PEP: 572
Title: Assignment Expressions
Author: Chris Angelico <rosuav@gmail.com>, Tim Peters <tim.peters@gmail.com>,
        Guido van Rossum <guido@python.org>
Status: Final
Type: Standards Track
Content-Type: text/x-rst
Created: 28-Feb-2018
Python-Version: 3.8
Post-History: 28-Feb-2018, 02-Mar-2018, 23-Mar-2018, 04-Apr-2018, 17-Apr-2018,
              25-Apr-2018, 09-Jul-2018, 05-Aug-2019
Resolution: https://mail.python.org/pipermail/python-dev/2018-July/154601.html


Abstract
========

This is a proposal for creating a way to assign to variables within an
expression using the notation ``NAME := expr``.

As part of this change, there is also an update to dictionary comprehension
evaluation order to ensure key expressions are executed before value
expressions (allowing the key to be bound to a name and then re-used as part of
calculating the corresponding value).

During discussion of this PEP, the operator became informally known as
"the walrus operator". The construct's formal name is "Assignment Expressions"
(as per the PEP title), but they may also be referred to as "Named Expressions"
(e.g. the CPython reference implementation uses that name internally).


Rationale
=========

Naming the result of an expression is an important part of programming,
allowing a descriptive name to be used in place of a longer expression,
and permitting reuse.  Currently, this feature is available only in
statement form, making it unavailable in list comprehensions and other
expression contexts.

Additionally, naming sub-parts of a large expression can assist an interactive
debugger, providing useful display hooks and partial results. Without a way to
capture sub-expressions inline, this would require refactoring of the original
code; with assignment expressions, this merely requires the insertion of a few
``name :=`` markers. Removing the need to refactor reduces the likelihood that
the code be inadvertently changed as part of debugging (a common cause of
Heisenbugs), and is easier to dictate to another programmer.

The importance of real code
---------------------------

During the development of this PEP many people (supporters and critics
both) have had a tendency to focus on toy examples on the one hand,
and on overly complex examples on the other.

The danger of toy examples is twofold: they are often too abstract to
make anyone go "ooh, that's compelling", and they are easily refuted
with "I would never write it that way anyway".

The danger of overly complex examples is that they provide a
convenient strawman for critics of the proposal to shoot down ("that's
obfuscated").

Yet there is some use for both extremely simple and extremely complex
examples: they are helpful to clarify the intended semantics.
Therefore, there will be some of each below.

However, in order to be *compelling*, examples should be rooted in
real code, i.e. code that was written without any thought of this PEP,
as part of a useful application, however large or small.  Tim Peters
has been extremely helpful by going over his own personal code
repository and picking examples of code he had written that (in his
view) would have been *clearer* if rewritten with (sparing) use of
assignment expressions.  His conclusion: the current proposal would
have allowed a modest but clear improvement in quite a few bits of
code.

Another use of real code is to observe indirectly how much value
programmers place on compactness.  Guido van Rossum searched through a
Dropbox code base and discovered some evidence that programmers value
writing fewer lines over shorter lines.

Case in point: Guido found several examples where a programmer
repeated a subexpression, slowing down the program, in order to save
one line of code, e.g. instead of writing::

    match = re.match(data)
    group = match.group(1) if match else None

they would write::

    group = re.match(data).group(1) if re.match(data) else None

Another example illustrates that programmers sometimes do more work to
save an extra level of indentation::

    match1 = pattern1.match(data)
    match2 = pattern2.match(data)
    if match1:
        result = match1.group(1)
    elif match2:
        result = match2.group(2)
    else:
        result = None

This code tries to match ``pattern2`` even if ``pattern1`` has a match
(in which case the match on ``pattern2`` is never used).  The more
efficient rewrite would have been::

    match1 = pattern1.match(data)
    if match1:
        result = match1.group(1)
    else:
        match2 = pattern2.match(data)
        if match2:
            result = match2.group(2)
        else:
            result = None


Syntax and semantics
====================

In most contexts where arbitrary Python expressions can be used, a
**named expression** can appear.  This is of the form ``NAME := expr``
where ``expr`` is any valid Python expression other than an
unparenthesized tuple, and ``NAME`` is an identifier.

The value of such a named expression is the same as the incorporated
expression, with the additional side-effect that the target is assigned
that value::

    # Handle a matched regex
    if (match := pattern.search(data)) is not None:
        # Do something with match

    # A loop that can't be trivially rewritten using 2-arg iter()
    while chunk := file.read(8192):
       process(chunk)

    # Reuse a value that's expensive to compute
    [y := f(x), y**2, y**3]

    # Share a subexpression between a comprehension filter clause and its output
    filtered_data = [y for x in data if (y := f(x)) is not None]

Exceptional cases
-----------------

There are a few places where assignment expressions are not allowed,
in order to avoid ambiguities or user confusion:

- Unparenthesized assignment expressions are prohibited at the top
  level of an expression statement.  Example::

    y := f(x)  # INVALID
    (y := f(x))  # Valid, though not recommended

  This rule is included to simplify the choice for the user between an
  assignment statement and an assignment expression -- there is no
  syntactic position where both are valid.

