Warning
This document is for an old release of Galaxy. You can alternatively view this page in the latest release if it exists or view the top of the latest release's documentation.
galaxy.datatypes package
Subpackages
- galaxy.datatypes.converters package
- Submodules
- galaxy.datatypes.converters.bed_to_gff_converter module
- galaxy.datatypes.converters.bgzip module
- galaxy.datatypes.converters.cram_to_bam module
- galaxy.datatypes.converters.fasta_to_len module
- galaxy.datatypes.converters.fasta_to_tabular_converter module
- galaxy.datatypes.converters.fastq_to_fqtoc module
- galaxy.datatypes.converters.fastqsolexa_to_fasta_converter module
- galaxy.datatypes.converters.fastqsolexa_to_qual_converter module
- galaxy.datatypes.converters.gff_to_bed_converter module
- galaxy.datatypes.converters.gff_to_interval_index_converter module
- galaxy.datatypes.converters.interval_to_bed_converter module
- galaxy.datatypes.converters.interval_to_bedstrict_converter module
- galaxy.datatypes.converters.interval_to_fli module
- galaxy.datatypes.converters.interval_to_interval_index_converter module
- galaxy.datatypes.converters.interval_to_tabix_converter module
- galaxy.datatypes.converters.lped_to_fped_converter module
- galaxy.datatypes.converters.lped_to_pbed_converter module
- galaxy.datatypes.converters.maf_to_fasta_converter module
- galaxy.datatypes.converters.maf_to_interval_converter module
- galaxy.datatypes.converters.parquet_to_csv_converter module
- galaxy.datatypes.converters.pbed_ldreduced_converter module
- galaxy.datatypes.converters.pbed_to_lped_converter module
- galaxy.datatypes.converters.picard_interval_list_to_bed6_converter module
- galaxy.datatypes.converters.pileup_to_interval_index_converter module
- galaxy.datatypes.converters.ref_to_seq_taxonomy_converter module
- galaxy.datatypes.converters.tabular_csv module
- galaxy.datatypes.converters.tabular_to_dbnsfp module
- galaxy.datatypes.converters.vcf_to_interval_index_converter module
- galaxy.datatypes.converters.vcf_to_vcf_bgzip module
- galaxy.datatypes.converters.wiggle_to_simple_converter module
- galaxy.datatypes.dataproviders package
- Submodules
- galaxy.datatypes.dataproviders.base module
- galaxy.datatypes.dataproviders.chunk module
- galaxy.datatypes.dataproviders.column module
ColumnarDataProvider
ColumnarDataProvider.settings
ColumnarDataProvider.__init__()
ColumnarDataProvider.parse_filter()
ColumnarDataProvider.create_numeric_filter()
ColumnarDataProvider.create_string_filter()
ColumnarDataProvider.create_list_filter()
ColumnarDataProvider.get_default_parsers()
ColumnarDataProvider.filter()
ColumnarDataProvider.parse_columns_from_line()
ColumnarDataProvider.parse_column_at_index()
ColumnarDataProvider.parse_value()
ColumnarDataProvider.get_column_type()
ColumnarDataProvider.filter_by_columns()
DictDataProvider
- galaxy.datatypes.dataproviders.dataset module
DatasetDataProvider
DatasetDataProvider.__init__()
DatasetDataProvider.get_column_metadata_from_dataset()
DatasetDataProvider.get_metadata_column_types()
DatasetDataProvider.get_metadata_column_names()
DatasetDataProvider.get_indeces_by_column_names()
DatasetDataProvider.get_metadata_column_index_by_name()
DatasetDataProvider.get_genomic_region_indeces()
DatasetDataProvider.settings
ConvertedDatasetDataProvider
DatasetColumnarDataProvider
DatasetDictDataProvider
GenomicRegionDataProvider
IntervalDataProvider
FastaDataProvider
TwoBitFastaDataProvider
WiggleDataProvider
BigWigDataProvider
DatasetSubprocessDataProvider
SamtoolsDataProvider
SQliteDataProvider
SQliteDataTableProvider
SQliteDataDictProvider
- galaxy.datatypes.dataproviders.decorators module
- galaxy.datatypes.dataproviders.exceptions module
- galaxy.datatypes.dataproviders.external module
- galaxy.datatypes.dataproviders.hierarchy module
- galaxy.datatypes.dataproviders.line module
FilteredLineDataProvider
RegexLineDataProvider
BlockDataProvider
BlockDataProvider.__init__()
BlockDataProvider.init_new_block()
BlockDataProvider.filter()
BlockDataProvider.is_new_block()
BlockDataProvider.add_line_to_block()
BlockDataProvider.assemble_current_block()
BlockDataProvider.filter_block()
BlockDataProvider.handle_last_block()
BlockDataProvider.settings
- galaxy.datatypes.display_applications package
- Submodules
- galaxy.datatypes.display_applications.application module
quote_plus_string()
DisplayApplicationLink
DynamicDisplayApplicationBuilder
PopulatedDisplayApplicationLink
PopulatedDisplayApplicationLink.__init__()
PopulatedDisplayApplicationLink.display_ready()
PopulatedDisplayApplicationLink.get_param_value()
PopulatedDisplayApplicationLink.preparing_display()
PopulatedDisplayApplicationLink.prepare_display()
PopulatedDisplayApplicationLink.get_prepare_steps()
PopulatedDisplayApplicationLink.display_url()
PopulatedDisplayApplicationLink.get_param_name_by_url()
PopulatedDisplayApplicationLink.allow_cors
DisplayApplication
- galaxy.datatypes.display_applications.parameters module
DisplayApplicationParameter
DisplayApplicationParameter.type
DisplayApplicationParameter.from_elem()
DisplayApplicationParameter.__init__()
DisplayApplicationParameter.get_value()
DisplayApplicationParameter.prepare()
DisplayApplicationParameter.ready()
DisplayApplicationParameter.is_preparing()
DisplayApplicationParameter.build_url()
DatasetLikeObject
DisplayApplicationDataParameter
DisplayApplicationDataParameter.type
DisplayApplicationDataParameter.__init__()
DisplayApplicationDataParameter.datatypes_registry
DisplayApplicationDataParameter.formats
DisplayApplicationDataParameter.get_value()
DisplayApplicationDataParameter.prepare()
DisplayApplicationDataParameter.is_preparing()
DisplayApplicationDataParameter.ready()
DisplayApplicationTemplateParameter
DisplayParameterValueWrapper
DisplayDataValueWrapper
- galaxy.datatypes.display_applications.util module
- galaxy.datatypes.util package
- Submodules
- galaxy.datatypes.util.generic_util module
- galaxy.datatypes.util.gff_util module
- galaxy.datatypes.util.maf_utilities module
maketrans()
src_split()
src_merge()
get_species_in_block()
tool_fail()
TempFileHandler
RegionAlignment
RegionAlignment.DNA_COMPLEMENT
RegionAlignment.MAX_SEQUENCE_SIZE
RegionAlignment.__init__()
