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Source code for galaxy.datatypes.binary

"""Binary classes"""
from __future__ import print_function

import binascii
import gzip
import io
import logging
import os
import shutil
import struct
import subprocess
import sys
import tarfile
import tempfile
import zipfile
from collections import OrderedDict
from json import dumps

import h5py
import pysam
import pysam.bcftools
from bx.seq.twobit import TWOBIT_MAGIC_NUMBER, TWOBIT_MAGIC_NUMBER_SWAP, TWOBIT_MAGIC_SIZE

from galaxy import util
from galaxy.datatypes import metadata
from galaxy.datatypes.data import (
    DatatypeValidation,
    get_file_peek,
)
from galaxy.datatypes.metadata import DictParameter, ListParameter, MetadataElement, MetadataParameter
from galaxy.util import nice_size, sqlite
from galaxy.util.checkers import is_bz2, is_gzip
from . import data, dataproviders

log = logging.getLogger(__name__)

# Currently these supported binary data types must be manually set on upload


[docs]class Binary(data.Data): """Binary data""" edam_format = "format_2333"
[docs] @staticmethod def register_sniffable_binary_format(data_type, ext, type_class): """Deprecated method.""" pass
[docs] @staticmethod def register_unsniffable_binary_ext(ext): """Deprecated method.""" pass
[docs] def set_peek(self, dataset, is_multi_byte=False): """Set the peek and blurb text""" if not dataset.dataset.purged: dataset.peek = 'binary data' dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def get_mime(self): """Returns the mime type of the datatype""" return 'application/octet-stream'
[docs]class Ab1(Binary): """Class describing an ab1 binary sequence file""" file_ext = "ab1" edam_format = "format_3000" edam_data = "data_0924"
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary ab1 sequence file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary ab1 sequence file (%s)" % (nice_size(dataset.get_size()))
[docs]class Idat(Binary): """Binary data in idat format""" file_ext = "idat" edam_format = "format_2058" edam_data = "data_2603"
[docs] def sniff(self, filename): try: header = open(filename, 'rb').read(4) if header == b'IDAT': return True return False except Exception: return False
[docs]class Cel(Binary): """ Cel File format described at: http://media.affymetrix.com/support/developer/powertools/changelog/gcos-agcc/cel.html """ file_ext = "cel" edam_format = "format_1638" edam_data = "data_3110" MetadataElement(name="version", default="3", desc="Version", readonly=True, visible=True, optional=True, no_value="3")
[docs] def sniff(self, filename): """ Try to guess if the file is a Cel file. >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('affy_v_agcc.cel') >>> Cel().sniff(fname) True >>> fname = get_test_fname('affy_v_3.cel') >>> Cel().sniff(fname) True >>> fname = get_test_fname('affy_v_4.cel') >>> Cel().sniff(fname) True >>> fname = get_test_fname('test.gal') >>> Cel().sniff(fname) False """ with open(filename, 'rb') as handle: header_bytes = handle.read(8) found_cel_4 = False found_cel_3 = False found_cel_agcc = False if struct.unpack("<ii", header_bytes[:9]) == (64, 4): found_cel_4 = True elif struct.unpack(">bb", header_bytes[:2]) == (59, 1): found_cel_agcc = True elif header_bytes.decode("utf8", errors="ignore").startswith('[CEL]'): found_cel_3 = True return found_cel_3 or found_cel_4 or found_cel_agcc
[docs] def set_meta(self, dataset, **kwd): """ Set metadata for Cel file. """ with open(dataset.file_name, 'rb') as handle: header_bytes = handle.read(8) if struct.unpack("<ii", header_bytes[:9]) == (64, 4): dataset.metadata.version = "4" elif struct.unpack(">bb", header_bytes[:2]) == (59, 1): dataset.metadata.version = "agcc" elif header_bytes.decode("utf8", errors="ignore").startswith('[CEL]'): dataset.metadata.version = "3"
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.blurb = "Cel version: %s" % dataset.metadata.version dataset.peek = get_file_peek(dataset.file_name) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs]class MashSketch(Binary): """ Mash Sketch file. Sketches are used by the MinHash algorithm to allow fast distance estimations with low storage and memory requirements. To make a sketch, each k-mer in a sequence is hashed, which creates a pseudo-random identifier. By sorting these identifiers (hashes), a small subset from the top of the sorted list can represent the entire sequence (these are min-hashes). The more similar another sequence is, the more min-hashes it is likely to share. """ file_ext = "msh"
[docs]class CompressedArchive(Binary): """ Class describing an compressed binary file This class can be sublass'ed to implement archive filetypes that will not be unpacked by upload.py. """ file_ext = "compressed_archive" compressed = True
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Compressed binary file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Compressed binary file (%s)" % (nice_size(dataset.get_size()))
[docs]class DynamicCompressedArchive(CompressedArchive):
[docs] def matches_any(self, target_datatypes): """Treat two aspects of compressed datatypes separately. """ compressed_target_datatypes = [] uncompressed_target_datatypes = [] for target_datatype in target_datatypes: if hasattr(target_datatype, "uncompressed_datatype_instance") and target_datatype.compressed_format == self.compressed_format: uncompressed_target_datatypes.append(target_datatype.uncompressed_datatype_instance) else: compressed_target_datatypes.append(target_datatype) # TODO: Add gz and bz2 as proper datatypes and use those instances instead of # CompressedArchive() in the following check. return self.uncompressed_datatype_instance.matches_any(uncompressed_target_datatypes) or \ CompressedArchive().matches_any(compressed_target_datatypes)
[docs]class GzDynamicCompressedArchive(DynamicCompressedArchive): compressed_format = "gzip"
[docs]class Bz2DynamicCompressedArchive(DynamicCompressedArchive): compressed_format = "bz2"
[docs]class CompressedZipArchive(CompressedArchive): """ Class describing an compressed binary file This class can be sublass'ed to implement archive filetypes that will not be unpacked by upload.py. """ file_ext = "zip"
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Compressed zip file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Compressed zip file (%s)" % (nice_size(dataset.get_size()))
[docs]class GenericAsn1Binary(Binary): """Class for generic ASN.1 binary format""" file_ext = "asn1-binary" edam_format = "format_1966" edam_data = "data_0849"
[docs]class BamNative(CompressedArchive): """Class describing a BAM binary file that is not necessarily sorted""" edam_format = "format_2572" edam_data = "data_0863" file_ext = "unsorted.bam" sort_flag = None MetadataElement(name="bam_version", default=None, desc="BAM Version", param=MetadataParameter, readonly=True, visible=False, optional=True, no_value=None) MetadataElement(name="sort_order", default=None, desc="Sort Order", param=MetadataParameter, readonly=True, visible=False, optional=True, no_value=None) MetadataElement(name="read_groups", default=[], desc="Read Groups", param=MetadataParameter, readonly=True, visible=False, optional=True, no_value=[]) MetadataElement(name="reference_names", default=[], desc="Chromosome Names", param=MetadataParameter, readonly=True, visible=False, optional=True, no_value=[]) MetadataElement(name="reference_lengths", default=[], desc="Chromosome Lengths", param=MetadataParameter, readonly=True, visible=False, optional=True, no_value=[]) MetadataElement(name="bam_header", default={}, desc="Dictionary of BAM Headers", param=MetadataParameter, readonly=True, visible=False, optional=True, no_value={}) MetadataElement(name="columns", default=12, desc="Number of columns", readonly=True, visible=False, no_value=0) MetadataElement(name="column_types", default=['str', 'int', 'str', 'int', 'int', 'str', 'str', 'int', 'int', 'str', 'str', 'str'], desc="Column types", param=metadata.ColumnTypesParameter, readonly=True, visible=False, no_value=[]) MetadataElement(name="column_names", default=['QNAME', 'FLAG', 'RNAME', 'POS', 'MAPQ', 'CIGAR', 'MRNM', 'MPOS', 'ISIZE', 'SEQ', 'QUAL', 'OPT'], desc="Column names", readonly=True, visible=False, optional=True, no_value=[])