- Unparenthesized assignment expressions are prohibited at the top
  level of the right hand side of an assignment statement.  Example::

    y0 = y1 := f(x)  # INVALID
    y0 = (y1 := f(x))  # Valid, though discouraged

  Again, this rule is included to avoid two visually similar ways of
  saying the same thing.

- Unparenthesized assignment expressions are prohibited for the value
  of a keyword argument in a call.  Example::

    foo(x = y := f(x))  # INVALID
    foo(x=(y := f(x)))  # Valid, though probably confusing

  This rule is included to disallow excessively confusing code, and
  because parsing keyword arguments is complex enough already.

- Unparenthesized assignment expressions are prohibited at the top
  level of a function default value.  Example::

    def foo(answer = p := 42):  # INVALID
        ...
    def foo(answer=(p := 42)):  # Valid, though not great style
        ...

  This rule is included to discourage side effects in a position whose
  exact semantics are already confusing to many users (cf. the common
  style recommendation against mutable default values), and also to
  echo the similar prohibition in calls (the previous bullet).

- Unparenthesized assignment expressions are prohibited as annotations
  for arguments, return values and assignments.  Example::

    def foo(answer: p := 42 = 5):  # INVALID
        ...
    def foo(answer: (p := 42) = 5):  # Valid, but probably never useful
        ...

  The reasoning here is similar to the two previous cases; this
  ungrouped assortment of symbols and operators composed of ``:`` and
  ``=`` is hard to read correctly.

- Unparenthesized assignment expressions are prohibited in lambda functions.
  Example::

    (lambda: x := 1) # INVALID
    lambda: (x := 1) # Valid, but unlikely to be useful
    (x := lambda: 1) # Valid
    lambda line: (m := re.match(pattern, line)) and m.group(1) # Valid

  This allows ``lambda`` to always bind less tightly than ``:=``; having a
  name binding at the top level inside a lambda function is unlikely to be of
  value, as there is no way to make use of it. In cases where the name will be
  used more than once, the expression is likely to need parenthesizing anyway,
  so this prohibition will rarely affect code.

- Assignment expressions inside of f-strings require parentheses. Example::

    >>> f'{(x:=10)}'  # Valid, uses assignment expression
    '10'
    >>> x = 10
    >>> f'{x:=10}'    # Valid, passes '=10' to formatter
    '        10'

  This shows that what looks like an assignment operator in an f-string is
  not always an assignment operator.  The f-string parser uses ``:`` to
  indicate formatting options.  To preserve backwards compatibility,
  assignment operator usage inside of f-strings must be parenthesized.
  As noted above, this usage of the assignment operator is not recommended.

Scope of the target
-------------------

An assignment expression does not introduce a new scope.  In most
cases the scope in which the target will be bound is self-explanatory:
it is the current scope.  If this scope contains a ``nonlocal`` or
``global`` declaration for the target, the assignment expression
honors that.  A lambda (being an explicit, if anonymous, function
definition) counts as a scope for this purpose.

There is one special case: an assignment expression occurring in a
list, set or dict comprehension or in a generator expression (below
collectively referred to as "comprehensions") binds the target in the
containing scope, honoring a ``nonlocal`` or ``global`` declaration
for the target in that scope, if one exists.  For the purpose of this
rule the containing scope of a nested comprehension is the scope that
contains the outermost comprehension.  A lambda counts as a containing
scope.

The motivation for this special case is twofold.  First, it allows us
to conveniently capture a "witness" for an ``any()`` expression, or a
counterexample for ``all()``, for example::

    if any((comment := line).startswith('#') for line in lines):
        print("First comment:", comment)
    else:
        print("There are no comments")

    if all((nonblank := line).strip() == '' for line in lines):
        print("All lines are blank")
    else:
        print("First non-blank line:", nonblank)

Second, it allows a compact way of updating mutable state from a
comprehension, for example::

    # Compute partial sums in a list comprehension
    total = 0
    partial_sums = [total := total + v for v in values]
    print("Total:", total)

However, an assignment expression target name cannot be the same as a
``for``-target name appearing in any comprehension containing the
assignment expression.  The latter names are local to the
comprehension in which they appear, so it would be contradictory for a
contained use of the same name to refer to the scope containing the
outermost comprehension instead.

For example, ``[i := i+1 for i in range(5)]`` is invalid: the ``for
i`` part establishes that ``i`` is local to the comprehension, but the
``i :=`` part insists that ``i`` is not local to the comprehension.
The same reason makes these examples invalid too::

    [[(j := j) for i in range(5)] for j in range(5)] # INVALID
    [i := 0 for i, j in stuff]                       # INVALID
    [i+1 for i in (i := stuff)]                      # INVALID

While it's technically possible to assign consistent semantics to these cases,
it's difficult to determine whether those semantics actually make *sense* in the
absence of real use cases. Accordingly, the reference implementation [1]_ will ensure
that such cases raise ``SyntaxError``, rather than executing with implementation
defined behaviour.