RegionAlignment.add_species()
RegionAlignment.get_species_names()
RegionAlignment.get_sequence()
RegionAlignment.get_sequence_reverse_complement()
RegionAlignment.set_position()
RegionAlignment.set_range()
RegionAlignment.flush()
GenomicRegionAlignment
SplicedAlignment
maf_index_by_uid()
open_or_build_maf_index()
build_maf_index_species_chromosomes()
build_maf_index()
component_overlaps_region()
chop_block_by_region()
orient_block_by_region()
get_oriented_chopped_blocks_for_region()
get_oriented_chopped_blocks_with_index_offset_for_region()
iter_blocks_split_by_src()
iter_blocks_split_by_species()
get_chopped_blocks_for_region()
get_chopped_blocks_with_index_offset_for_region()
get_region_alignment()
reduce_block_by_primary_genome()
fill_region_alignment()
get_spliced_region_alignment()
line_enumerator()
get_starts_ends_fields_from_gene_bed()
iter_components_by_src()
get_components_by_src()
iter_components_by_src_start()
get_components_by_src_start()
sort_block_components_by_block()
get_species_in_maf()
parse_species_option()
remove_temp_index_file()
get_fasta_header()
get_attributes_from_fasta_header()
iter_fasta_alignment()
Submodules
galaxy.datatypes.annotation module
- class galaxy.datatypes.annotation.SnapHmm(**kwd)[source]
Bases:
Text
- file_ext = 'snaphmm'
- edam_data = 'data_1364'
- set_peek(dataset: DatasetProtocol, **kwd) None [source]
Set the peek. This method is used by various subclasses of Text.
- sniff_prefix(file_prefix: FilePrefix) bool [source]
SNAP model files start with zoeHMM
- metadata_spec: MetadataSpecCollection = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.annotation.Augustus(**kwd)[source]
Bases:
CompressedArchive
Class describing an Augustus prediction model
- file_ext = 'augustus'
- edam_data = 'data_0950'
- compressed = True
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
galaxy.datatypes.anvio module
Datatypes for Anvi’o https://github.com/merenlab/anvio
- class galaxy.datatypes.anvio.AnvioComposite(**kwd)[source]
Bases:
Html
Base class to use for Anvi’o composite datatypes. Generally consist of a sqlite database, plus optional additional files
- file_ext = 'anvio_composite'
- generate_primary_file(dataset: HasExtraFilesAndMetadata) str [source]
This is called only at upload to write the html file cannot rename the datasets here - they come with the default unfortunately
- metadata_spec: MetadataSpecCollection = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.anvio.AnvioDB(*args, **kwd)[source]
Bases:
AnvioComposite
Class for AnvioDB database files.
- file_ext = 'anvio_db'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Set the anvio_basename based upon actual extra_files_path contents.
- metadata_spec: metadata.MetadataSpecCollection = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.anvio.AnvioStructureDB(*args, **kwd)[source]
Bases:
AnvioDB
Class for Anvio Structure DB database files.
- file_ext = 'anvio_structure_db'
- metadata_spec: metadata.MetadataSpecCollection = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.anvio.AnvioGenomesDB(*args, **kwd)[source]
Bases:
AnvioDB
Class for Anvio Genomes DB database files.
- file_ext = 'anvio_genomes_db'
- metadata_spec: metadata.MetadataSpecCollection = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.anvio.AnvioContigsDB(*args, **kwd)[source]
Bases:
AnvioDB
Class for Anvio Contigs DB database files.
- file_ext = 'anvio_contigs_db'
- metadata_spec: metadata.MetadataSpecCollection = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.anvio.AnvioProfileDB(*args, **kwd)[source]
Bases:
AnvioDB
Class for Anvio Profile DB database files.
- file_ext = 'anvio_profile_db'
- metadata_spec: metadata.MetadataSpecCollection = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.anvio.AnvioPanDB(*args, **kwd)[source]
Bases:
AnvioDB
Class for Anvio Pan DB database files.
- file_ext = 'anvio_pan_db'
- metadata_spec: metadata.MetadataSpecCollection = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.anvio.AnvioSamplesDB(*args, **kwd)[source]
Bases:
AnvioDB
Class for Anvio Samples DB database files.
- file_ext = 'anvio_samples_db'
- metadata_spec: metadata.MetadataSpecCollection = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
galaxy.datatypes.assembly module
velvet datatypes James E Johnson - University of Minnesota for velvet assembler tool in galaxy
- class galaxy.datatypes.assembly.Amos(**kwd)[source]
Bases:
Text
Class describing the AMOS assembly file
- edam_data = 'data_0925'
- edam_format = 'format_3582'
- file_ext = 'afg'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
Determines whether the file is an amos assembly file format Example:
{CTG iid:1 eid:1 seq: CCTCTCCTGTAGAGTTCAACCGA-GCCGGTAGAGTTTTATCA . qlt: DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD . {TLE src:1027 off:0 clr:618,0 gap: 250 612 . } }
- metadata_spec: MetadataSpecCollection = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.assembly.Sequences(**kwd)[source]
Bases:
Fasta
Class describing the Sequences file generated by velveth
- edam_data = 'data_0925'
- file_ext = 'sequences'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
Determines whether the file is a velveth produced fasta format The id line has 3 fields separated by tabs: sequence_name sequence_index category:
>SEQUENCE_0_length_35 1 1 GGATATAGGGCCAACCCAACTCAACGGCCTGTCTT >SEQUENCE_1_length_35 2 1 CGACGAATGACAGGTCACGAATTTGGCGGGGATTA
- metadata_spec: MetadataSpecCollection = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'sequences': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.assembly.Roadmaps(**kwd)[source]
Bases:
Text
Class describing the Sequences file generated by velveth
- edam_format = 'format_2561'
- file_ext = 'roadmaps'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- Determines whether the file is a velveth produced RoadMap::
142858 21 1 ROADMAP 1 ROADMAP 2 …
- metadata_spec: MetadataSpecCollection = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.assembly.Velvet(**kwd)[source]
Bases:
Html
- file_ext = 'velvet'
- regenerate_primary_file(dataset: DatasetProtocol) None [source]
cannot do this until we are setting metadata
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Set the number of lines of data in dataset.
