Source code for

Module defining input/output interfaces to HoloViews.

There are two components for input/output:

Exporters: Process (composite) HoloViews objects one at a time. For
           instance, an exporter may render a HoloViews object as a
           svg or perhaps pickle it.

Archives: A collection of HoloViews objects that are first collected
          then processed together. For instance, collecting HoloViews
          objects for a report then generating a PDF or collecting
          HoloViews objects to dump to HDF5.
from __future__ import absolute_import

import re, os, time, string, zipfile, tarfile, shutil, itertools, pickle
from collections import defaultdict

from io import BytesIO
from hashlib import sha256

import param
from param.parameterized import bothmethod

from .dimension import LabelledData
from .element import Collator, Element
from .overlay import Overlay, Layout
from .ndmapping import OrderedDict, NdMapping, UniformNdMapping
from .options import Store
from .util import unique_iterator, group_sanitizer, label_sanitizer

[docs]def sanitizer(name, replacements=[(':','_'), ('/','_'), ('\\','_')]): """ String sanitizer to avoid problematic characters in filenames. """ for old,new in replacements: name = name.replace(old,new) return name
[docs]class Reference(param.Parameterized): """ A Reference allows access to an object to be deferred until it is needed in the appropriate context. References are used by Collector to capture the state of an object at collection time. One particularly important property of references is that they should be pickleable. This means that you can pickle Collectors so that you can unpickle them in different environments and still collect from the required object. A Reference only needs to have a resolved_type property and a resolve method. The constructor will take some specification of where to find the target object (may be the object itself). """ @property def resolved_type(self): """ Returns the type of the object resolved by this references. If multiple types are possible, the return is a tuple of types. """ raise NotImplementedError
[docs] def resolve(self, container=None): """ Return the referenced object. Optionally, a container may be passed in from which the object is to be resolved. """ raise NotImplementedError
[docs]class Exporter(param.ParameterizedFunction): """ An Exporter is a parameterized function that accepts a HoloViews object and converts it to a new some new format. This mechanism is designed to be very general so here are a few examples: Pickling: Native Python, supported by HoloViews. Rendering: Any plotting backend may be used (default uses matplotlib) Storage: Saving to a database (e.g SQL), HDF5 etc. """ # Mime-types that need encoding as utf-8 upon export utf8_mime_types = ['image/svg+xml', 'text/html', 'text/json'] key_fn = param.Callable(doc=""" Function that generates the metadata key from the HoloViews object being saved. The metadata key is a single high-dimensional key of values associated with dimension labels. The returned dictionary must have string keys and simple literals that may be conviently used for dictionary-style indexing. Returns an empty dictionary by default.""") info_fn = param.Callable(lambda x: {'repr':repr(x)}, doc=""" Function that generates additional metadata information from the HoloViews object being saved. Unlike metadata keys, the information returned may be unsuitable for use as a key index and may include entries such as the object's repr. Regardless, the info metadata should still only contain items that will be quick to load and inspect. """)
[docs] @classmethod def encode(cls, entry): """ Classmethod that applies conditional encoding based on mime-type. Given an entry as returned by __call__ return the data in the appropriate encoding. """ (data, info) = entry if info['mime_type'] in cls.utf8_mime_types: return data.encode('utf-8') else: return data
@bothmethod def _filename(self_or_cls, filename): "Add the file extension if not already present" if not filename.endswith(self_or_cls.file_ext): return '%s.%s' % (filename, self_or_cls.file_ext) else: return filename @bothmethod def _merge_metadata(self_or_cls, obj, fn, *dicts): """ Returns a merged metadata info dictionary from the supplied function and additional dictionaries """ merged = dict([(k,v) for d in dicts for (k,v) in d.items()]) return dict(merged, **fn(obj)) if fn else merged def __call__(self, obj, fmt=None): """ Given a HoloViews object return the raw exported data and corresponding metadata as the tuple (data, metadata). The metadata should include: 'file-ext' : The file extension if applicable (else empty string) 'mime_type': The mime-type of the data. The fmt argument may be used with exporters that support multiple output formats. If not supplied, the exporter is to pick an appropriate format automatically. """ raise NotImplementedError("Exporter not implemented.")
