsdcIO.ImgtWriter,
    "nib": NibIO.NibWriter,
    "phd": PhdIO.PhdWriter,
    "pir": PirIO.PirWriter,
    "fastq": QualityIO.FastqPhredWriter,
    "fastq-sanger": QualityIO.FastqPhredWriter,
    "fastq-solexa": QualityIO.FastqSolexaWriter,
    "fastq-illumina": QualityIO.FastqIlluminaWriter,
    "qual": QualityIO.QualPhredWriter,
    "seqxml": SeqXmlIO.SeqXmlWriter,
    "sff": SffIO.SffWriter,
    "tab": TabIO.TabWriter,
    "xdna": XdnaIO.XdnaWriter,
}


class AlignmentSequenceIterator(SequenceIterator):
    """Pareses an alignment file and yields sequence records."""

    modes = "t"

    @property
    @abstractmethod
    def fmt(self):
        """Alignment file format name."""

    @property
    @abstractmethod
    def _alignment_iterator_class(self):
        """Alignment iterator class."""

    def __init__(self, source: _IOSource) -> None:
        """Initialize the iterator."""
        super().__init__(source, fmt=self.fmt)
        # We need type(self) here, because _alignment_iterator_class is
        # actually a function instead of a class for some formats in
        # Bio.AlignIO, and Python will turn the function into a bound method
        # with self as the first argument.
        alignment_iterator_class = type(self)._alignment_iterator_class
        alignments = alignment_iterator_class(self.stream, None)  # type: ignore
        self.iterator = (record for alignment in alignments for record in alignment)

    def __next__(self):
        """Return the next SeqRecord from the underlying alignment iterator."""
        return next(self.iterator)


for fmt, alignment_iterator_class in AlignIO._FormatToIterator.items():
    name = fmt.replace("-", " ").title().replace(" ", "") + "AlignmentSequenceIterator"
    cls = type(
        name,
        (AlignmentSequenceIterator,),
        {
            "fmt": fmt,
            "_alignment_iterator_class": alignment_iterator_class,
        },
    )
    _FormatToIterator[fmt] = cls


class AlignmentSequenceWriter(SequenceWriter):
    """Writes sequences as an alignment."""

    modes = "t"

    @property
    @abstractmethod
    def _alignment_writer_class(self):
        """Alignment writer class."""

    def write_records(self, records):
        """Write records to the output file, and return the number of records.

        records - A list or iterator returning SeqRecord objects
        """
        from Bio.Align import MultipleSeqAlignment

        alignment = MultipleSeqAlignment(records)
        alignment_writer_class = self._alignment_writer_class
        alignment_writer = alignment_writer_class(self.handle)
        alignment_count = alignment_writer.write_file([alignment])
        if alignment_count != 1:
            raise RuntimeError(
                "Internal error - the underlying writer "
                "should have returned 1, not %r" % alignment_count
            )
        count = len(alignment)
        return count


for fmt, alignment_writer_class in AlignIO._FormatToWriter.items():
    name = fmt.replace("-", " ").title().replace(" ", "") + "AlignmentSequenceWriter"
    cls = type(
        name,
        (AlignmentSequenceWriter,),
        {"_alignment_writer_class": alignment_writer_class},
    )
    _FormatToWriter[fmt] = cls  # type: ignore


del AlignIO


def write(
    sequences: Iterable[SeqRecord] | SeqRecord,
    handle: _TextIOSource,
    format: str,
) -> int:
    """Write complete set of sequences to a file.

    Arguments:
     - sequences - A list (or iterator) of SeqRecord objects, or a single
       SeqRecord.
     - handle    - File handle object to write to, or filename as string.
     - format    - lower case string describing the file format to write.

    Note if providing a file handle, your code should close the handle
    after calling this function (to ensure the data gets flushed to disk).