- metadata_spec: MetadataSpecCollection = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'long_reads': <galaxy.model.metadata.MetadataElementSpec object>, 'paired_end_reads': <galaxy.model.metadata.MetadataElementSpec object>, 'short2_reads': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
galaxy.datatypes.binary module
Binary classes
- class galaxy.datatypes.binary.Binary(**kwd)[source]
Bases:
Data
Binary data
- edam_format = 'format_2333'
- file_ext = 'binary'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Ab1(**kwd)[source]
Bases:
Binary
Class describing an ab1 binary sequence file
- file_ext = 'ab1'
- edam_format = 'format_3000'
- edam_data = 'data_0924'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Idat(**kwd)[source]
Bases:
Binary
Binary data in idat format
- file_ext = 'idat'
- edam_format = 'format_2058'
- edam_data = 'data_2603'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Cel(**kwd)[source]
Bases:
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'
- sniff(filename: str) bool [source]
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
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Set metadata for Cel file.
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.MashSketch(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.CompressedArchive(**kwd)[source]
Bases:
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
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Meryldb(**kwd)[source]
Bases:
CompressedArchive
MerylDB is a tar.gz archive, with 128 files. 64 data files and 64 index files.
- file_ext = 'meryldb'
- sniff(filename: str) bool [source]
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') >>> Meryldb().sniff(fname) False >>> fname = get_test_fname('read-db.meryldb') >>> Meryldb().sniff(fname) True
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Visium(**kwd)[source]
Bases:
CompressedArchive
Visium is a tar.gz archive with at least a ‘Spatial’ subfolder, a filtered h5 file and a raw h5 file.
- file_ext = 'visium.tar.gz'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Bref3(**kwd)[source]
Bases:
Binary
Bref3 format is a binary format for storing phased, non-missing genotypes for a list of samples.
- file_ext = 'bref3'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.DynamicCompressedArchive(**kwd)[source]
Bases:
CompressedArchive
- matches_any(target_datatypes: List[Any]) bool [source]
Treat two aspects of compressed datatypes separately.
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.GzDynamicCompressedArchive(**kwd)[source]
Bases:
DynamicCompressedArchive
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Bz2DynamicCompressedArchive(**kwd)[source]
Bases:
DynamicCompressedArchive
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.CompressedZipArchive(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.GenericAsn1Binary(**kwd)[source]
Bases:
Binary
Class for generic ASN.1 binary format
- file_ext = 'asn1-binary'
- edam_format = 'format_1966'
- edam_data = 'data_0849'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.BamNative(**kwd)[source]
Bases:
CompressedArchive
,_BamOrSam
Class describing a BAM binary file that is not necessarily sorted
- edam_format = 'format_2572'
- edam_data = 'data_0863'
- file_ext = 'unsorted.bam'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- static merge(split_files: List[str], output_file: str) None [source]
Merges BAM files
- Parameters:
split_files – List of bam file paths to merge
output_file – Write merged bam file to this location
- to_archive(dataset: DatasetProtocol, name: str = '') Iterable [source]
Collect archive paths and file handles that need to be exported when archiving dataset.
- Parameters:
dataset – HistoryDatasetAssociation
name – archive name, in collection context corresponds to collection name(s) and element_identifier, joined by ‘/’, e.g ‘fastq_collection/sample1/forward’
- groom_dataset_content(file_name: str) None [source]
Ensures that the BAM file contents are coordinate-sorted. This function is called on an output dataset after the content is initially generated.
- display_data(trans, dataset: DatasetHasHidProtocol, preview: bool = False, filename: str | None = None, to_ext: str | None = None, offset: int | None = None, ck_size: int | None = None, **kwd)[source]
Displays data in central pane if preview is True, else handles download.
Datatypes should be very careful if overriding this method and this interface between datatypes and Galaxy will likely change.
TODO: Document alternatives to overriding this method (data providers?).
- validate(dataset: DatasetProtocol, **kwd) DatatypeValidation [source]
- metadata_spec: metadata.MetadataSpecCollection = {'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Bam(**kwd)[source]
Bases:
BamNative
Class describing a BAM binary file
- edam_format = 'format_2572'
- edam_data = 'data_0863'
- file_ext = 'bam'
- get_index_flag(file_name: str) str [source]
Return pysam flag for bai index (default) or csi index (contig size > (2**29 - 1) )
- dataset_content_needs_grooming(file_name: str) bool [source]
Check if file_name is a coordinate-sorted BAM file
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, metadata_tmp_files_dir: str | None = None, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- line_dataprovider(dataset: DatasetProtocol, **settings) FilteredLineDataProvider [source]
- regex_line_dataprovider(dataset: DatasetProtocol, **settings) RegexLineDataProvider [source]
- column_dataprovider(dataset: DatasetProtocol, **settings) ColumnarDataProvider [source]
- dict_dataprovider(dataset: DatasetProtocol, **settings) DictDataProvider [source]
- header_dataprovider(dataset: DatasetProtocol, **settings) RegexLineDataProvider [source]
- id_seq_qual_dataprovider(dataset: DatasetProtocol, **settings) DictDataProvider [source]
- genomic_region_dataprovider(dataset: DatasetProtocol, **settings) ColumnarDataProvider [source]
- genomic_region_dict_dataprovider(dataset: DatasetProtocol, **settings) DictDataProvider [source]
- samtools_dataprovider(dataset: DatasetProtocol, **settings) SamtoolsDataProvider [source]
Generic samtools interface - all options available through settings.
