Sequences and Map Types¶

The following sections describe the sequence and mapping types that are built into Zerynth.

Iterator Types¶

Python supports a concept of iteration over containers. This is implemented using two distinct methods; these are used to allow user-defined classes to support iteration.

One method needs to be defined for container objects to provide iteration support:

container.__iter__()

Return an iterator object. The object is required to support the iterator protocol described below.

iterator objects themselves are required to support the following two methods, which together form the iterator protocol:

iterator.\__iter__()

Return the iterator object itself. This is required to allow both containersand iterators to be used with the for and in statements.

iterator.\__next__()

Return the next item from the container. If there are no further items, raise the StopIteration exception.

Once an iterator’s __next__() method raisesStopIteration, it must continue to do so on subsequent calls. Implementations that do not obey this property are deemed broken.

Sequence Types¶

There are three basic sequence types: lists, tuples, and range objects. Additional sequence types tailored for processing of binary data and text strings are described in dedicated sections.

Common Sequence Operations¶

The operations in the following table are supported by most sequence types,both mutable and immutable.

This table lists the sequence operations sorted in ascending priority. In the table, n, i, j and are sequences of the same type, n, i, j and k are integers and is an arbitrary object that meets any type and value restrictions imposed by s.

The in and not in operations have the same priorities as thecomparison operations. The + (concatenation) and * (repetition)operations have the same priority as the corresponding numeric operations.

Sequences of the same type also support comparisons. In particular, tuples and lists are compared lexicographically by comparing corresponding elements.This means that to compare equal, every element must compare equal and the two sequences must be of the same type and have the same length.

Notes:

1. While the in and not in operations are used only for simple containment testing in the general case, some specialised sequences(such as str(), bytes() and bytearray()) also use them for subsequence testing:

 >>> "gg" in "eggs"
True

1. Values of n less than 0 are treated as 0 (which yields an empty sequence of the same type as s). Note that items in the sequence s are not copied; they are referenced multiple times. This often haunts new Python programmers; consider:

>>> lists = [[]] * 3
>>> lists
[[], [], []]
>>> lists[0].append(3)
>>> lists
[[3], [3], [3]]

What has happened is that [[]] is a one-element list containing an empty list, so all three elements of [[]] * 3 are references to this single empty list. Modifying any of the elements of lists modifies this single list.You can create a list of different lists this way:

>>> lists = [[] for i in range(3)]
>>> lists[0].append(3)
>>> lists[1].append(5)
>>> lists[2].append(7)
>>> lists
[[3], [5], [7]]

1. If i or j is negative, the index is relative to the end of the string:len(s) + i or len(s) + j is substituted. But note that -0 isstill 0.

2. The slice of s from i to is defined as the sequence of items with index k such that i <= k < j. If i or j,i or is greater than len(s), uselen(s). If i is comitted or None, use 0. If j is omitted or None, use len(s). If i is greater than or equal to j, the slice is empty.

3. The slice of s from i to j with step k is defined as the sequence of items with index x = i + n*k such that 0 <= n < (j-i)/k. In other words,the indices are i, i+k, i+2*k, i+3*k and so on, stopping when j is reached (but never including j). If i or j). If is greater thanlen(s), use len(s). If i or j are omitted or None, they become“end” values (which end depends on the sign of k). Note, k cannot be zero. If isNone, it is treated like1`.

4. Concatenating immutable sequences always results in a new object. This means that building up a sequence by repeated concatenation will have a quadratic runtime cost in the total sequence length. To get a linear runtime cost, you must switch to one of the alternatives below:

   • if concatenating str() objects, you can build a list and usestr.join() at the end.

   • if concatenating bytes() objects, you can similarly usebytes.join() or you can do in-place concatenation with a bytearray() object. bytearray()objects are mutable and have an efficient overallocation mechanism

   • if concatenating tuple() objects, extend a list() instead

   • for other types, investigate the relevant class documentation

5. Some sequence types (such as range()) only support item sequences that follow specific patterns, and hence don’t support sequence concatenation or repetition.