[docs] @bothmethod def save(self_or_cls, obj, basename, fmt=None, key={}, info={}, **kwargs): """ Similar to the call method except saves exporter data to disk into a file with specified basename. For exporters that support multiple formats, the fmt argument may also be supplied (which typically corresponds to the file-extension). The supplied metadata key and info dictionaries will be used to update the output of the relevant key and info functions which is then saved (if supported). """ raise NotImplementedError("Exporter save method not implemented.")
[docs]class Importer(param.ParameterizedFunction): """ An Importer is a parameterized function that accepts some data in some format and returns a HoloViews object. This mechanism is designed to be very general so here are a few examples: Unpickling: Native Python, supported by HoloViews. Servers: Loading data over a network connection. Storage: Loading from a database (e.g SQL), HDF5 etc. """ def __call__(self, data): """ Given raw data in the appropriate format return the corresponding HoloViews object. Acts as the inverse of Exporter when supplied the data portion of an Exporter's output. """ raise NotImplementedError("Importer not implemented.")
[docs] @bothmethod def load(self_or_cls, src, entries=None): """ Given some source (e.g. a filename, a network connection etc), return the loaded HoloViews object. """ raise NotImplementedError("Importer load method not implemented.")
@bothmethod def loader(self_or_cls, kwargs): return self_or_cls.load(**kwargs)
[docs] @bothmethod def info(self_or_cls, src): """ Returns the 'info' portion of the metadata (if available). """ raise NotImplementedError("Importer info method not implemented.")
[docs] @bothmethod def key(self_or_cls, src): """ Returns the metadata key (if available). """ raise NotImplementedError("Importer keys method not implemented.")
[docs]class Serializer(Exporter): "A generic exporter that supports any arbitrary serializer" serializer=param.Callable(Store.dumps, doc=""" The serializer function, set to Store.dumps by default. The serializer should take an object and output a serialization as a string or byte stream. Any suitable serializer may be used. For instance, pickle.dumps may be used although this will not save customized options.""") mime_type=param.String('application/python-pickle', allow_None=True, doc=""" The mime-type associated with the serializer (if applicable).""") file_ext = param.String('pkl', doc=""" The file extension associated with the corresponding file format (if applicable).""") def __call__(self, obj, **kwargs): data = self.serializer(obj) return data, {'file-ext': self.file_ext, 'mime_type':self.mime_type} @bothmethod def save(self_or_cls, obj, filename, info={}, key={}, **kwargs): data, base_info = self_or_cls(obj, **kwargs) key = self_or_cls._merge_metadata(obj, self_or_cls.key_fn, key) info = self_or_cls._merge_metadata(obj, self_or_cls.info_fn, info, base_info) metadata, _ = self_or_cls({'info':info, 'key':key}, **kwargs) filename = self_or_cls._filename(filename) with open(filename, 'ab') as f: f.write(metadata) f.write(data)
[docs]class Deserializer(Importer): "A generic importer that supports any arbitrary de-serializer." deserializer=param.Callable(Store.load, doc=""" The deserializer function, set to Store.load by default. The deserializer should take a file-like object that can be read from until the first object has been deserialized. If the file has not been exhausted, the deserializer should be able to continue parsing and loading objects. Any suitable deserializer may be used. For instance, pickle.load may be used although this will not load customized options.""") def __call__(self, data): return self.deserializer(BytesIO(data)) @bothmethod def load(self_or_cls, filename): with open(filename, 'rb') as f: data = self_or_cls.deserializer(f) try: data = self_or_cls.deserializer(f) except: pass return data @bothmethod def key(self_or_cls, filename): with open(filename, "rb") as f: metadata = self_or_cls.deserializer(f) metadata = metadata if isinstance(metadata, dict) else {} return metadata.get('key', {}) @bothmethod def info(self_or_cls, filename): with open(filename, "rb") as f: metadata = self_or_cls.deserializer(f) metadata = metadata if isinstance(metadata, dict) else {} return metadata.get('info', {})