- dataproviders: Dict[str, Any] = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'column': <function Bam.column_dataprovider>, 'dict': <function Bam.dict_dataprovider>, 'genomic-region': <function Bam.genomic_region_dataprovider>, 'genomic-region-dict': <function Bam.genomic_region_dict_dataprovider>, 'header': <function Bam.header_dataprovider>, 'id-seq-qual': <function Bam.id_seq_qual_dataprovider>, 'line': <function Bam.line_dataprovider>, 'regex-line': <function Bam.regex_line_dataprovider>, 'samtools': <function Bam.samtools_dataprovider>}
- metadata_spec: metadata.MetadataSpecCollection = {'bam_csi_index': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_index': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.ProBam(**kwd)[source]
Bases:
Bam
Class describing a BAM binary file - extended for proteomics data
- edam_format = 'format_3826'
- edam_data = 'data_0863'
- file_ext = 'probam'
- metadata_spec: metadata.MetadataSpecCollection = {'bam_csi_index': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_index': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.BamInputSorted(**kwd)[source]
Bases:
BamNative
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.
- file_ext = 'qname_input_sorted.bam'
- dataset_content_needs_grooming(file_name: str) bool [source]
Groom if the file is coordinate sorted
- metadata_spec: metadata.MetadataSpecCollection = {'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.BamQuerynameSorted(**kwd)[source]
Bases:
BamInputSorted
A class for queryname sorted BAM files.
- file_ext = 'qname_sorted.bam'
- dataset_content_needs_grooming(file_name: str) bool [source]
Check if file_name is a queryname-sorted BAM file
- metadata_spec: metadata.MetadataSpecCollection = {'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.CRAM(**kwd)[source]
Bases:
Binary
- file_ext = 'cram'
- edam_format = 'format_3462'
- edam_data = 'data_0863'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, metadata_tmp_files_dir: str | None = None, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'cram_index': <galaxy.model.metadata.MetadataElementSpec object>, 'cram_version': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.BaseBcf(**kwd)[source]
Bases:
CompressedArchive
- edam_format = 'format_3020'
- edam_data = 'data_3498'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Bcf(**kwd)[source]
Bases:
BaseBcf
Class describing a (BGZF-compressed) BCF file
- file_ext = 'bcf'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, metadata_tmp_files_dir: str | None = None, **kwd) None [source]
Creates the index for the BCF file.
- metadata_spec: MetadataSpecCollection = {'bcf_index': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.BcfUncompressed(**kwd)[source]
Bases:
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'
- compressed = False
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.H5(**kwd)[source]
Bases:
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'
- get_structured_content(dataset, content_type=None, path='/', dtype='origin', format='json', flatten=False, selection=None, **kwargs)[source]
Implements h5grove protocol (https://silx-kit.github.io/h5grove/). This allows the h5web visualization tool (https://github.com/silx-kit/h5web) to be used directly with Galaxy datasets.
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Loom(**kwd)[source]
Bases:
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'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'col_attrs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'col_attrs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'col_graphs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'col_graphs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'creation_date': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'description': <galaxy.model.metadata.MetadataElementSpec object>, 'doi': <galaxy.model.metadata.MetadataElementSpec object>, 'layers_count': <galaxy.model.metadata.MetadataElementSpec object>, 'layers_names': <galaxy.model.metadata.MetadataElementSpec object>, 'loom_spec_version': <galaxy.model.metadata.MetadataElementSpec object>, 'row_attrs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'row_attrs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'row_graphs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'row_graphs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'shape': <galaxy.model.metadata.MetadataElementSpec object>, 'title': <galaxy.model.metadata.MetadataElementSpec object>, 'url': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Anndata(**kwd)[source]
Bases:
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 >>> Anndata().sniff(get_test_fname('import.loom.krumsiek11.h5ad')) True >>> Anndata().sniff(get_test_fname('adata_0_6_small2.h5ad')) True >>> Anndata().sniff(get_test_fname('adata_0_6_small.h5ad')) True >>> Anndata().sniff(get_test_fname('adata_0_7_4_small2.h5ad')) True >>> Anndata().sniff(get_test_fname('adata_0_7_4_small.h5ad')) True >>> Anndata().sniff(get_test_fname('adata_unk2.h5ad')) True >>> Anndata().sniff(get_test_fname('adata_unk.h5ad')) True
- file_ext = 'h5ad'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'anndata_spec_version': <galaxy.model.metadata.MetadataElementSpec object>, 'creation_date': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'description': <galaxy.model.metadata.MetadataElementSpec object>, 'doi': <galaxy.model.metadata.MetadataElementSpec object>, 'layers_count': <galaxy.model.metadata.MetadataElementSpec object>, 'layers_names': <galaxy.model.metadata.MetadataElementSpec object>, 'obs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'obs_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'obs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'obs_size': <galaxy.model.metadata.MetadataElementSpec object>, 'obsm_count': <galaxy.model.metadata.MetadataElementSpec object>, 'obsm_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'raw_var_count': <galaxy.model.metadata.MetadataElementSpec object>, 'raw_var_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'raw_var_size': <galaxy.model.metadata.MetadataElementSpec object>, 'row_attrs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'shape': <galaxy.model.metadata.MetadataElementSpec object>, 'title': <galaxy.model.metadata.MetadataElementSpec object>, 'uns_count': <galaxy.model.metadata.MetadataElementSpec object>, 'uns_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'url': <galaxy.model.metadata.MetadataElementSpec object>, 'var_count': <galaxy.model.metadata.MetadataElementSpec object>, 'var_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'var_size': <galaxy.model.metadata.MetadataElementSpec object>, 'varm_count': <galaxy.model.metadata.MetadataElementSpec object>, 'varm_layers': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Grib(**kwd)[source]
Bases:
Binary
Class describing an GRIB file
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.grib') >>> Grib().sniff_prefix(FilePrefix(fname)) True >>> fname = FilePrefix(get_test_fname('interval.interval')) >>> Grib().sniff_prefix(fname) False
- file_ext = 'grib'
- edam_format = 'format_2333'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Set the GRIB edition.