    Returns the number of records written (as an integer).
    """
    from Bio import AlignIO

    # Try and give helpful error messages:
    if not isinstance(format, str):
        raise TypeError("Need a string for the file format (lower case)")
    if not format:
        raise ValueError("Format required (lower case string)")
    if not format.islower():
        raise ValueError(f"Format string '{format}' should be lower case")

    if isinstance(handle, SeqRecord):
        raise TypeError("Check arguments, handle should NOT be a SeqRecord")
    if isinstance(handle, list):
        # e.g. list of SeqRecord objects
        raise TypeError("Check arguments, handle should NOT be a list")

    if isinstance(sequences, SeqRecord):
        # This raised an exception in older versions of Biopython
        sequences = [sequences]

    writer_class = _FormatToWriter.get(format)
    if writer_class is not None:
        count = writer_class(handle).write_file(sequences)
        if not isinstance(count, int):
            raise RuntimeError(
                "Internal error - the underlying %s writer "
                "should have returned the record count, not %r" % (format, count)
            )
        return count

    if format in _FormatToIterator:
        raise ValueError(f"Reading format '{format}' is supported, but not writing")

    raise ValueError(f"Unknown format '{format}'")


def parse(handle, format, alphabet=None):
    r"""Turn a sequence file into an iterator returning SeqRecords.

    Arguments:
     - handle   - handle to the file, or the filename as a string
     - format   - lower case string describing the file format.
     - alphabet - no longer used, should be None.

    Typical usage, opening a file to read in, and looping over the record(s):

    >>> from Bio import SeqIO
    >>> filename = "Fasta/sweetpea.nu"
    >>> for record in SeqIO.parse(filename, "fasta"):
    ...    print("ID %s" % record.id)
    ...    print("Sequence length %i" % len(record))
    ID gi|3176602|gb|U78617.1|LOU78617
    Sequence length 309

    For lazy-loading file formats such as twobit, for which the file contents
    is read on demand only, ensure that the file remains open while extracting
    sequence data.

    If you have a string 'data' containing the file contents, you must
    first turn this into a handle in order to parse it:

    >>> data = ">Alpha\nACCGGATGTA\n>Beta\nAGGCTCGGTTA\n"
    >>> from Bio import SeqIO
    >>> from io import StringIO
    >>> for record in SeqIO.parse(StringIO(data), "fasta"):
    ...     print("%s %s" % (record.id, record.seq))
    Alpha ACCGGATGTA
    Beta AGGCTCGGTTA

    Use the Bio.SeqIO.read(...) function when you expect a single record
    only.
    """
    # NOTE - The above docstring has some raw \n characters needed
    # for the StringIO example, hence the whole docstring is in raw
    # string mode (see the leading r before the opening quote).

    # Try and give helpful error messages:
    if not isinstance(format, str):
        raise TypeError("Need a string for the file format (lower case)")
    if not format:
        raise ValueError("Format required (lower case string)")
    if not format.islower():
        raise ValueError(f"Format string '{format}' should be lower case")
    if alphabet is not None:
        raise ValueError("The alphabet argument is no longer supported")

    iterator_generator = _FormatToIterator.get(format)
    if iterator_generator:
        return iterator_generator(handle)

    raise ValueError(f"Unknown format '{format}'")


def read(handle, format, alphabet=None):
    """Turn a sequence file into a single SeqRecord.

    Arguments:
     - handle   - handle to the file, or the filename as a string
       (note older versions of Biopython only took a handle).
     - format   - string describing the file format.
     - alphabet - no longer used, should be None.

    This function is for use parsing sequence files containing
    exactly one record.  For example, reading a GenBank file:

    >>> from Bio import SeqIO
    >>> record = SeqIO.read("GenBank/arab1.gb", "genbank")
    >>> print("ID %s" % record.id)
    ID AC007323.5
    >>> print("Sequence length %i" % len(record))
    Sequence length 86436

    If the handle contains no records, or more than one record,
    an exception is raised.  For example:

    >>> from Bio import SeqIO
    >>> record = SeqIO.read("GenBank/cor6_6.gb", "genbank")
    Traceback (most recent call last):
        ...
    ValueError: More than one record found in handle

    If however you want the first record from a file containing
    multiple records this function would raise an exception (as
    shown in the example above).  Instead use:

    >>> from Bio import SeqIO
    >>> record = next(SeqIO.parse("GenBank/cor6_6.gb", "genbank"))
    >>> print("First record's ID %s" % record.id)
    First record's ID X55053.1

    Use the Bio.SeqIO.parse(handle, format) function if you want
    to read multiple records from the handle.
    """
    with parse(handle, format, alphabet) as records:
        try:
            record = next(records)
        except StopIteration:
            raise ValueError("No records found in handle") from None
        try:
            next(records)
            raise ValueError("More than one record found in handle")
        except StopIteration:
            pass
    return record


def to_dict(sequences, key_function=None):
    """Turn a sequence iterator or list into a dictionary.