[docs]class Pickler(Exporter): """ The recommended pickler for serializing HoloViews object to a .hvz file (a simple zip archive of pickle files). In addition to the functionality offered by Store.dump and Store.load, this file format offers three additional features: 1. Optional (zip) compression. 2. Ability to save and load components of a Layout independently. 3. Support for metadata per saved component. The output file with the .hvz file extension is simply a zip archive containing pickled HoloViews objects. """ protocol = param.Integer(default=2, doc=""" The pickling protocol where 0 is ASCII, 1 supports old Python versions and 2 is efficient for new style classes.""") compress = param.Boolean(default=True, doc=""" Whether compression is enabled or not""") mime_type = 'application/zip' file_ext = 'hvz' def __call__(self, obj, key={}, info={}, **kwargs): buff = BytesIO(), buff, key=key, info=info, **kwargs) return, {'file-ext': 'hvz', 'mime_type':self.mime_type} @bothmethod def save(self_or_cls, obj, filename, key={}, info={}, **kwargs): base_info = {'file-ext': 'hvz', 'mime_type':self_or_cls.mime_type} key = self_or_cls._merge_metadata(obj, self_or_cls.key_fn, key) info = self_or_cls._merge_metadata(obj, self_or_cls.info_fn, info, base_info) compression = zipfile.ZIP_STORED if self_or_cls.compress else zipfile.ZIP_DEFLATED filename = self_or_cls._filename(filename) if isinstance(filename, str) else filename with zipfile.ZipFile(filename, 'w', compression=compression) as f: if isinstance(obj, Layout) and not isinstance(obj, Overlay): entries = ['.'.join(k) for k in] components = list( entries = entries if len(entries) > 1 else [entries[0]+'(L)'] else: entries = ['%s.%s' % (group_sanitizer(, False), label_sanitizer(obj.label, False))] components = [obj] for component, entry in zip(components, entries): f.writestr(entry, Store.dumps(component, protocol=self_or_cls.protocol)) f.writestr('metadata', pickle.dumps({'info':info, 'key':key}))
[docs]class Unpickler(Importer): """ The inverse of Pickler used to load the .hvz file format which is simply a zip archive of pickle objects. Unlike a regular pickle file, info and key metadata as well as individual components of a Layout may be loaded without needing to load the entire file into memory. The components that may be individually loaded may be found using the entries method. """ def __call__(self, data, entries=None): buff = BytesIO(data) return self.load(buff, entries=entries) @bothmethod def load(self_or_cls, filename, entries=None): components, single_layout = [], False entries = entries if entries else self_or_cls.entries(filename) with zipfile.ZipFile(filename, 'r') as f: for entry in entries: if entry not in f.namelist(): raise Exception("Entry %s not available" % entry) components.append(Store.loads( single_layout = entry.endswith('(L)') if len(components) == 1 and not single_layout: return components[0] else: return Layout.from_values(components) @bothmethod def _load_metadata(self_or_cls, filename, name): with zipfile.ZipFile(filename, 'r') as f: if 'metadata' not in f.namelist(): raise Exception("No metadata available") metadata = pickle.loads('metadata')) if name not in metadata: raise KeyError("Entry %s is missing from the metadata" % name) return metadata[name] @bothmethod def key(self_or_cls, filename): return self_or_cls._load_metadata(filename, 'key') @bothmethod def info(self_or_cls, filename): return self_or_cls._load_metadata(filename, 'info') @bothmethod def entries(self_or_cls, filename): with zipfile.ZipFile(filename, 'r') as f: return [el for el in f.namelist() if el != 'metadata']
[docs] @bothmethod def collect(self_or_cls, files, drop=[], metadata=True): """ Given a list or NdMapping type containing file paths return a Layout of Collators, which can be called to load a given set of files using the current Importer. If supplied as a list each file is expected to disambiguate itself with contained metadata. If an NdMapping type is supplied additional key dimensions may be supplied as long as they do not clash with the file metadata. Any key dimension may be dropped by name by supplying a drop argument. """ aslist = not isinstance(files, (NdMapping, Element)) if isinstance(files, Element): files = Collator(files) file_kdims = files.kdims else: file_kdims = files.kdims drop_extra = files.drop if isinstance(files, Collator) else [] mdata_dims = [] if metadata: fnames = [fname[0] if isinstance(fname, tuple) else fname for fname in files.values()] mdata_dims = {kdim for fname in fnames for kdim in self_or_cls.key(fname).keys()} file_dims = set(files.dimensions('key', label=True)) added_dims = set(mdata_dims) - file_dims overlap_dims = file_dims & set(mdata_dims) kwargs = dict(kdims=file_kdims + sorted(added_dims), vdims=['filename', 'entries'], value_transform=self_or_cls.loader, drop=drop_extra + drop) layout_data = defaultdict(lambda: Collator(None, **kwargs)) for key, fname in fname = fname[0] if isinstance(fname, tuple) else fname mdata = self_or_cls.key(fname) if metadata else {} for odim in overlap_dims: kval = key[files.get_dimension_index(odim)] if kval != mdata[odim]: raise KeyError("Metadata supplies inconsistent " "value for dimension %s" % odim) mkey = tuple(mdata.get(d, None) for d in added_dims) key = mkey if aslist else key + mkey if isinstance(fname, tuple) and len(fname) == 1: (fname,) = fname for entry in self_or_cls.entries(fname): layout_data[entry][key] = (fname, [entry]) return Layout(layout_data.items())
