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Source code for galaxy.datatypes.data

import logging
import mimetypes
import os
import shutil
import string
import tempfile
from inspect import isclass
from typing import (

from markupsafe import escape
from typing_extensions import Literal

from galaxy import util
from galaxy.datatypes.metadata import (
    MetadataElement,  # import directly to maintain ease of use in Datatype class definitions
from galaxy.datatypes.protocols import (
from galaxy.datatypes.sniff import (
from galaxy.exceptions import ObjectNotFound
from galaxy.util import (
from galaxy.util.bunch import Bunch
from galaxy.util.compression_utils import FileObjType
from galaxy.util.markdown import (
from galaxy.util.sanitize_html import sanitize_html
from galaxy.util.zipstream import ZipstreamWrapper
from . import (
    dataproviders as p_dataproviders,

    from galaxy.datatypes.display_applications.application import DisplayApplication
    from galaxy.datatypes.registry import Registry

    "image/svg+xml",  # Unfiltered by Galaxy and may contain JS that would be executed by some browsers.
    "application/xml",  # Some browsers will evaluate SVG embedded JS in such XML documents.
DEFAULT_MIME_TYPE = "text/plain"  # Vulnerable mime types will be replaced with this.

log = logging.getLogger(__name__)

# Valid first column and strand column values vor bed, other formats
col1_startswith = ["chr", "chl", "groupun", "reftig_", "scaffold", "super_", "vcho"]
valid_strand = ["+", "-", "."]

DOWNLOAD_FILENAME_PATTERN_DATASET = "Galaxy${hid}-[${name}].${ext}"
DOWNLOAD_FILENAME_PATTERN_COLLECTION_ELEMENT = "Galaxy${hdca_hid}-[${hdca_name}__${element_identifier}].${ext}"

Headers = Dict[str, Any]

[docs]class DatatypeConverterNotFoundException(Exception): pass
[docs]class DatatypeValidation:
[docs] def __init__(self, state: str, message: str) -> None: self.state = state self.message = message
[docs] @staticmethod def validated() -> "DatatypeValidation": return DatatypeValidation("ok", "Dataset validated by datatype validator.")
[docs] @staticmethod def invalid(message: str) -> "DatatypeValidation": return DatatypeValidation("invalid", message)
[docs] @staticmethod def unvalidated() -> "DatatypeValidation": return DatatypeValidation(UNKNOWN, "Dataset validation unimplemented for this datatype.")
def __repr__(self) -> str: return f"DatatypeValidation[state={self.state},message={self.message}]"
[docs]def validate(dataset_instance: DatasetProtocol) -> DatatypeValidation: try: datatype_validation = dataset_instance.datatype.validate(dataset_instance) except Exception as e: datatype_validation = DatatypeValidation.invalid(f"Problem running datatype validation method [{str(e)}]") return datatype_validation
[docs]def get_params_and_input_name( converter, deps: Optional[Dict], target_context: Optional[Dict] = None ) -> Tuple[Dict, str]: # Generate parameter dictionary params = {} # determine input parameter name and add to params input_name = "input1" for key, value in converter.inputs.items(): if deps and value.name in deps: params[value.name] = deps[value.name] elif value.type == "data": input_name = key elif value.optional: params[value.name] = None # add potentially required/common internal tool parameters e.g. '__job_resource' if target_context: for key, value in target_context.items(): if key.startswith("__"): params[key] = value return params, input_name
[docs]class DataMeta(type): """ Metaclass for Data class. Sets up metadata spec. """
[docs] def __init__(cls, name, bases, dict_): cls.metadata_spec = metadata.MetadataSpecCollection() for base in bases: # loop through bases (class/types) of cls if hasattr(base, "metadata_spec"): # base of class Data (object) has no metadata cls.metadata_spec.update(base.metadata_spec) # add contents of metadata spec of base class to cls metadata.Statement.process(cls)
def _is_binary_file(data): from galaxy.datatypes import binary return isinstance(data.datatype, binary.Binary) or type(data.datatype) is Data def _get_max_peek_size(data): from galaxy.datatypes import ( binary, text, ) max_peek_size = DEFAULT_MAX_PEEK_SIZE # 1 MB if isinstance(data.datatype, text.Html): max_peek_size = 10000000 # 10 MB for html elif isinstance(data.datatype, binary.Binary): max_peek_size = 100000 # 100 KB for binary return max_peek_size def _get_file_size(data): file_size = int(data.dataset.file_size or 0) if file_size == 0: if data.dataset.object_store: file_size = data.dataset.object_store.size(data.dataset) else: file_size = os.stat(data.get_file_name()).st_size return file_size
[docs]@p_dataproviders.decorators.has_dataproviders class Data(metaclass=DataMeta): """ Base class for all datatypes. Implements basic interfaces as well as class methods for metadata. >>> class DataTest( Data ): ... MetadataElement( name="test" ) ... >>> DataTest.metadata_spec.test.name 'test' >>> DataTest.metadata_spec.test.desc 'test' >>> type( DataTest.metadata_spec.test.param ) <class 'galaxy.model.metadata.MetadataParameter'> """ edam_data = "data_0006" edam_format = "format_1915" file_ext = "data" # Data is not chunkable by default. CHUNKABLE = False #: Dictionary of metadata fields for this datatype metadata_spec: metadata.MetadataSpecCollection # Add metadata elements MetadataElement( name="dbkey", desc="Database/Build", default="?", param=metadata.DBKeyParameter, multiple=False, optional=True, no_value="?", ) # Stores the set of display applications, and viewing methods, supported by this datatype supported_display_apps: Dict[str, Any] = {} # The dataset contains binary data --> do not space_to_tab or convert newlines, etc. # Allow binary file uploads of this type when True. is_binary: Union[bool, Literal["maybe"]] = True # Composite datatypes composite_type: Optional[str] = None composite_files: Dict[str, Any] = {} primary_file_name = "index" # Allow user to change between this datatype and others. If left to None, # datatype change is allowed if the datatype is not composite. allow_datatype_change: Optional[bool] = None # A per datatype setting (inherited): max file size (in bytes) for setting optional metadata _max_optional_metadata_filesize = None # Trackster track type. track_type: Optional[str] = None # Data sources. data_sources: Dict[str, str] = {} dataproviders: Dict[str, Any]