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'grib_edition': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.GmxBinary(**kwd)[source]
Bases:
Binary
Base class for GROMACS binary files - xtc, trr, cpt
- file_ext = ''
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.Trr(**kwd)[source]
Bases:
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'
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Cpt(**kwd)[source]
Bases:
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'
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Xtc(**kwd)[source]
Bases:
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'
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Edr(**kwd)[source]
Bases:
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'
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Biom2(**kwd)[source]
Bases:
H5
Class describing a biom2 file (http://biom-format.org/documentation/biom_format.html)
- file_ext = 'biom2'
- edam_format = 'format_3746'
- sniff(filename: str) bool [source]
>>> 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
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'creation_date': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'format': <galaxy.model.metadata.MetadataElementSpec object>, 'format_url': <galaxy.model.metadata.MetadataElementSpec object>, 'format_version': <galaxy.model.metadata.MetadataElementSpec object>, 'generated_by': <galaxy.model.metadata.MetadataElementSpec object>, 'id': <galaxy.model.metadata.MetadataElementSpec object>, 'nnz': <galaxy.model.metadata.MetadataElementSpec object>, 'shape': <galaxy.model.metadata.MetadataElementSpec object>, 'type': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Cool(**kwd)[source]
Bases:
H5
Class describing the cool format (https://github.com/mirnylab/cooler)
- file_ext = 'cool'
- sniff(filename: str) bool [source]
>>> 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
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.MCool(**kwd)[source]
Bases:
H5
Class describing the multi-resolution cool format (https://github.com/mirnylab/cooler)
- file_ext = 'mcool'
- sniff(filename: str) bool [source]
>>> 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
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.H5MLM(**kwd)[source]
Bases:
H5
Machine learning model generated by Galaxy-ML.
- file_ext = 'h5mlm'
- TARGET_URL = 'https://github.com/goeckslab/Galaxy-ML'
- max_peek_size = 1000
- max_preview_size = 1000000
- CONFIG = '-model_config-'
- HTTP_REPR = '-http_repr-'
- HYPERPARAMETER = '-model_hyperparameters-'
- REPR = '-repr-'
- URL = '-URL-'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, metadata_tmp_files_dir: str | None = None, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- display_data(trans, dataset: DatasetHasHidProtocol, preview: bool = False, filename: str | None = None, to_ext: str | None = None, **kwd)[source]
Displays data in central pane if preview is True, else handles download.
Datatypes should be very careful if overriding this method and this interface between datatypes and Galaxy will likely change.
TODO: Document alternatives to overriding this method (data providers?).
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'hyper_params': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.LudwigModel(**kwd)[source]
Bases:
Html
Composite datatype that encloses multiple files for a Ludwig trained model.
- file_ext = 'ludwig_model'
- metadata_spec: MetadataSpecCollection = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.HexrdMaterials(**kwd)[source]
Bases:
H5
Class describing a Hexrd Materials file: https://github.com/HEXRD/hexrd
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('hexrd.materials.h5') >>> HexrdMaterials().sniff(fname) True >>> fname = get_test_fname('test.loom') >>> HexrdMaterials().sniff(fname) False
- file_ext = 'hexrd.materials.h5'
- edam_format = 'format_3590'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'LatticeParameters': <galaxy.model.metadata.MetadataElementSpec object>, 'SpaceGroupNumber': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'materials': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Scf(**kwd)[source]
Bases:
Binary
Class describing an scf binary sequence file
- edam_format = 'format_1632'
- edam_data = 'data_0924'
- file_ext = 'scf'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Sff(**kwd)[source]
Bases:
Binary
Standard Flowgram Format (SFF)
- edam_format = 'format_3284'
- edam_data = 'data_0924'
- file_ext = 'sff'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.BigWig(**kwd)[source]
Bases:
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'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.BigBed(**kwd)[source]
Bases:
BigWig
BigBed support from UCSC.
- edam_format = 'format_3004'
- edam_data = 'data_3002'
- file_ext = 'bigbed'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.TwoBit(**kwd)[source]
Bases:
Binary
Class describing a TwoBit format nucleotide file
- edam_format = 'format_3009'
- edam_data = 'data_0848'
- file_ext = 'twobit'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.SQlite(**kwd)[source]
Bases:
Binary
Class describing a Sqlite database
- file_ext = 'sqlite'
- edam_format = 'format_3621'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- sqlite_dataprovider(dataset: DatasetProtocol, **settings) SQliteDataProvider [source]
- sqlite_datatableprovider(dataset: DatasetProtocol, **settings) SQliteDataTableProvider [source]
- sqlite_datadictprovider(dataset: DatasetProtocol, **settings) SQliteDataDictProvider [source]
- dataproviders: Dict[str, Any] = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'sqlite': <function SQlite.sqlite_dataprovider>, 'sqlite-dict': <function SQlite.sqlite_datadictprovider>, 'sqlite-table': <function SQlite.sqlite_datatableprovider>}
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.GeminiSQLite(**kwd)[source]
Bases:
SQlite
Class describing a Gemini Sqlite database
- file_ext = 'gemini.sqlite'
- edam_format = 'format_3622'
- edam_data = 'data_3498'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'gemini_version': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.ChiraSQLite(**kwd)[source]
Bases:
SQlite
Class describing a ChiRAViz Sqlite database
- file_ext = 'chira.sqlite'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.CuffDiffSQlite(**kwd)[source]
Bases:
SQlite
Class describing a CuffDiff SQLite database
- file_ext = 'cuffdiff.sqlite'
- edam_format = 'format_3621'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'cuffdiff_version': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'genes': <galaxy.model.metadata.MetadataElementSpec object>, 'samples': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.MzSQlite(**kwd)[source]
Bases:
SQlite
Class describing a Proteomics Sqlite database
- file_ext = 'mz.sqlite'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.PQP(**kwd)[source]
Bases:
SQlite
Class describing a Peptide query parameters file
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.pqp') >>> PQP().sniff(fname) True >>> fname = get_test_fname('test.osw') >>> PQP().sniff(fname) False
- file_ext = 'pqp'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- sniff(filename: str) bool [source]