    Arguments:
     - sequences  - An iterator that returns SeqRecord objects,
       or simply a list of SeqRecord objects.
     - key_function - Optional callback function which when given a
       SeqRecord should return a unique key for the dictionary.

    e.g. key_function = lambda rec : rec.name
    or,  key_function = lambda rec : rec.description.split()[0]

    If key_function is omitted then record.id is used, on the assumption
    that the records objects returned are SeqRecords with a unique id.

    If there are duplicate keys, an error is raised.

    Since Python 3.7, the default dict class maintains key order, meaning
    this dictionary will reflect the order of records given to it. For
    CPython and PyPy, this was already implemented for Python 3.6, so
    effectively you can always assume the record order is preserved.

    Example usage, defaulting to using the record.id as key:

    >>> from Bio import SeqIO
    >>> filename = "GenBank/cor6_6.gb"
    >>> format = "genbank"
    >>> id_dict = SeqIO.to_dict(SeqIO.parse(filename, format))
    >>> print(list(id_dict))
    ['X55053.1', 'X62281.1', 'M81224.1', 'AJ237582.1', 'L31939.1', 'AF297471.1']
    >>> print(id_dict["L31939.1"].description)
    Brassica rapa (clone bif72) kin mRNA, complete cds

    A more complex example, using the key_function argument in order to
    use a sequence checksum as the dictionary key:

    >>> from Bio import SeqIO
    >>> from Bio.SeqUtils.CheckSum import seguid
    >>> filename = "GenBank/cor6_6.gb"
    >>> format = "genbank"
    >>> seguid_dict = SeqIO.to_dict(SeqIO.parse(filename, format),
    ...               key_function = lambda rec : seguid(rec.seq))
    >>> for key, record in sorted(seguid_dict.items()):
    ...     print("%s %s" % (key, record.id))
    /wQvmrl87QWcm9llO4/efg23Vgg AJ237582.1
    BUg6YxXSKWEcFFH0L08JzaLGhQs L31939.1
    SabZaA4V2eLE9/2Fm5FnyYy07J4 X55053.1
    TtWsXo45S3ZclIBy4X/WJc39+CY M81224.1
    l7gjJFE6W/S1jJn5+1ASrUKW/FA X62281.1
    uVEYeAQSV5EDQOnFoeMmVea+Oow AF297471.1

    This approach is not suitable for very large sets of sequences, as all
    the SeqRecord objects are held in memory. Instead, consider using the
    Bio.SeqIO.index() function (if it supports your particular file format).

    This dictionary will reflect the order of records given to it.
    """
    # This is to avoid a lambda function:

    def _default_key_function(rec):
        return rec.id

    if key_function is None:
        key_function = _default_key_function

    d = {}
    for record in sequences:
        key = key_function(record)
        if key in d:
            raise ValueError(f"Duplicate key '{key}'")
        d[key] = record
    return d


def index(filename, format, alphabet=None, key_function=None):
    """Indexes a sequence file and returns a dictionary like object.

    Arguments:
     - filename - string giving name of file to be indexed
     - format   - lower case string describing the file format
     - alphabet - no longer used, leave as None
     - key_function - Optional callback function which when given a
       SeqRecord identifier string should return a unique key for the
       dictionary.

    This indexing function will return a dictionary like object, giving the
    SeqRecord objects as values.

    As of Biopython 1.69, this will preserve the ordering of the records in
    file when iterating over the entries.

    >>> from Bio import SeqIO
    >>> records = SeqIO.index("Quality/example.fastq", "fastq")
    >>> len(records)
    3
    >>> list(records)  # make a list of the keys
    ['EAS54_6_R1_2_1_413_324', 'EAS54_6_R1_2_1_540_792', 'EAS54_6_R1_2_1_443_348']
    >>> print(records["EAS54_6_R1_2_1_540_792"].format("fasta"))
    >EAS54_6_R1_2_1_540_792
    TTGGCAGGCCAAGGCCGATGGATCA
    <BLANKLINE>
    >>> "EAS54_6_R1_2_1_540_792" in records
    True
    >>> print(records.get("Missing", None))
    None
    >>> records.close()

    If the file is BGZF compressed, this is detected automatically. Ordinary
    GZIP files are not supported:

    >>> from Bio import SeqIO
    >>> records = SeqIO.index("Quality/example.fastq.bgz", "fastq")
    >>> len(records)
    3
    >>> print(records["EAS54_6_R1_2_1_540_792"].seq)
    TTGGCAGGCCAAGGCCGATGGATCA
    >>> records.close()

    When you call the index function, it will scan through the file, noting
    the location of each record. When you access a particular record via the
    dictionary methods, the code will jump to the appropriate part of the
    file and then parse that section into a SeqRecord.