6. index raises ValueError when x is not found in s. When supported, the additional arguments to the index method allow efficient searching of subsections of the sequence. Passing the extra arguments is roughly equivalent to using s[i:j].index(x), only without copying any data and with the returned index being relative to the start of the sequence rather than the start of the slice.

Immutable Sequence Types¶

The only feature that immutable sequence types generally implement that is not also implemented by mutable sequence types is hashing support.

This support allows immutable sequences, such as tuple() instances, to be used as dict() keys and stored in set() and frozenset()instances.

Attempting to hash an immutable sequence that contains unhashable values will result in TypeError.

Mutable Sequence Types¶

The operations in the following table are defined on mutable sequence types.

In the table s is an instance of a mutable sequence type, t is arbitrary object and x is an arbitrary object that meets any type and value restrictions imposed by s (for example, bytearray() only accepts integers that meet the value restriction 0 <= x <= 255).

Notes:

1. t must have the same length as the slice it is replacing.
2. The optional argument i defaults to -1, so that by default the last item is removed and returned.
3. remove raises ValueError when x is not found in s.
4. The reverse() method modifies the sequence in place for economy of space when reversing a large sequence. To remind users that it operates by side effect, it does not return the reversed sequence.
5. clear() and copy() are included for consistency with the interfaces of mutable containers that don’t support slicing operations(such as dict() and set())
6. The value n is an integer. Zero and negative values of n clear the sequence. Items in the sequence are not copied; they are referenced multiple times, as explained for s * n.

Lists¶

Lists are mutable sequences, typically used to store collections of homogeneous items (where the precise degree of similarity will vary by application).

Lists may be constructed in several ways:

• Using a pair of square brackets to denote the empty list: []
• Using square brackets, separating items with commas: [a], [a, b, c]
• Using a list comprehension: [x for x in iterable]

Lists implement all of the common and mutable sequence operations.

Tuples¶

Tuples are immutable sequences, typically used to store collections of heterogeneous data (such as the 2-tuples produced by the enumerate()built-in). Tuples are also used for cases where an immutable sequence of homogeneous data is needed.

Tuples may be constructed in a number of ways:

• Using a pair of parentheses to denote the empty tuple: ()
• Using a trailing comma for a singleton tuple: a, or (a,)
• Separating items with commas: a, b, c or (a, b, c)

Tuples implement all of the common sequence operations.

Ranges¶

The range type represents an immutable sequence of numbers and is commonly used for looping a specific number of times in forloops.

class range(stop) class range(start,stop[,step] )

The arguments to the range constructor must be integers. If the step argument is omitted, it defaults to 1. If the start argument is omitted, it defaults to 0. If step is zero, ValueError is raised.

For a positive st, the contents of a range r are determined by the formula r[i] = start + step*i where i >= 0 andr[i] < stop.

For a negative *step, the contents of the range are still determined by the formula r[i] = start + step*i, but the constraints are i >= 0and r[i] > stop.

A range object will be empty if r[0] does not meet the value constraint. Ranges do support negative indices, but these are interpreted as indexing from the end of the sequence determined by the positive indices.

Ranges implement all of the common sequence operations except concatenation and repetition (due to the fact that range objects can only represent sequences that follow a strict pattern and repetition and concatenation will usually violate that pattern).

The advantage of the range() type over a regular list() ortuple() is that a range() object will always take the same(small) amount of memory, no matter the size of the range it represents (as it only stores the start,stop and step values, calculating individual items and sub ranges as needed).

Testing range objects for equality with == and != compares them as sequences. That is, two range objects are considered equal if they represent the same sequence of values. (Note that two range objects that compare equal might have different start, stop and step attributes, for examplerange(0) == range(2, 1, 3) or range(0, 3, 2) == range(0, 4, 2).)

Strings¶

Textual data in Python is handled with strin.. Strings are immutable sequences of 8 bit characters. Zerynth does not support Unicode yet. String literals are written in a variety of ways:

• Single quotes: 'allows embedded "double" quotes'
• Double quotes: "allows embedded 'single' quotes".
• Triple quoted: '''Three single quotes''', """Three double quotes"""

Triple quoted strings may span multiple lines - all associated white space will be included in the string literal.