[docs] def __init__(self, **kwd): """Initialize the datatype""" self.supported_display_apps = self.supported_display_apps.copy() self.composite_files = self.composite_files.copy() self.display_applications = {}
[docs] @classmethod def is_datatype_change_allowed(cls) -> bool: """ Returns the value of the `allow_datatype_change` class attribute if set in a subclass, or True iff the datatype is not composite. """ if cls.allow_datatype_change is not None: return cls.allow_datatype_change return cls.composite_type is None
[docs] def dataset_content_needs_grooming(self, file_name: str) -> bool: """This function is called on an output dataset file after the content is initially generated.""" return False
[docs] def groom_dataset_content(self, file_name: str) -> None: """This function is called on an output dataset file if dataset_content_needs_grooming returns True."""
[docs] def init_meta(self, dataset: HasMetadata, copy_from: Optional[HasMetadata] = None) -> None: # Metadata should be left mostly uninitialized. Dataset will # handle returning default values when metadata is not set. # copy_from allows metadata to be passed in that will be # copied. (although this seems ambiguous, see # Dataset.set_metadata. It always copies the rhs in order to # flag the object as modified for SQLAlchemy. if copy_from: dataset.metadata = copy_from.metadata
[docs] def set_meta(self, dataset: DatasetProtocol, *, overwrite: bool = True, **kwd) -> None: """Unimplemented method, allows guessing of metadata from contents of file"""
[docs] def missing_meta(self, dataset: HasMetadata, check: Optional[List] = None, skip: Optional[List] = None) -> bool: """ Checks for empty metadata values. Returns False if no non-optional metadata is missing and the missing metadata key otherwise. Specifying a list of 'check' values will only check those names provided; when used, optionality is ignored Specifying a list of 'skip' items will return True even when a named metadata value is missing; when used, optionality is ignored """ if skip is None: skip = [] if check: to_check = check else: to_check = dataset.metadata.keys() for key in to_check: if key in skip: continue if not check and len(skip) == 0 and dataset.metadata.spec[key].get("optional"): continue # we skip check for optional and nonrequested values here if not dataset.metadata.element_is_set(key) and ( check or dataset.metadata.spec[key].check_required_metadata ): # FIXME: Optional metadata isn't always properly annotated, # so skip check if check_required_metadata is false on the datatype that defined the metadata element. # See https://github.com/galaxyproject/tools-iuc/issues/4367 return key return False
[docs] def set_max_optional_metadata_filesize(self, max_value: int) -> None: try: max_value = int(max_value) except (TypeError, ValueError): return self.__class__._max_optional_metadata_filesize = max_value
[docs] def get_max_optional_metadata_filesize(self) -> int: rval = self.__class__._max_optional_metadata_filesize if rval is None: return -1 return rval
max_optional_metadata_filesize = property(get_max_optional_metadata_filesize, set_max_optional_metadata_filesize)
[docs] def set_peek(self, dataset: DatasetProtocol, **kwd) -> None: """ Set the peek and blurb text """ if not dataset.dataset.purged: dataset.peek = "" dataset.blurb = "data" else: dataset.peek = "file does not exist" dataset.blurb = "file purged from disk"
[docs] def display_peek(self, dataset: DatasetProtocol) -> str: """Create HTML table, used for displaying peek""" out = ['<table cellspacing="0" cellpadding="3">'] try: if not dataset.peek: dataset.set_peek() data = dataset.peek lines = data.splitlines() for line in lines: line = line.strip() if not line: continue out.append(f"<tr><td>{escape(unicodify(line, 'utf-8'))}</td></tr>") out.append("</table>") return "".join(out) except Exception as exc: return f"Can't create peek: {unicodify(exc)}"
def _archive_main_file( self, archive: ZipstreamWrapper, display_name: str, data_filename: str ) -> Tuple[bool, str, str]: """Called from _archive_composite_dataset to add central file to archive. Unless subclassed, this will add the main dataset file (argument data_filename) to the archive, as an HTML file with its filename derived from the dataset name (argument outfname). Returns a tuple of boolean, string, string: (error, msg, messagetype) """ error, msg, messagetype = False, "", "" archname = f"{display_name}.html" # fake the real nature of the html file try: archive.write(data_filename, archname) except OSError: error = True log.exception("Unable to add composite parent %s to temporary library download archive", data_filename) msg = "Unable to create archive for download, please report this error" messagetype = "error" return error, msg, messagetype def _archive_composite_dataset( self, trans, data: DatasetHasHidProtocol, headers: Headers, do_action: str = "zip" ) -> Tuple[Union[ZipstreamWrapper, str], Headers]: # save a composite object into a compressed archive for downloading outfname = data.name[0:150] outfname = "".join(c in FILENAME_VALID_CHARS and c or "_" for c in outfname) archive = ZipstreamWrapper( archive_name=outfname, upstream_mod_zip=trans.app.config.upstream_mod_zip, upstream_gzip=trans.app.config.upstream_gzip, ) error = False msg = "" ext = data.extension path = data.get_file_name() efp = data.extra_files_path # Add any central file to the archive, display_name = os.path.splitext(outfname)[0] if not display_name.endswith(ext): display_name = f"{display_name}_{ext}" error, msg = self._archive_main_file(archive, display_name, path)[:2] if not error: # Add any child files to the archive, for fpath, rpath in self.