This restriction applies even if the assignment expression is never executed::

    [False and (i := 0) for i, j in stuff]     # INVALID
    [i for i, j in stuff if True or (j := 1)]  # INVALID

For the comprehension body (the part before the first "for" keyword) and the
filter expression (the part after "if" and before any nested "for"), this
restriction applies solely to target names that are also used as iteration
variables in the comprehension. Lambda expressions appearing in these
positions introduce a new explicit function scope, and hence may use assignment
expressions with no additional restrictions.

Due to design constraints in the reference implementation (the symbol table
analyser cannot easily detect when names are re-used between the leftmost
comprehension iterable expression and the rest of the comprehension), named
expressions are disallowed entirely as part of comprehension iterable
expressions (the part after each "in", and before any subsequent "if" or
"for" keyword)::

    [i+1 for i in (j := stuff)]                    # INVALID
    [i+1 for i in range(2) for j in (k := stuff)]  # INVALID
    [i+1 for i in [j for j in (k := stuff)]]       # INVALID
    [i+1 for i in (lambda: (j := stuff))()]        # INVALID

A further exception applies when an assignment expression occurs in a
comprehension whose containing scope is a class scope.  If the rules
above were to result in the target being assigned in that class's
scope, the assignment expression is expressly invalid. This case also raises
``SyntaxError``::

    class Example:
        [(j := i) for i in range(5)]  # INVALID

(The reason for the latter exception is the implicit function scope created
for comprehensions -- there is currently no runtime mechanism for a
function to refer to a variable in the containing class scope, and we
do not want to add such a mechanism.  If this issue ever gets resolved
this special case may be removed from the specification of assignment
expressions.  Note that the problem already exists for *using* a
variable defined in the class scope from a comprehension.)

See Appendix B for some examples of how the rules for targets in
comprehensions translate to equivalent code.


Relative precedence of ``:=``
-----------------------------

The ``:=`` operator groups more tightly than a comma in all syntactic
positions where it is legal, but less tightly than all other operators,
including ``or``, ``and``, ``not``, and conditional expressions
(``A if C else B``).  As follows from section
"Exceptional cases" above, it is never allowed at the same level as
``=``.  In case a different grouping is desired, parentheses should be
used.

The ``:=`` operator may be used directly in a positional function call
argument; however it is invalid directly in a keyword argument.

Some examples to clarify what's technically valid or invalid::

    # INVALID
    x := 0

    # Valid alternative
    (x := 0)

    # INVALID
    x = y := 0

    # Valid alternative
    x = (y := 0)

    # Valid
    len(lines := f.readlines())

    # Valid
    foo(x := 3, cat='vector')

    # INVALID
    foo(cat=category := 'vector')

    # Valid alternative
    foo(cat=(category := 'vector'))

Most of the "valid" examples above are not recommended, since human
readers of Python source code who are quickly glancing at some code
may miss the distinction.  But simple cases are not objectionable::

    # Valid
    if any(len(longline := line) >= 100 for line in lines):
        print("Extremely long line:", longline)

This PEP recommends always putting spaces around ``:=``, similar to
:pep:`8`'s recommendation for ``=`` when used for assignment, whereas the
latter disallows spaces around ``=`` used for keyword arguments.)

Change to evaluation order
--------------------------

In order to have precisely defined semantics, the proposal requires
evaluation order to be well-defined.  This is technically not a new
requirement, as function calls may already have side effects.  Python
already has a rule that subexpressions are generally evaluated from
left to right.  However, assignment expressions make these side
effects more visible, and we propose a single change to the current
evaluation order:

- In a dict comprehension ``{X: Y for ...}``, ``Y`` is currently
  evaluated before ``X``.  We propose to change this so that ``X`` is
  evaluated before ``Y``.  (In a dict display like ``{X: Y}`` this is
  already the case, and also in ``dict((X, Y) for ...)`` which should
  clearly be equivalent to the dict comprehension.)

Differences between  assignment expressions and assignment statements
---------------------------------------------------------------------

Most importantly, since ``:=`` is an expression, it can be used in contexts
where statements are illegal, including lambda functions and comprehensions.

Conversely, assignment expressions don't support the advanced features
found in assignment statements:

- Multiple targets are not directly supported::

    x = y = z = 0  # Equivalent: (z := (y := (x := 0)))

- Single assignment targets other than a single ``NAME`` are
  not supported::

    # No equivalent
    a[i] = x
    self.rest = []

- Priority around commas is different::

    x = 1, 2  # Sets x to (1, 2)
    (x := 1, 2)  # Sets x to 1

- Iterable packing and unpacking (both regular or extended forms) are
  not supported::

    # Equivalent needs extra parentheses
    loc = x, y  # Use (loc := (x, y))
    info = name, phone, *rest  # Use (info := (name, phone, *rest))

    # No equivalent
    px, py, pz = position
    name, phone, email, *other_info = contact

- Inline type annotations are not supported::

    # Closest equivalent is "p: Optional[int]" as a separate declaration
    p: Optional[int] = None

- Augmented assignment is not supported::

    total += tax  # Equivalent: (total := total + tax)


Specification changes during implementation
===========================================

The following changes have been made based on implementation experience and
additional review after the PEP was first accepted and before Python 3.8 was
released:

* for consistency with other similar exceptions, and to avoid locking in an
  exception name that is not necessarily going to improve clarity for end users,
  the originally proposed ``TargetScopeError`` subclass of ``SyntaxError`` was
  dropped in favour of just raising ``SyntaxError`` directly. [3]_
* due to a limitation in CPython's symbol table analysis process, the reference
  implementation raises ``SyntaxError`` for all uses of named expressions inside
  comprehension iterable expressions, rather than only raising them when the
  named expression target conflicts with one of the iteration variables in the
  comprehension. This could be revisited given sufficiently compelling examples,
  but the extra complexity needed to implement the more selective restriction
  doesn't seem worthwhile for purely hypothetical use cases.


