text: # Copyright 2006-2018 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.
  
  # Nice link:
  # http://www.ebi.ac.uk/help/formats_frame.html
  
  r"""Sequence input/output as SeqRecord objects.
  
  Bio.SeqIO is also documented at SeqIO_ and by a whole chapter in our tutorial:
  
    - `HTML Tutorial`_
    - `PDF Tutorial`_
  
  .. _SeqIO: http://biopython.org/wiki/SeqIO
  .. _`HTML Tutorial`: http://biopython.org/DIST/docs/tutorial/Tutorial.html
  .. _`PDF Tutorial`: http://biopython.org/DIST/docs/tutorial/Tutorial.pdf
  
  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 string,
  hence the use of decode to turn it into a (unicode) 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 identifer 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
      - 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 gaps in
  #   (e.g. - and . characters) including how the alphabet interacts
  #
  # - 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 Bio.File import as_handle
  from Bio.SeqRecord import SeqRecord
  from Bio.Align import MultipleSeqAlignment
  from Bio.Alphabet import Alphabet, AlphabetEncoder, _get_base_alphabet
  
  from . import AbiIO
  from . import AceIO
  from . import FastaIO
  from . import GckIO
  from . import IgIO  # IntelliGenetics or MASE format
  from . import InsdcIO  # EMBL and GenBank
  from . import NibIO
  from . import PdbIO
  from . import PhdIO
  from . import PirIO
  from . import SeqXmlIO
  from . import SffIO
  from . import SnapGeneIO
  from . import SwissIO
  from . import TabIO
  from . import QualityIO  # FastQ and qual files
  from . import UniprotIO
  from . import XdnaIO
  
  # 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,
      "ig": IgIO.IgIterator,
      "embl": InsdcIO.EmblIterator,
      "embl-cds": InsdcIO.EmblCdsFeatureIterator,
      "gb": InsdcIO.GenBankIterator,
      "gck": GckIO.GckIterator,
      "genbank": InsdcIO.GenBankIterator,
      "genbank-cds": InsdcIO.GenBankCdsFeatureIterator,
      "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,
      # Not sure about this in the long run:
      "sff-trim": SffIO._SffTrimIterator,
      "swiss": SwissIO.SwissIterator,
      "tab": TabIO.TabIterator,
      "uniprot-xml": UniprotIO.UniprotIterator,
      "xdna": XdnaIO.XdnaIterator,
  }
  
  _FormatToString = {
      "fasta": FastaIO.as_fasta,
      "fasta-2line": FastaIO.as_fasta_2line,
      "tab": TabIO.as_tab,
      "fastq": QualityIO.as_fastq,
      "fastq-sanger": QualityIO.as_fastq,
      "fastq-solexa": QualityIO.as_fastq_solexa,
      "fastq-illumina": QualityIO.as_fastq_illumina,
      "qual": QualityIO.as_qual,
  }
  
  # This could exclude file formats covered by _FormatToString?
  # 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,
  }
  
  
  def write(sequences, handle, format):
      """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("Format string '%s' should be lower case" % format)
  
      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]
  
      # Map the file format to a writer function/class
      format_function = _FormatToString.get(format)
      if format_function is not None:
          count = 0
          with as_handle(handle, "w") as fp:
              for record in sequences:
                  fp.write(format_function(record))
                  count += 1
          return count
  
      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 AlignIO._FormatToWriter:
          # Try and turn all the records into a single alignment,
          # and write that using Bio.AlignIO
          alignment = MultipleSeqAlignment(sequences)
          alignment_count = AlignIO.write([alignment], handle, format)
          if alignment_count != 1:
              raise RuntimeError(
                  "Internal error - the underlying writer "
                  "should have returned 1, not %r" % alignment_count
              )
          count = len(alignment)
          return count
  
      if format in _FormatToIterator or format in AlignIO._FormatToIterator:
          raise ValueError("Reading format '%s' is supported, but not writing" % format)
  
      raise ValueError("Unknown format '%s'" % 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
         (note older versions of Biopython only took a handle).
       - format   - lower case string describing the file format.
       - alphabet - optional Alphabet object, useful when the sequence type
         cannot be automatically inferred from the file itself
         (e.g. format="fasta" or "tab")
  
      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 file formats like FASTA where the alphabet cannot be determined, it
      may be useful to specify the alphabet explicitly:
  
      >>> from Bio import SeqIO
      >>> from Bio.Alphabet import generic_dna
      >>> filename = "Fasta/sweetpea.nu"
      >>> for record in SeqIO.parse(filename, "fasta", generic_dna):
      ...    print("ID %s" % record.id)
      ...    print("Sequence length %i" % len(record))
      ...    print("Sequence alphabet %s" % record.seq.alphabet)
      ID gi|3176602|gb|U78617.1|LOU78617
      Sequence length 309
      Sequence alphabet DNAAlphabet()
  
