Data Structures

Werkzeug provides some subclasses of common Python objects to extend them with additional features. Some of them are used to make them immutable, others are used to change some semantics to better work with HTTP.

General Purpose

Changelog

Changed in version 0.6: The general purpose classes are now pickleable in each protocol as long as the contained objects are pickleable. This means that the FileMultiDict won’t be pickleable as soon as it contains a file.

class werkzeug.datastructures.TypeConversionDict

Works like a regular dict but the get() method can perform type conversions. MultiDict and CombinedMultiDict are subclasses of this class and provide the same feature.

Changelog

Added in version 0.5.

get(key: K) → V | None

get(key: K, default: V) → V

get(key: K, default: T) → V | T

get(key: str, type: Callable[[V], T]) → T | None

get(key: str, default: T, type: Callable[[V], T]) → T

Return the default value if the requested data doesn’t exist. If type is provided and is a callable it should convert the value, return it or raise a ValueError if that is not possible. In this case the function will return the default as if the value was not found:

>>> d = TypeConversionDict(foo='42', bar='blub')
>>> d.get('foo', type=int)
42
>>> d.get('bar', -1, type=int)
-1

Parameters:

• key – The key to be looked up.

• default – The default value to be returned if the key can’t be looked up. If not further specified None is returned.

• type – A callable that is used to cast the value in the MultiDict. If a ValueError or a TypeError is raised by this callable the default value is returned.

Changelog

Changed in version 3.0.2: Returns the default value on TypeError, too.

class werkzeug.datastructures.ImmutableTypeConversionDict

Works like a TypeConversionDict but does not support modifications.

Changelog

Added in version 0.5.

copy()

Return a shallow mutable copy of this object. Keep in mind that the standard library’s copy() function is a no-op for this class like for any other python immutable type (eg: tuple).

Return type:

TypeConversionDict[K, V]

class werkzeug.datastructures.MultiDict(mapping=None)

A MultiDict is a dictionary subclass customized to deal with multiple values for the same key which is for example used by the parsing functions in the wrappers. This is necessary because some HTML form elements pass multiple values for the same key.

MultiDict implements all standard dictionary methods. Internally, it saves all values for a key as a list, but the standard dict access methods will only return the first value for a key. If you want to gain access to the other values, too, you have to use the list methods as explained below.

Basic Usage:

>>> d = MultiDict([('a', 'b'), ('a', 'c')])
>>> d
MultiDict([('a', 'b'), ('a', 'c')])
>>> d['a']
'b'
>>> d.getlist('a')
['b', 'c']
>>> 'a' in d
True

It behaves like a normal dict thus all dict functions will only return the first value when multiple values for one key are found.

From Werkzeug 0.3 onwards, the KeyError raised by this class is also a subclass of the BadRequest HTTP exception and will render a page for a 400 BAD REQUEST if caught in a catch-all for HTTP exceptions.

A MultiDict can be constructed from an iterable of (key, value) tuples, a dict, a MultiDict or from Werkzeug 0.2 onwards some keyword parameters.

Parameters:

mapping (MultiDict[K, V] | cabc.Mapping[K, V | list[V] | tuple[V, ...] | set[V]] | cabc.Iterable[tuple[K, V]] | None) – the initial value for the MultiDict. Either a regular dict, an iterable of (key, value) tuples or None.

Changed in version 3.1: Implement | and |= operators.

add(key, value)

Adds a new value for the key.

Changelog

Added in version 0.6.

Parameters:

• key (K) – the key for the value.

• value (V) – the value to add.

Return type:

None

getlist(key: K) → list[V]

getlist(key: K, type: Callable[[V], T]) → list[T]

Return the list of items for a given key. If that key is not in the MultiDict, the return value will be an empty list. Just like get, getlist accepts a type parameter. All items will be converted with the callable defined there.

Parameters:

• key – The key to be looked up.

• type – Callable to convert each value. If a ValueError or TypeError is raised, the value is omitted.

Returns:

a list of all the values for the key.

Changed in version 3.1: Catches TypeError in addition to ValueError.

setlist(key, new_list)

Remove the old values for a key and add new ones. Note that the list you pass the values in will be shallow-copied before it is inserted in the dictionary.

>>> d = MultiDict()
>>> d.setlist('foo', ['1', '2'])
>>> d['foo']
'1'
>>> d.getlist('foo')
['1', '2']

Parameters:

• key (K) – The key for which the values are set.

• new_list (Iterable[V]) – An iterable with the new values for the key. Old values are removed first.

Return type:

None

setdefault(key: K) → None

setdefault(key: K, default: V) → V

Returns the value for the key if it is in the dict, otherwise it returns default and sets that value for key.

Parameters:

• key – The key to be looked up.