Examples
========

Examples from the Python standard library
-----------------------------------------

site.py
^^^^^^^

*env_base* is only used on these lines, putting its assignment on the if
moves it as the "header" of the block.

- Current::

    env_base = os.environ.get("PYTHONUSERBASE", None)
    if env_base:
        return env_base

- Improved::

    if env_base := os.environ.get("PYTHONUSERBASE", None):
        return env_base

_pydecimal.py
^^^^^^^^^^^^^

Avoid nested ``if`` and remove one indentation level.

- Current::

    if self._is_special:
        ans = self._check_nans(context=context)
        if ans:
            return ans

- Improved::

    if self._is_special and (ans := self._check_nans(context=context)):
        return ans

copy.py
^^^^^^^

Code looks more regular and avoid multiple nested if.
(See Appendix A for the origin of this example.)

- Current::

    reductor = dispatch_table.get(cls)
    if reductor:
        rv = reductor(x)
    else:
        reductor = getattr(x, "__reduce_ex__", None)
        if reductor:
            rv = reductor(4)
        else:
            reductor = getattr(x, "__reduce__", None)
            if reductor:
                rv = reductor()
            else:
                raise Error(
                    "un(deep)copyable object of type %s" % cls)

- Improved::

    if reductor := dispatch_table.get(cls):
        rv = reductor(x)
    elif reductor := getattr(x, "__reduce_ex__", None):
        rv = reductor(4)
    elif reductor := getattr(x, "__reduce__", None):
        rv = reductor()
    else:
        raise Error("un(deep)copyable object of type %s" % cls)

datetime.py
^^^^^^^^^^^

*tz* is only used for ``s += tz``, moving its assignment inside the if
helps to show its scope.

- Current::

    s = _format_time(self._hour, self._minute,
                     self._second, self._microsecond,
                     timespec)
    tz = self._tzstr()
    if tz:
        s += tz
    return s

- Improved::

    s = _format_time(self._hour, self._minute,
                     self._second, self._microsecond,
                     timespec)
    if tz := self._tzstr():
        s += tz
    return s

sysconfig.py
^^^^^^^^^^^^

Calling ``fp.readline()`` in the ``while`` condition and calling
``.match()`` on the if lines make the code more compact without making
it harder to understand.

- Current::

    while True:
        line = fp.readline()
        if not line:
            break
        m = define_rx.match(line)
        if m:
            n, v = m.group(1, 2)
            try:
                v = int(v)
            except ValueError:
                pass
            vars[n] = v
        else:
            m = undef_rx.match(line)
            if m:
                vars[m.group(1)] = 0

- Improved::

    while line := fp.readline():
        if m := define_rx.match(line):
            n, v = m.group(1, 2)
            try:
                v = int(v)
            except ValueError:
                pass
            vars[n] = v
        elif m := undef_rx.match(line):
            vars[m.group(1)] = 0


Simplifying list comprehensions
-------------------------------

A list comprehension can map and filter efficiently by capturing
the condition::

    results = [(x, y, x/y) for x in input_data if (y := f(x)) > 0]

Similarly, a subexpression can be reused within the main expression, by
giving it a name on first use::

    stuff = [[y := f(x), x/y] for x in range(5)]

Note that in both cases the variable ``y`` is bound in the containing
scope (i.e. at the same level as ``results`` or ``stuff``).


Capturing condition values
--------------------------

Assignment expressions can be used to good effect in the header of
an ``if`` or ``while`` statement::

    # Loop-and-a-half
    while (command := input("> ")) != "quit":
        print("You entered:", command)

    # Capturing regular expression match objects
    # See, for instance, Lib/pydoc.py, which uses a multiline spelling
    # of this effect
    if match := re.search(pat, text):
        print("Found:", match.group(0))
    # The same syntax chains nicely into 'elif' statements, unlike the
    # equivalent using assignment statements.
    elif match := re.search(otherpat, text):
        print("Alternate found:", match.group(0))
    elif match := re.search(third, text):
        print("Fallback found:", match.group(0))

    # Reading socket data until an empty string is returned
    while data := sock.recv(8192):
        print("Received data:", data)

Particularly with the ``while`` loop, this can remove the need to have an
infinite loop, an assignment, and a condition. It also creates a smooth
parallel between a loop which simply uses a function call as its condition,
and one which uses that as its condition but also uses the actual value.