[docs]class Archive(param.Parameterized): """ An Archive is a means to collect and store a collection of HoloViews objects in any number of different ways. Examples of possible archives: * Generating tar or zip files (compressed or uncompressed). * Collating a report or document (e.g. PDF, HTML, LaTex). * Storing a collection of HoloViews objects to a database or HDF5. """ exporters= param.List(default=[], doc=""" The exporter functions used to convert HoloViews objects into the appropriate format(s).""" )
[docs] def add(self, obj, *args, **kwargs): """ Add a HoloViews object to the archive. """ raise NotImplementedError
[docs] def export(self,*args, **kwargs): """ Finalize and close the archive. """ raise NotImplementedError
[docs]def simple_name_generator(obj): """ Simple name_generator designed for HoloViews objects. Objects are labeled with {group}-{label} for each nested object, based on a depth-first search. Adjacent objects with identical representations yield only a single copy of the representation, to avoid long names for the common case of a container whose element(s) share the same group and label. """ if isinstance(obj, LabelledData): labels = obj.traverse(lambda x: ( + ('-' +x.label if x.label else ''))) labels=[l[0] for l in itertools.groupby(labels)] obj_str = ','.join(labels) else: obj_str = repr(obj) return obj_str
[docs]class FileArchive(Archive): """ A file archive stores files on disk, either unpacked in a directory or in an archive format (e.g. a zip file). """ exporters= param.List(default=[Pickler], doc=""" The exporter functions used to convert HoloViews objects into the appropriate format(s).""") dimension_formatter = param.String("{name}_{range}", doc=""" A string formatter for the output file based on the supplied HoloViews objects dimension names and values. Valid fields are the {name}, {range} and {unit} of the dimensions.""") object_formatter = param.Callable(default=simple_name_generator, doc=""" Callable that given an object returns a string suitable for inclusion in file and directory names. This is what generates the value used in the {obj} field of the filename formatter.""") filename_formatter = param.String('{dimensions},{obj}', doc=""" A string formatter for output filename based on the HoloViews object that is being rendered to disk. The available fields are the {type}, {group}, {label}, {obj} of the holoviews object added to the archive as well as {timestamp}, {obj} and {SHA}. The {timestamp} is the export timestamp using timestamp_format, {obj} is the object representation as returned by object_formatter and {SHA} is the SHA of the {obj} value used to compress it into a shorter string.""") timestamp_format = param.String("%Y_%m_%d-%H_%M_%S", doc=""" The timestamp format that will be substituted for the {timestamp} field in the export name.""") root = param.String('.', doc=""" The root directory in which the output directory is located. May be an absolute or relative path.""") archive_format = param.ObjectSelector('zip', objects=['zip', 'tar'], doc=""" The archive format to use if there are multiple files and pack is set to True. Supported formats include 'zip' and 'tar'.""") pack = param.Boolean(default=False, doc=""" Whether or not to pack to contents into the specified archive format. If pack is False, the contents will be output to a directory. Note that if there is only a single file in the archive, no packing will occur and no directory is created. Instead, the file is treated as a single-file archive.""") export_name = param.String(default='{timestamp}', doc=""" The name assigned to the overall export. If an archive file is used, this is the correspond filename (e.g of the exporter zip file). Alternatively, if unpack=False, this is the name of the output directory. Lastly, for archives of a single file, this is the basename of the output file. The {timestamp} field is available to include the timestamp at the time of export in the chosen timestamp format.""") unique_name = param.Boolean(default=False, doc=""" Whether the export name should be made unique with a numeric suffix. If set to False, any existing export of the same name will be removed and replaced.""") max_filename = param.Integer(default=100, bounds=(0,None), doc=""" Maximum length to enforce on generated filenames. 100 is the practical maximum for zip and tar file generation, but you may wish to use a lower value to avoid long filenames.""") flush_archive = param.Boolean(default=True, doc=""" Flushed the contents of the archive after export. """) ffields = {'type', 'group', 'label', 'obj', 'SHA', 'timestamp', 'dimensions'} efields = {'timestamp'}