String literals that are part of a single expression and have only white space between them will be implicitly converted to a single string literal. That is, ("spam " "eggs") == "spam eggs".

Strings may also be created from other objects using the strbuiltin.

Since there is no separate “character” type, indexing a string produces strings of length 1. That is, for a non-empty string s, s[0] == s[0:1].

There is also no mutable string type, but str.join() can be used to efficiently construct strings from multiple fragments.

class str(object='')

Return a string version of object. If *object is not provided, returns the empty string. Returns object.__str__(), which is the “informal” or nicely printable string representation of *object. For string objects, this is the string itself. If *object does not have a __str__() method, then str() raises TypeError.

String Methods¶

Strings implement all of the common sequence operations, along with the additional methods described below.

Strings also support string formatting based on C printf style formatting..

str.count(sub[,start[,end] ])

Return the number of non-overlapping occurrences of substring sub in the range [start]. Optional arguments start and *end are interpreted as in slice notation.

str.endswith(suffix[,start[,end] ])

Return True if the string ends with the specified suffix, otherwise return False. With optional *start`, test beginning at that position. With optional *end, stop comparing at that position.

str.find(sub[,start[,end] ])

Return the lowest index in the string where substring sub is found within the slice s[start:end]. Optional arguments start and end are interpreted as in slice notation. Return -1 if sub is not found.

str.index(sub[,start[,end] ])

Like find(), but raise ValueError when the substring is not found.

str.join(iterable)

Return a string which is the concatenation of the strings in the iterable iterableiterable must be a builtin sequence or builtin map. A TypeErrorwill be raised if there are any non-string values in *iterable, excluding byte and byterray objects that are treated as strings. The separator between elements is the string providing this method.

str.lower()

Return a copy of the string with all the cased characters converted to lowercase.

str.replace(old,new)

Return a copy of the string with all occurrences of substring old replaced by new.

str.split(sep=None, maxsplit=-1)

Return a list of the words in the string, using sep as the delimiter string. If *maxsplit is given, at most *maxsplit splits are done (thus, the list will have at most maxsplit+1 elements). If *maxsplit is not specified or -1, then there is no limit on the number of splits (all possible splits are made).

If sep is given, consecutive delimiters are not grouped together and are deemed to delimit empty strings (for example, '1,,2'.split(',') returns ['1', '', '2']). The sep argument may consist of multiple characters (for example, '1<>2<>3'.split('<>') returns ['1', '2', '3']). Splitting an empty string with a specified separator returns [''].

For example:

>>> '1,2,3'.split(',')
['1', '2', '3']
>>> '1,2,3'.split(',', maxsplit=1)
['1', '2,3']
>>> '1,2,,3,'.split(',')
['1', '2', '', '3', '']

If sep is not specified, a different splitting algorithm is applied: runs of consecutive whites pace are regarded as a single separator, and the result will contain no empty strings at the start or end if the string has leading or trailing white space. Consequently, splitting an empty string or a string consisting of just white space with a None separator returns [].

For example:

>>> '1 2 3'.split()
['1', '2', '3']
>>> '1 2 3'.split(maxsplit=1)
['1', '2 3']
>>> '   1   2   3   '.split()
['1', '2', '3']

str.startswith(prefix[,start[,end] ])

Return True if string starts with the prefix, otherwise return False. With optional start test string beginning at that position. With optional end, stop comparing string at that position.

str.strip([chars[,dir=0] ])

Return a copy of the string with the leading and trailing characters removed. The chars argument is a string specifying the set of characters to be removed. If omitted, the chars argument defaults to removing whitespace. The chars argument is not a prefix or suffix; rather, all combinations of its values are stripped:

>>> '   spacious   '.strip()
'spacious'
>>> 'www.example.com'.strip('cmowz.')
'example'

The dir parameter controls the side of stripping:

• dir=0, strip chars from left and right side of str
• dir>0, strip chars from left side of str
• dir<0, strip chars from right side of str

upper()

Return a copy of the string with all the cased characters converted to uppercase.

printf-style String Formatting¶

String objects have one unique built-in operation: the % operator (modulo). This is also known as the string formatting or interpolation* operator. Given format % values (where *format is a string), % conversion specifications in *format are replaced with zero or more elements of *valuesThe effect is similar to using the sprintf() in the C language.