Fork
----

An example from the low-level UNIX world::

    if pid := os.fork():
        # Parent code
    else:
        # Child code


Rejected alternative proposals
==============================

Proposals broadly similar to this one have come up frequently on python-ideas.
Below are a number of alternative syntaxes, some of them specific to
comprehensions, which have been rejected in favour of the one given above.


Changing the scope rules for comprehensions
-------------------------------------------

A previous version of this PEP proposed subtle changes to the scope
rules for comprehensions, to make them more usable in class scope and
to unify the scope of the "outermost iterable" and the rest of the
comprehension.  However, this part of the proposal would have caused
backwards incompatibilities, and has been withdrawn so the PEP can
focus on assignment expressions.


Alternative spellings
---------------------

Broadly the same semantics as the current proposal, but spelled differently.

1. ``EXPR as NAME``::

       stuff = [[f(x) as y, x/y] for x in range(5)]

   Since ``EXPR as NAME`` already has meaning in ``import``,
   ``except`` and ``with`` statements (with different semantics), this
   would create unnecessary confusion or require special-casing
   (e.g. to forbid assignment within the headers of these statements).

   (Note that ``with EXPR as VAR`` does *not* simply assign the value
   of ``EXPR`` to ``VAR`` -- it calls ``EXPR.__enter__()`` and assigns
   the result of *that* to ``VAR``.)

   Additional reasons to prefer ``:=`` over this spelling include:

   - In ``if f(x) as y`` the assignment target doesn't jump out at you
     -- it just reads like ``if f x blah blah`` and it is too similar
     visually to ``if f(x) and y``.

   - In all other situations where an ``as`` clause is allowed, even
     readers with intermediary skills are led to anticipate that
     clause (however optional) by the keyword that starts the line,
     and the grammar ties that keyword closely to the as clause:

     - ``import foo as bar``
     - ``except Exc as var``
     - ``with ctxmgr() as var``

     To the contrary, the assignment expression does not belong to the
     ``if`` or ``while`` that starts the line, and we intentionally
     allow assignment expressions in other contexts as well.

   - The parallel cadence between

     - ``NAME = EXPR``
     - ``if NAME := EXPR``

     reinforces the visual recognition of assignment expressions.

2. ``EXPR -> NAME``::

       stuff = [[f(x) -> y, x/y] for x in range(5)]

   This syntax is inspired by languages such as R and Haskell, and some
   programmable calculators. (Note that a left-facing arrow ``y <- f(x)`` is
   not possible in Python, as it would be interpreted as less-than and unary
   minus.) This syntax has a slight advantage over 'as' in that it does not
   conflict with ``with``, ``except`` and ``import``, but otherwise is
   equivalent.  But it is entirely unrelated to Python's other use of
   ``->`` (function return type annotations), and compared to ``:=``
   (which dates back to Algol-58) it has a much weaker tradition.

3. Adorning statement-local names with a leading dot::

       stuff = [[(f(x) as .y), x/.y] for x in range(5)] # with "as"
       stuff = [[(.y := f(x)), x/.y] for x in range(5)] # with ":="

   This has the advantage that leaked usage can be readily detected, removing
   some forms of syntactic ambiguity.  However, this would be the only place
   in Python where a variable's scope is encoded into its name, making
   refactoring harder.

4. Adding a ``where:`` to any statement to create local name bindings::

       value = x**2 + 2*x where:
           x = spam(1, 4, 7, q)

   Execution order is inverted (the indented body is performed first, followed
   by the "header").  This requires a new keyword, unless an existing keyword
   is repurposed (most likely ``with:``).  See :pep:`3150` for prior discussion
   on this subject (with the proposed keyword being ``given:``).

5. ``TARGET from EXPR``::

       stuff = [[y from f(x), x/y] for x in range(5)]

   This syntax has fewer conflicts than ``as`` does (conflicting only with the
   ``raise Exc from Exc`` notation), but is otherwise comparable to it. Instead
   of paralleling ``with expr as target:`` (which can be useful but can also be
   confusing), this has no parallels, but is evocative.


Special-casing conditional statements
-------------------------------------

One of the most popular use-cases is ``if`` and ``while`` statements.  Instead
of a more general solution, this proposal enhances the syntax of these two
statements to add a means of capturing the compared value::

    if re.search(pat, text) as match:
        print("Found:", match.group(0))

This works beautifully if and ONLY if the desired condition is based on the
truthiness of the captured value.  It is thus effective for specific
use-cases (regex matches, socket reads that return ``''`` when done), and
completely useless in more complicated cases (e.g. where the condition is
``f(x) < 0`` and you want to capture the value of ``f(x)``).  It also has
no benefit to list comprehensions.

Advantages: No syntactic ambiguities. Disadvantages: Answers only a fraction
of possible use-cases, even in ``if``/``while`` statements.


Special-casing comprehensions
-----------------------------

Another common use-case is comprehensions (list/set/dict, and genexps). As
above, proposals have been made for comprehension-specific solutions.