[docs] @staticmethod def merge(split_files, output_file): """ Merges BAM files :param split_files: List of bam file paths to merge :param output_file: Write merged bam file to this location """ pysam.merge('-O', 'BAM', output_file, *split_files)
[docs] def init_meta(self, dataset, copy_from=None): Binary.init_meta(self, dataset, copy_from=copy_from)
[docs] def sniff(self, filename): return BamNative.is_bam(filename)
[docs] @classmethod def is_bam(cls, filename): # BAM is compressed in the BGZF format, and must not be uncompressed in Galaxy. # The first 4 bytes of any bam file is 'BAM\1', and the file is binary. try: header = gzip.open(filename).read(4) if header == b'BAM\1': return True return False except Exception: return False
[docs] def set_meta(self, dataset, overwrite=True, **kwd): try: bam_file = pysam.AlignmentFile(dataset.file_name, mode='rb') # TODO: Reference names, lengths, read_groups and headers can become very large, truncate when necessary dataset.metadata.reference_names = list(bam_file.references) dataset.metadata.reference_lengths = list(bam_file.lengths) dataset.metadata.bam_header = OrderedDict((k, v) for k, v in bam_file.header.items()) dataset.metadata.read_groups = [read_group['ID'] for read_group in dataset.metadata.bam_header.get('RG', []) if 'ID' in read_group] dataset.metadata.sort_order = dataset.metadata.bam_header.get('HD', {}).get('SO', None) dataset.metadata.bam_version = dataset.metadata.bam_header.get('HD', {}).get('VN', None) except Exception: # Per Dan, don't log here because doing so will cause datasets that # fail metadata to end in the error state pass
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary bam alignments file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary bam alignments file (%s)" % (nice_size(dataset.get_size()))
[docs] def to_archive(self, trans, dataset, name=""): rel_paths = [] file_paths = [] rel_paths.append("%s.%s" % (name or dataset.file_name, dataset.extension)) file_paths.append(dataset.file_name) rel_paths.append("%s.%s.bai" % (name or dataset.file_name, dataset.extension)) file_paths.append(dataset.metadata.bam_index.file_name) return zip(file_paths, rel_paths)
[docs] def groom_dataset_content(self, file_name): """ Ensures that the BAM file contents are coordinate-sorted. This function is called on an output dataset after the content is initially generated. """ # Use pysam to sort the BAM file # This command may also creates temporary files <out.prefix>.%d.bam when the # whole alignment cannot fit into memory. # do this in a unique temp directory, because of possible <out.prefix>.%d.bam temp files if not self.dataset_content_needs_grooming(file_name): # Don't re-sort if already sorted return tmp_dir = tempfile.mkdtemp() tmp_sorted_dataset_file_name_prefix = os.path.join(tmp_dir, 'sorted') sorted_file_name = "%s.bam" % tmp_sorted_dataset_file_name_prefix slots = os.environ.get('GALAXY_SLOTS', 1) sort_args = [] if self.sort_flag: sort_args = [self.sort_flag] sort_args.extend(["-@%s" % slots, file_name, '-T', tmp_sorted_dataset_file_name_prefix, '-O', 'BAM', '-o', sorted_file_name]) try: pysam.sort(*sort_args) except Exception: shutil.rmtree(tmp_dir, ignore_errors=True) raise # Move samtools_created_sorted_file_name to our output dataset location shutil.move(sorted_file_name, file_name) # Remove temp file and empty temporary directory os.rmdir(tmp_dir)
[docs] def get_chunk(self, trans, dataset, offset=0, ck_size=None): if not offset == -1: try: with pysam.AlignmentFile(dataset.file_name, "rb") as bamfile: ck_size = 300 # 300 lines ck_data = "" header_line_count = 0 if offset == 0: ck_data = bamfile.text.replace('\t', ' ') header_line_count = bamfile.text.count('\n') else: bamfile.seek(offset) for line_number, alignment in enumerate(bamfile): # return only Header lines if 'header_line_count' exceeds 'ck_size' # FIXME: Can be problematic if bam has million lines of header offset = bamfile.tell() if (line_number + header_line_count) > ck_size: break else: bamline = alignment.tostring(bamfile) # Galaxy display each tag as separate column because 'tostring()' funcition put tabs in between each tag of tags column. # Below code will remove spaces between each tag. bamline_modified = ('\t').join(bamline.split()[:11] + [(' ').join(bamline.split()[11:])]) ck_data = "%s\n%s" % (ck_data, bamline_modified) else: # Nothing to enumerate; we've either offset to the end # of the bamfile, or there is no data. (possible with # header-only bams) offset = -1 except Exception as e: offset = -1 ck_data = "Could not display BAM file, error was:\n%s" % e else: ck_data = '' offset = -1 return dumps({'ck_data': util.unicodify(ck_data), 'offset': offset})
[docs] def display_data(self, trans, dataset, preview=False, filename=None, to_ext=None, offset=None, ck_size=None, **kwd): preview = util.string_as_bool(preview) if offset is not None: return self.get_chunk(trans, dataset, offset, ck_size) elif to_ext or not preview: return super(BamNative, self).display_data(trans, dataset, preview, filename, to_ext, **kwd) else: column_names = dataset.metadata.column_names if not column_names: column_names = [] column_types = dataset.metadata.column_types if not column_types: column_types = [] column_number = dataset.metadata.columns if column_number is None: column_number = 1 return trans.fill_template("/dataset/tabular_chunked.mako", dataset=dataset, chunk=self.get_chunk(trans, dataset, 0), column_number=column_number, column_names=column_names, column_types=column_types)
[docs] def validate(self, dataset, **kwd): if not BamNative.is_bam(dataset.file_name): return DatatypeValidation.invalid("This dataset does not appear to a BAM file.") elif self.dataset_content_needs_grooming(dataset.file_name): return DatatypeValidation.invalid("This BAM file does not appear to have the correct sorting for declared datatype.") return DatatypeValidation.validated()
[docs]@dataproviders.decorators.has_dataproviders class Bam(BamNative): """Class describing a BAM binary file""" edam_format = "format_2572" edam_data = "data_0863" file_ext = "bam" track_type = "ReadTrack" data_sources = {"data": "bai", "index": "bigwig"} MetadataElement(name="bam_index", desc="BAM Index File", param=metadata.FileParameter, file_ext="bai", readonly=True, no_value=None, visible=False, optional=True)
[docs] def dataset_content_needs_grooming(self, file_name): """ Check if file_name is a coordinate-sorted BAM file """ # The best way to ensure that BAM files are coordinate-sorted and indexable # is to actually index them. index_name = tempfile.NamedTemporaryFile(prefix="bam_index").name try: # If pysam fails to index a file it will write to stderr, # and this causes the set_meta script to fail. So instead # we start another process and discard stderr. cmd = ['python', '-c', "import pysam; pysam.index('%s', '%s')" % (file_name, index_name)] with open(os.devnull, 'w') as devnull: subprocess.check_call(cmd, stderr=devnull, shell=False) needs_sorting = False except subprocess.CalledProcessError: needs_sorting = True try: os.unlink(index_name) except Exception: pass return needs_sorting
[docs] def set_meta(self, dataset, overwrite=True, **kwd): # These metadata values are not accessible by users, always overwrite super(Bam, self).set_meta(dataset=dataset, overwrite=overwrite, **kwd) index_file = dataset.metadata.bam_index if not index_file: index_file = dataset.metadata.spec['bam_index'].param.new_file(dataset=dataset) pysam.index(dataset.file_name, index_file.file_name) dataset.metadata.bam_index = index_file
[docs] def sniff(self, file_name): return super(Bam, self).sniff(file_name) and not self.dataset_content_needs_grooming(file_name)
# ------------- Dataproviders # pipe through samtools view # ALSO: (as Sam) # bam does not use '#' to indicate comments/headers - we need to strip out those headers from the std. providers # TODO:?? seems like there should be an easier way to do/inherit this - metadata.comment_char? # TODO: incorporate samtools options to control output: regions first, then flags, etc.