table definition according to https://github.com/grosenberger/OpenMS/blob/develop/src/openms/source/ANALYSIS/OPENSWATH/TransitionPQPFile.cpp#L264 for now VERSION GENE PEPTIDE_GENE_MAPPING are excluded, since there is test data wo these tables, see also here https://github.com/OpenMS/OpenMS/issues/4365
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.OSW(**kwd)[source]
Bases:
SQlite
Class describing OpenSwath output
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.osw') >>> OSW().sniff(fname) True >>> fname = get_test_fname('test.sqmass') >>> OSW().sniff(fname) False
- file_ext = 'osw'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.SQmass(**kwd)[source]
Bases:
SQlite
Class describing a Sqmass database
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.sqmass') >>> SQmass().sniff(fname) True >>> fname = get_test_fname('test.pqp') >>> SQmass().sniff(fname) False
- file_ext = 'sqmass'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.BlibSQlite(**kwd)[source]
Bases:
SQlite
Class describing a Proteomics Spectral Library Sqlite database
- file_ext = 'blib'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'blib_version': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.DlibSQlite(**kwd)[source]
Bases:
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
- file_ext = 'dlib'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'dlib_version': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.ElibSQlite(**kwd)[source]
Bases:
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
- file_ext = 'elib'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.IdpDB(**kwd)[source]
Bases:
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'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.GAFASQLite(**kwd)[source]
Bases:
SQlite
Class describing a GAFA SQLite database
- file_ext = 'gafa.sqlite'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'gafa_schema_version': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.NcbiTaxonomySQlite(**kwd)[source]
Bases:
SQlite
Class describing the NCBI Taxonomy database stored in SQLite as done by rust-ncbitaxonomy
- file_ext = 'ncbitaxonomy.sqlite'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'ncbitaxonomy_schema_version': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>, 'taxon_count': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Xlsx(**kwd)[source]
Bases:
Binary
Class for Excel 2007 (xlsx) files
- file_ext = 'xlsx'
- compressed = True
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.ExcelXls(**kwd)[source]
Bases:
Binary
Class describing an Excel (xls) file
- file_ext = 'excel.xls'
- edam_format = 'format_3468'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.Sra(**kwd)[source]
Bases:
Binary
Sequence Read Archive (SRA) datatype originally from mdshw5/sra-tools-galaxy
- file_ext = 'sra'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
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
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.RData(**kwd)[source]
Bases:
CompressedArchive
Generic R Data file datatype implementation, i.e. files generated with R’s save or save.img function see https://www.loc.gov/preservation/digital/formats/fdd/fdd000470.shtml and https://cran.r-project.org/doc/manuals/r-patched/R-ints.html#Serialization-Formats
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.rdata') >>> RData().sniff(fname) True >>> from galaxy.util.bunch import Bunch >>> dataset = Bunch() >>> dataset.metadata = Bunch >>> dataset.get_file_name = lambda : fname >>> dataset.has_data = lambda: True >>> RData().set_meta(dataset) >>> dataset.metadata.version '3'
- VERSION_2_PREFIX = b'RDX2\nX\n'
- VERSION_3_PREFIX = b'RDX3\nX\n'
- file_ext = 'rdata'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.RDS(**kwd)[source]
Bases:
CompressedArchive
File using a serialized R object generated with R’s saveRDS function see https://cran.r-project.org/doc/manuals/r-patched/R-ints.html#Serialization-Formats
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('int-r3.rds') >>> RDS().sniff(fname) True >>> fname = get_test_fname('int-r4.rds') >>> RDS().sniff(fname) True >>> fname = get_test_fname('int-r3-version2.rds') >>> RDS().sniff(fname) True >>> from galaxy.util.bunch import Bunch >>> dataset = Bunch() >>> dataset.metadata = Bunch >>> dataset.get_file_name = lambda : get_test_fname('int-r4.rds') >>> dataset.has_data = lambda: True >>> RDS().set_meta(dataset) >>> dataset.metadata.version '3' >>> dataset.metadata.rversion '4.1.1' >>> dataset.metadata.minrversion '3.5.0'
- file_ext = 'rds'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'minrversion': <galaxy.model.metadata.MetadataElementSpec object>, 'rversion': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.OxliBinary(**kwd)[source]
Bases:
Binary
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.OxliCountGraph(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.OxliNodeGraph(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.OxliTagSet(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.OxliStopTags(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.OxliSubset(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.OxliGraphLabels(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.PostgresqlArchive(**kwd)[source]
Bases:
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
- file_ext = 'postgresql'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.MongoDBArchive(**kwd)[source]
Bases:
CompressedArchive
Class describing a Mongo database packed into a tar archive
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('mongodb_fake.tar.bz2') >>> MongoDBArchive().sniff(fname) True >>> fname = get_test_fname('test.fast5.tar') >>> MongoDBArchive().sniff(fname) False
- file_ext = 'mongodb'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.GeneNoteBook(**kwd)[source]
Bases:
MongoDBArchive
Class describing a bzip2-compressed GeneNoteBook archive
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('mongodb_fake.tar.bz2') >>> GeneNoteBook().sniff(fname) True >>> fname = get_test_fname('test.fast5.tar.gz') >>> GeneNoteBook().sniff(fname) False
- file_ext = 'genenotebook'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Fast5Archive(**kwd)[source]
Bases:
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
- file_ext = 'fast5.tar'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fast5_count': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Fast5ArchiveGz(**kwd)[source]
Bases:
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.xz') >>> Fast5ArchiveGz().sniff(fname) False >>> 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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fast5_count': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Fast5ArchiveXz(**kwd)[source]
Bases:
Fast5Archive
Class describing a xz-compressed FAST5 archive
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.fast5.tar.gz') >>> Fast5ArchiveXz().sniff(fname) False >>> fname = get_test_fname('test.fast5.tar.xz') >>> Fast5ArchiveXz().sniff(fname) True >>> fname = get_test_fname('test.fast5.tar.bz2') >>> Fast5ArchiveXz().sniff(fname) False >>> fname = get_test_fname('test.fast5.tar') >>> Fast5ArchiveXz().sniff(fname) False