1. ``where``, ``let``, or ``given``::

       stuff = [(y, x/y) where y = f(x) for x in range(5)]
       stuff = [(y, x/y) let y = f(x) for x in range(5)]
       stuff = [(y, x/y) given y = f(x) for x in range(5)]

   This brings the subexpression to a location in between the 'for' loop and
   the expression. It introduces an additional language keyword, which creates
   conflicts. Of the three, ``where`` reads the most cleanly, but also has the
   greatest potential for conflict (e.g. SQLAlchemy and numpy have ``where``
   methods, as does ``tkinter.dnd.Icon`` in the standard library).

2. ``with NAME = EXPR``::

       stuff = [(y, x/y) with y = f(x) for x in range(5)]

   As above, but reusing the ``with`` keyword. Doesn't read too badly, and needs
   no additional language keyword. Is restricted to comprehensions, though,
   and cannot as easily be transformed into "longhand" for-loop syntax. Has
   the C problem that an equals sign in an expression can now create a name
   binding, rather than performing a comparison. Would raise the question of
   why "with NAME = EXPR:" cannot be used as a statement on its own.

3. ``with EXPR as NAME``::

       stuff = [(y, x/y) with f(x) as y for x in range(5)]

   As per option 2, but using ``as`` rather than an equals sign. Aligns
   syntactically with other uses of ``as`` for name binding, but a simple
   transformation to for-loop longhand would create drastically different
   semantics; the meaning of ``with`` inside a comprehension would be
   completely different from the meaning as a stand-alone statement, while
   retaining identical syntax.

Regardless of the spelling chosen, this introduces a stark difference between
comprehensions and the equivalent unrolled long-hand form of the loop.  It is
no longer possible to unwrap the loop into statement form without reworking
any name bindings.  The only keyword that can be repurposed to this task is
``with``, thus giving it sneakily different semantics in a comprehension than
in a statement; alternatively, a new keyword is needed, with all the costs
therein.


Lowering operator precedence
----------------------------

There are two logical precedences for the ``:=`` operator. Either it should
bind as loosely as possible, as does statement-assignment; or it should bind
more tightly than comparison operators. Placing its precedence between the
comparison and arithmetic operators (to be precise: just lower than bitwise
OR) allows most uses inside ``while`` and ``if`` conditions to be spelled
without parentheses, as it is most likely that you wish to capture the value
of something, then perform a comparison on it::

    pos = -1
    while pos := buffer.find(search_term, pos + 1) >= 0:
        ...

Once find() returns -1, the loop terminates. If ``:=`` binds as loosely as
``=`` does, this would capture the result of the comparison (generally either
``True`` or ``False``), which is less useful.

While this behaviour would be convenient in many situations, it is also harder
to explain than "the := operator behaves just like the assignment statement",
and as such, the precedence for ``:=`` has been made as close as possible to
that of ``=`` (with the exception that it binds tighter than comma).


Allowing commas to the right
----------------------------

Some critics have claimed that the assignment expressions should allow
unparenthesized tuples on the right, so that these two would be equivalent::

    (point := (x, y))
    (point := x, y)

(With the current version of the proposal, the latter would be
equivalent to ``((point := x), y)``.)

However, adopting this stance would logically lead to the conclusion
that when used in a function call, assignment expressions also bind
less tight than comma, so we'd have the following confusing equivalence::

    foo(x := 1, y)
    foo(x := (1, y))

The less confusing option is to make ``:=`` bind more tightly than comma.


Always requiring parentheses
----------------------------

It's been proposed to just always require parentheses around an
assignment expression.  This would resolve many ambiguities, and
indeed parentheses will frequently be needed to extract the desired
subexpression.  But in the following cases the extra parentheses feel
redundant::

    # Top level in if
    if match := pattern.match(line):
        return match.group(1)

    # Short call
    len(lines := f.readlines())


Frequently Raised Objections
============================

Why not just turn existing assignment into an expression?
---------------------------------------------------------

C and its derivatives define the ``=`` operator as an expression, rather than
a statement as is Python's way.  This allows assignments in more contexts,
including contexts where comparisons are more common.  The syntactic similarity
between ``if (x == y)`` and ``if (x = y)`` belies their drastically different
semantics.  Thus this proposal uses ``:=`` to clarify the distinction.


With assignment expressions, why bother with assignment statements?
-------------------------------------------------------------------

The two forms have different flexibilities.  The ``:=`` operator can be used
inside a larger expression; the ``=`` statement can be augmented to ``+=`` and
its friends, can be chained, and can assign to attributes and subscripts.


Why not use a sublocal scope and prevent namespace pollution?
-------------------------------------------------------------

Previous revisions of this proposal involved sublocal scope (restricted to a
single statement), preventing name leakage and namespace pollution.  While a
definite advantage in a number of situations, this increases complexity in
many others, and the costs are not justified by the benefits. In the interests
of language simplicity, the name bindings created here are exactly equivalent
to any other name bindings, including that usage at class or module scope will
create externally-visible names.  This is no different from ``for`` loops or
other constructs, and can be solved the same way: ``del`` the name once it is
no longer needed, or prefix it with an underscore.

(The author wishes to thank Guido van Rossum and Christoph Groth for their
suggestions to move the proposal in this direction. [2]_)


Style guide recommendations
===========================

As expression assignments can sometimes be used equivalently to statement
assignments, the question of which should be preferred will arise. For the
benefit of style guides such as :pep:`8`, two recommendations are suggested.