• default – The default value to be returned if the key is not in the dict. If not further specified it’s None.

setlistdefault(key, default_list=None)

Like setdefault but sets multiple values. The list returned is not a copy, but the list that is actually used internally. This means that you can put new values into the dict by appending items to the list:

>>> d = MultiDict({"foo": 1})
>>> d.setlistdefault("foo").extend([2, 3])
>>> d.getlist("foo")
[1, 2, 3]

Parameters:

• key (K) – The key to be looked up.

• default_list (Iterable[V] | None) – An iterable of default values. It is either copied (in case it was a list) or converted into a list before returned.

Returns:

a list

Return type:

list[V]

items(multi=False)

Return an iterator of (key, value) pairs.

Parameters:

multi (bool) – If set to True the iterator returned will have a pair for each value of each key. Otherwise it will only contain pairs for the first value of each key.

Return type:

Iterable[tuple[K, V]]

lists()

Return a iterator of (key, values) pairs, where values is the list of all values associated with the key.

Return type:

Iterable[tuple[K, list[V]]]

values()

Returns an iterator of the first value on every key’s value list.

Return type:

Iterable[V]

listvalues()

Return an iterator of all values associated with a key. Zipping keys() and this is the same as calling lists():

>>> d = MultiDict({"foo": [1, 2, 3]})
>>> zip(d.keys(), d.listvalues()) == d.lists()
True

Return type:

Iterable[list[V]]

copy()

Return a shallow copy of this object.

Return type:

te.Self

deepcopy(memo=None)

Return a deep copy of this object.

Parameters:

memo (t.Any)

Return type:

te.Self

to_dict() → dict[K, V]

to_dict(flat: Literal[False]) → dict[K, list[V]]

Return the contents as regular dict. If flat is True the returned dict will only have the first item present, if flat is False all values will be returned as lists.

Parameters:

flat – If set to False the dict returned will have lists with all the values in it. Otherwise it will only contain the first value for each key.

Returns:

a dict

update(mapping)

update() extends rather than replaces existing key lists:

>>> a = MultiDict({'x': 1})
>>> b = MultiDict({'x': 2, 'y': 3})
>>> a.update(b)
>>> a
MultiDict([('y', 3), ('x', 1), ('x', 2)])

If the value list for a key in other_dict is empty, no new values will be added to the dict and the key will not be created:

>>> x = {'empty_list': []}
>>> y = MultiDict()
>>> y.update(x)
>>> y
MultiDict([])

Parameters:

mapping (MultiDict[K, V] | Mapping[K, V | list[V] | tuple[V, ...] | set[V]] | Iterable[tuple[K, V]])

Return type:

None

pop(key: K) → V

pop(key: K, default: V) → V

pop(key: K, default: T) → V | T

Pop the first item for a list on the dict. Afterwards the key is removed from the dict, so additional values are discarded:

>>> d = MultiDict({"foo": [1, 2, 3]})
>>> d.pop("foo")
1
>>> "foo" in d
False

Parameters:

• key – the key to pop.

• default – if provided the value to return if the key was not in the dictionary.

popitem()

Pop an item from the dict.

Return type:

tuple[K, V]

poplist(key)

Pop the list for a key from the dict. If the key is not in the dict an empty list is returned.

Changelog

Changed in version 0.5: If the key does no longer exist a list is returned instead of raising an error.

Parameters:

key (K)

Return type:

list[V]

popitemlist()

Pop a (key, list) tuple from the dict.

Return type:

tuple[K, list[V]]

clear() → None.  Remove all items from D.

classmethod fromkeys(iterable, value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, type=None)

Return the default value if the requested data doesn’t exist. If type is provided and is a callable it should convert the value, return it or raise a ValueError if that is not possible. In this case the function will return the default as if the value was not found:

>>> d = TypeConversionDict(foo='42', bar='blub')
>>> d.get('foo', type=int)
42
>>> d.get('bar', -1, type=int)
-1

Parameters:

• key (K) – The key to be looked up.

• default (V | T | None) – The default value to be returned if the key can’t be looked up. If not further specified None is returned.

• type (Callable[[V], T] | None) – A callable that is used to cast the value in the MultiDict. If a ValueError or a TypeError is raised by this callable the default value is returned.

Return type:

V | T | None

Changelog

Changed in version 3.0.2: Returns the default value on TypeError, too.

keys() → a set-like object providing a view on D's keys

class werkzeug.datastructures.OrderedMultiDict

Works like a regular MultiDict but preserves the order of the fields. To convert the ordered multi dict into a list you can use the items() method and pass it multi=True.

In general an OrderedMultiDict is an order of magnitude slower than a MultiDict.

note

Due to a limitation in Python you cannot convert an ordered multi dict into a regular dict by using dict(multidict). Instead you have to use the to_dict() method, otherwise the internal bucket objects are exposed.

Deprecated since version 3.1: Will be removed in Werkzeug 3.2. Use MultiDict instead.

class werkzeug.datastructures.ImmutableMultiDict

An immutable OrderedMultiDict.