- file_ext = 'fast5.tar.xz'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fast5_count': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Fast5ArchiveBz2(**kwd)[source]
Bases:
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.xz') >>> Fast5ArchiveBz2().sniff(fname) False >>> 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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fast5_count': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.SearchGuiArchive(**kwd)[source]
Bases:
CompressedArchive
Class describing a SearchGUI archive
- file_ext = 'searchgui_archive'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'searchgui_major_version': <galaxy.model.metadata.MetadataElementSpec object>, 'searchgui_version': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.NetCDF(**kwd)[source]
Bases:
Binary
Binary data in netCDF format
- file_ext = 'netcdf'
- edam_format = 'format_3650'
- edam_data = 'data_0943'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.Dcd(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Vel(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.DAA(**kwd)[source]
Bases:
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'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.RMA6(**kwd)[source]
Bases:
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'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.DMND(**kwd)[source]
Bases:
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'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.ICM(**kwd)[source]
Bases:
Binary
Class describing an ICM (interpolated context model) file, used by Glimmer
- file_ext = 'icm'
- edam_data = 'data_0950'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Parquet(**kwd)[source]
Bases:
Binary
Class describing Apache Parquet file (https://parquet.apache.org/)
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('example.parquet') >>> Parquet().sniff(fname) True >>> fname = get_test_fname('test.mz5') >>> Parquet().sniff(fname) False
- file_ext = 'parquet'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.BafTar(**kwd)[source]
Bases:
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'
- edam_format = 'format_3712'
- file_ext = 'brukerbaf.d.tar'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.YepTar(**kwd)[source]
Bases:
BafTar
A tar’d up .d directory containing Agilent/Bruker YEP format data
- file_ext = 'agilentbrukeryep.d.tar'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.TdfTar(**kwd)[source]
Bases:
BafTar
A tar’d up .d directory containing Bruker TDF format data
- file_ext = 'brukertdf.d.tar'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.MassHunterTar(**kwd)[source]
Bases:
BafTar
A tar’d up .d directory containing Agilent MassHunter format data
- file_ext = 'agilentmasshunter.d.tar'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.MassLynxTar(**kwd)[source]
Bases:
BafTar
A tar’d up .d directory containing Waters MassLynx format data
- file_ext = 'watersmasslynx.raw.tar'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.WiffTar(**kwd)[source]
Bases:
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'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Wiff2Tar(**kwd)[source]
Bases:
BafTar
A tar’d up .wiff2/.scan pair containing Sciex WIFF format data
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('some.wiff2.tar') >>> Wiff2Tar().sniff(fname) True >>> fname = get_test_fname('brukerbaf.d.tar') >>> Wiff2Tar().sniff(fname) False >>> fname = get_test_fname('test.fast5.tar') >>> Wiff2Tar().sniff(fname) False
- file_ext = 'wiff2.tar'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Pretext(**kwd)[source]
Bases:
Binary
PretextMap contact map file Try to guess if the file is a Pretext file.
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('sample.pretext') >>> Pretext().sniff(fname) True
- file_ext = 'pretext'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.binary.JP2(**kwd)[source]
Bases:
Binary
JPEG 2000 binary image format
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.jp2') >>> JP2().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> JP2().sniff(fname) False
- file_ext = 'jp2'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Npz(**kwd)[source]
Bases:
CompressedArchive
Class describing an Numpy NPZ file
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('hexrd.images.npz') >>> Npz().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> Npz().sniff(fname) False
- file_ext = 'npz'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'files': <galaxy.model.metadata.MetadataElementSpec object>, 'nfiles': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.HexrdImagesNpz(**kwd)[source]
Bases:
Npz
Class describing an HEXRD Images Numpy NPZ file
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('hexrd.images.npz') >>> HexrdImagesNpz().sniff(fname) True >>> fname = get_test_fname('eta_ome.npz') >>> HexrdImagesNpz().sniff(fname) False
- file_ext = 'hexrd.images.npz'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'files': <galaxy.model.metadata.MetadataElementSpec object>, 'nfiles': <galaxy.model.metadata.MetadataElementSpec object>, 'nframes': <galaxy.model.metadata.MetadataElementSpec object>, 'omegas': <galaxy.model.metadata.MetadataElementSpec object>, 'panel_id': <galaxy.model.metadata.MetadataElementSpec object>, 'shape': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.HexrdEtaOmeNpz(**kwd)[source]
Bases:
Npz
Class describing an HEXRD Eta-Ome Numpy NPZ file
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('hexrd.eta_ome.npz') >>> HexrdEtaOmeNpz().sniff(fname) True >>> fname = get_test_fname('hexrd.images.npz') >>> HexrdEtaOmeNpz().sniff(fname) False
- file_ext = 'hexrd.eta_ome.npz'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'HKLs': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'files': <galaxy.model.metadata.MetadataElementSpec object>, 'nfiles': <galaxy.model.metadata.MetadataElementSpec object>, 'nframes': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.FITS(**kwd)[source]
Bases:
Binary
FITS (Flexible Image Transport System) file data format, widely used in astronomy Represents sky images (in celestial coordinates) and tables https://fits.gsfc.nasa.gov/fits_primer.html
- file_ext = 'fits'
- sniff(filename: str) bool [source]
Determines whether the file is a FITS file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘test.fits’) >>> FITS().sniff(fname) True >>> fname = FilePrefix(get_test_fname(‘interval.interval’)) >>> FITS().sniff(fname) False
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- metadata_spec: MetadataSpecCollection = {'HDUs': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.binary.Numpy(**kwd)[source]
Bases:
Binary
Class defining a numpy data file
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.npy') >>> Numpy().sniff(fname) True
- file_ext = 'npy'
- set_meta(dataset: DatasetProtocol, overwrite: bool = True, **kwd) None [source]
Unimplemented method, allows guessing of metadata from contents of file
- sniff_prefix(file_prefix: FilePrefix) bool [source]
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'version_str': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
galaxy.datatypes.blast module
NCBI BLAST datatypes.