[docs] @dataproviders.decorators.dataprovider_factory('line', dataproviders.line.FilteredLineDataProvider.settings) def line_dataprovider(self, dataset, **settings): samtools_source = dataproviders.dataset.SamtoolsDataProvider(dataset) settings['comment_char'] = '@' return dataproviders.line.FilteredLineDataProvider(samtools_source, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('regex-line', dataproviders.line.RegexLineDataProvider.settings) def regex_line_dataprovider(self, dataset, **settings): samtools_source = dataproviders.dataset.SamtoolsDataProvider(dataset) settings['comment_char'] = '@' return dataproviders.line.RegexLineDataProvider(samtools_source, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('column', dataproviders.column.ColumnarDataProvider.settings) def column_dataprovider(self, dataset, **settings): samtools_source = dataproviders.dataset.SamtoolsDataProvider(dataset) settings['comment_char'] = '@' return dataproviders.column.ColumnarDataProvider(samtools_source, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('dict', dataproviders.column.DictDataProvider.settings) def dict_dataprovider(self, dataset, **settings): samtools_source = dataproviders.dataset.SamtoolsDataProvider(dataset) settings['comment_char'] = '@' return dataproviders.column.DictDataProvider(samtools_source, **settings)
# these can't be used directly - may need BamColumn, BamDict (Bam metadata -> column/dict) # OR - see genomic_region_dataprovider # @dataproviders.decorators.dataprovider_factory('dataset-column', dataproviders.column.ColumnarDataProvider.settings) # def dataset_column_dataprovider(self, dataset, **settings): # settings['comment_char'] = '@' # return super(Sam, self).dataset_column_dataprovider(dataset, **settings) # @dataproviders.decorators.dataprovider_factory('dataset-dict', dataproviders.column.DictDataProvider.settings) # def dataset_dict_dataprovider(self, dataset, **settings): # settings['comment_char'] = '@' # return super(Sam, self).dataset_dict_dataprovider(dataset, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('header', dataproviders.line.RegexLineDataProvider.settings) def header_dataprovider(self, dataset, **settings): # in this case we can use an option of samtools view to provide just what we need (w/o regex) samtools_source = dataproviders.dataset.SamtoolsDataProvider(dataset, '-H') return dataproviders.line.RegexLineDataProvider(samtools_source, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('id-seq-qual', dataproviders.column.DictDataProvider.settings) def id_seq_qual_dataprovider(self, dataset, **settings): settings['indeces'] = [0, 9, 10] settings['column_types'] = ['str', 'str', 'str'] settings['column_names'] = ['id', 'seq', 'qual'] return self.dict_dataprovider(dataset, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('genomic-region', dataproviders.column.ColumnarDataProvider.settings) def genomic_region_dataprovider(self, dataset, **settings): # GenomicRegionDataProvider currently requires a dataset as source - may not be necc. # TODO:?? consider (at least) the possible use of a kwarg: metadata_source (def. to source.dataset), # or remove altogether... # samtools_source = dataproviders.dataset.SamtoolsDataProvider(dataset) # return dataproviders.dataset.GenomicRegionDataProvider(samtools_source, metadata_source=dataset, # 2, 3, 3, **settings) # instead, set manually and use in-class column gen settings['indeces'] = [2, 3, 3] settings['column_types'] = ['str', 'int', 'int'] return self.column_dataprovider(dataset, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('genomic-region-dict', dataproviders.column.DictDataProvider.settings) def genomic_region_dict_dataprovider(self, dataset, **settings): settings['indeces'] = [2, 3, 3] settings['column_types'] = ['str', 'int', 'int'] settings['column_names'] = ['chrom', 'start', 'end'] return self.dict_dataprovider(dataset, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('samtools') def samtools_dataprovider(self, dataset, **settings): """Generic samtools interface - all options available through settings.""" dataset_source = dataproviders.dataset.DatasetDataProvider(dataset) return dataproviders.dataset.SamtoolsDataProvider(dataset_source, **settings)
[docs]class ProBam(Bam): """Class describing a BAM binary file - extended for proteomics data""" edam_format = "format_3826" edam_data = "data_0863" file_ext = "probam"
[docs]class BamInputSorted(BamNative): sort_flag = '-n' file_ext = 'qname_input_sorted.bam' """ A class for BAM files that can formally be unsorted or queryname sorted. Alignments are either ordered based on the order with which the queries appear when producing the alignment, or ordered by their queryname. This notaby keeps alignments produced by paired end sequencing adjacent. """
[docs] def sniff(self, file_name): # We never want to sniff to this datatype return False
[docs] def dataset_content_needs_grooming(self, file_name): """ Groom if the file is coordinate sorted """ # The best way to ensure that BAM files are coordinate-sorted and indexable # is to actually index them. with pysam.AlignmentFile(filename=file_name) as f: # The only sure thing we know here is that the sort order can't be coordinate return f.header.get('HD', {}).get('SO') == 'coordinate'
[docs]class BamQuerynameSorted(BamInputSorted): """A class for queryname sorted BAM files.""" sort_flag = '-n' file_ext = "qname_sorted.bam"
[docs] def sniff(self, file_name): return BamNative().sniff(file_name) and not self.dataset_content_needs_grooming(file_name)
[docs] def dataset_content_needs_grooming(self, file_name): """ Check if file_name is a queryname-sorted BAM file """ # The best way to ensure that BAM files are coordinate-sorted and indexable # is to actually index them. with pysam.AlignmentFile(filename=file_name) as f: return f.header.get('HD', {}).get('SO') != 'queryname'
[docs]class CRAM(Binary): file_ext = "cram" edam_format = "format_3462" edam_data = "format_0863" MetadataElement(name="cram_version", default=None, desc="CRAM Version", param=MetadataParameter, readonly=True, visible=False, optional=False, no_value=None) MetadataElement(name="cram_index", desc="CRAM Index File", param=metadata.FileParameter, file_ext="crai", readonly=True, no_value=None, visible=False, optional=True)
[docs] def set_meta(self, dataset, overwrite=True, **kwd): major_version, minor_version = self.get_cram_version(dataset.file_name) if major_version != -1: dataset.metadata.cram_version = str(major_version) + "." + str(minor_version) if not dataset.metadata.cram_index: index_file = dataset.metadata.spec['cram_index'].param.new_file(dataset=dataset) if self.set_index_file(dataset, index_file): dataset.metadata.cram_index = index_file
[docs] def get_cram_version(self, filename): try: with open(filename, "rb") as fh: header = bytearray(fh.read(6)) return header[4], header[5] except Exception as exc: log.warning('%s, get_cram_version Exception: %s', self, exc) return -1, -1
[docs] def set_index_file(self, dataset, index_file): try: pysam.index(dataset.file_name, index_file.file_name) return True except Exception as exc: log.warning('%s, set_index_file Exception: %s', self, exc) return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = 'CRAM binary alignment file' dataset.blurb = 'binary data' else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def sniff(self, filename): try: header = open(filename, 'rb').read(4) if header == b"CRAM": return True return False except Exception: return False
[docs]class BaseBcf(CompressedArchive): edam_format = "format_3020" edam_data = "data_3498"
[docs]class Bcf(BaseBcf): """ Class describing a (BGZF-compressed) BCF file """ file_ext = "bcf" MetadataElement(name="bcf_index", desc="BCF Index File", param=metadata.FileParameter, file_ext="csi", readonly=True, no_value=None, visible=False, optional=True)
[docs] def sniff(self, filename): # BCF is compressed in the BGZF format, and must not be uncompressed in Galaxy. try: header = gzip.open(filename).read(3) # The first 3 bytes of any BCF file are 'BCF', and the file is binary. if header == b'BCF': return True return False except Exception: return False
[docs] def set_meta(self, dataset, overwrite=True, **kwd): """ Creates the index for the BCF file. """ # These metadata values are not accessible by users, always overwrite index_file = dataset.metadata.bcf_index if not index_file: index_file = dataset.metadata.spec['bcf_index'].param.new_file(dataset=dataset) # Create the bcf index dataset_symlink = os.path.join(os.path.dirname(index_file.file_name), '__dataset_%d_%s' % (dataset.id, os.path.basename(index_file.file_name))) os.symlink(dataset.file_name, dataset_symlink) try: cmd = ['python', '-c', "import pysam.bcftools; pysam.bcftools.index('%s')" % (dataset_symlink)] subprocess.check_call(cmd) shutil.move(dataset_symlink + '.csi', index_file.file_name) except Exception as e: raise Exception('Error setting BCF metadata: %s' % util.unicodify(e)) finally: # Remove temp file and symlink os.remove(dataset_symlink) dataset.metadata.bcf_index = index_file
[docs]class BcfUncompressed(BaseBcf): """ Class describing an uncompressed BCF file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('1.bcf_uncompressed') >>> BcfUncompressed().sniff(fname) True >>> fname = get_test_fname('1.bcf') >>> BcfUncompressed().sniff(fname) False """ file_ext = "bcf_uncompressed"
[docs] def sniff(self, filename): try: header = open(filename, mode='rb').read(3) # The first 3 bytes of any BCF file are 'BCF', and the file is binary. if header == b'BCF': return True return False except Exception: return False
[docs]class H5(Binary): """ Class describing an HDF5 file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.mz5') >>> H5().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> H5().sniff(fname) False """ file_ext = "h5" edam_format = "format_3590"