Deprecated since version 3.1: Will be removed in Werkzeug 3.2. Use ImmutableMultiDict instead.

Changelog

Added in version 0.6.

werkzeug.datastructures.ImmutableOrderedMultiDict

alias of _ImmutableOrderedMultiDict

class werkzeug.datastructures.CombinedMultiDict(dicts=None)

A read only MultiDict that you can pass multiple MultiDict instances as sequence and it will combine the return values of all wrapped dicts:

>>> from werkzeug.datastructures import CombinedMultiDict, MultiDict
>>> post = MultiDict([('foo', 'bar')])
>>> get = MultiDict([('blub', 'blah')])
>>> combined = CombinedMultiDict([get, post])
>>> combined['foo']
'bar'
>>> combined['blub']
'blah'

This works for all read operations and will raise a TypeError for methods that usually change data which isn’t possible.

From Werkzeug 0.3 onwards, the KeyError raised by this class is also a subclass of the BadRequest HTTP exception and will render a page for a 400 BAD REQUEST if caught in a catch-all for HTTP exceptions.

Parameters:

dicts (cabc.Iterable[MultiDict[K, V]] | None)

class werkzeug.datastructures.ImmutableDict

An immutable dict.

Changelog

Added in version 0.5.

copy()

Return a shallow mutable copy of this object. Keep in mind that the standard library’s copy() function is a no-op for this class like for any other python immutable type (eg: tuple).

Return type:

dict[K, V]

class werkzeug.datastructures.ImmutableList(iterable=(), /)

An immutable list.

Changelog

Added in version 0.5.

Private:

class werkzeug.datastructures.FileMultiDict(mapping=None)

A special MultiDict that has convenience methods to add files to it. This is used for EnvironBuilder and generally useful for unittesting.

Changelog

Added in version 0.5.

Parameters:

mapping (MultiDict[K, V] | cabc.Mapping[K, V | list[V] | tuple[V, ...] | set[V]] | cabc.Iterable[tuple[K, V]] | None)

add_file(name, file, filename=None, content_type=None)

Adds a new file to the dict. file can be a file name or a file-like or a FileStorage object.

Parameters:

• name (str) – the name of the field.

• file (str | PathLike[str] | IO[bytes] | FileStorage) – a filename or file-like object

• filename (str | None) – an optional filename

• content_type (str | None) – an optional content type

Return type:

None

HTTP Related

class werkzeug.datastructures.Headers([defaults])

An object that stores some headers. It has a dict-like interface, but is ordered, can store the same key multiple times, and iterating yields (key, value) pairs instead of only keys.

This data structure is useful if you want a nicer way to handle WSGI headers which are stored as tuples in a list.

From Werkzeug 0.3 onwards, the KeyError raised by this class is also a subclass of the BadRequest HTTP exception and will render a page for a 400 BAD REQUEST if caught in a catch-all for HTTP exceptions.

Headers is mostly compatible with the Python wsgiref.headers.Headers class, with the exception of __getitem__. wsgiref will return None for headers['missing'], whereas Headers will raise a KeyError.

To create a new Headers object, pass it a list, dict, or other Headers object with default values. These values are validated the same way values added later are.

Parameters:

defaults (Headers | MultiDict[str, t.Any] | cabc.Mapping[str, t.Any | list[t.Any] | tuple[t.Any, ...] | set[t.Any]] | cabc.Iterable[tuple[str, t.Any]] | None) – The list of default values for the Headers.

Changed in version 3.1: Implement | and |= operators.

Changelog

Changed in version 2.1.0: Default values are validated the same as values added later.

Changed in version 0.9: This data structure now stores unicode values similar to how the multi dicts do it. The main difference is that bytes can be set as well which will automatically be latin1 decoded.

Changed in version 0.9: The linked() function was removed without replacement as it was an API that does not support the changes to the encoding model.

get(key: str) → str | None

get(key: str, default: str) → str

get(key: str, default: T) → str | T

get(key: str, type: Callable[[str], T]) → T | None

get(key: str, default: T, type: Callable[[str], T]) → T

Return the default value if the requested data doesn’t exist. If type is provided and is a callable it should convert the value, return it or raise a ValueError if that is not possible. In this case the function will return the default as if the value was not found:

>>> d = Headers([('Content-Length', '42')])
>>> d.get('Content-Length', type=int)
42

Parameters:

• key – The key to be looked up.

• default – The default value to be returned if the key can’t be looked up. If not further specified None is returned.

• type – A callable that is used to cast the value in the Headers. If a ValueError is raised by this callable the default value is returned.

Changelog

Changed in version 3.0: The as_bytes parameter was removed.

Changed in version 0.9: The as_bytes parameter was added.

getlist(key: str) → list[str]

getlist(key: str, type: Callable[[str], T]) → list[T]

Return the list of items for a given key. If that key is not in the Headers, the return value will be an empty list. Just like get(), getlist() accepts a type parameter. All items will be converted with the callable defined there.