__archive_extra_files_path(extra_files_path=efp): try: archive.write(fpath, rpath) except OSError: error = True log.exception("Unable to add %s to temporary library download archive", rpath) msg = "Unable to create archive for download, please report this error" continue if not error: headers.update(archive.get_headers()) return archive, headers return trans.show_error_message(msg), headers def __archive_extra_files_path(self, extra_files_path: str) -> Generator[Tuple[str, str], None, None]: """Yield filepaths and relative filepaths for files in extra_files_path""" for root, _, files in os.walk(extra_files_path): for fname in files: fpath = os.path.join(root, fname) rpath = os.path.relpath(fpath, extra_files_path) yield fpath, rpath def _serve_raw( self, dataset: DatasetHasHidProtocol, to_ext: Optional[str], headers: Headers, **kwd ) -> Tuple[IO, Headers]: headers["Content-Length"] = str(os.stat(dataset.get_file_name()).st_size) headers[ "content-type" ] = "application/octet-stream" # force octet-stream so Safari doesn't append mime extensions to filename filename = self._download_filename( dataset, to_ext, hdca=kwd.get("hdca"), element_identifier=kwd.get("element_identifier"), filename_pattern=kwd.get("filename_pattern"), ) headers["Content-Disposition"] = f'attachment; filename="{filename}"' return open(dataset.get_file_name(), mode="rb"), headers
[docs] def to_archive(self, dataset: DatasetProtocol, name: str = "") -> Iterable: """ Collect archive paths and file handles that need to be exported when archiving `dataset`. :param dataset: HistoryDatasetAssociation :param name: archive name, in collection context corresponds to collection name(s) and element_identifier, joined by '/', e.g 'fastq_collection/sample1/forward' """ rel_paths = [] file_paths = [] if dataset.datatype.composite_type or dataset.extension.endswith("html"): main_file = f"{name}.html" rel_paths.append(main_file) file_paths.append(dataset.get_file_name()) for fpath, rpath in self.__archive_extra_files_path(dataset.extra_files_path): rel_paths.append(os.path.join(name, rpath)) file_paths.append(fpath) else: rel_paths.append(f"{name or dataset.get_file_name()}.{dataset.extension}") file_paths.append(dataset.get_file_name()) return zip(file_paths, rel_paths)
def _serve_file_download(self, headers, data, trans, to_ext, file_size, **kwd): composite_extensions = trans.app.datatypes_registry.get_composite_extensions() composite_extensions.append("html") # for archiving composite datatypes composite_extensions.append("data_manager_json") # for downloading bundles if bundled. if data.extension in composite_extensions: return self._archive_composite_dataset(trans, data, headers, do_action=kwd.get("do_action", "zip")) else: headers["Content-Length"] = str(file_size) filename = self._download_filename( data, to_ext, hdca=kwd.get("hdca"), element_identifier=kwd.get("element_identifier"), filename_pattern=kwd.get("filename_pattern"), ) headers[ "content-type" ] = "application/octet-stream" # force octet-stream so Safari doesn't append mime extensions to filename headers["Content-Disposition"] = f'attachment; filename="{filename}"' return open(data.get_file_name(), "rb"), headers def _serve_binary_file_contents_as_text(self, trans, data, headers, file_size, max_peek_size): headers["content-type"] = "text/html" return ( trans.fill_template_mako( "/dataset/binary_file.mako", data=data, file_contents=open(data.get_file_name(), "rb").read(max_peek_size), file_size=util.nice_size(file_size), truncated=file_size > max_peek_size, ), headers, ) def _serve_file_contents(self, trans, data, headers, preview, file_size, max_peek_size): from galaxy.datatypes import images preview = util.string_as_bool(preview) if not preview or isinstance(data.datatype, images.Image) or file_size < max_peek_size: return self._yield_user_file_content(trans, data, data.get_file_name(), headers), headers # preview large text file headers["content-type"] = "text/html" return ( trans.fill_template_mako( "/dataset/large_file.mako", truncated_data=open(data.get_file_name(), "rb").read(max_peek_size), data=data, ), headers, )