[docs] @classmethod def parse_fields(cls, formatter): "Returns the format fields otherwise raise exception" if formatter is None: return [] try: parse = list(string.Formatter().parse(formatter)) return set(f for f in list(zip(*parse))[1] if f is not None) except: raise SyntaxError("Could not parse formatter %r" % formatter)
def __init__(self, **params): super(FileArchive, self).__init__(**params) # Items with key: (basename,ext) and value: (data, info) self._files = OrderedDict() self._validate_formatters() def _dim_formatter(self, obj): if not obj: return '' key_dims = obj.traverse(lambda x: x.kdims, [UniformNdMapping]) constant_dims = obj.traverse(lambda x: x.cdims) dims = [] map(dims.extend, key_dims + constant_dims) dims = unique_iterator(dims) dim_strings = [] for dim in dims: lower, upper = obj.range( lower, upper = (dim.pprint_value(lower), dim.pprint_value(upper)) if lower == upper: range = dim.pprint_value(lower) else: range = "%s-%s" % (lower, upper) formatters = {'name':, 'range': range, 'unit': dim.unit} dim_strings.append(self.dimension_formatter.format(**formatters)) return '_'.join(dim_strings) def _validate_formatters(self): if not self.parse_fields(self.filename_formatter).issubset(self.ffields): raise Exception("Valid filename fields are: %s" % ','.join(sorted(self.ffields))) elif not self.parse_fields(self.export_name).issubset(self.efields): raise Exception("Valid export fields are: %s" % ','.join(sorted(self.efields))) try: time.strftime(self.timestamp_format, tuple(time.localtime())) except: raise Exception("Timestamp format invalid")
[docs] def add(self, obj=None, filename=None, data=None, info={}, **kwargs): """ If a filename is supplied, it will be used. Otherwise, a filename will be generated from the supplied object. Note that if the explicit filename uses the {timestamp} field, it will be formatted upon export. The data to be archived is either supplied explicitly as 'data' or automatically rendered from the object. """ if [filename, obj] == [None, None]: raise Exception("Either filename or a HoloViews object is " "needed to create an entry in the archive.") elif obj is None and not self.parse_fields(filename).issubset({'timestamp'}): raise Exception("Only the {timestamp} formatter may be used unless an object is supplied.") elif [obj, data] == [None, None]: raise Exception("Either an object or explicit data must be " "supplied to create an entry in the archive.") elif data and 'mime_type' not in info: raise Exception("The mime-type must be supplied in the info dictionary " "when supplying data directly") self._validate_formatters() entries = [] if data is None: for exporter in self.exporters: rendered = exporter(obj) if rendered is None: continue (data, new_info) = rendered info = dict(info, **new_info) entries.append((data, info)) else: entries.append((data, info)) for (data, info) in entries: self._add_content(obj, data, info, filename=filename)
def _add_content(self, obj, data, info, filename=None): (unique_key, ext) = self._compute_filename(obj, info, filename=filename) self._files[(unique_key, ext)] = (data, info) def _compute_filename(self, obj, info, filename=None): if filename is None: hashfn = sha256() obj_str = 'None' if obj is None else self.object_formatter(obj) dimensions = self._dim_formatter(obj) dimensions = dimensions if dimensions else '' hashfn.update(obj_str.encode('utf-8')) label = sanitizer(getattr(obj, 'label', 'no-label')) group = sanitizer(getattr(obj, 'group', 'no-group')) format_values = {'timestamp': '{timestamp}', 'dimensions': dimensions, 'group': group, 'label': label, 'type': obj.__class__.__name__, 'obj': sanitizer(obj_str), 'SHA': hashfn.hexdigest()} filename = self._format(self.filename_formatter, dict(info, **format_values)) filename = self._normalize_name(filename) ext = info.get('file-ext', '') (unique_key, ext) = self._unique_name(filename, ext, self._files.keys(), force=True) return (unique_key, ext) def _zip_archive(self, export_name, files, root): archname = '.'