Parameters:

• key – The key to be looked up.

• type – A callable that is used to cast the value in the Headers. If a ValueError is raised by this callable the value will be removed from the list.

Returns:

a list of all the values for the key.

Changelog

Changed in version 3.0: The as_bytes parameter was removed.

Changed in version 0.9: The as_bytes parameter was added.

get_all(name)

Return a list of all the values for the named field.

This method is compatible with the wsgiref get_all() method.

Parameters:

name (str)

Return type:

list[str]

extend(arg=None, /, **kwargs)

Extend headers in this object with items from another object containing header items as well as keyword arguments.

To replace existing keys instead of extending, use update() instead.

If provided, the first argument can be another Headers object, a MultiDict, dict, or iterable of pairs.

Changelog

Changed in version 1.0: Support MultiDict. Allow passing kwargs.

Parameters:

• arg (Headers | MultiDict[str, Any] | Mapping[str, Any | list[Any] | tuple[Any, ...] | set[Any]] | Iterable[tuple[str, Any]] | None)

• kwargs (str)

Return type:

None

remove(key)

Remove a key.

Parameters:

key (str) – The key to be removed.

Return type:

None

pop() → tuple[str, str]

pop(key: str) → str

pop(key: int | None = None) → tuple[str, str]

pop(key: str, default: str) → str

pop(key: str, default: T) → str | T

Removes and returns a key or index.

Parameters:

key – The key to be popped. If this is an integer the item at that position is removed, if it’s a string the value for that key is. If the key is omitted or None the last item is removed.

Returns:

an item.

popitem()

Removes a key or index and returns a (key, value) item.

Return type:

tuple[str, str]

add(key, value, /, **kwargs)

Add a new header tuple to the list.

Keyword arguments can specify additional parameters for the header value, with underscores converted to dashes:

>>> d = Headers()
>>> d.add('Content-Type', 'text/plain')
>>> d.add('Content-Disposition', 'attachment', filename='foo.png')

The keyword argument dumping uses dump_options_header() behind the scenes.

Changelog

Changed in version 0.4.1: keyword arguments were added for wsgiref compatibility.

Parameters:

• key (str)

• value (Any)

• kwargs (Any)

Return type:

None

add_header(key, value, /, **kwargs)

Add a new header tuple to the list.

An alias for add() for compatibility with the wsgiref add_header() method.

Parameters:

• key (str)

• value (Any)

• kwargs (Any)

Return type:

None

clear()

Clears all headers.

Return type:

None

set(key, value, /, **kwargs)

Remove all header tuples for key and add a new one. The newly added key either appears at the end of the list if there was no entry or replaces the first one.

Keyword arguments can specify additional parameters for the header value, with underscores converted to dashes. See add() for more information.

Changelog

Changed in version 0.6.1: set() now accepts the same arguments as add().

Parameters:

• key (str) – The key to be inserted.

• value (Any) – The value to be inserted.

• kwargs (Any)

Return type:

None

setlist(key, values)

Remove any existing values for a header and add new ones.

Parameters:

• key (str) – The header key to set.

• values (Iterable[Any]) – An iterable of values to set for the key.

Return type:

None

Changelog

Added in version 1.0.

setdefault(key, default)

Return the first value for the key if it is in the headers, otherwise set the header to the value given by default and return that.

Parameters:

• key (str) – The header key to get.

• default (Any) – The value to set for the key if it is not in the headers.

Return type:

str

setlistdefault(key, default)

Return the list of values for the key if it is in the headers, otherwise set the header to the list of values given by default and return that.

Unlike MultiDict.setlistdefault(), modifying the returned list will not affect the headers.

Parameters:

• key (str) – The header key to get.

• default (Iterable[Any]) – An iterable of values to set for the key if it is not in the headers.

Return type:

list[str]

Changelog

Added in version 1.0.

update(arg=None, /, **kwargs)

Replace headers in this object with items from another headers object and keyword arguments.

To extend existing keys instead of replacing, use extend() instead.

If provided, the first argument can be another Headers object, a MultiDict, dict, or iterable of pairs.

Changelog

Added in version 1.0.

Parameters:

• arg (Headers | MultiDict[str, Any] | Mapping[str, Any | list[Any] | tuple[Any, ...] | Set[Any]] | Iterable[tuple[str, Any]] | None)

• kwargs (Any | list[Any] | tuple[Any, ...] | Set[Any])

Return type:

None

to_wsgi_list()

Convert the headers into a list suitable for WSGI.

Returns:

list

Return type:

list[tuple[str, str]]

class werkzeug.datastructures.EnvironHeaders(environ)

Read only version of the headers from a WSGI environment. This provides the same interface as Headers and is constructed from a WSGI environment. From Werkzeug 0.3 onwards, the KeyError raised by this class is also a subclass of the BadRequest HTTP exception and will render a page for a 400 BAD REQUEST if caught in a catch-all for HTTP exceptions.