[docs] def display_data( self, trans, dataset: DatasetHasHidProtocol, preview: bool = False, filename: Optional[str] = None, to_ext: Optional[str] = None, **kwd, ): """ 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?). """ headers = kwd.get("headers", {}) # Prevent IE8 from sniffing content type since we're explicit about it. This prevents intentionally text/plain # content from being rendered in the browser headers["X-Content-Type-Options"] = "nosniff" if filename and filename != "index": # For files in extra_files_path extra_dir = dataset.dataset.extra_files_path_name file_path = trans.app.object_store.get_filename(dataset.dataset, extra_dir=extra_dir, alt_name=filename) if os.path.exists(file_path): if os.path.isdir(file_path): with tempfile.NamedTemporaryFile( mode="w", delete=False, dir=trans.app.config.new_file_path, prefix="gx_html_autocreate_" ) as tmp_fh: tmp_file_name = tmp_fh.name dir_items = sorted(os.listdir(file_path)) base_path, item_name = os.path.split(file_path) tmp_fh.write( "<html><head><h3>Directory %s contents: %d items</h3></head>\n" % (escape(item_name), len(dir_items)) ) tmp_fh.write('<body><p/><table cellpadding="2">\n') for index, fname in enumerate(dir_items): if index % 2 == 0: bgcolor = "#D8D8D8" else: bgcolor = "#FFFFFF" # Can't have an href link here because there is no route # defined for files contained within multiple subdirectory # levels of the primary dataset. Something like this is # close, but not quite correct: # href = url_for(controller='dataset', action='display', # dataset_id=trans.security.encode_id(dataset.dataset.id), # preview=preview, filename=fname, to_ext=to_ext) tmp_fh.write(f'<tr bgcolor="{bgcolor}"><td>{escape(fname)}</td></tr>\n') tmp_fh.write("</table></body></html>\n") return self._yield_user_file_content(trans, dataset, tmp_file_name, headers), headers mime = mimetypes.guess_type(file_path)[0] if not mime: try: mime = trans.app.datatypes_registry.get_mimetype_by_extension(file_path.split(".")[-1]) except Exception: mime = "text/plain" self._clean_and_set_mime_type(trans, mime, headers) # type: ignore[arg-type] return self._yield_user_file_content(trans, dataset, file_path, headers), headers else: raise ObjectNotFound(f"Could not find '{filename}' on the extra files path {file_path}.") self._clean_and_set_mime_type(trans, dataset.get_mime(), headers) downloading = to_ext is not None file_size = _get_file_size(dataset) if not os.path.exists(dataset.get_file_name()): raise ObjectNotFound(f"File Not Found ({dataset.get_file_name()}).") if downloading: trans.log_event(f"Download dataset id: {str(dataset.id)}") return self._serve_file_download(headers, dataset, trans, to_ext, file_size, **kwd) else: # displaying trans.log_event(f"Display dataset id: {str(dataset.id)}") max_peek_size = _get_max_peek_size(dataset) if ( _is_binary_file(dataset) and preview and hasattr(trans, "fill_template_mako") ): # preview file which format is unknown (to Galaxy), we still try to display this as text return self._serve_binary_file_contents_as_text(trans, dataset, headers, file_size, max_peek_size) else: # text/html, or image, or display was called without preview flag return self._serve_file_contents(trans, dataset, headers, preview, file_size, max_peek_size)
[docs] def display_as_markdown(self, dataset_instance: DatasetProtocol) -> str: """Prepare for embedding dataset into a basic Markdown document. This is a somewhat experimental interface and should not be implemented on datatypes not tightly tied to a Galaxy version (e.g. datatypes in the Tool Shed). Speaking very loosely - the datatype should load a bounded amount of data from the supplied dataset instance and prepare for embedding it into Markdown. This should be relatively vanilla Markdown - the result of this is bleached and it should not contain nested Galaxy Markdown directives. If the data cannot reasonably be displayed, just indicate this and do not throw an exception. """ if self.file_ext in {"png", "jpg"}: return self.handle_dataset_as_image(dataset_instance) if self.is_binary: result = "*cannot display binary content*\n" else: with open(dataset_instance.get_file_name()) as f: contents = f.read(DEFAULT_MAX_PEEK_SIZE) result = literal_via_fence(contents) if len(contents) == DEFAULT_MAX_PEEK_SIZE: result += indicate_data_truncated() return result
def _yield_user_file_content(self, trans, from_dataset: HasCreatingJob, filename: str, headers: Headers) -> IO: """This method is responsible for sanitizing the HTML if needed.""" if trans.app.config.sanitize_all_html and headers.get("content-type", None) == "text/html": # Sanitize anytime we respond with plain text/html content. # Check to see if this dataset's parent job is allowlisted # We cannot currently trust imported datasets for rendering. if not from_dataset.creating_job.imported and from_dataset.creating_job.tool_id.startswith( tuple(trans.app.config.sanitize_allowlist) ): return open(filename, mode="rb") # This is returning to the browser, it needs to be encoded. # TODO Ideally this happens a layer higher, but this is a bad # issue affecting many tools with open(filename) as f: return sanitize_html(f.read()).encode("utf-8") return open(filename, mode="rb") def _download_filename( self, dataset: DatasetHasHidProtocol, to_ext: Optional[str] = None, hdca: Optional[DatasetHasHidProtocol] = None, element_identifier: Optional[str] = None, filename_pattern: Optional[str] = None, ) -> str: def escape(raw_identifier): return "".join(c in FILENAME_VALID_CHARS and c or "_" for c in raw_identifier)[0:150] if not to_ext or to_ext == "data": # If a client requests to_ext with the extension 'data', they are # deferring to the server, set it based on datatype. to_ext = dataset.extension template_values = { "name": escape(dataset.name), "ext": to_ext, "hid": dataset.hid, } if not filename_pattern: if hdca is None: filename_pattern = DOWNLOAD_FILENAME_PATTERN_DATASET else: filename_pattern = DOWNLOAD_FILENAME_PATTERN_COLLECTION_ELEMENT if hdca is not None: # Use collection context to build up filename. template_values["element_identifier"] = element_identifier template_values["hdca_name"] = escape(hdca.name) template_values["hdca_hid"] = hdca.hid return string.Template(filename_pattern).substitute(**template_values)