[docs] def __init__(self, **kwd): Binary.__init__(self, **kwd) self._magic = binascii.unhexlify("894844460d0a1a0a")
[docs] def sniff(self, filename): # The first 8 bytes of any hdf5 file are 0x894844460d0a1a0a try: header = open(filename, 'rb').read(8) if header == self._magic: return True return False except Exception: return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary HDF5 file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary HDF5 file (%s)" % (nice_size(dataset.get_size()))
[docs]class Loom(H5): """ Class describing a Loom file: http://loompy.org/ >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.loom') >>> Loom().sniff(fname) True >>> fname = get_test_fname('test.mz5') >>> Loom().sniff(fname) False """ file_ext = "loom" edam_format = "format_3590" MetadataElement(name="title", default="", desc="title", readonly=True, visible=True, no_value="") MetadataElement(name="description", default="", desc="description", readonly=True, visible=True, no_value="") MetadataElement(name="url", default="", desc="url", readonly=True, visible=True, no_value="") MetadataElement(name="doi", default="", desc="doi", readonly=True, visible=True, no_value="") MetadataElement(name="loom_spec_version", default="", desc="loom_spec_version", readonly=True, visible=True, no_value="") MetadataElement(name="creation_date", default=None, desc="creation_date", readonly=True, visible=True, no_value=None) MetadataElement(name="shape", default=(), desc="shape", param=metadata.ListParameter, readonly=True, visible=True, no_value=()) MetadataElement(name="layers_count", default=0, desc="layers_count", readonly=True, visible=True, no_value=0) MetadataElement(name="layers_names", desc="layers_names", default=[], param=metadata.SelectParameter, multiple=True, readonly=True, no_value=None) MetadataElement(name="row_attrs_count", default=0, desc="row_attrs_count", readonly=True, visible=True, no_value=0) MetadataElement(name="row_attrs_names", desc="row_attrs_names", default=[], param=metadata.SelectParameter, multiple=True, readonly=True, no_value=None) MetadataElement(name="col_attrs_count", default=0, desc="col_attrs_count", readonly=True, visible=True, no_value=0) MetadataElement(name="col_attrs_names", desc="col_attrs_names", default=[], param=metadata.SelectParameter, multiple=True, readonly=True, no_value=None) MetadataElement(name="col_graphs_count", default=0, desc="col_graphs_count", readonly=True, visible=True, no_value=0) MetadataElement(name="col_graphs_names", desc="col_graphs_names", default=[], param=metadata.SelectParameter, multiple=True, readonly=True, no_value=None) MetadataElement(name="row_graphs_count", default=0, desc="row_graphs_count", readonly=True, visible=True, no_value=0) MetadataElement(name="row_graphs_names", desc="row_graphs_names", default=[], param=metadata.SelectParameter, multiple=True, readonly=True, no_value=None)
[docs] def sniff(self, filename): if super(Loom, self).sniff(filename): with h5py.File(filename, 'r') as loom_file: # Check the optional but distinctive LOOM_SPEC_VERSION attribute if bool(loom_file.attrs.get('LOOM_SPEC_VERSION')): return True # Check some mandatory H5 datasets and groups for el in ('matrix', 'row_attrs', 'col_attrs'): if loom_file.get(el) is None: return False else: return True return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary Loom file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary Loom file (%s)" % (nice_size(dataset.get_size()))
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(Loom, self).set_meta(dataset, overwrite=overwrite, **kwd) try: with h5py.File(dataset.file_name, 'r') as loom_file: dataset.metadata.title = util.unicodify(loom_file.attrs.get('title')) dataset.metadata.description = util.unicodify(loom_file.attrs.get('description')) dataset.metadata.url = util.unicodify(loom_file.attrs.get('url')) dataset.metadata.doi = util.unicodify(loom_file.attrs.get('doi')) dataset.metadata.loom_spec_version = util.unicodify(loom_file.attrs.get('LOOM_SPEC_VERSION')) dataset.creation_date = util.unicodify(loom_file.attrs.get('creation_date')) dataset.metadata.shape = tuple(loom_file['matrix'].shape) tmp = list(loom_file.get('layers', {}).keys()) dataset.metadata.layers_count = len(tmp) dataset.metadata.layers_names = tmp tmp = list(loom_file['row_attrs'].keys()) dataset.metadata.row_attrs_count = len(tmp) dataset.metadata.row_attrs_names = tmp tmp = list(loom_file['col_attrs'].keys()) dataset.metadata.col_attrs_count = len(tmp) dataset.metadata.col_attrs_names = tmp # According to the Loom file format specification, col_graphs # and row_graphs are mandatory groups, but files created by # Bioconductor LoomExperiment do not always have them: # https://github.com/Bioconductor/LoomExperiment/issues/7 tmp = list(loom_file.get('col_graphs', {}).keys()) dataset.metadata.col_graphs_count = len(tmp) dataset.metadata.col_graphs_names = tmp tmp = list(loom_file.get('row_graphs', {}).keys()) dataset.metadata.row_graphs_count = len(tmp) dataset.metadata.row_graphs_names = tmp except Exception as e: log.warning('%s, set_meta Exception: %s', self, e)
[docs]class Anndata(H5): """ Class describing an HDF5 anndata files: http://anndata.rtfd.io >>> from galaxy.datatypes.sniff import get_test_fname >>> Anndata().sniff(get_test_fname('pbmc3k_tiny.h5ad')) True >>> Anndata().sniff(get_test_fname('test.mz5')) False """ file_ext = 'h5ad'
[docs] def sniff(self, filename): if super(Anndata, self).sniff(filename): try: with h5py.File(filename, 'r') as f: return all(attr in f for attr in ['X', 'obs', 'var']) except Exception: return False return False
[docs]class GmxBinary(Binary): """ Base class for GROMACS binary files - xtc, trr, cpt """ magic_number = None # variables to be overwritten in the child class file_ext = ""
[docs] def sniff(self, filename): # The first 4 bytes of any GROMACS binary file containing the magic number try: header = open(filename, 'rb').read(struct.calcsize('>1i')) if struct.unpack('>1i', header)[0] == self.magic_number: return True return False except Exception: return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary GROMACS %s file" % (self.file_ext) dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary GROMACS %s trajectory file (%s)" % (self.file_ext, nice_size(dataset.get_size()))
[docs]class Trr(GmxBinary): """ Class describing an trr file from the GROMACS suite >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('md.trr') >>> Trr().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> Trr().sniff(fname) False """ file_ext = "trr" magic_number = 1993 # magic number reference: https://github.com/gromacs/gromacs/blob/cec211b2c835ba6e8ea849fb1bf67d7fc19693a4/src/gromacs/fileio/trrio.cpp
[docs]class Cpt(GmxBinary): """ Class describing a checkpoint (.cpt) file from the GROMACS suite >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('md.cpt') >>> Cpt().sniff(fname) True >>> fname = get_test_fname('md.trr') >>> Cpt().sniff(fname) False """ file_ext = "cpt" magic_number = 171817 # magic number reference: https://github.com/gromacs/gromacs/blob/cec211b2c835ba6e8ea849fb1bf67d7fc19693a4/src/gromacs/fileio/checkpoint.cpp
[docs]class Xtc(GmxBinary): """ Class describing an xtc file from the GROMACS suite >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('md.xtc') >>> Xtc().sniff(fname) True >>> fname = get_test_fname('md.trr') >>> Xtc().sniff(fname) False """ file_ext = "xtc" magic_number = 1995 # reference: https://github.com/gromacs/gromacs/blob/cec211b2c835ba6e8ea849fb1bf67d7fc19693a4/src/gromacs/fileio/xtcio.cpp
[docs]class Edr(GmxBinary): """ Class describing an edr file from the GROMACS suite >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('md.edr') >>> Edr().sniff(fname) True >>> fname = get_test_fname('md.trr') >>> Edr().sniff(fname) False """ file_ext = "edr" magic_number = -55555 # reference: https://github.com/gromacs/gromacs/blob/cec211b2c835ba6e8ea849fb1bf67d7fc19693a4/src/gromacs/fileio/enxio.cpp
[docs]class Biom2(H5): """ Class describing a biom2 file (http://biom-format.org/documentation/biom_format.html) """ MetadataElement(name="id", default=None, desc="table id", readonly=True, visible=True, no_value=None) MetadataElement(name="format_url", default=None, desc="format-url", readonly=True, visible=True, no_value=None) MetadataElement(name="format_version", default=None, desc="format-version", readonly=True, visible=True, no_value=None) MetadataElement(name="format", default=None, desc="format", readonly=True, visible=True, no_value=None) MetadataElement(name="type", default=None, desc="table type", readonly=True, visible=True, no_value=None) MetadataElement(name="generated_by", default=None, desc="generated by", readonly=True, visible=True, no_value=None) MetadataElement(name="creation_date", default=None, desc="creation date", readonly=True, visible=True, no_value=None) MetadataElement(name="nnz", default=-1, desc="nnz: The number of non-zero elements in the table", readonly=True, visible=True, no_value=-1) MetadataElement(name="shape", default=(), desc="shape: The number of rows and columns in the dataset", readonly=True, visible=True, no_value=()) file_ext = "biom2" edam_format = "format_3746"
[docs] def sniff(self, filename): """ >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('biom2_sparse_otu_table_hdf5.biom2') >>> Biom2().sniff(fname) True >>> fname = get_test_fname('test.mz5') >>> Biom2().sniff(fname) False >>> fname = get_test_fname('wiggle.wig') >>> Biom2().sniff(fname) False """ if super(Biom2, self).sniff(filename): with h5py.File(filename, 'r') as f: required_fields = {'id', 'format-url', 'type', 'generated-by', 'creation-date', 'nnz', 'shape'} return required_fields.issubset(f.attrs.keys()) return False