If format requires a single argument, values may be a single non-tuple object. Otherwise, values must be a tuple or list with exactly the number of items specified by the format string, or a single dictionary.

A conversion specifier contains two or more characters and has the following components, which must occur in this order:

1. The '%' character, which marks the start of the specifier.
2. Mapping key (optional), consisting of a parenthesised sequence of characters (for example, (somename)).
3. Conversion flags (optional), which affect the result of some conversion types.
4. Minimum field width (optional). If specified as an '*' (asterisk), the actual width is read from the next element of the tuple in values, and the object to convert comes after the minimum field width and optional precision.
5. Precision (optional), given as a '.' (dot) followed by the precision. If specified as '*' (an asterisk), the actual precision is read from the next element of the tuple in values, and the value to convert comes after the precision.
6. Conversion type.

When the right argument is a dictionary (or other mapping type), then the formats in the string must include a parenthesized mapping key into that dictionary inserted immediately after the '%' character. The mapping key selects the value to be formatted from the mapping.

For example:

>>> print('%(language)s has %(number)03d quote types.' %
...       {'language': "Python", "number": 2})
Python has 002 quote types.

In this case no * specifiers may occur in a format (since they require a sequential parameter list).

The conversion flag characters are:

Binary Sequence Types¶

The core built-in types for manipulating binary data are bytes() and bytearray().

Bytes¶

Bytes objects are immutable sequences of single bytes. Bytes are very similar to strings in Zerynth, except that when iterating over them, integers are generated instead of strings.

Firstly, the syntax for bytes literals is largely the same as that for string literals, except that a b prefix is added:

• Single quotes: b'still allows embedded "double" quotes'
• Double quotes: b"still allows embedded 'single' quotes".
• Triple quoted: b'''3 single quotes''', b"""3 double quotes"""

Only ASCII characters are permitted in bytes literals. Any binary values over 127 must be entered into bytes literals using the appropriate escape sequence.

While bytes literals and representations are based on ASCII text, bytes objects actually behave like immutable sequences of integers, with each value in the sequence restricted such that 0 <= x < 256 (attempts to violate this restriction will trigger ValueError). This is done deliberately to emphasize that while many binary formats include ASCII based elements and can be usefully manipulated with some text-oriented algorithms, this is not generally the case for arbitrary binary data (blindly applying text processing algorithms to binary data formats that are not ASCII compatible will usually lead to data corruption).

In addition to the literal forms, bytes objects can be created in a number of other ways:

• A zero-filled bytes object of a specified length: bytes(10)
• From an iterable of integers: bytes([1,2,3])

Since 2 hexadecimal digits correspond precisely to a single byte, hexadecimalnumbers are a commonly used format for describing binary data.

Since bytes objects are sequences of integers (akin to a tuple), for a bytes object , b[0] will be an integer, while b[0:1] will be a bytes object of length 1. (This contrasts with text strings, where both indexing and slicing will produce a string of length 1.)

Bytearray Objects¶

bytearray() objects are a mutable counterpart to bytes() objects. There is no dedicated literal syntax for bytearray objects, instead they are always created by calling the constructor:

• Creating an empty instance: bytearray()
• Creating a zero-filled instance with a given length: bytearray(10)
• From an iterable of integers: bytearray([1,2,3])

As bytearray objects are mutable, they support the mutable sequence operations in addition to the common bytes and bytearray operations described in Bytes and Bytearray Operations.

Since 2 hexadecimal digits correspond precisely to a single byte, hexadecimal numbers are a commonly used format for describing binary data.