[docs] def display_name(self, dataset: HasName) -> str: """Returns formatted html of dataset name""" try: return escape(unicodify(dataset.name, "utf-8")) except Exception: return "name unavailable"
[docs] def display_info(self, dataset: HasInfo) -> str: """Returns formatted html of dataset info""" try: # Change new line chars to html info: str = escape(dataset.info) if info.find("\r\n") >= 0: info = info.replace("\r\n", "<br/>") if info.find("\r") >= 0: info = info.replace("\r", "<br/>") if info.find("\n") >= 0: info = info.replace("\n", "<br/>") info = unicodify(info, "utf-8") return info except Exception: return "info unavailable"
[docs] def get_mime(self) -> str: """Returns the mime type of the datatype""" return "application/octet-stream"
[docs] def add_display_app(self, app_id: str, label: str, file_function: str, links_function: str) -> None: """ Adds a display app to the datatype. app_id is a unique id label is the primary display label, e.g., display at 'UCSC' file_function is a string containing the name of the function that returns a properly formatted display links_function is a string containing the name of the function that returns a list of (link_name,link) """ self.supported_display_apps = self.supported_display_apps.copy() self.supported_display_apps[app_id] = { "label": label, "file_function": file_function, "links_function": links_function, }
[docs] def remove_display_app(self, app_id: str) -> None: """Removes a display app from the datatype""" self.supported_display_apps = self.supported_display_apps.copy() try: del self.supported_display_apps[app_id] except Exception: log.exception( "Tried to remove display app %s from datatype %s, but this display app is not declared.", type, self.__class__.__name__, )
[docs] def clear_display_apps(self) -> None: self.supported_display_apps = {}
[docs] def add_display_application(self, display_application: "DisplayApplication") -> None: """New style display applications""" assert display_application.id not in self.display_applications, "Attempted to add a display application twice" self.display_applications[display_application.id] = display_application
[docs] def get_display_application(self, key: str, default: Optional["DisplayApplication"] = None) -> "DisplayApplication": return self.display_applications.get(key, default)
[docs] def get_display_applications_by_dataset(self, dataset: DatasetProtocol, trans) -> Dict[str, "DisplayApplication"]: rval = {} for key, value in self.display_applications.items(): value = value.filter_by_dataset(dataset, trans) if value.links: rval[key] = value return rval
[docs] def get_display_types(self) -> List[str]: """Returns display types available""" return list(self.supported_display_apps.keys())
[docs] def get_display_label(self, type: str) -> str: """Returns primary label for display app""" try: return self.supported_display_apps[type]["label"] except Exception: return UNKNOWN
[docs] def as_display_type(self, dataset: DatasetProtocol, type: str, **kwd) -> Union[FileObjType, str]: """Returns modified file contents for a particular display type""" try: if type in self.get_display_types(): return getattr(self, self.supported_display_apps[type]["file_function"])(dataset, **kwd) except Exception: log.exception( "Function %s is referred to in datatype %s for displaying as type %s, but is not accessible", self.supported_display_apps[type]["file_function"], self.__class__.__name__, type, ) return f"This display type ({type}) is not implemented for this datatype ({dataset.ext})."
[docs] def get_converter_types(self, original_dataset: HasExt, datatypes_registry: "Registry") -> Dict[str, Dict]: """Returns available converters by type for this dataset""" return datatypes_registry.get_converters_by_datatype(original_dataset.ext)
[docs] def find_conversion_destination( self, dataset: DatasetProtocol, accepted_formats: List[str], datatypes_registry, **kwd ) -> Tuple[bool, Optional[str], Any]: """Returns ( direct_match, converted_ext, existing converted dataset )""" return datatypes_registry.find_conversion_destination_for_dataset_by_extensions( dataset, accepted_formats, **kwd )
[docs] def convert_dataset( self, trans, original_dataset: DatasetHasHidProtocol, target_type: str, return_output: bool = False, visible: bool = True, deps: Optional[Dict] = None, target_context: Optional[Dict] = None, history=None, ): """This function adds a job to the queue to convert a dataset to another type. Returns a message about success/failure.""" converter = trans.app.datatypes_registry.get_converter_by_target_type(original_dataset.ext, target_type) if converter is None: raise DatatypeConverterNotFoundException( f"A converter does not exist for {original_dataset.ext} to {target_type}." ) params, input_name = get_params_and_input_name(converter, deps, target_context) params[input_name] = original_dataset # Make the target datatype available to the converter params["__target_datatype__"] = target_type # Run converter, job is dispatched through Queue job, converted_datasets, *_ = converter.execute(trans, incoming=params, set_output_hid=visible, history=history) trans.app.job_manager.enqueue(job, tool=converter) if len(params) > 0: trans.log_event(f"Converter params: {str(params)}", tool_id=converter.id) if not visible: for value in converted_datasets.values(): value.visible = False if return_output: return converted_datasets return f"The file conversion of {converter.name} on data {original_dataset.hid} has been added to the Queue."