Parameters:

environ (WSGIEnvironment)

class werkzeug.datastructures.HeaderSet(headers=None, on_update=None)

Similar to the ETags class this implements a set-like structure. Unlike ETags this is case insensitive and used for vary, allow, and content-language headers.

If not constructed using the parse_set_header() function the instantiation works like this:

>>> hs = HeaderSet(['foo', 'bar', 'baz'])
>>> hs
HeaderSet(['foo', 'bar', 'baz'])

Parameters:

• headers (cabc.Iterable[str] | None)

• on_update (cabc.Callable[[te.Self], None] | None)

add(header)

Add a new header to the set.

Parameters:

header (str)

Return type:

None

remove(header)

Remove a header from the set. This raises an KeyError if the header is not in the set.

Changelog

Changed in version 0.5: In older versions a IndexError was raised instead of a KeyError if the object was missing.

Parameters:

• header (str) – the header to be removed.

• self (te.Self)

Return type:

None

update(iterable)

Add all the headers from the iterable to the set.

Parameters:

• iterable (cabc.Iterable[str]) – updates the set with the items from the iterable.

• self (te.Self)

Return type:

None

discard(header)

Like remove() but ignores errors.

Parameters:

header (str) – the header to be discarded.

Return type:

None

find(header)

Return the index of the header in the set or return -1 if not found.

Parameters:

header (str) – the header to be looked up.

Return type:

int

index(header)

Return the index of the header in the set or raise an IndexError.

Parameters:

header (str) – the header to be looked up.

Return type:

int

clear()

Clear the set.

Parameters:

self (te.Self)

Return type:

None

as_set(preserve_casing=False)

Return the set as real python set type. When calling this, all the items are converted to lowercase and the ordering is lost.

Parameters:

preserve_casing (bool) – if set to True the items in the set returned will have the original case like in the HeaderSet, otherwise they will be lowercase.

Return type:

set[str]

to_header()

Convert the header set into an HTTP header string.

Return type:

str

class werkzeug.datastructures.Accept(values=())

An Accept object is just a list subclass for lists of (value, quality) tuples. It is automatically sorted by specificity and quality.

All Accept objects work similar to a list but provide extra functionality for working with the data. Containment checks are normalized to the rules of that header:

>>> a = CharsetAccept([('ISO-8859-1', 1), ('utf-8', 0.7)])
>>> a.best
'ISO-8859-1'
>>> 'iso-8859-1' in a
True
>>> 'UTF8' in a
True
>>> 'utf7' in a
False

To get the quality for an item you can use normal item lookup:

>>> print a['utf-8']
0.7
>>> a['utf7']
0

Changelog

Changed in version 1.0.0: Accept internal values are no longer ordered alphabetically for equal quality tags. Instead the initial order is preserved.

Changed in version 0.5: Accept objects are forced immutable now.

Parameters:

values (Accept | cabc.Iterable[tuple[str, float]] | None)

quality(key)

Returns the quality of the key.

Changelog

Added in version 0.6: In previous versions you had to use the item-lookup syntax (eg: obj[key] instead of obj.quality(key))

Parameters:

key (str)

Return type:

float

index(key)

Get the position of an entry or raise ValueError.

Parameters:

key (str | tuple[str, float]) – The key to be looked up.

Return type:

int

Changelog

Changed in version 0.5: This used to raise IndexError, which was inconsistent with the list API.

find(key)

Get the position of an entry or return -1.

Parameters:

key (str | tuple[str, float]) – The key to be looked up.

Return type:

int

values()

Iterate over all values.

Return type:

Iterator[str]

to_header()

Convert the header set into an HTTP header string.

Return type:

str

best_match(matches: Iterable[str]) → str | None

best_match(matches: Iterable[str], default: str = None) → str

Returns the best match from a list of possible matches based on the specificity and quality of the client. If two items have the same quality and specificity, the one is returned that comes first.

Parameters:

• matches – a list of matches to check for

• default – the value that is returned if none match

property best: str | None

The best match as value.

class werkzeug.datastructures.MIMEAccept(values=())

Like Accept but with special methods and behavior for mimetypes.

Parameters:

values (Accept | cabc.Iterable[tuple[str, float]] | None)

property accept_html: bool

True if this object accepts HTML.

property accept_xhtml: bool

True if this object accepts XHTML.

property accept_json: bool

True if this object accepts JSON.

class werkzeug.datastructures.CharsetAccept(values=())

Like Accept but with normalization for charsets.

Parameters:

values (Accept | cabc.Iterable[tuple[str, float]] | None)

class werkzeug.datastructures.LanguageAccept(values=())

Like Accept but with normalization for language tags.