Since bytearray objects are sequences of integers (akin to a list), for a bytearray object b, b[0] will be an integer, while b[0:1] will be a bytearray object of length 1. (This contrasts with text strings, where both indexing and slicing will produce a string of length 1.)

Bytes and Bytearray Operations¶

Both bytes and bytearray objects support the common sequence operations. They interoperate not just with operands of the same type, but with any bytes-like object. Due to this flexibility, they can be freely mixed in operations without causing errors. However, the return type of the result may depend on the order of operands.

For example, you can write:

a = "abc"
b = a.replace(b"a", "f")

and:

a = b"abc"
b = a.replace("a", b"f")

bytes.count(sub[,start[,end] ]) bytearray.count(sub[, start[, end] ])

Return the number of non-overlapping occurrences of subsequence sub in the range [start,end]. Optional arguments start and end are interpreted as in slice notation.

The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.

bytes.endswith(suffix[,start[,end] ]) bytearray.endswith(suffix[,start[,end] ])

Return True if the binary data ends with the specified suffix, otherwise return False. With optional start, test beginning at that position. With optional end, stop comparing at that position.

bytes.find(sub[,start[,end] ]) bytearray.find(sub[,start[,end] ])

Return the lowest index in the data where the subsequence sub is found, such that sub is contained in the slice s[start:end]. Optional arguments start and end are interpreted as in slice notation. Return -1 if sub is not found.

The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.

The find() method should be used only if you need to know the position of sub. To check if sub is a substring or not, use the in operator.

bytes.index(sub[, start[, end] ]) bytearray.index(sub[, start[, end] ])

Like find(), but raise ValueError when the subsequence is not found.

The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.

bytes.join(iterable) bytearray.join(iterable)

Return a bytes or bytearray object which is the concatenation of the binary data sequences in the iterable iterable. A TypeError will be raised if there are any values in iterable that are not bytes-like objects or strings. The separator between elements is the contents of the bytes or bytearray object providing this method.

bytes.replace(old,new) bytearray.replace(old, new)

Return a copy of the sequence with all occurrences of subsequence old replaced by new.

bytes.startswith(prefix[,start[,end] ]) bytearray.startswith(prefix[,start[,end] ])

Return True if the binary data starts with the specified prefix, otherwise return False. With optional start, test beginning at that position. With optional end, stop comparing at that position.

bytes.split(sep=None,maxsplit=-1) bytearray.split(sep=None, maxsplit=-1)

Split the binary sequence into subsequences of the same type, using sep as the delimiter string. If maxsplit is given and non-negative, at most maxsplit splits are done (thus, the list will have at most maxsplit+1 elements). If maxsplit is not specified or is -1, then there is no limit on the number of splits (all possible splits are made).

If sep is given, consecutive delimiters are not grouped together and are deemed to delimit empty subsequences (for example, b'1,,2'.split(b',') returns [b'1', b'', b'2']). The sep argument may consist of a multibyte sequence (for example, b'1<>2<>3'.split(b'<>') returns [b'1', b'2', b'3']). Splitting an empty sequence with a specified separator returns [b''] or [bytearray(b'')] depending on the type of object being split.

For example:

>>> b'1,2,3'.split(b',')
[b'1', b'2', b'3']
>>> b'1,2,3'.split(b',', maxsplit=1)
[b'1', b'2,3']
>>> b'1,2,,3,'.split(b',')
[b'1', b'2', b'', b'3', b'']

If sep is not specified, a different splitting algorithm is applied: runs of consecutive ASCII whitespace are regarded as a single separator, and the result will contain no empty strings at the start or end if the sequence has leading or trailing whitespace. Consequently, splitting an empty sequence or a sequence consisting solely of ASCII whitespace without a specified separator returns [].