# We need to clear associated files before we set metadata # so that as soon as metadata starts to be set, e.g. implicitly converted datasets are deleted and no longer available 'while' metadata is being set, not just after # We'll also clear after setting metadata, for backwards compatibility
[docs] def after_setting_metadata(self, dataset: HasClearAssociatedFiles) -> None: """This function is called on the dataset after metadata is set.""" dataset.clear_associated_files(metadata_safe=True)
[docs] def before_setting_metadata(self, dataset: HasClearAssociatedFiles) -> None: """This function is called on the dataset before metadata is set.""" dataset.clear_associated_files(metadata_safe=True)
def __new_composite_file( self, name: str, optional: bool = False, mimetype: Optional[str] = None, description: Optional[str] = None, substitute_name_with_metadata: Optional[str] = None, is_binary: bool = False, to_posix_lines: bool = True, space_to_tab: bool = False, **kwds, ) -> Bunch: kwds["name"] = name kwds["optional"] = optional kwds["mimetype"] = mimetype kwds["description"] = description kwds["substitute_name_with_metadata"] = substitute_name_with_metadata kwds["is_binary"] = is_binary kwds["to_posix_lines"] = to_posix_lines kwds["space_to_tab"] = space_to_tab composite_file = Bunch(**kwds) return composite_file
[docs] def add_composite_file(self, name: str, **kwds) -> None: # self.composite_files = self.composite_files.copy() self.composite_files[name] = self.__new_composite_file(name, **kwds)
@property def writable_files(self): files = {} if self.composite_type != "auto_primary_file": files[self.primary_file_name] = self.__new_composite_file(self.primary_file_name) for key, value in self.get_composite_files().items(): files[key] = value return files
[docs] def get_writable_files_for_dataset(self, dataset: Optional[HasMetadata]) -> Dict: files = {} if self.composite_type != "auto_primary_file": files[self.primary_file_name] = self.__new_composite_file(self.primary_file_name) for key, value in self.get_composite_files(dataset).items(): files[key] = value return files
[docs] def get_composite_files(self, dataset: Optional[HasMetadata] = None): def substitute_composite_key(key, composite_file): if composite_file.substitute_name_with_metadata: if dataset: meta_value = str(dataset.metadata.get(composite_file.substitute_name_with_metadata)) else: meta_value = self.metadata_spec[composite_file.substitute_name_with_metadata].default return key % meta_value return key files = {} for key, value in self.composite_files.items(): files[substitute_composite_key(key, value)] = value return files
[docs] def generate_primary_file(self, dataset: HasExtraFilesAndMetadata) -> str: raise Exception("generate_primary_file is not implemented for this datatype.")
@property def has_resolution(self): return False
[docs] def matches_any(self, target_datatypes: List[Any]) -> bool: """ Check if this datatype is of any of the target_datatypes or is a subtype thereof. """ datatype_classes = tuple(datatype if isclass(datatype) else datatype.__class__ for datatype in target_datatypes) return isinstance(self, datatype_classes)
[docs] @staticmethod def merge(split_files: List[str], output_file: str) -> None: """ Merge files with copy.copyfileobj() will not hit the max argument limitation of cat. gz and bz2 files are also working. """ if not split_files: raise ValueError(f"Asked to merge zero files as {output_file}") elif len(split_files) == 1: shutil.copyfileobj(open(split_files[0], "rb"), open(output_file, "wb")) else: with open(output_file, "wb") as fdst: for fsrc in split_files: shutil.copyfileobj(open(fsrc, "rb"), fdst)
# ------------- Dataproviders
[docs] def has_dataprovider(self, data_format: str) -> bool: """ Returns True if `data_format` is available in `dataproviders`. """ return data_format in self.dataproviders
[docs] def dataprovider(self, dataset: DatasetProtocol, data_format: str, **settings): """ Base dataprovider factory for all datatypes that returns the proper provider for the given `data_format` or raises a `NoProviderAvailable`. """ if self.has_dataprovider(data_format): return self.dataproviders[data_format](self, dataset, **settings) raise p_dataproviders.exceptions.NoProviderAvailable(self, data_format)
[docs] def validate(self, dataset: DatasetProtocol, **kwd) -> DatatypeValidation: return DatatypeValidation.unvalidated()
[docs] @p_dataproviders.decorators.dataprovider_factory("base") def base_dataprovider(self, dataset: DatasetProtocol, **settings) -> p_dataproviders.base.DataProvider: dataset_source = p_dataproviders.dataset.DatasetDataProvider(dataset) return p_dataproviders.base.DataProvider(dataset_source, **settings)
[docs] @p_dataproviders.decorators.dataprovider_factory("chunk", p_dataproviders.chunk.ChunkDataProvider.settings) def chunk_dataprovider(self, dataset: DatasetProtocol, **settings) -> p_dataproviders.chunk.ChunkDataProvider: dataset_source = p_dataproviders.dataset.DatasetDataProvider(dataset) return p_dataproviders.chunk.ChunkDataProvider(dataset_source, **settings)