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(Biom2, self).set_meta(dataset, overwrite=overwrite, **kwd) try: with h5py.File(dataset.file_name, 'r') as f: attributes = f.attrs dataset.metadata.id = util.unicodify(attributes['id']) dataset.metadata.format_url = util.unicodify(attributes['format-url']) if 'format-version' in attributes: # biom 2.1 dataset.metadata.format_version = '.'.join(str(_) for _ in attributes['format-version']) elif 'format' in attributes: # biom 2.0 dataset.metadata.format = util.unicodify(attributes['format']) dataset.metadata.type = util.unicodify(attributes['type']) dataset.metadata.shape = tuple((int(_) for _ in attributes['shape'])) dataset.metadata.generated_by = util.unicodify(attributes['generated-by']) dataset.metadata.creation_date = util.unicodify(attributes['creation-date']) dataset.metadata.nnz = int(attributes['nnz']) except Exception as e: log.warning('%s, set_meta Exception: %s', self, util.unicodify(e))
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: lines = ['Biom2 (HDF5) file'] try: with h5py.File(dataset.file_name) as f: for k, v in f.attrs.items(): lines.append('%s: %s' % (k, util.unicodify(v))) except Exception as e: log.warning('%s, set_peek Exception: %s', self, util.unicodify(e)) dataset.peek = '\n'.join(lines) dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Biom2 (HDF5) file (%s)" % (nice_size(dataset.get_size()))
[docs]class Cool(H5): """ Class describing the cool format (https://github.com/mirnylab/cooler) """ file_ext = "cool"
[docs] def sniff(self, filename): """ >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('matrix.cool') >>> Cool().sniff(fname) True >>> fname = get_test_fname('test.mz5') >>> Cool().sniff(fname) False >>> fname = get_test_fname('wiggle.wig') >>> Cool().sniff(fname) False >>> fname = get_test_fname('biom2_sparse_otu_table_hdf5.biom2') >>> Cool().sniff(fname) False """ MAGIC = "HDF5::Cooler" URL = "https://github.com/mirnylab/cooler" if super(Cool, self).sniff(filename): keys = ['chroms', 'bins', 'pixels', 'indexes'] with h5py.File(filename, 'r') as handle: fmt = util.unicodify(handle.attrs.get('format')) url = util.unicodify(handle.attrs.get('format-url')) if fmt == MAGIC or url == URL: if not all(name in handle.keys() for name in keys): return False return True return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Cool (HDF5) file for storing genomic interaction data." dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Cool (HDF5) file (%s)." % (nice_size(dataset.get_size()))
[docs]class MCool(H5): """ Class describing the multi-resolution cool format (https://github.com/mirnylab/cooler) """ file_ext = "mcool"
[docs] def sniff(self, filename): """ >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('matrix.mcool') >>> MCool().sniff(fname) True >>> fname = get_test_fname('matrix.cool') >>> MCool().sniff(fname) False >>> fname = get_test_fname('test.mz5') >>> MCool().sniff(fname) False >>> fname = get_test_fname('wiggle.wig') >>> MCool().sniff(fname) False >>> fname = get_test_fname('biom2_sparse_otu_table_hdf5.biom2') >>> MCool().sniff(fname) False """ MAGIC = "HDF5::Cooler" URL = "https://github.com/mirnylab/cooler" if super(MCool, self).sniff(filename): keys0 = ['resolutions'] with h5py.File(filename, 'r') as handle: if not all(name in handle.keys() for name in keys0): return False res0 = list(handle['resolutions'].keys())[0] keys = ['chroms', 'bins', 'pixels', 'indexes'] fmt = util.unicodify(handle['resolutions'][res0].attrs.get('format')) url = util.unicodify(handle['resolutions'][res0].attrs.get('format-url')) if fmt == MAGIC or url == URL: if not all(name in handle['resolutions'][res0].keys() for name in keys): return False return True return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Multi-resolution Cool (HDF5) file for storing genomic interaction data." dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "MCool (HDF5) file (%s)." % (nice_size(dataset.get_size()))
[docs]class Scf(Binary): """Class describing an scf binary sequence file""" edam_format = "format_1632" edam_data = "data_0924" file_ext = "scf"
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary scf sequence file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary scf sequence file (%s)" % (nice_size(dataset.get_size()))
[docs]class Sff(Binary): """ Standard Flowgram Format (SFF) """ edam_format = "format_3284" edam_data = "data_0924" file_ext = "sff"
[docs] def sniff(self, filename): # The first 4 bytes of any sff file is '.sff', and the file is binary. For details # about the format, see http://www.ncbi.nlm.nih.gov/Traces/trace.cgi?cmd=show&f=formats&m=doc&s=format try: header = open(filename, 'rb').read(4) if header == b'.sff': return True return False except Exception: return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary sff file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary sff file (%s)" % (nice_size(dataset.get_size()))
[docs]class BigWig(Binary): """ Accessing binary BigWig files from UCSC. The supplemental info in the paper has the binary details: http://bioinformatics.oxfordjournals.org/cgi/content/abstract/btq351v1 """ edam_format = "format_3006" edam_data = "data_3002" file_ext = "bigwig" track_type = "LineTrack" data_sources = {"data_standalone": "bigwig"}
[docs] def __init__(self, **kwd): Binary.__init__(self, **kwd) self._magic = 0x888FFC26 self._name = "BigWig"
def _unpack(self, pattern, handle): return struct.unpack(pattern, handle.read(struct.calcsize(pattern)))
[docs] def sniff(self, filename): try: magic = self._unpack("I", open(filename, 'rb')) return magic[0] == self._magic except Exception: return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary UCSC %s file" % self._name dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary UCSC %s file (%s)" % (self._name, nice_size(dataset.get_size()))
[docs]class BigBed(BigWig): """BigBed support from UCSC.""" edam_format = "format_3004" edam_data = "data_3002" file_ext = "bigbed" data_sources = {"data_standalone": "bigbed"}
[docs] def __init__(self, **kwd): Binary.__init__(self, **kwd) self._magic = 0x8789F2EB self._name = "BigBed"
[docs]class TwoBit(Binary): """Class describing a TwoBit format nucleotide file""" edam_format = "format_3009" edam_data = "data_0848" file_ext = "twobit"
[docs] def sniff(self, filename): try: # All twobit files start with a 16-byte header. If the file is smaller than 16 bytes, it's obviously not a valid twobit file. if os.path.getsize(filename) < 16: return False header = open(filename, 'rb').read(TWOBIT_MAGIC_SIZE) magic = struct.unpack(">L", header)[0] if magic == TWOBIT_MAGIC_NUMBER or magic == TWOBIT_MAGIC_NUMBER_SWAP: return True except IOError: return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary TwoBit format nucleotide file" dataset.blurb = nice_size(dataset.get_size()) else: return super(TwoBit, self).set_peek(dataset)
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary TwoBit format nucleotide file (%s)" % (nice_size(dataset.get_size()))
[docs]@dataproviders.decorators.has_dataproviders class SQlite(Binary): """Class describing a Sqlite database """ MetadataElement(name="tables", default=[], param=ListParameter, desc="Database Tables", readonly=True, visible=True, no_value=[]) MetadataElement(name="table_columns", default={}, param=DictParameter, desc="Database Table Columns", readonly=True, visible=True, no_value={}) MetadataElement(name="table_row_count", default={}, param=DictParameter, desc="Database Table Row Count", readonly=True, visible=True, no_value={}) file_ext = "sqlite" edam_format = "format_3621"
[docs] def init_meta(self, dataset, copy_from=None): Binary.init_meta(self, dataset, copy_from=copy_from)
[docs] def set_meta(self, dataset, overwrite=True, **kwd): try: tables = [] columns = dict() rowcounts = dict() conn = sqlite.connect(dataset.file_name) c = conn.cursor() tables_query = "SELECT name,sql FROM sqlite_master WHERE type='table' ORDER BY name" rslt = c.execute(tables_query).fetchall() for table, _ in rslt: tables.append(table) try: col_query = 'SELECT * FROM %s LIMIT 0' % table cur = conn.cursor().execute(col_query) cols = [col[0] for col in cur.description] columns[table] = cols except Exception as exc: log.warning('%s, set_meta Exception: %s', self, exc) for table in tables: try: row_query = "SELECT count(*) FROM %s" % table rowcounts[table] = c.execute(row_query).fetchone()[0] except Exception as exc: log.warning('%s, set_meta Exception: %s', self, exc) dataset.metadata.tables = tables dataset.metadata.table_columns = columns dataset.metadata.table_row_count = rowcounts except Exception as exc: log.warning('%s, set_meta Exception: %s', self, exc)
[docs] def sniff(self, filename): # The first 16 bytes of any SQLite3 database file is 'SQLite format 3\0', and the file is binary. For details # about the format, see http://www.sqlite.org/fileformat.html try: header = open(filename, 'rb').read(16) if header == b'SQLite format 3\0': return True return False except Exception: return False
[docs] def sniff_table_names(self, filename, table_names): # All table names should be in the schema try: conn = sqlite.connect(filename) c = conn.cursor() tables_query = "SELECT name FROM sqlite_master WHERE type='table' ORDER BY name" result = c.execute(tables_query).fetchall() result = [_[0] for _ in result] for table_name in table_names: if table_name not in result: return False return True except Exception as e: log.warning('%s, sniff Exception: %s', self, e) return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "SQLite Database" lines = ['SQLite Database'] if dataset.metadata.tables: for table in dataset.metadata.tables: try: lines.append('%s [%s]' % (table, dataset.metadata.table_row_count[table])) except Exception: continue dataset.peek = '\n'.join(lines) dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "SQLite Database (%s)" % (nice_size(dataset.get_size()))