1. If either assignment statements or assignment expressions can be
   used, prefer statements; they are a clear declaration of intent.

2. If using assignment expressions would lead to ambiguity about
   execution order, restructure it to use statements instead.


Acknowledgements
================

The authors wish to thank Alyssa Coghlan and Steven D'Aprano for their
considerable contributions to this proposal, and members of the
core-mentorship mailing list for assistance with implementation.


Appendix A: Tim Peters's findings
=================================

Here's a brief essay Tim Peters wrote on the topic.

I dislike "busy" lines of code, and also dislike putting conceptually
unrelated logic on a single line.  So, for example, instead of::

    i = j = count = nerrors = 0

I prefer::

    i = j = 0
    count = 0
    nerrors = 0

instead.  So I suspected I'd find few places I'd want to use
assignment expressions.  I didn't even consider them for lines already
stretching halfway across the screen.  In other cases, "unrelated"
ruled::

    mylast = mylast[1]
    yield mylast[0]

is a vast improvement over the briefer::

    yield (mylast := mylast[1])[0]

The original two statements are doing entirely different conceptual
things, and slamming them together is conceptually insane.

In other cases, combining related logic made it harder to understand,
such as rewriting::

    while True:
        old = total
        total += term
        if old == total:
            return total
        term *= mx2 / (i*(i+1))
        i += 2

as the briefer::

    while total != (total := total + term):
        term *= mx2 / (i*(i+1))
        i += 2
    return total

The ``while`` test there is too subtle, crucially relying on strict
left-to-right evaluation in a non-short-circuiting or method-chaining
context.  My brain isn't wired that way.

But cases like that were rare.  Name binding is very frequent, and
"sparse is better than dense" does not mean "almost empty is better
than sparse".  For example, I have many functions that return ``None``
or ``0`` to communicate "I have nothing useful to return in this case,
but since that's expected often I'm not going to annoy you with an
exception".  This is essentially the same as regular expression search
functions returning ``None`` when there is no match.  So there was lots
of code of the form::

    result = solution(xs, n)
    if result:
        # use result

I find that clearer, and certainly a bit less typing and
pattern-matching reading, as::

    if result := solution(xs, n):
        # use result

It's also nice to trade away a small amount of horizontal whitespace
to get another _line_ of surrounding code on screen.  I didn't give
much weight to this at first, but it was so very frequent it added up,
and I soon enough became annoyed that I couldn't actually run the
briefer code.  That surprised me!

There are other cases where assignment expressions really shine.
Rather than pick another from my code, Kirill Balunov gave a lovely
example from the standard library's ``copy()`` function in ``copy.py``::

    reductor = dispatch_table.get(cls)
    if reductor:
        rv = reductor(x)
    else:
        reductor = getattr(x, "__reduce_ex__", None)
        if reductor:
            rv = reductor(4)
        else:
            reductor = getattr(x, "__reduce__", None)
            if reductor:
                rv = reductor()
            else:
                raise Error("un(shallow)copyable object of type %s" % cls)

The ever-increasing indentation is semantically misleading: the logic
is conceptually flat, "the first test that succeeds wins"::

    if reductor := dispatch_table.get(cls):
        rv = reductor(x)
    elif reductor := getattr(x, "__reduce_ex__", None):
        rv = reductor(4)
    elif reductor := getattr(x, "__reduce__", None):
        rv = reductor()
    else:
        raise Error("un(shallow)copyable object of type %s" % cls)

Using easy assignment expressions allows the visual structure of the
code to emphasize the conceptual flatness of the logic;
ever-increasing indentation obscured it.

A smaller example from my code delighted me, both allowing to put
inherently related logic in a single line, and allowing to remove an
annoying "artificial" indentation level::

    diff = x - x_base
    if diff:
        g = gcd(diff, n)
        if g > 1:
            return g

became::

    if (diff := x - x_base) and (g := gcd(diff, n)) > 1:
        return g

That ``if`` is about as long as I want my lines to get, but remains easy
to follow.

So, in all, in most lines binding a name, I wouldn't use assignment
expressions, but because that construct is so very frequent, that
leaves many places I would.  In most of the latter, I found a small
win that adds up due to how often it occurs, and in the rest I found a
moderate to major win.  I'd certainly use it more often than ternary
``if``, but significantly less often than augmented assignment.

A numeric example
-----------------

I have another example that quite impressed me at the time.

Where all variables are positive integers, and a is at least as large
as the n'th root of x, this algorithm returns the floor of the n'th
root of x (and roughly doubling the number of accurate bits per
iteration)::

    while a > (d := x // a**(n-1)):
        a = ((n-1)*a + d) // n
    return a

It's not obvious why that works, but is no more obvious in the "loop
and a half" form. It's hard to prove correctness without building on
the right insight (the "arithmetic mean - geometric mean inequality"),
and knowing some non-trivial things about how nested floor functions
behave. That is, the challenges are in the math, not really in the
coding.