    Note that not all the input formats supported by Bio.SeqIO can be used
    with this index function. It is designed to work only with sequential
    file formats (e.g. "fasta", "gb", "fastq") and is not suitable for any
    interlaced file format (e.g. alignment formats such as "clustal").

    For small files, it may be more efficient to use an in memory Python
    dictionary, e.g.

    >>> from Bio import SeqIO
    >>> records = SeqIO.to_dict(SeqIO.parse("Quality/example.fastq", "fastq"))
    >>> len(records)
    3
    >>> list(records)  # make a list of the keys
    ['EAS54_6_R1_2_1_413_324', 'EAS54_6_R1_2_1_540_792', 'EAS54_6_R1_2_1_443_348']
    >>> print(records["EAS54_6_R1_2_1_540_792"].format("fasta"))
    >EAS54_6_R1_2_1_540_792
    TTGGCAGGCCAAGGCCGATGGATCA
    <BLANKLINE>

    As with the to_dict() function, by default the id string of each record
    is used as the key. You can specify a callback function to transform
    this (the record identifier string) into your preferred key. For example:

    >>> from Bio import SeqIO
    >>> def make_tuple(identifier):
    ...     parts = identifier.split("_")
    ...     return int(parts[-2]), int(parts[-1])
    >>> records = SeqIO.index("Quality/example.fastq", "fastq",
    ...                       key_function=make_tuple)
    >>> len(records)
    3
    >>> list(records)  # make a list of the keys
    [(413, 324), (540, 792), (443, 348)]
    >>> print(records[(540, 792)].format("fasta"))
    >EAS54_6_R1_2_1_540_792
    TTGGCAGGCCAAGGCCGATGGATCA
    <BLANKLINE>
    >>> (540, 792) in records
    True
    >>> "EAS54_6_R1_2_1_540_792" in records
    False
    >>> print(records.get("Missing", None))
    None
    >>> records.close()

    Another common use case would be indexing an NCBI style FASTA file,
    where you might want to extract the GI number from the FASTA identifier
    to use as the dictionary key.

    Notice that unlike the to_dict() function, here the key_function does
    not get given the full SeqRecord to use to generate the key. Doing so
    would impose a severe performance penalty as it would require the file
    to be completely parsed while building the index. Right now this is
    usually avoided.

    See Also: Bio.SeqIO.index_db() and Bio.SeqIO.to_dict()

    """
    # Try and give helpful error messages:
    if not isinstance(format, str):
        raise TypeError("Need a string for the file format (lower case)")
    if not format:
        raise ValueError("Format required (lower case string)")
    if not format.islower():
        raise ValueError(f"Format string '{format}' should be lower case")
    if alphabet is not None:
        raise ValueError("The alphabet argument is no longer supported")

    # Map the file format to a sequence iterator:
    from Bio.File import _IndexedSeqFileDict

    from ._index import _FormatToRandomAccess  # Lazy import

    try:
        proxy_class = _FormatToRandomAccess[format]
    except KeyError:
        raise ValueError(f"Unsupported format {format!r}") from None
    repr = "SeqIO.index(%r, %r, alphabet=%r, key_function=%r)" % (
        filename,
        format,
        alphabet,
        key_function,
    )

    try:
        random_access_proxy = proxy_class(filename, format)
    except TypeError:
        raise TypeError(
            "Need a string or path-like object for the filename (not a handle)"
        ) from None

    return _IndexedSeqFileDict(random_access_proxy, key_function, repr, "SeqRecord")


def index_db(
    index_filename, filenames=None, format=None, alphabet=None, key_function=None
):
    """Index several sequence files and return a dictionary like object.

    The index is stored in an SQLite database rather than in memory (as in the
    Bio.SeqIO.index(...) function).

    Arguments:
     - index_filename - Where to store the SQLite index
     - filenames - list of strings specifying file(s) to be indexed, or when
       indexing a single file this can be given as a string.
       (optional if reloading an existing index, but must match)
     - format   - lower case string describing the file format
       (optional if reloading an existing index, but must match)
     - alphabet - no longer used, leave as None.
     - key_function - Optional callback function which when given a
       SeqRecord identifier string should return a unique
       key for the dictionary.