      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).
      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("Format string '%s' should be lower case" % format)
      if alphabet is not None and not isinstance(alphabet, (Alphabet, AlphabetEncoder)):
          raise ValueError("Invalid alphabet, %r" % alphabet)
  
      iterator_generator = _FormatToIterator.get(format)
      if iterator_generator:
          if alphabet is None:
              i = iterator_generator(handle)
          else:
              try:
                  i = iterator_generator(handle, alphabet=alphabet)
              except TypeError:
                  i = _force_alphabet(iterator_generator(handle), alphabet)
          return i
      if format in AlignIO._FormatToIterator:
          # Use Bio.AlignIO to read in the alignments
          i = (
              r
              for alignment in AlignIO.parse(handle, format, alphabet=alphabet)
              for r in alignment
          )
          return i
      raise ValueError("Unknown format '%s'" % format)
  
  
  def _force_alphabet(record_iterator, alphabet):
      """Iterate over records, over-riding the alphabet (PRIVATE)."""
      # Assume the alphabet argument has been pre-validated
      given_base_class = _get_base_alphabet(alphabet).__class__
      for record in record_iterator:
          if isinstance(_get_base_alphabet(record.seq.alphabet), given_base_class):
              record.seq.alphabet = alphabet
              yield record
          else:
              raise ValueError(
                  "Specified alphabet %r clashes with "
                  "that determined from the file, %r" % (alphabet, record.seq.alphabet)
              )
  
  
  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 - optional Alphabet object, useful when the sequence type
         cannot be automatically inferred from the file itself
         (e.g. format="fasta" or "tab")
  
      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.
      """
      iterator = parse(handle, format, alphabet)
      try:
          record = next(iterator)
      except StopIteration:
          raise ValueError("No records found in handle") from None
      try:
          next(iterator)
          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).
  
      Since Python 3.6, the default dict class maintains key order, meaning
      this dictionary will reflect the order of records given to it. As of
      Biopython 1.72, on older versions of Python we explicitly use an
      OrderedDict so that you can always assume the record order is preserved.
      """
      # 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("Duplicate key '%s'" % 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 - optional Alphabet object, useful when the sequence type
         cannot be automatically inferred from the file itself
         (e.g. format="fasta" or "tab")
       - 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(filename, str):
          raise TypeError("Need a filename (not a handle)")
      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("Format string '%s' should be lower case" % format)
      if alphabet is not None and not isinstance(alphabet, (Alphabet, AlphabetEncoder)):
          raise ValueError("Invalid alphabet, %r" % alphabet)
  
      # Map the file format to a sequence iterator:
      from ._index import _FormatToRandomAccess  # Lazy import
      from Bio.File import _IndexedSeqFileDict
  
      try:
          proxy_class = _FormatToRandomAccess[format]
      except KeyError:
          raise ValueError("Unsupported format %r" % format)
      repr = "SeqIO.index(%r, %r, alphabet=%r, key_function=%r)" % (
          filename,
          format,
          alphabet,
          key_function,
      )
      return _IndexedSeqFileDict(
          proxy_class(filename, format, alphabet), 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 - optional Alphabet object, useful when the sequence type
         cannot be automatically inferred from the file itself
         (e.g. format="fasta" or "tab")
       - 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.
  
      """
      # Try and give helpful error messages:
      if not isinstance(index_filename, str):
          raise TypeError("Need a string for the index filename")
      if isinstance(filenames, str):
          # 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 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("Format string '%s' should be lower case" % format)
      if alphabet is not None and not isinstance(alphabet, (Alphabet, AlphabetEncoder)):
          raise ValueError("Invalid alphabet, %r" % alphabet)
  
      # Map the file format to a sequence iterator:
      from ._index import _FormatToRandomAccess  # Lazy import
      from Bio.File import _SQLiteManySeqFilesDict
  
      repr = (
          "SeqIO.index_db(%r, filenames=%r, format=%r, alphabet=%r, key_function=%r)"
          % (index_filename, filenames, format, alphabet, 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, alphabet)
          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, alphabet=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
       - alphabet - optional alphabet to assume
  
      **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>
      """
      f = _converter.get((in_format, out_format))
      if f:
          count = f(in_file, out_file, alphabet)
      else:
          records = parse(in_file, in_format, alphabet)
          count = write(records, out_file, out_format)
      return count
  
  
  # This helpful trick for testing no longer works with the
  # local imports :(
  #
  # if __name__ == "__main__":
  #    from Bio._utils import run_doctest
  #    run_doctest()
  