[docs] @dataproviders.decorators.dataprovider_factory('sqlite', dataproviders.dataset.SQliteDataProvider.settings) def sqlite_dataprovider(self, dataset, **settings): dataset_source = dataproviders.dataset.DatasetDataProvider(dataset) return dataproviders.dataset.SQliteDataProvider(dataset_source, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('sqlite-table', dataproviders.dataset.SQliteDataTableProvider.settings) def sqlite_datatableprovider(self, dataset, **settings): dataset_source = dataproviders.dataset.DatasetDataProvider(dataset) return dataproviders.dataset.SQliteDataTableProvider(dataset_source, **settings)
[docs] @dataproviders.decorators.dataprovider_factory('sqlite-dict', dataproviders.dataset.SQliteDataDictProvider.settings) def sqlite_datadictprovider(self, dataset, **settings): dataset_source = dataproviders.dataset.DatasetDataProvider(dataset) return dataproviders.dataset.SQliteDataDictProvider(dataset_source, **settings)
[docs]class GeminiSQLite(SQlite): """Class describing a Gemini Sqlite database """ MetadataElement(name="gemini_version", default='0.10.0', param=MetadataParameter, desc="Gemini Version", readonly=True, visible=True, no_value='0.10.0') file_ext = "gemini.sqlite" edam_format = "format_3622" edam_data = "data_3498"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(GeminiSQLite, self).set_meta(dataset, overwrite=overwrite, **kwd) try: conn = sqlite.connect(dataset.file_name) c = conn.cursor() tables_query = "SELECT version FROM version" result = c.execute(tables_query).fetchall() for version, in result: dataset.metadata.gemini_version = version # TODO: Can/should we detect even more attributes, such as use of PED file, what was input annotation type, etc. except Exception as e: log.warning('%s, set_meta Exception: %s', self, e)
[docs] def sniff(self, filename): if super(GeminiSQLite, self).sniff(filename): table_names = ["gene_detailed", "gene_summary", "resources", "sample_genotype_counts", "sample_genotypes", "samples", "variant_impacts", "variants", "version"] return self.sniff_table_names(filename, table_names) return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Gemini SQLite Database, version %s" % (dataset.metadata.gemini_version or 'unknown') dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Gemini SQLite Database, version %s" % (dataset.metadata.gemini_version or 'unknown')
[docs]class CuffDiffSQlite(SQlite): """Class describing a CuffDiff SQLite database """ MetadataElement(name="cuffdiff_version", default='2.2.1', param=MetadataParameter, desc="CuffDiff Version", readonly=True, visible=True, no_value='2.2.1') MetadataElement(name="genes", default=[], param=MetadataParameter, desc="Genes", readonly=True, visible=True, no_value=[]) MetadataElement(name="samples", default=[], param=MetadataParameter, desc="Samples", readonly=True, visible=True, no_value=[]) file_ext = "cuffdiff.sqlite" # TODO: Update this when/if there is a specific EDAM format for CuffDiff SQLite data. edam_format = "format_3621"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(CuffDiffSQlite, self).set_meta(dataset, overwrite=overwrite, **kwd) try: genes = [] samples = [] conn = sqlite.connect(dataset.file_name) c = conn.cursor() tables_query = "SELECT value FROM runInfo where param = 'version'" result = c.execute(tables_query).fetchall() for version, in result: dataset.metadata.cuffdiff_version = version genes_query = 'SELECT gene_id, gene_short_name FROM genes ORDER BY gene_short_name' result = c.execute(genes_query).fetchall() for gene_id, gene_name in result: if gene_name is None: continue gene = '%s: %s' % (gene_id, gene_name) if gene not in genes: genes.append(gene) samples_query = 'SELECT DISTINCT(sample_name) as sample_name FROM samples ORDER BY sample_name' result = c.execute(samples_query).fetchall() for sample_name, in result: if sample_name not in samples: samples.append(sample_name) dataset.metadata.genes = genes dataset.metadata.samples = samples except Exception as e: log.warning('%s, set_meta Exception: %s', self, e)
[docs] def sniff(self, filename): if super(CuffDiffSQlite, self).sniff(filename): # These tables should be in any CuffDiff SQLite output. table_names = ['CDS', 'genes', 'isoforms', 'replicates', 'runInfo', 'samples', 'TSS'] return self.sniff_table_names(filename, table_names) return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "CuffDiff SQLite Database, version %s" % (dataset.metadata.cuffdiff_version or 'unknown') dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "CuffDiff SQLite Database, version %s" % (dataset.metadata.gemini_version or 'unknown')
[docs]class MzSQlite(SQlite): """Class describing a Proteomics Sqlite database """ file_ext = "mz.sqlite"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(MzSQlite, self).set_meta(dataset, overwrite=overwrite, **kwd)
[docs] def sniff(self, filename): if super(MzSQlite, self).sniff(filename): table_names = ["DBSequence", "Modification", "Peaks", "Peptide", "PeptideEvidence", "Score", "SearchDatabase", "Source", "SpectraData", "Spectrum", "SpectrumIdentification"] return self.sniff_table_names(filename, table_names) return False
[docs]class BlibSQlite(SQlite): """Class describing a Proteomics Spectral Library Sqlite database """ MetadataElement(name="blib_version", default='1.8', param=MetadataParameter, desc="Blib Version", readonly=True, visible=True, no_value='1.8') file_ext = "blib"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(BlibSQlite, self).set_meta(dataset, overwrite=overwrite, **kwd) try: conn = sqlite.connect(dataset.file_name) c = conn.cursor() tables_query = "SELECT majorVersion,minorVersion FROM LibInfo" (majorVersion, minorVersion) = c.execute(tables_query).fetchall()[0] dataset.metadata.blib_version = '%s.%s' % (majorVersion, minorVersion) except Exception as e: log.warning('%s, set_meta Exception: %s', self, e)
[docs] def sniff(self, filename): if super(BlibSQlite, self).sniff(filename): table_names = ['IonMobilityTypes', 'LibInfo', 'Modifications', 'RefSpectra', 'RefSpectraPeakAnnotations', 'RefSpectraPeaks', 'ScoreTypes', 'SpectrumSourceFiles'] return self.sniff_table_names(filename, table_names) return False
[docs]class DlibSQlite(SQlite): """ Class describing a Proteomics Spectral Library Sqlite database DLIBs only have the "entries", "metadata", and "peptidetoprotein" tables populated. ELIBs have the rest of the tables populated too, such as "peptidequants" or "peptidescores". >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.dlib') >>> DlibSQlite().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> DlibSQlite().sniff(fname) False """ MetadataElement(name="dlib_version", default='1.8', param=MetadataParameter, desc="Dlib Version", readonly=True, visible=True, no_value='1.8') file_ext = "dlib"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(DlibSQlite, self).set_meta(dataset, overwrite=overwrite, **kwd) try: conn = sqlite.connect(dataset.file_name) c = conn.cursor() tables_query = "SELECT Value FROM metadata WHERE Key = 'version'" version = c.execute(tables_query).fetchall()[0] dataset.metadata.dlib_version = '%s' % (version) except Exception as e: log.warning('%s, set_meta Exception: %s', self, e)
[docs] def sniff(self, filename): if super(DlibSQlite, self).sniff(filename): table_names = ['entries', 'metadata', 'peptidetoprotein'] return self.sniff_table_names(filename, table_names) return False
[docs]class ElibSQlite(SQlite): """ Class describing a Proteomics Chromatagram Library Sqlite database DLIBs only have the "entries", "metadata", and "peptidetoprotein" tables populated. ELIBs have the rest of the tables populated too, such as "peptidequants" or "peptidescores". >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.elib') >>> ElibSQlite().sniff(fname) True >>> fname = get_test_fname('test.dlib') >>> ElibSQlite().sniff(fname) False """ MetadataElement(name="version", default='0.1.14', param=MetadataParameter, desc="Elib Version", readonly=True, visible=True, no_value='0.1.14') file_ext = "elib"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(ElibSQlite, self).set_meta(dataset, overwrite=overwrite, **kwd) try: conn = sqlite.connect(dataset.file_name) c = conn.cursor() tables_query = "SELECT Value FROM metadata WHERE Key = 'version'" version = c.execute(tables_query).fetchall()[0] dataset.metadata.dlib_version = '%s' % (version) except Exception as e: log.warning('%s, set_meta Exception: %s', self, e)
[docs] def sniff(self, filename): if super(ElibSQlite, self).sniff(filename): table_names = ['entries', 'fragmentquants', 'metadata', 'peptidelocalizations', 'peptidequants', 'peptidescores', 'peptidetoprotein', 'proteinscores', 'retentiontimes'] if self.sniff_table_names(filename, table_names): try: conn = sqlite.connect(filename) c = conn.cursor() row_query = "SELECT count(*) FROM peptidescores" count = c.execute(row_query).fetchone()[0] return int(count) > 0 except Exception as e: log.warning('%s, sniff Exception: %s', self, e) return False
[docs]class IdpDB(SQlite): """ Class describing an IDPicker 3 idpDB (sqlite) database >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.idpdb') >>> IdpDB().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> IdpDB().sniff(fname) False """ file_ext = "idpdb"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(IdpDB, self).set_meta(dataset, overwrite=overwrite, **kwd)
[docs] def sniff(self, filename): if super(IdpDB, self).sniff(filename): table_names = ["About", "Analysis", "AnalysisParameter", "PeptideSpectrumMatch", "Spectrum", "SpectrumSource"] return self.sniff_table_names(filename, table_names) return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "IDPickerDB SQLite file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "IDPickerDB SQLite file (%s)" % (nice_size(dataset.get_size()))
[docs]class GAFASQLite(SQlite): """Class describing a GAFA SQLite database""" MetadataElement(name='gafa_schema_version', default='0.3.0', param=MetadataParameter, desc='GAFA schema version', readonly=True, visible=True, no_value='0.3.0') file_ext = 'gafa.sqlite'