    This indexing function will return a dictionary like object, giving the
    SeqRecord objects as values:

    >>> from Bio import SeqIO
    >>> files = ["GenBank/NC_000932.faa", "GenBank/NC_005816.faa"]
    >>> def get_gi(name):
    ...     parts = name.split("|")
    ...     i = parts.index("gi")
    ...     assert i != -1
    ...     return parts[i+1]
    >>> idx_name = ":memory:" #use an in memory SQLite DB for this test
    >>> records = SeqIO.index_db(idx_name, files, "fasta", key_function=get_gi)
    >>> len(records)
    95
    >>> records["7525076"].description
    'gi|7525076|ref|NP_051101.1| Ycf2 [Arabidopsis thaliana]'
    >>> records["45478717"].description
    'gi|45478717|ref|NP_995572.1| pesticin [Yersinia pestis biovar Microtus str. 91001]'
    >>> records.close()

    In this example the two files contain 85 and 10 records respectively.

    BGZF compressed files are supported, and detected automatically. Ordinary
    GZIP compressed files are not supported.

    See Also: Bio.SeqIO.index() and Bio.SeqIO.to_dict(), and the Python module
    glob which is useful for building lists of files.

    """
    from os import fspath

    def is_pathlike(obj):
        """Test if the given object can be accepted as a path."""
        try:
            fspath(obj)
            return True
        except TypeError:
            return False

    # Try and give helpful error messages:
    if not is_pathlike(index_filename):
        raise TypeError("Need a string or path-like object for filename (not a handle)")
    if is_pathlike(filenames):
        # Make the API a little more friendly, and more similar
        # to Bio.SeqIO.index(...) for indexing just one file.
        filenames = [filenames]
    if filenames is not None and not isinstance(filenames, list):
        raise TypeError(
            "Need a list of filenames (as strings or path-like "
            "objects), or one filename"
        )
    if format is not None and not isinstance(format, str):
        raise TypeError("Need a string for the file format (lower case)")
    if format and not format.islower():
        raise ValueError(f"Format string '{format}' should be lower case")
    if alphabet is not None:
        raise ValueError("The alphabet argument is no longer supported")

    # Map the file format to a sequence iterator:
    from Bio.File import _SQLiteManySeqFilesDict

    from ._index import _FormatToRandomAccess  # Lazy import

    repr = "SeqIO.index_db(%r, filenames=%r, format=%r, key_function=%r)" % (
        index_filename,
        filenames,
        format,
        key_function,
    )

    def proxy_factory(format, filename=None):
        """Given a filename returns proxy object, else boolean if format OK."""
        if filename:
            return _FormatToRandomAccess[format](filename, format)
        else:
            return format in _FormatToRandomAccess

    return _SQLiteManySeqFilesDict(
        index_filename, filenames, proxy_factory, format, key_function, repr
    )