Parameters:

values (Accept | cabc.Iterable[tuple[str, float]] | None)

class werkzeug.datastructures.RequestCacheControl(values=(), on_update=None)

A cache control for requests. This is immutable and gives access to all the request-relevant cache control headers.

To get a header of the RequestCacheControl object again you can convert the object into a string or call the to_header() method. If you plan to subclass it and add your own items have a look at the sourcecode for that class.

Changed in version 3.1: Dict values are always str | None. Setting properties will convert the value to a string. Setting a non-bool property to False is equivalent to setting it to None. Getting typed properties will return None if conversion raises ValueError, rather than the string.

Changed in version 3.1: max_age is None if present without a value, rather than -1.

Changed in version 3.1: no_cache is a boolean, it is True instead of "*" when present.

Changed in version 3.1: max_stale is True if present without a value, rather than "*".

Changed in version 3.1: no_transform is a boolean. Previously it was mistakenly always None.

Changed in version 3.1: min_fresh is None if present without a value, rather than "*".

Changelog

Changed in version 2.1: Setting int properties such as max_age will convert the value to an int.

Added in version 0.5: Response-only properties are not present on this request class.

Parameters:

• values (cabc.Mapping[str, t.Any] | cabc.Iterable[tuple[str, t.Any]] | None)

• on_update (cabc.Callable[[_CacheControl], None] | None)

static cache_property(key, empty, type, *, doc=None)

Return a new property object for a cache header. Useful if you want to add support for a cache extension in a subclass.

Parameters:

• key (str) – The attribute name present in the parsed cache-control header dict.

• empty (Any) – The value to use if the key is present without a value.

• type (type[Any] | None) – The type to convert the string value to instead of a string. If conversion raises a ValueError, the returned value is None.

• doc (str | None) – The docstring for the property. If not given, it is generated based on the other params.

Return type:

Any

Changed in version 3.1: Added the doc param.

Changelog

Changed in version 2.0: Renamed from cache_property.

copy() → a shallow copy of D

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

to_header()

Convert the stored values into a cache control header.

Return type:

str

values() → an object providing a view on D's values

property max_age

The max-age attribute. A int, or None if not present.

property max_stale

The max-stale attribute. A int, True if present with no value, or None if not present.

property min_fresh

The min-fresh attribute. A int, or None if not present.

property no_cache

The no-cache attribute. A bool, either present or not.

property no_store

The no-store attribute. A bool, either present or not.

property no_transform

The no-transform attribute. A bool, either present or not.

property only_if_cached

The only-if-cached attribute. A bool, either present or not.

property stale_if_error

The stale-if-error attribute. A int, or None if not present.

class werkzeug.datastructures.ResponseCacheControl(values=(), on_update=None)

A cache control for responses. Unlike RequestCacheControl this is mutable and gives access to response-relevant cache control headers.

To get a header of the ResponseCacheControl object again you can convert the object into a string or call the to_header() method. If you plan to subclass it and add your own items have a look at the sourcecode for that class.

Changed in version 3.1: Dict values are always str | None. Setting properties will convert the value to a string. Setting a non-bool property to False is equivalent to setting it to None. Getting typed properties will return None if conversion raises ValueError, rather than the string.

Changed in version 3.1: no_cache is True if present without a value, rather than "*".

Changed in version 3.1: private is True if present without a value, rather than "*".

Changed in version 3.1: no_transform is a boolean. Previously it was mistakenly always None.

Changed in version 3.1: Added the must_understand, stale_while_revalidate, and stale_if_error properties.

Changelog

Changed in version 2.1.1: s_maxage converts the value to an int.

Changed in version 2.1: Setting int properties such as max_age will convert the value to an int.

Added in version 0.5: Request-only properties are not present on this response class.

Parameters:

• values (cabc.Mapping[str, t.Any] | cabc.Iterable[tuple[str, t.Any]] | None)

• on_update (cabc.Callable[[_CacheControl], None] | None)

static cache_property(key, empty, type, *, doc=None)

Return a new property object for a cache header. Useful if you want to add support for a cache extension in a subclass.

Parameters:

• key (str) – The attribute name present in the parsed cache-control header dict.

• empty (Any) – The value to use if the key is present without a value.

• type (type[Any] | None) – The type to convert the string value to instead of a string. If conversion raises a ValueError, the returned value is None.

• doc (str | None) – The docstring for the property. If not given, it is generated based on the other params.

Return type:

Any

Changed in version 3.1: Added the doc param.

Changelog

Changed in version 2.0: Renamed from cache_property.

clear() → None.  Remove all items from D.

Return type:

None

copy() → a shallow copy of D

classmethod fromkeys(iterable, value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

pop(k[, d]) → v, remove specified key and return the corresponding value.

If the key is not found, return the default if given; otherwise, raise a KeyError.

Parameters:

• self (te.Self)

• key (K)

• default (V | T)

Return type:

V | T

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

Return type:

tuple[K, V]

setdefault(key, default=None)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

Parameters:

• self (te.Self)

• key (K)

• default (V | None)

Return type:

V

to_header()

Convert the stored values into a cache control header.