For example:

>>> b'1 2 3'.split()
[b'1', b'2', b'3']
>>> b'1 2 3'.split(maxsplit=1)
[b'1', b'2 3']
>>> b'   1   2   3   '.split()
[b'1', b'2', b'3']

bytes.strip([chars[,dir=0] ]) bytearray.strip([chars[,dir=0] ])

Return a copy of the binary sequence with the leading and trailing characters removed. The chars argument is a string or binary sequence specifying the set of characters to be removed. If omitted, the chars argument defaults to removing whitespace. The chars argument is not a prefix or suffix; rather, all combinations of its values are stripped:

>>> b'   spacious   '.strip()
b'spacious'
>>> b'www.example.com'.strip(b'cmowz.')
b'example'

The dir parameter controls the side of stripping:

• dir=0, strip chars from left and right side of str
• dir>0, strip chars from left side of str
• dir<0, strip chars from right side of str

The following methods on bytes and bytearray objects assume the use of ASCII compatible binary formats and should not be applied to arbitrary binary data. Note that all of the bytearray methods in this section do not operate in place, and instead produce new objects.

bytes.lower() bytearray.lower()

Return a copy of the sequence with all the uppercase ASCII characters converted to their corresponding lowercase counterpart.

Lowercase ASCII characters are those byte values in the sequence b'abcdefghijklmnopqrstuvwxyz'. Uppercase ASCII characters are those byte values in the sequence b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

bytes.upper() bytearray.upper()

Return a copy of the sequence with all the lowercase ASCII characters converted to their corresponding uppercase counterpart.

Lowercase ASCII characters are those byte values in the sequence b'abcdefghijklmnopqrstuvwxyz'. Uppercase ASCII characters are those byte values in the sequence b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

Shorts and Shortarrays¶

Both Shorts and Shortarrays are sequence types added by Zerynth to the standard Python. Shorts and shortsarray objects actually behave like sequences of integers, with each value in the sequence restricted such that 0 <= x < 65536 (attempts to violate this restriction will trigger ValueError).

Shorts objects are immutable sequences of 16 bits integers. Shorts and shortsarray can’t be specified with literals, but only using one of the following ways:

• A zero-filled bytes object of a specified length: shorts(10)
• From an iterable of integers: shorts([1,2,3])

Since 4 hexadecimal digits correspond precisely to a 16 bit integer, hexadecimal numbers are a commonly used format for describing binary data.

Since shorts objects are sequences of integers (akin to a tuple), for a shorts object b, b[0] will be an integer, while b[0:1] will be a shorts object of length 1.

Shortarray objects are mutable sequences of 16 bits integers. Shorts and shortsarray can’t be specified with literals, but only using one of the following ways:

• A zero-filled bytes object of a specified length: shortarray(10)
• From an iterable of integers: shortarray([1,2,3])

Since 4 hexadecimal digits correspond precisely to a 16 bit integer, hexadecimal numbers are a commonly used format for describing binary data.

Since shortarray objects are sequences of integers (akin to a list), for a shortarray object b, b[0] will be an integer, while b[0:1] will be a shortarray object of length 1.

Shorts and shortarryas support only a limited set of methods:

• count and index with the same syntax and semantics of the corresponding methods for bytes
• common methods for mutable objects (only for shortarrays).

Set Types¶

A set object is an unordered collection of distinct hashable objects. Common uses include membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.

Like other collections, sets support x in set, len(set), and for x in set. Being an unordered collection, sets do not record element position or order of insertion. Accordingly, sets do not support indexing, slicing, or other sequence-like behavior.

There are currently two built-in set types, set() and frozenset(). The set() type is mutable — the contents can be changed using methods like add() and remove(). Since it is mutable, it has no hash value and cannot be used as either a dictionary key or as an element of another set. The frozenset() type is immutable and hashable — its contents cannot be altered after it is created; it can therefore be used as a dictionary key or as an element of another set.

Non-empty sets (not frozensets) can be created by placing a comma-separated list of elements within braces, for example: {'jack', 'sjoerd'}, in addition to the set() constructor.

The constructors for both classes work the same:

class set ([iterable]) class frozenset ([iterable])

Return a new set or frozenset object whose elements are taken from iterable. The elements of a set must be hashable. To represent sets of sets, the inner sets must be frozenset() objects. If iterable is not specified, a new empty set is returned.