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(GAFASQLite, self).set_meta(dataset, overwrite=overwrite, **kwd) try: conn = sqlite.connect(dataset.file_name) c = conn.cursor() version_query = 'SELECT version FROM meta' results = c.execute(version_query).fetchall() if len(results) == 0: raise Exception('version not found in meta table') elif len(results) > 1: raise Exception('Multiple versions found in meta table') dataset.metadata.gafa_schema_version = results[0][0] except Exception as e: log.warning("%s, set_meta Exception: %s", self, e)
[docs] def sniff(self, filename): if super(IdpDB, self).sniff(filename): table_names = frozenset(['gene', 'gene_family', 'gene_family_member', 'meta', 'transcript']) return self.sniff_table_names(filename, table_names) return False
[docs]class Xlsx(Binary): """Class for Excel 2007 (xlsx) files""" file_ext = "xlsx" compressed = True
[docs] def sniff(self, filename): # Xlsx is compressed in zip format and must not be uncompressed in Galaxy. try: if zipfile.is_zipfile(filename): tempzip = zipfile.ZipFile(filename) if "[Content_Types].xml" in tempzip.namelist() and tempzip.read("[Content_Types].xml").find(b'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet.main+xml') != -1: return True return False except Exception: return False
[docs]class ExcelXls(Binary): """Class describing an Excel (xls) file""" file_ext = "excel.xls" edam_format = "format_3468"
[docs] def sniff(self, filename): mime_type = subprocess.check_output(['file', '--mime-type', filename]) return b"application/vnd.ms-excel" in mime_type
[docs] def get_mime(self): """Returns the mime type of the datatype""" return 'application/vnd.ms-excel'
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Microsoft Excel XLS file" dataset.blurb = data.nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Microsoft Excel XLS file (%s)" % (data.nice_size(dataset.get_size()))
[docs]class Sra(Binary): """ Sequence Read Archive (SRA) datatype originally from mdshw5/sra-tools-galaxy""" file_ext = 'sra'
[docs] def sniff(self, filename): """ The first 8 bytes of any NCBI sra file is 'NCBI.sra', and the file is binary. For details about the format, see http://www.ncbi.nlm.nih.gov/books/n/helpsra/SRA_Overview_BK/#SRA_Overview_BK.4_SRA_Data_Structure """ try: header = open(filename, 'rb').read(8) if header == b'NCBI.sra': return True else: return False except Exception: return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = 'Binary sra file' dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return 'Binary sra file (%s)' % (nice_size(dataset.get_size()))
[docs]class RData(Binary): """Generic R Data file datatype implementation""" file_ext = 'rdata'
[docs] def sniff(self, filename): rdata_header = b'RDX2\nX\n' try: header = open(filename, 'rb').read(7) if header == rdata_header: return True header = gzip.open(filename).read(7) if header == rdata_header: return True except Exception: return False
[docs]class OxliBinary(Binary): @staticmethod def _sniff(filename, oxlitype): try: with open(filename, 'rb') as fileobj: header = fileobj.read(4) if header == b'OXLI': fileobj.read(1) # skip the version number ftype = fileobj.read(1) if binascii.hexlify(ftype) == oxlitype: return True return False except IOError: return False
[docs]class OxliCountGraph(OxliBinary): """ OxliCountGraph starts with "OXLI" + one byte version number + 8-bit binary '1' Test file generated via:: load-into-counting.py --n_tables 1 --max-tablesize 1 \\ oxli_countgraph.oxlicg khmer/tests/test-data/100-reads.fq.bz2 using khmer 2.0 >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('sequence.csfasta') >>> OxliCountGraph().sniff(fname) False >>> fname = get_test_fname("oxli_countgraph.oxlicg") >>> OxliCountGraph().sniff(fname) True """ file_ext = 'oxlicg'
[docs] def sniff(self, filename): return OxliBinary._sniff(filename, b"01")
[docs]class OxliNodeGraph(OxliBinary): """ OxliNodeGraph starts with "OXLI" + one byte version number + 8-bit binary '2' Test file generated via:: load-graph.py --n_tables 1 --max-tablesize 1 oxli_nodegraph.oxling \\ khmer/tests/test-data/100-reads.fq.bz2 using khmer 2.0 >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('sequence.csfasta') >>> OxliNodeGraph().sniff(fname) False >>> fname = get_test_fname("oxli_nodegraph.oxling") >>> OxliNodeGraph().sniff(fname) True """ file_ext = 'oxling'
[docs] def sniff(self, filename): return OxliBinary._sniff(filename, b"02")
[docs]class OxliTagSet(OxliBinary): """ OxliTagSet starts with "OXLI" + one byte version number + 8-bit binary '3' Test file generated via:: load-graph.py --n_tables 1 --max-tablesize 1 oxli_nodegraph.oxling \\ khmer/tests/test-data/100-reads.fq.bz2; mv oxli_nodegraph.oxling.tagset oxli_tagset.oxlits using khmer 2.0 >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('sequence.csfasta') >>> OxliTagSet().sniff(fname) False >>> fname = get_test_fname("oxli_tagset.oxlits") >>> OxliTagSet().sniff(fname) True """ file_ext = 'oxlits'
[docs] def sniff(self, filename): return OxliBinary._sniff(filename, b"03")
[docs]class OxliStopTags(OxliBinary): """ OxliStopTags starts with "OXLI" + one byte version number + 8-bit binary '4' Test file adapted from khmer 2.0's "khmer/tests/test-data/goodversion-k32.stoptags" >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('sequence.csfasta') >>> OxliStopTags().sniff(fname) False >>> fname = get_test_fname("oxli_stoptags.oxlist") >>> OxliStopTags().sniff(fname) True """ file_ext = 'oxlist'
[docs] def sniff(self, filename): return OxliBinary._sniff(filename, b"04")
[docs]class OxliSubset(OxliBinary): """ OxliSubset starts with "OXLI" + one byte version number + 8-bit binary '5' Test file generated via:: load-graph.py -k 20 example tests/test-data/random-20-a.fa; partition-graph.py example; mv example.subset.0.pmap oxli_subset.oxliss using khmer 2.0 >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('sequence.csfasta') >>> OxliSubset().sniff(fname) False >>> fname = get_test_fname("oxli_subset.oxliss") >>> OxliSubset().sniff(fname) True """ file_ext = 'oxliss'
[docs] def sniff(self, filename): return OxliBinary._sniff(filename, b"05")
[docs]class OxliGraphLabels(OxliBinary): """ OxliGraphLabels starts with "OXLI" + one byte version number + 8-bit binary '6' Test file generated via:: python -c "from khmer import GraphLabels; \\ gl = GraphLabels(20, 1e7, 4); \\ gl.consume_fasta_and_tag_with_labels('tests/test-data/test-labels.fa'); \\ gl.save_labels_and_tags('oxli_graphlabels.oxligl')" using khmer 2.0 >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('sequence.csfasta') >>> OxliGraphLabels().sniff(fname) False >>> fname = get_test_fname("oxli_graphlabels.oxligl") >>> OxliGraphLabels().sniff(fname) True """ file_ext = 'oxligl'
[docs] def sniff(self, filename): return OxliBinary._sniff(filename, b"06")
[docs]class PostgresqlArchive(CompressedArchive): """ Class describing a Postgresql database packed into a tar archive >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('postgresql_fake.tar.bz2') >>> PostgresqlArchive().sniff(fname) True >>> fname = get_test_fname('test.fast5.tar') >>> PostgresqlArchive().sniff(fname) False """ MetadataElement(name="version", default=None, param=MetadataParameter, desc="PostgreSQL database version", readonly=True, visible=True, no_value=None) file_ext = "postgresql"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(PostgresqlArchive, self).set_meta(dataset, overwrite=overwrite, **kwd) try: if dataset and tarfile.is_tarfile(dataset.file_name): with tarfile.open(dataset.file_name, 'r') as temptar: pg_version_file = temptar.extractfile('postgresql/db/PG_VERSION') dataset.metadata.version = util.unicodify(pg_version_file.read()).strip() except Exception as e: log.warning('%s, set_meta Exception: %s', self, util.unicodify(e))
[docs] def sniff(self, filename): if filename and tarfile.is_tarfile(filename): with tarfile.open(filename, 'r') as temptar: return 'postgresql/db/PG_VERSION' in temptar.getnames() return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "PostgreSQL Archive (%s)" % (nice_size(dataset.get_size())) dataset.blurb = "PostgreSQL version %s" % (dataset.metadata.version or 'unknown') else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "PostgreSQL Archive (%s)" % (nice_size(dataset.get_size()))
[docs]class Fast5Archive(CompressedArchive): """ Class describing a FAST5 archive >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.fast5.tar') >>> Fast5Archive().sniff(fname) True """ MetadataElement(name="fast5_count", default='0', param=MetadataParameter, desc="Read Count", readonly=True, visible=True, no_value=None) file_ext = "fast5.tar"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(Fast5Archive, self).set_meta(dataset, overwrite=overwrite, **kwd) try: if dataset and tarfile.is_tarfile(dataset.file_name): with tarfile.open(dataset.file_name, 'r') as temptar: dataset.metadata.fast5_count = sum( 1 for f in temptar if f.name.endswith('.fast5') ) except Exception as e: log.warning('%s, set_meta Exception: %s', self, e)
[docs] def sniff(self, filename): try: if filename and tarfile.is_tarfile(filename): with tarfile.open(filename, 'r') as temptar: for f in temptar: if not f.isfile(): continue if f.name.endswith('.fast5'): return True else: return False except Exception as e: log.warning('%s, sniff Exception: %s', self, e) return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "FAST5 Archive (%s)" % (nice_size(dataset.get_size())) dataset.blurb = "%s sequences" % (dataset.metadata.fast5_count or 'unknown') else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "FAST5 Archive (%s)" % (nice_size(dataset.get_size()))
[docs]class Fast5ArchiveGz(Fast5Archive): """ Class describing a gzip-compressed FAST5 archive >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.fast5.tar.gz') >>> Fast5ArchiveGz().sniff(fname) True >>> fname = get_test_fname('test.fast5.tar.bz2') >>> Fast5ArchiveGz().sniff(fname) False >>> fname = get_test_fname('test.fast5.tar') >>> Fast5ArchiveGz().sniff(fname) False """ file_ext = "fast5.tar.gz"