Return type:

str

update([E, ]**F) → None.  Update D from dict/iterable E and F.

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

Parameters:

• arg (Mapping[K, V] | Iterable[tuple[K, V]] | None)

• kwargs (V)

Return type:

None

values() → an object providing a view on D's values

property immutable

The immutable attribute. A bool, either present or not.

property max_age

The max-age attribute. A int, or None if not present.

property must_revalidate

The must-revalidate attribute. A bool, either present or not.

property must_understand

The must-understand attribute. A bool, either present or not.

property no_cache

The no-cache attribute. A str, True if present with no value, or None if not present.

property no_store

The no-store attribute. A bool, either present or not.

property no_transform

The no-transform attribute. A bool, either present or not.

property private

The private attribute. A str, True if present with no value, or None if not present.

property proxy_revalidate

The proxy-revalidate attribute. A bool, either present or not.

property public

The public attribute. A bool, either present or not.

property s_maxage

The s-maxage attribute. A int, or None if not present.

property stale_if_error

The stale-if-error attribute. A int, or None if not present.

property stale_while_revalidate

The stale-while-revalidate attribute. A int, or None if not present.

class werkzeug.datastructures.ETags(strong_etags=None, weak_etags=None, star_tag=False)

A set that can be used to check if one etag is present in a collection of etags.

Parameters:

• strong_etags (cabc.Iterable[str] | None)

• weak_etags (cabc.Iterable[str] | None)

• star_tag (bool)

as_set(include_weak=False)

Convert the ETags object into a python set. Per default all the weak etags are not part of this set.

Parameters:

include_weak (bool)

Return type:

set[str]

is_weak(etag)

Check if an etag is weak.

Parameters:

etag (str)

Return type:

bool

is_strong(etag)

Check if an etag is strong.

Parameters:

etag (str)

Return type:

bool

contains_weak(etag)

Check if an etag is part of the set including weak and strong tags.

Parameters:

etag (str)

Return type:

bool

contains(etag)

Check if an etag is part of the set ignoring weak tags. It is also possible to use the in operator.

Parameters:

etag (str)

Return type:

bool

contains_raw(etag)

When passed a quoted tag it will check if this tag is part of the set. If the tag is weak it is checked against weak and strong tags, otherwise strong only.

Parameters:

etag (str)

Return type:

bool

to_header()

Convert the etags set into a HTTP header string.

Return type:

str

class werkzeug.datastructures.Authorization(auth_type, data=None, token=None)

Represents the parts of an Authorization request header.

Request.authorization returns an instance if the header is set.

An instance can be used with the test Client request methods’ auth parameter to send the header in test requests.

Depending on the auth scheme, either parameters or token will be set. The Basic scheme’s token is decoded into the username and password parameters.

For convenience, auth["key"] and auth.key both access the key in the parameters dict, along with auth.get("key") and "key" in auth.

Changelog

Changed in version 2.3: The token parameter and attribute was added to support auth schemes that use a token instead of parameters, such as Bearer.

Changed in version 2.3: The object is no longer a dict.

Changed in version 0.5: The object is an immutable dict.

Parameters:

• auth_type (str)

• data (dict[str, str | None] | None)

• token (str | None)

type

The authorization scheme, like basic, digest, or bearer.

parameters

A dict of parameters parsed from the header. Either this or token will have a value for a given scheme.

token

A token parsed from the header. Either this or parameters will have a value for a given scheme.

Changelog

Added in version 2.3.

classmethod from_header(value)

Parse an Authorization header value and return an instance, or None if the value is empty.

Parameters:

value (str | None) – The header value to parse.

Return type:

te.Self | None

Changelog

Added in version 2.3.

to_header()

Produce an Authorization header value representing this data.

Changelog

Added in version 2.0.

Return type:

str

class werkzeug.datastructures.WWWAuthenticate(auth_type, values=None, token=None)

Represents the parts of a WWW-Authenticate response header.

Set Response.www_authenticate to an instance of list of instances to set values for this header in the response. Modifying this instance will modify the header value.

Depending on the auth scheme, either parameters or token should be set. The Basic scheme will encode username and password parameters to a token.

For convenience, auth["key"] and auth.key both act on the parameters dict, and can be used to get, set, or delete parameters. auth.get("key") and "key" in auth are also provided.

Changelog

Changed in version 2.3: The token parameter and attribute was added to support auth schemes that use a token instead of parameters, such as Bearer.

Changed in version 2.3: The object is no longer a dict.

Changed in version 2.3: The on_update parameter was removed.