Instances of set() and frozenset() provide the following operations:

len(s)

Return the cardinality of set s.

x in s

Test x for membership in s.

x not in s

Test x for non-membership in s.

isdisjoint(other)

Return True if the set has no elements in common with other. Sets are disjoint if and only if their intersection is the empty set.

issubset(other) set <= other

Test whether every element in the set is in other.

set < other

Test whether the set is a proper subset of other, that is, set <= other and set != other.

issuperset(other) set >= other

Test whether every element in other is in the set.

set > other

Test whether the set is a proper superset of other, that is, set >= other and set != other.

union(other,...) set | other | ...

Return a new set with elements from the set and all others.

intersection(other,...) set & other & ...

Return a new set with elements from the set and all others.

difference(other,...) set - other - ...

Return a new set with elements common to the set and all others.

symmetric_difference(other) set ^ other

Return a new set with elements in either the set or other but not both.

copy()

Return a new set with a shallow copy of s.

The following table lists operations available for set() that do not apply to immutable instances of frozenset():

update(other,...) set |= other | ...

Update the set, adding elements from all others.

intersection_update(other, ...) set &= other & ...

Update the set, keeping only elements found in it and all others.

difference_update(other, ...) set -= other | ...

Update the set, removing elements found in others.

symmetric_difference_update(other) set ^= other

Update the set, keeping only elements found in either set, but not in both.

add(elem)

Add element elem to the set.

remove(elem)

Remove element elem from the set. Raises KeyError if elem is not contained in the set.

discard(elem)

Remove element elem from the set if it is present.

pop()

Remove and return an arbitrary element from the set. Raises KeyError if the set is empty.

clear()

Remove all elements from the set.

Mapping Types¶

A mapping object maps hashable values to arbitrary objects. Mappings are mutable objects. There is currently only one standard mapping type, the dictionary.

A dictionary’s keys are almost arbitrary values. Values that are not hashable, that is, values containing lists, dictionaries or other mutable types (that are compared by value rather than by object identity) may not be used as keys. Numeric types used for keys obey the normal rules for numeric comparison: if two numbers compare equal (such as 1 and 1.0) then they can be used interchangeably to index the same dictionary entry. (Note however, that since computers store floating-point numbers as approximations it is usually unwise to use them as dictionary keys.)

Dictionaries can be created by placing a comma-separated list of key: value pairs within braces, for example: {'jack': 4098, 'sjoerd': 4127} or {4098:'jack', 4127: 'sjoerd'}, or by the dict() constructor.

class dict(*args)

If no positional argument is given, an empty dictionary is created. If a positional argument is given and it is a mapping object, a dictionary is created with the same key-value pairs as the mapping object. Otherwise,the positional argument must be an iterable object. Each item in the iterable must itself be an iterable with exactly two objects. The first object of each item becomes a key in the new dictionary, and the second object the corresponding value. If a key occurs more than once, the last value for that key becomes the corresponding value in the new dictionary.

These are the operations that dictionaries support:

len(d)

Return the number of items in the dictionary d.

d[key]

Return the item of d with key key. Raises a KeyError if key is not in the map.

d[key] = value

Set d[key] to value.

del d[key]

Remove d[key] from d. Raises a KeyError if key is not in the map.

key in d

Return True if d has a key key, else False.

key not in d

Equivalent to not key in d.

clear()

Remove all items from the dictionary.

copy()

Return a shallow copy of the dictionary.

items()

Return a new view of the dictionary’s items ((key, value) pairs).

keys()

Return a new view of the dictionary’s keys. See the documentation of view objects.

pop(key[, default])

If key is in the dictionary, remove it and return its value, else return default. If default is not given and key is not in the dictionary, a KeyError is raised.

popitem()

Remove and return an arbitrary (key, value) pair from the dictionary.

popitem() is useful to destructively iterate over a dictionary, as often used in set algorithms. If the dictionary is empty, calling popitem() raises a KeyError.

update([other])

Update the dictionary with the key/value pairs from other, overwriting existing keys. Return None.

update() accepts another dictionary object.

values() Return a new view of the dictionary’s values.