[docs] def sniff(self, filename): if not is_gzip(filename): return False return Fast5Archive.sniff(self, filename)
[docs]class Fast5ArchiveBz2(Fast5Archive): """ Class describing a bzip2-compressed FAST5 archive >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.fast5.tar.bz2') >>> Fast5ArchiveBz2().sniff(fname) True >>> fname = get_test_fname('test.fast5.tar.gz') >>> Fast5ArchiveBz2().sniff(fname) False >>> fname = get_test_fname('test.fast5.tar') >>> Fast5ArchiveBz2().sniff(fname) False """ file_ext = "fast5.tar.bz2"
[docs] def sniff(self, filename): if not is_bz2(filename): return False return Fast5Archive.sniff(self, filename)
[docs]class SearchGuiArchive(CompressedArchive): """Class describing a SearchGUI archive """ MetadataElement(name="searchgui_version", default='1.28.0', param=MetadataParameter, desc="SearchGui Version", readonly=True, visible=True, no_value=None) MetadataElement(name="searchgui_major_version", default='1', param=MetadataParameter, desc="SearchGui Major Version", readonly=True, visible=True, no_value=None) file_ext = "searchgui_archive"
[docs] def set_meta(self, dataset, overwrite=True, **kwd): super(SearchGuiArchive, self).set_meta(dataset, overwrite=overwrite, **kwd) try: if dataset and zipfile.is_zipfile(dataset.file_name): with zipfile.ZipFile(dataset.file_name) as tempzip: if 'searchgui.properties' in tempzip.namelist(): with tempzip.open('searchgui.properties') as fh: for line in io.TextIOWrapper(fh): if line.startswith('searchgui.version'): version = line.split('=')[1].strip() dataset.metadata.searchgui_version = version dataset.metadata.searchgui_major_version = version.split('.')[0] except Exception as e: log.warning('%s, set_meta Exception: %s', self, e)
[docs] def sniff(self, filename): try: if filename and zipfile.is_zipfile(filename): with zipfile.ZipFile(filename, 'r') as tempzip: is_searchgui = 'searchgui.properties' in tempzip.namelist() return is_searchgui except Exception as e: log.warning('%s, sniff Exception: %s', self, e) return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "SearchGUI Archive, version %s" % (dataset.metadata.searchgui_version or 'unknown') dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "SearchGUI Archive, version %s" % (dataset.metadata.searchgui_version or 'unknown')
[docs]class NetCDF(Binary): """Binary data in netCDF format""" file_ext = "netcdf" edam_format = "format_3650" edam_data = "data_0943"
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary netCDF file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary netCDF file (%s)" % (nice_size(dataset.get_size()))
[docs] def sniff(self, filename): try: with open(filename, 'rb') as f: header = f.read(3) if header == b'CDF': return True return False except Exception: return False
[docs]class Dcd(Binary): """ Class describing a dcd file from the CHARMM molecular simulation program >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test_glucose_vacuum.dcd') >>> Dcd().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> Dcd().sniff(fname) False """ file_ext = "dcd" edam_data = "data_3842"
[docs] def __init__(self, **kwd): Binary.__init__(self, **kwd) self._magic_number = b'CORD'
[docs] def sniff(self, filename): # Match the keyword 'CORD' at position 4 or 8 - intsize dependent # Not checking for endianness try: with open(filename, 'rb') as header: intsize = 4 header.seek(intsize) if header.read(intsize) == self._magic_number: return True else: intsize = 8 header.seek(intsize) if header.read(intsize) == self._magic_number: return True return False except Exception: return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary CHARMM/NAMD dcd file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary CHARMM/NAMD dcd file (%s)" % (nice_size(dataset.get_size()))
[docs]class Vel(Binary): """ Class describing a velocity file from the CHARMM molecular simulation program >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test_charmm.vel') >>> Vel().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> Vel().sniff(fname) False """ file_ext = "vel"
[docs] def __init__(self, **kwd): Binary.__init__(self, **kwd) self._magic_number = b'VELD'
[docs] def sniff(self, filename): # Match the keyword 'VELD' at position 4 or 8 - intsize dependent # Not checking for endianness try: with open(filename, 'rb') as header: intsize = 4 header.seek(intsize) if header.read(intsize) == self._magic_number: return True else: intsize = 8 header.seek(intsize) if header.read(intsize) == self._magic_number: return True return False except Exception: return False
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary CHARMM velocity file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "Binary CHARMM velocity file (%s)" % (nice_size(dataset.get_size()))
[docs]class DAA(Binary): """ Class describing an DAA (diamond alignment archive) file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('diamond.daa') >>> DAA().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> DAA().sniff(fname) False """ file_ext = "daa"
[docs] def __init__(self, **kwd): Binary.__init__(self, **kwd) self._magic = binascii.unhexlify("6be33e6d47530e3c")
[docs] def sniff(self, filename): # The first 8 bytes of any daa file are 0x3c0e53476d3ee36b with open(filename, 'rb') as f: return f.read(8) == self._magic
[docs]class RMA6(Binary): """ Class describing an RMA6 (MEGAN6 read-match archive) file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('diamond.rma6') >>> RMA6().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> RMA6().sniff(fname) False """ file_ext = "rma6"
[docs] def __init__(self, **kwd): Binary.__init__(self, **kwd) self._magic = binascii.unhexlify("000003f600000006")
[docs] def sniff(self, filename): # The first 8 bytes of any daa file are 0x3c0e53476d3ee36b with open(filename, 'rb') as f: return f.read(8) == self._magic
[docs]class DMND(Binary): """ Class describing an DMND file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('diamond_db.dmnd') >>> DMND().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> DMND().sniff(fname) False """ file_ext = "dmnd"
[docs] def __init__(self, **kwd): Binary.__init__(self, **kwd) self._magic = binascii.unhexlify("6d18ee15a4f84a02")
[docs] def sniff(self, filename): # The first 8 bytes of any dmnd file are 0x24af8a415ee186d with open(filename, 'rb') as f: return f.read(8) == self._magic
[docs]class ICM(Binary): """ Class describing an ICM (interpolated context model) file, used by Glimmer """ file_ext = "icm" edam_data = "data_0950"
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = "Binary ICM (interpolated context model) file" dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def sniff(self, dataset): line = open(dataset).read(100) if '>ver = ' in line and 'len = ' in line and 'depth = ' in line and 'periodicity =' in line and 'nodes = ' in line: return True return False
[docs]class BafTar(CompressedArchive): """ Base class for common behavior of tar files of directory-based raw file formats >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('brukerbaf.d.tar') >>> BafTar().sniff(fname) True >>> fname = get_test_fname('test.fast5.tar') >>> BafTar().sniff(fname) False """ edam_data = "data_2536" # mass spectrometry data edam_format = "format_3712" # TODO: add more raw formats to EDAM? file_ext = "brukerbaf.d.tar"
[docs] def get_signature_file(self): return "analysis.baf"
[docs] def sniff(self, filename): if tarfile.is_tarfile(filename): with tarfile.open(filename) as rawtar: return self.get_signature_file() in [os.path.basename(f).lower() for f in rawtar.getnames()] return False
[docs] def get_type(self): return "Bruker BAF directory archive"
[docs] def set_peek(self, dataset, is_multi_byte=False): if not dataset.dataset.purged: dataset.peek = self.get_type() dataset.blurb = nice_size(dataset.get_size()) else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def display_peek(self, dataset): try: return dataset.peek except Exception: return "%s (%s)" % (self.get_type(), nice_size(dataset.get_size()))
[docs]class YepTar(BafTar): """ A tar'd up .d directory containing Agilent/Bruker YEP format data """ file_ext = "agilentbrukeryep.d.tar"
[docs] def get_signature_file(self): return "analysis.yep"
[docs] def get_type(self): return "Agilent/Bruker YEP directory archive"
[docs]class TdfTar(BafTar): """ A tar'd up .d directory containing Bruker TDF format data """ file_ext = "brukertdf.d.tar"
[docs] def get_signature_file(self): return "analysis.tdf"
[docs] def get_type(self): return "Bruker TDF directory archive"
[docs]class MassHunterTar(BafTar): """ A tar'd up .d directory containing Agilent MassHunter format data """ file_ext = "agilentmasshunter.d.tar"
[docs] def get_signature_file(self): return "msscan.bin"
[docs] def get_type(self): return "Agilent MassHunter directory archive"
[docs]class MassLynxTar(BafTar): """ A tar'd up .d directory containing Waters MassLynx format data """ file_ext = "watersmasslynx.raw.tar"
[docs] def get_signature_file(self): return "_func001.dat"
[docs] def get_type(self): return "Waters MassLynx RAW directory archive"
[docs]class WiffTar(BafTar): """ A tar'd up .wiff/.scan pair containing Sciex WIFF format data >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('some.wiff.tar') >>> WiffTar().sniff(fname) True >>> fname = get_test_fname('brukerbaf.d.tar') >>> WiffTar().sniff(fname) False >>> fname = get_test_fname('test.fast5.tar') >>> WiffTar().sniff(fname) False """ file_ext = "wiff.tar"
[docs] def sniff(self, filename): if tarfile.is_tarfile(filename): with tarfile.open(filename) as rawtar: return ".wiff" in [os.path.splitext(os.path.basename(f).lower())[1] for f in rawtar.getnames()] return False
[docs] def get_type(self): return "Sciex WIFF/SCAN archive"
if __name__ == '__main__': import doctest doctest.testmod(sys.modules[__name__])