# TODO? - Handling aliases explicitly would let us shorten this list:
_converter = {
    ("genbank", "fasta"): InsdcIO._genbank_convert_fasta,
    ("gb", "fasta"): InsdcIO._genbank_convert_fasta,
    ("embl", "fasta"): InsdcIO._embl_convert_fasta,
    ("fastq", "fasta"): QualityIO._fastq_convert_fasta,
    ("fastq-sanger", "fasta"): QualityIO._fastq_convert_fasta,
    ("fastq-solexa", "fasta"): QualityIO._fastq_convert_fasta,
    ("fastq-illumina", "fasta"): QualityIO._fastq_convert_fasta,
    ("fastq", "tab"): QualityIO._fastq_convert_tab,
    ("fastq-sanger", "tab"): QualityIO._fastq_convert_tab,
    ("fastq-solexa", "tab"): QualityIO._fastq_convert_tab,
    ("fastq-illumina", "tab"): QualityIO._fastq_convert_tab,
    ("fastq", "fastq"): QualityIO._fastq_sanger_convert_fastq_sanger,
    ("fastq-sanger", "fastq"): QualityIO._fastq_sanger_convert_fastq_sanger,
    ("fastq-solexa", "fastq"): QualityIO._fastq_solexa_convert_fastq_sanger,
    ("fastq-illumina", "fastq"): QualityIO._fastq_illumina_convert_fastq_sanger,
    ("fastq", "fastq-sanger"): QualityIO._fastq_sanger_convert_fastq_sanger,
    ("fastq-sanger", "fastq-sanger"): QualityIO._fastq_sanger_convert_fastq_sanger,
    ("fastq-solexa", "fastq-sanger"): QualityIO._fastq_solexa_convert_fastq_sanger,
    ("fastq-illumina", "fastq-sanger"): QualityIO._fastq_illumina_convert_fastq_sanger,
    ("fastq", "fastq-solexa"): QualityIO._fastq_sanger_convert_fastq_solexa,
    ("fastq-sanger", "fastq-solexa"): QualityIO._fastq_sanger_convert_fastq_solexa,
    ("fastq-solexa", "fastq-solexa"): QualityIO._fastq_solexa_convert_fastq_solexa,
    ("fastq-illumina", "fastq-solexa"): QualityIO._fastq_illumina_convert_fastq_solexa,
    ("fastq", "fastq-illumina"): QualityIO._fastq_sanger_convert_fastq_illumina,
    ("fastq-sanger", "fastq-illumina"): QualityIO._fastq_sanger_convert_fastq_illumina,
    ("fastq-solexa", "fastq-illumina"): QualityIO._fastq_solexa_convert_fastq_illumina,
    (
        "fastq-illumina",
        "fastq-illumina",
    ): QualityIO._fastq_illumina_convert_fastq_illumina,
    ("fastq", "qual"): QualityIO._fastq_sanger_convert_qual,
    ("fastq-sanger", "qual"): QualityIO._fastq_sanger_convert_qual,
    ("fastq-solexa", "qual"): QualityIO._fastq_solexa_convert_qual,
    ("fastq-illumina", "qual"): QualityIO._fastq_illumina_convert_qual,
}


def convert(in_file, in_format, out_file, out_format, molecule_type=None):
    """Convert between two sequence file formats, return number of records.

    Arguments:
     - in_file - an input handle or filename
     - in_format - input file format, lower case string
     - out_file - an output handle or filename
     - out_format - output file format, lower case string
     - molecule_type - optional molecule type to apply, string containing
       "DNA", "RNA" or "protein".

    **NOTE** - If you provide an output filename, it will be opened which will
    overwrite any existing file without warning.

    The idea here is that while doing this will work::

        from Bio import SeqIO
        records = SeqIO.parse(in_handle, in_format)
        count = SeqIO.write(records, out_handle, out_format)

    it is shorter to write::

        from Bio import SeqIO
        count = SeqIO.convert(in_handle, in_format, out_handle, out_format)

    Also, Bio.SeqIO.convert is faster for some conversions as it can make some
    optimisations.

    For example, going from a filename to a handle:

    >>> from Bio import SeqIO
    >>> from io import StringIO
    >>> handle = StringIO("")
    >>> SeqIO.convert("Quality/example.fastq", "fastq", handle, "fasta")
    3
    >>> print(handle.getvalue())
    >EAS54_6_R1_2_1_413_324
    CCCTTCTTGTCTTCAGCGTTTCTCC
    >EAS54_6_R1_2_1_540_792
    TTGGCAGGCCAAGGCCGATGGATCA
    >EAS54_6_R1_2_1_443_348
    GTTGCTTCTGGCGTGGGTGGGGGGG
    <BLANKLINE>

    Note some formats like SeqXML require you to specify the molecule type
    when it cannot be determined by the parser:

    >>> from Bio import SeqIO
    >>> from io import BytesIO
    >>> handle = BytesIO()
    >>> SeqIO.convert("Quality/example.fastq", "fastq", handle, "seqxml", "DNA")
    3
    """
    if molecule_type:
        if not isinstance(molecule_type, str):
            raise TypeError(f"Molecule type should be a string, not {molecule_type!r}")
        elif (
            "DNA" in molecule_type
            or "RNA" in molecule_type
            or "protein" in molecule_type
        ):
            pass
        else:
            raise ValueError(f"Unexpected molecule type, {molecule_type!r}")
    f = _converter.get((in_format, out_format))
    if f:
        count = f(in_file, out_file)
    else:
        records = parse(in_file, in_format)
        if molecule_type:
            # Edit the records on the fly to set molecule type

            def over_ride(record):
                """Over-ride molecule in-place."""
                record.annotations["molecule_type"] = molecule_type
                return record

            records = (over_ride(_) for _ in records)
        count = write(records, out_file, out_format)
    return count


if __name__ == "__main__":
    from Bio._utils import run_doctest

    run_doctest()