[docs] @p_dataproviders.decorators.dataprovider_factory("chunk64", p_dataproviders.chunk.Base64ChunkDataProvider.settings) def chunk64_dataprovider( self, dataset: DatasetProtocol, **settings ) -> p_dataproviders.chunk.Base64ChunkDataProvider: dataset_source = p_dataproviders.dataset.DatasetDataProvider(dataset) return p_dataproviders.chunk.Base64ChunkDataProvider(dataset_source, **settings)
def _clean_and_set_mime_type(self, trans, mime: str, headers: Headers) -> None: if mime.lower() in XSS_VULNERABLE_MIME_TYPES: if not getattr(trans.app.config, "serve_xss_vulnerable_mimetypes", True): mime = DEFAULT_MIME_TYPE headers["content-type"] = mime
[docs] def handle_dataset_as_image(self, hda: DatasetProtocol) -> str: raise Exception("Unimplemented Method")
def __getstate__(self) -> Dict[str, Any]: state = self.__dict__.copy() state.pop("display_applications", None) return state
[docs]@p_dataproviders.decorators.has_dataproviders class Text(Data): edam_format = "format_2330" file_ext = "txt" line_class = "line" is_binary = False # Add metadata elements MetadataElement( name="data_lines", default=0, desc="Number of data lines", readonly=True, optional=True, visible=False, no_value=0, )
[docs] def get_mime(self) -> str: """Returns the mime type of the datatype""" return "text/plain"
[docs] def set_meta(self, dataset: DatasetProtocol, *, overwrite: bool = True, **kwd) -> None: """ Set the number of lines of data in dataset. """ dataset.metadata.data_lines = self.count_data_lines(dataset)
[docs] def estimate_file_lines(self, dataset: DatasetProtocol) -> Optional[int]: """ Perform a rough estimate by extrapolating number of lines from a small read. """ sample_size = 1048576 try: with compression_utils.get_fileobj(dataset.get_file_name()) as dataset_fh: dataset_read = dataset_fh.read(sample_size) sample_lines = dataset_read.count("\n") return int(sample_lines * (float(dataset.get_size()) / float(sample_size))) except UnicodeDecodeError: log.error(f"Unable to estimate lines in file {dataset.get_file_name()}") return None
[docs] def count_data_lines(self, dataset: HasFileName) -> Optional[int]: """ Count the number of lines of data in dataset, skipping all blank lines and comments. """ CHUNK_SIZE = 2**15 # 32Kb data_lines = 0 with compression_utils.get_fileobj(dataset.get_file_name()) as in_file: # FIXME: Potential encoding issue can prevent the ability to iterate over lines # causing set_meta process to fail otherwise OK jobs. A better solution than # a silent try/except is desirable. try: for line in iter_start_of_line(in_file, CHUNK_SIZE): line = line.strip() if line and not line.startswith("#"): data_lines += 1 except UnicodeDecodeError: log.error(f"Unable to count lines in file {dataset.get_file_name()}") return None return data_lines
[docs] def set_peek(self, dataset: DatasetProtocol, **kwd) -> None: """ Set the peek. This method is used by various subclasses of Text. """ line_count = kwd.get("line_count") width = kwd.get("width", 256) skipchars = kwd.get("skipchars") line_wrap = kwd.get("line_wrap", True) if not dataset.dataset.purged: # The file must exist on disk for the get_file_peek() method dataset.peek = get_file_peek(dataset.get_file_name(), width=width, skipchars=skipchars, line_wrap=line_wrap) if line_count is None: # See if line_count is stored in the metadata if dataset.metadata.data_lines: dataset.blurb = f"{util.commaify(str(dataset.metadata.data_lines))} {inflector.cond_plural(dataset.metadata.data_lines, self.line_class)}" else: # Number of lines is not known ( this should not happen ), and auto-detect is # needed to set metadata # This can happen when the file is larger than max_optional_metadata_filesize. if int(dataset.get_size()) <= 1048576: # Small dataset, recount all lines and reset peek afterward. lc = self.count_data_lines(dataset) if lc is not None: dataset.metadata.data_lines = lc dataset.blurb = f"{util.commaify(str(lc))} {inflector.cond_plural(lc, self.line_class)}" else: dataset.blurb = "Error: Cannot count lines in dataset" else: est_lines = self.estimate_file_lines(dataset) if est_lines is not None: dataset.blurb = f"~{util.commaify(util.roundify(str(est_lines)))} {inflector.cond_plural(est_lines, self.line_class)}" else: dataset.blurb = "Error: Cannot estimate lines in dataset" else: dataset.blurb = f"{util.commaify(str(line_count))} {inflector.cond_plural(line_count, self.line_class)}" else: dataset.peek = "file does not exist" dataset.blurb = "file purged from disk"