.join(self._unique_name(export_name, 'zip', root)) with zipfile.ZipFile(os.path.join(root, archname), 'w') as zipf: for (basename, ext), entry in files: filename = self._truncate_name(basename, ext) zipf.writestr(('%s/%s' % (export_name, filename)),Exporter.encode(entry)) def _tar_archive(self, export_name, files, root): archname = '.'.join(self._unique_name(export_name, 'tar', root)) with tarfile.TarFile(os.path.join(root, archname), 'w') as tarf: for (basename, ext), entry in files: filename = self._truncate_name(basename, ext) tarinfo = tarfile.TarInfo('%s/%s' % (export_name, filename)) filedata = Exporter.encode(entry) tarinfo.size = len(filedata) tarf.addfile(tarinfo, BytesIO(filedata)) def _single_file_archive(self, export_name, files, root): ((basename, ext), entry) = files[0] full_fname = '%s_%s' % (export_name, basename) (unique_name, ext) = self._unique_name(full_fname, ext, root) filename = self._truncate_name(self._normalize_name(unique_name), ext=ext) fpath = os.path.join(root, filename) with open(fpath, 'wb') as f: f.write(Exporter.encode(entry)) def _directory_archive(self, export_name, files, root): output_dir = os.path.join(root, self._unique_name(export_name,'', root)[0]) if os.path.isdir(output_dir): shutil.rmtree(output_dir) os.makedirs(output_dir) for (basename, ext), entry in files: filename = self._truncate_name(basename, ext) fpath = os.path.join(output_dir, filename) with open(fpath, 'wb') as f: f.write(Exporter.encode(entry)) def _unique_name(self, basename, ext, existing, force=False): """ Find a unique basename for a new file/key where existing is either a list of (basename, ext) pairs or an absolute path to a directory. By default, uniqueness is enforced depending on the state of the unique_name parameter (for export names). If force is True, this parameter is ignored and uniqueness is guaranteed. """ skip = False if force else (not self.unique_name) if skip: return (basename, ext) ext = '' if ext is None else ext if isinstance(existing, str): split = [os.path.splitext(el) for el in os.listdir(os.path.abspath(existing))] existing = [(n, ex if not ex else ex[1:]) for (n, ex) in split] new_name, counter = basename, 1 while (new_name, ext) in existing: new_name = basename+'-'+str(counter) counter += 1 return (sanitizer(new_name), ext) def _truncate_name(self, basename, ext='', tail=10, join='...', maxlen=None): maxlen = self.max_filename if maxlen is None else maxlen max_len = maxlen-len(ext) if len(basename) > max_len: start = basename[:max_len-(tail + len(join))] end = basename[-tail:] basename = start + join + end filename = '%s.%s' % (basename, ext) if ext else basename return filename def _normalize_name(self, basename): basename=re.sub('-+','-',basename) basename=re.sub('^[-,_]','',basename) return basename.replace(' ', '_')
[docs] def export(self, timestamp=None, info={}): """ Export the archive, directory or file. """ tval = tuple(time.localtime()) if timestamp is None else timestamp tstamp = time.strftime(self.timestamp_format, tval) info = dict(info, timestamp=tstamp) export_name = self._format(self.export_name, info) files = [((self._format(base, info), ext), val) for ((base, ext), val) in self._files.items()] root = os.path.abspath(self.root) # Make directory and populate if multiple files and not packed if len(self) > 1 and not self.pack: self._directory_archive(export_name, files, root) elif len(files) == 1: self._single_file_archive(export_name, files, root) elif self.archive_format == 'zip': self._zip_archive(export_name, files, root) elif self.archive_format == 'tar': self._tar_archive(export_name, files, root) if self.flush_archive: self._files = OrderedDict()
def _format(self, formatter, info): filtered = {k:v for k,v in info.items() if k in self.parse_fields(formatter)} return formatter.format(**filtered) def __len__(self): "The number of files currently specified in the archive" return len(self._files) def __repr__(self): return self.pprint()
[docs] def contents(self, maxlen=70): "Print the current (unexported) contents of the archive" lines = [] if len(self._files) == 0: print("Empty %s" % self.__class__.__name__) return fnames = [self._truncate_name(maxlen=maxlen, *k) for k in self._files] max_len = max([len(f) for f in fnames]) for name,v in zip(fnames, self._files.values()): mime_type = v[1].get('mime_type', 'no mime type') lines.append('%s : %s' % (name.ljust(max_len), mime_type)) print('\n'.join(lines))
[docs] def listing(self): "Return a list of filename entries currently in the archive" return ['.'.join([f,ext]) if ext else f for (f,ext) in self._files.keys()]