Covers the blastxml
format and the BLAST databases.
- class galaxy.datatypes.blast.BlastXml(**kwd)[source]
Bases:
GenericXml
NCBI Blast XML Output data
- file_ext = 'blastxml'
- edam_format = 'format_3331'
- edam_data = 'data_0857'
- sniff_prefix(file_prefix: FilePrefix) bool [source]
Determines whether the file is blastxml
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('megablast_xml_parser_test1.blastxml') >>> BlastXml().sniff(fname) True >>> fname = get_test_fname('tblastn_four_human_vs_rhodopsin.blastxml') >>> BlastXml().sniff(fname) True >>> fname = get_test_fname('interval.interval') >>> BlastXml().sniff(fname) False
- static merge(split_files: List[str], output_file: str) None [source]
Merging multiple XML files is non-trivial and must be done in subclasses.
- metadata_spec: MetadataSpecCollection = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- sniff(filename)
- class galaxy.datatypes.blast.BlastNucDb(**kwd)[source]
Bases:
_BlastDb
Class for nucleotide BLAST database files.
- file_ext = 'blastdbn'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.blast.BlastProtDb(**kwd)[source]
Bases:
_BlastDb
Class for protein BLAST database files.
- file_ext = 'blastdbp'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.blast.BlastDomainDb(**kwd)[source]
Bases:
_BlastDb
Class for domain BLAST database files.
- file_ext = 'blastdbd'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.blast.LastDb(**kwd)[source]
Bases:
Data
Class for LAST database files.
- file_ext = 'lastdb'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.blast.BlastNucDb5(**kwd)[source]
Bases:
_BlastDb
Class for nucleotide BLAST database files.
- file_ext = 'blastdbn5'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.blast.BlastProtDb5(**kwd)[source]
Bases:
_BlastDb
Class for protein BLAST database files.
- file_ext = 'blastdbp5'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.blast.BlastDomainDb5(**kwd)[source]
Bases:
_BlastDb
Class for domain BLAST database files.
- file_ext = 'blastdbd5'
- metadata_spec: MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
galaxy.datatypes.checkers module
Module proxies galaxy.util.checkers
for backward compatibility.
External datatypes may make use of these functions.
- galaxy.datatypes.checkers.check_bz2(file_path: str, check_content: bool = True) Tuple[bool, bool] [source]
- galaxy.datatypes.checkers.check_gzip(file_path: str, check_content: bool = True) Tuple[bool, bool] [source]
- galaxy.datatypes.checkers.check_html(name, file_path: bool = True) bool [source]
Returns True if the file/string contains HTML code.
- galaxy.datatypes.checkers.check_image(file_path: str) bool [source]
Simple wrapper around image_type to yield a True/False verdict
galaxy.datatypes.chrominfo module
- class galaxy.datatypes.chrominfo.ChromInfo(**kwd)[source]
Bases:
Tabular
- file_ext = 'len'
- metadata_spec: MetadataSpecCollection = {'chrom': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'length': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
galaxy.datatypes.constructive_solid_geometry module
Constructive Solid Geometry file formats.
- class galaxy.datatypes.constructive_solid_geometry.Ply(**kwd)[source]
Bases:
object
The PLY format describes an object as a collection of vertices, faces and other elements, along with properties such as color and normal direction that can be attached to these elements. A PLY file contains the description of exactly one object.
- subtype = ''
- sniff_prefix(file_prefix: FilePrefix) bool [source]
The structure of a typical PLY file: Header, Vertex List, Face List, (lists of other elements)
- sniff(filename)
- class galaxy.datatypes.constructive_solid_geometry.PlyAscii(**kwd)[source]
-
>>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname('test.plyascii') >>> PlyAscii().sniff(fname) True >>> fname = get_test_fname('test.vtkascii') >>> PlyAscii().sniff(fname) False
- file_ext = 'plyascii'
- subtype = 'ascii'
- metadata_spec: metadata.MetadataSpecCollection = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'face': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'other_elements': <galaxy.model.metadata.MetadataElementSpec object>, 'vertex': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.constructive_solid_geometry.PlyBinary(**kwd)[source]
-
- file_ext = 'plybinary'
- subtype = 'binary'
- metadata_spec: metadata.MetadataSpecCollection = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'face': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'other_elements': <galaxy.model.metadata.MetadataElementSpec object>, 'vertex': <galaxy.model.metadata.MetadataElementSpec object>}
Dictionary of metadata fields for this datatype
- class galaxy.datatypes.constructive_solid_geometry.Vtk(**kwd)[source]
Bases:
object
The Visualization Toolkit provides a number of source and writer objects to read and write popular data file formats. The Visualization Toolkit also provides some of its own file formats.
There are two different styles of file formats available in VTK. The simplest are the legacy, serial formats that are easy to read and write either by hand or programmatically. However, these formats are less flexible than the XML based file formats which support random access, parallel I/O, and portable data compression and are preferred to the serial VTK file formats whenever possible.
All keyword phrases are written in ASCII form whether the file is binary or ASCII. The binary section of the file (if in binary form) is the data proper; i.e., the numbers that define points coordinates, scalars, cell indices, and so forth.
Binary data must be placed into the file immediately after the newline (’\n’) character from the previous ASCII keyword and parameter sequence.
TODO: only legacy formats are currently supported and support for XML formats should be added.
- subtype = ''
- sniff_prefix(file_prefix: FilePrefix) bool [source]
VTK files can be either ASCII or binary, with two different styles of file formats: legacy or XML. We’ll assume if the file contains a valid VTK header, then it is a valid VTK file.
- set_structure_metadata(line: str, dataset: DatasetProtocol, dataset_type: str | None) Tuple[DatasetProtocol, str | None] [source]
The fourth part of legacy VTK files is the dataset structure. The geometry part describes the geometry and topology of the dataset. This part begins with a line containing the keyword DATASET followed by a keyword describing the type of dataset. Then, depending upon the type of dataset, other keyword/ data combinations define the actual data.
<