[docs] @classmethod def split(cls, input_datasets: List, subdir_generator_function: Callable, split_params: Dict) -> None: """ Split the input files by line. """ if split_params is None: return if len(input_datasets) > 1: raise Exception("Text file splitting does not support multiple files") input_files = [ds.get_file_name() for ds in input_datasets] lines_per_file = None chunk_size = None if split_params["split_mode"] == "number_of_parts": lines_per_file = [] # Computing the length is expensive! def _file_len(fname): with open(fname) as f: return sum(1 for _ in f) length = _file_len(input_files[0]) parts = int(split_params["split_size"]) if length < parts: parts = length len_each, remainder = divmod(length, parts) while length > 0: chunk = len_each if remainder > 0: chunk += 1 lines_per_file.append(chunk) remainder -= 1 length -= chunk elif split_params["split_mode"] == "to_size": chunk_size = int(split_params["split_size"]) else: raise Exception(f"Unsupported split mode {split_params['split_mode']}") f = open(input_files[0]) try: chunk_idx = 0 file_done = False part_file = None while not file_done: if lines_per_file is None: this_chunk_size = chunk_size elif chunk_idx < len(lines_per_file): this_chunk_size = lines_per_file[chunk_idx] chunk_idx += 1 lines_remaining = this_chunk_size part_file = None while lines_remaining > 0: a_line = f.readline() if a_line == "": file_done = True break if part_file is None: part_dir = subdir_generator_function() part_path = os.path.join(part_dir, os.path.basename(input_files[0])) part_file = open(part_path, "w") part_file.write(a_line) lines_remaining -= 1 except Exception as e: log.error("Unable to split files: %s", unicodify(e)) raise finally: f.close() if part_file: part_file.close()
# ------------- Dataproviders
[docs] @p_dataproviders.decorators.dataprovider_factory("line", p_dataproviders.line.FilteredLineDataProvider.settings) def line_dataprovider(self, dataset: DatasetProtocol, **settings) -> p_dataproviders.line.FilteredLineDataProvider: """ Returns an iterator over the dataset's lines (that have been stripped) optionally excluding blank lines and lines that start with a comment character. """ dataset_source = p_dataproviders.dataset.DatasetDataProvider(dataset) return p_dataproviders.line.FilteredLineDataProvider(dataset_source, **settings)
[docs] @p_dataproviders.decorators.dataprovider_factory("regex-line", p_dataproviders.line.RegexLineDataProvider.settings) def regex_line_dataprovider( self, dataset: DatasetProtocol, **settings ) -> p_dataproviders.line.RegexLineDataProvider: """ Returns an iterator over the dataset's lines optionally including/excluding lines that match one or more regex filters. """ dataset_source = p_dataproviders.dataset.DatasetDataProvider(dataset) return p_dataproviders.line.RegexLineDataProvider(dataset_source, **settings)
[docs]class Directory(Data): """Class representing a directory of files."""
[docs]class GenericAsn1(Text): """Class for generic ASN.1 text format""" edam_data = "data_0849" edam_format = "format_1966" file_ext = "asn1"
[docs]class LineCount(Text): """ Dataset contains a single line with a single integer that denotes the line count for a related dataset. Used for custom builds. """
[docs]class Newick(Text): """New Hampshire/Newick Format""" edam_data = "data_0872" edam_format = "format_1910" file_ext = "newick"
[docs] def sniff(self, filename: str) -> bool: """Returning false as the newick format is too general and cannot be sniffed.""" return False
[docs]@build_sniff_from_prefix class Nexus(Text): """Nexus format as used By Paup, Mr Bayes, etc""" edam_data = "data_0872" edam_format = "format_1912" file_ext = "nex"
[docs] def sniff_prefix(self, file_prefix: FilePrefix) -> bool: """All Nexus Files Simply puts a '#NEXUS' in its first line""" return file_prefix.string_io().read(6).upper() == "#NEXUS"
# ------------- Utility methods -------------- # nice_size used to be here, but to resolve cyclical dependencies it's been # moved to galaxy.util. It belongs there anyway since it's used outside # datatypes. nice_size = util.nice_size
[docs]def get_test_fname(fname): """Returns test data filename""" path = os.path.dirname(__file__) full_path = os.path.join(path, "test", fname) return full_path
[docs]def get_file_peek(file_name, width=256, line_count=5, skipchars=None, line_wrap=True): """ Returns the first line_count lines wrapped to width. >>> def assert_peek_is(file_name, expected, *args, **kwd): ... path = get_test_fname(file_name) ... peek = get_file_peek(path, *args, **kwd) ... assert peek == expected, "%s != %s" % (peek, expected) >>> assert_peek_is('0_nonewline', u'0') >>> assert_peek_is('0.txt', u'0\\n') >>> assert_peek_is('4.bed', u'chr22\\t30128507\\t31828507\\tuc003bnx.1_cds_2_0_chr22_29227_f\\t0\\t+\\n', line_count=1) >>> assert_peek_is('1.bed', u'chr1\\t147962192\\t147962580\\tCCDS989.1_cds_0_0_chr1_147962193_r\\t0\\t-\\nchr1\\t147984545\\t147984630\\tCCDS990.1_cds_0_0_chr1_147984546_f\\t0\\t+\\n', line_count=2) """ # Set size for file.readline() to a negative number to force it to # read until either a newline or EOF. Needed for datasets with very # long lines. if width == "unlimited": width = -1 if skipchars is None: skipchars = [] lines = [] count = 0 last_line_break = False with compression_utils.get_fileobj(file_name) as temp: while count < line_count: try: line = temp.readline(width) except UnicodeDecodeError: return "binary file" if line == "": break last_line_break = False if line.endswith("\n"): line = line[:-1] last_line_break = True elif not line_wrap: for i in file_reader(temp, 1): if i == "\n": last_line_break = True if not i or i == "\n": break skip_line = False for skipchar in skipchars: if line.startswith(skipchar): skip_line = True break if not skip_line: lines.append(line) count += 1 return "\n".join(lines) + ("\n" if last_line_break else "")