If you do know all that, then the assignment-expression form is easily
read as "while the current guess is too large, get a smaller guess",
where the "too large?" test and the new guess share an expensive
sub-expression.

To my eyes, the original form is harder to understand::

    while True:
        d = x // a**(n-1)
        if a <= d:
            break
        a = ((n-1)*a + d) // n
    return a


Appendix B: Rough code translations for comprehensions
======================================================

This appendix attempts to clarify (though not specify) the rules when
a target occurs in a comprehension or in a generator expression.
For a number of illustrative examples we show the original code,
containing a comprehension, and the translation, where the
comprehension has been replaced by an equivalent generator function
plus some scaffolding.

Since ``[x for ...]`` is equivalent to ``list(x for ...)`` these
examples all use list comprehensions without loss of generality.
And since these examples are meant to clarify edge cases of the rules,
they aren't trying to look like real code.

Note: comprehensions are already implemented via synthesizing nested
generator functions like those in this appendix.  The new part is
adding appropriate declarations to establish the intended scope of
assignment expression targets (the same scope they resolve to as if
the assignment were performed in the block containing the outermost
comprehension).  For type inference purposes, these illustrative
expansions do not imply that assignment expression targets are always
Optional (but they do indicate the target binding scope).

Let's start with a reminder of what code is generated for a generator
expression without assignment expression.

- Original code (EXPR usually references VAR)::

    def f():
        a = [EXPR for VAR in ITERABLE]

- Translation (let's not worry about name conflicts)::

    def f():
        def genexpr(iterator):
            for VAR in iterator:
                yield EXPR
        a = list(genexpr(iter(ITERABLE)))

Let's add a simple assignment expression.

- Original code::

    def f():
        a = [TARGET := EXPR for VAR in ITERABLE]

- Translation::

    def f():
        if False:
            TARGET = None  # Dead code to ensure TARGET is a local variable
        def genexpr(iterator):
            nonlocal TARGET
            for VAR in iterator:
                TARGET = EXPR
                yield TARGET
        a = list(genexpr(iter(ITERABLE)))

Let's add a ``global TARGET`` declaration in ``f()``.

- Original code::

    def f():
        global TARGET
        a = [TARGET := EXPR for VAR in ITERABLE]

- Translation::

    def f():
        global TARGET
        def genexpr(iterator):
            global TARGET
            for VAR in iterator:
                TARGET = EXPR
                yield TARGET
        a = list(genexpr(iter(ITERABLE)))

Or instead let's add a ``nonlocal TARGET`` declaration in ``f()``.

- Original code::

    def g():
        TARGET = ...
        def f():
            nonlocal TARGET
            a = [TARGET := EXPR for VAR in ITERABLE]

- Translation::

    def g():
        TARGET = ...
        def f():
            nonlocal TARGET
            def genexpr(iterator):
                nonlocal TARGET
                for VAR in iterator:
                    TARGET = EXPR
                    yield TARGET
            a = list(genexpr(iter(ITERABLE)))

Finally, let's nest two comprehensions.

- Original code::

    def f():
        a = [[TARGET := i for i in range(3)] for j in range(2)]
        # I.e., a = [[0, 1, 2], [0, 1, 2]]
        print(TARGET)  # prints 2

- Translation::

    def f():
        if False:
            TARGET = None
        def outer_genexpr(outer_iterator):
            nonlocal TARGET
            def inner_generator(inner_iterator):
                nonlocal TARGET
                for i in inner_iterator:
                    TARGET = i
                    yield i
            for j in outer_iterator:
                yield list(inner_generator(range(3)))
        a = list(outer_genexpr(range(2)))
        print(TARGET)


Appendix C: No Changes to Scope Semantics
=========================================

Because it has been a point of confusion, note that nothing about Python's
scoping semantics is changed.  Function-local scopes continue to be resolved
at compile time, and to have indefinite temporal extent at run time ("full
closures").  Example::

    a = 42
    def f():
        # `a` is local to `f`, but remains unbound
        # until the caller executes this genexp:
        yield ((a := i) for i in range(3))
        yield lambda: a + 100
        print("done")
        try:
            print(f"`a` is bound to {a}")
            assert False
        except UnboundLocalError:
            print("`a` is not yet bound")

Then::

    >>> results = list(f()) # [genexp, lambda]
    done
    `a` is not yet bound
    # The execution frame for f no longer exists in CPython,
    # but f's locals live so long as they can still be referenced.
    >>> list(map(type, results))
    [<class 'generator'>, <class 'function'>]
    >>> list(results[0])
    [0, 1, 2]
    >>> results[1]()
    102
    >>> a
    42


References
==========

.. [1] Proof of concept implementation
   (https://github.com/Rosuav/cpython/tree/assignment-expressions)
.. [2] Pivotal post regarding inline assignment semantics
   (https://mail.python.org/pipermail/python-ideas/2018-March/049409.html)
.. [3] Discussion of PEP 572 TargetScopeError
   (https://mail.python.org/archives/list/python-dev@python.org/thread/FXVSYCTQOTT7JCFACKPGPXKULBCGEPQY/)


Copyright
=========

This document has been placed in the public domain.