Parameters:

• auth_type (str)

• values (dict[str, str | None] | None)

• token (str | None)

property type: str

The authorization scheme, like basic, digest, or bearer.

property parameters: dict[str, str | None]

A dict of parameters for the header. Only one of this or token should have a value for a given scheme.

property token: str | None

A dict of parameters for the header. Only one of this or token should have a value for a given scheme.

classmethod from_header(value)

Parse a WWW-Authenticate header value and return an instance, or None if the value is empty.

Parameters:

value (str | None) – The header value to parse.

Return type:

te.Self | None

Changelog

Added in version 2.3.

to_header()

Produce a WWW-Authenticate header value representing this data.

Return type:

str

class werkzeug.datastructures.IfRange(etag=None, date=None)

Very simple object that represents the If-Range header in parsed form. It will either have neither a etag or date or one of either but never both.

Changelog

Added in version 0.7.

Parameters:

• etag (str | None)

• date (datetime | None)

etag

The etag parsed and unquoted. Ranges always operate on strong etags so the weakness information is not necessary.

date

The date in parsed format or None.

to_header()

Converts the object back into an HTTP header.

Return type:

str

class werkzeug.datastructures.Range(units, ranges)

Represents a Range header. All methods only support only bytes as the unit. Stores a list of ranges if given, but the methods only work if only one range is provided.

Raises:

ValueError – If the ranges provided are invalid.

Parameters:

• units (str)

• ranges (cabc.Sequence[tuple[int, int | None]])

Changelog

Changed in version 0.15: The ranges passed in are validated.

Added in version 0.7.

units

The units of this range. Usually “bytes”.

ranges

A list of (begin, end) tuples for the range header provided. The ranges are non-inclusive.

range_for_length(length)

If the range is for bytes, the length is not None and there is exactly one range and it is satisfiable it returns a (start, stop) tuple, otherwise None.

Parameters:

length (int | None)

Return type:

tuple[int, int] | None

make_content_range(length)

Creates a ContentRange object from the current range and given content length.

Parameters:

length (int | None)

Return type:

ContentRange | None

to_header()

Converts the object back into an HTTP header.

Return type:

str

to_content_range_header(length)

Converts the object into Content-Range HTTP header, based on given length

Parameters:

length (int | None)

Return type:

str | None

class werkzeug.datastructures.ContentRange(units, start, stop, length=None, on_update=None)

Represents the content range header.

Changelog

Added in version 0.7.

Parameters:

• units (str | None)

• start (int | None)

• stop (int | None)

• length (int | None)

• on_update (cabc.Callable[[ContentRange], None] | None)

units: str | None

The units to use, usually “bytes”

start: int | None

The start point of the range or None.

stop: int | None

The stop point of the range (non-inclusive) or None. Can only be None if also start is None.

length: int | None

The length of the range or None.

set(start, stop, length=None, units='bytes')

Simple method to update the ranges.

Parameters:

• start (int | None)

• stop (int | None)

• length (int | None)

• units (str | None)

Return type:

None

unset()

Sets the units to None which indicates that the header should no longer be used.

Return type:

None

Others

class werkzeug.datastructures.FileStorage(stream=None, filename=None, name=None, content_type=None, content_length=None, headers=None)

The FileStorage class is a thin wrapper over incoming files. It is used by the request object to represent uploaded files. All the attributes of the wrapper stream are proxied by the file storage so it’s possible to do storage.read() instead of the long form storage.stream.read().

Parameters:

• stream (t.IO[bytes] | None)

• filename (str | None)

• name (str | None)

• content_type (str | None)

• content_length (int | None)

• headers (Headers | None)

stream

The input stream for the uploaded file. This usually points to an open temporary file.

filename

The filename of the file on the client. Can be a str, or an instance of os.PathLike.

name

The name of the form field.

headers

The multipart headers as Headers object. This usually contains irrelevant information but in combination with custom multipart requests the raw headers might be interesting.

Changelog

Added in version 0.6.

property content_type: str | None

The content-type sent in the header. Usually not available

property content_length: int

The content-length sent in the header. Usually not available

property mimetype: str

Like content_type, but without parameters (eg, without charset, type etc.) and always lowercase. For example if the content type is text/HTML; charset=utf-8 the mimetype would be 'text/html'.

Changelog

Added in version 0.7.

property mimetype_params: dict[str, str]

The mimetype parameters as dict. For example if the content type is text/html; charset=utf-8 the params would be {'charset': 'utf-8'}.

Changelog

Added in version 0.7.

save(dst, buffer_size=16384)

Save the file to a destination path or file object. If the destination is a file object you have to close it yourself after the call. The buffer size is the number of bytes held in memory during the copy process. It defaults to 16KB.

For secure file saving also have a look at secure_filename().

Parameters:

• dst (str | PathLike[str] | IO[bytes]) – a filename, os.PathLike, or open file object to write to.

• buffer_size (int) – Passed as the length parameter of shutil.copyfileobj().

Return type:

None

Changelog

Changed in version 1.0: Supports pathlib.

close()

Close the underlying file if possible.

Return type:

None