ML style pattern matching is syntactic sugar, that combines "if" statements
with tuple unpacking, access to object attributes, and assignments. It is a
compact, yet very readable syntax for algorithms, that would otherwise require
nested "if" statements. It is especially useful for writing interpreters, and
processing complex trees.
Instead of a specification in BNF, here is a function written with the
proposed pattern matching syntax. It demonstrates the features that I find
most important. The comments and the print statements explain what is done.
Proposed Syntax
---------------
def foo(x):
match x with
| 1 -> # Equality
print("x is equal to 1")
| a:int -> # Type check
print("x has type int: %s" % a)
| (a, b) -> # Tuple unpacking
print("x is a tuple with length 2: (%s, %s)" % (a, b))
| {| a, b |} -> # Attribute existence and access
print("x is an object with attributes 'a' and 'b'.")
print("a=%s, b=%s" % (a, b))
# Additional condition
| (a, b, c) with a > b ->
print("x is a tuple with length 3: (%s, %s, %s)" % (a, b, c))
print("The first element is greater than the second element.")
# Complex case
| {| c:int, d=1 |}:Foo ->
print("x has type Foo")
print("x is an object with attributes 'c' and 'd'.")
print("'c' has type 'int', 'd' is equal to 1.")
print("c=%s, d=%s" % (c, d))
# Default case
| _ ->
print("x can be anything")
Equivalent Current Python
-------------------------
The first four cases could be handled more simply, but handling all cases in
the same way leads IMHO to more simple code overall.
def foo(x):
while True:
# Equality
if x == 1:
print("x is equal to 1")
break
# Type check
if isinstance(x, int):
a = x
print("x is an integer: %s" % a)
break
# Tuple unpacking
if isinstance(x, tuple) and len(x) == 2:
a, b = x
print("x is a tuple with length 2: (%s, %s)" % (a, b))
break
# Attribute existence testing and access
if hasattr(x, "a") and hasattr(x, "b"):
a, b = x.a, x.b
print("x is an object with attributes 'a' and 'b'.")
print("a=%s, b=%s" % (a, b))
break
# Additional condition
if isinstance(x, tuple) and len(x) == 3:
a, b, c = x
if a > b :
print("x is a tuple with length 3: (%s, %s, %s)" % (a, b, c))
print("The first element is greater than the second "
"element.")
break
# Complex case
if isinstance(x, Foo) and hasattr(x, "c") and hasattr(x, "d"):
c, d = x.c, x.d
if isinstance(c, int) and d == 1:
print("x has type Foo")
print("x is an object with attributes 'c' and 'd'.")
print("'c' has type 'int', 'd' is equal to 1.")
print("c=%s, d=%s" % (c, d))
break
# Default case
print("x can be anything")
break
Additional Code to Run Function "foo"
-------------------------------------
class Bar(object):
def __init__(self, a, b):
self.a = a
self.b = b
class Foo(object):
def __init__(self, c, d):
self.c = c
self.d = d
foo(1) # Equality
foo(2) # Type check
foo((1, 2)) # Tuple unpacking
foo(Bar(1, 2)) # Attribute existence testing and access
foo((2, 1, 3)) # Additional condition
foo(Foo(2, 1)) # Complex case
foo("hello") # Default case
I left out dict and set, because I'm not sure how they should be handled. I
think list should be handled like tuples. Probably there should be a universal
matching syntax for all sequences, similarly to the already existing syntax:
a, b, *c = s
I don't really like the "->" digraph at the end of each match case. A colon
would be much more consistent, but I use colons already for type checking
(a:int).
I generally think that Python should acquire more features from functional
languages. In analogy to "RPython" it should ultimately lead to "MLPython", a
subset of the Python language that can be type checked and reasoned about by
external tools, similarly to what is possible with Ocaml.
Eike.
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My BNF is weak -- thanks for the code!
I am unfamiliar with OCAML -- if x can match more than one condition,
will it match all possible, or just the first one? If just the first
one, the python code below can be simplified by ditching the while loop,
removing the breaks, and using elif and else.
def foo(x):
# Equality
if x == 1:
print("x is equal to 1")
# Type check
elif isinstance(x, int):
a = x
print("x is an integer: %s" % a)
# Tuple unpacking
elif isinstance(x, tuple) and len(x) == 2:
a, b = x
print("x is a tuple with length 2: (%s, %s)" % (a, b))
# Attribute existence testing and access
elif hasattr(x, "a") and hasattr(x, "b"):
a, b = x.a, x.b
print("x is an object with attributes 'a' and 'b'.")
print("a=%s, b=%s" % (a, b))
# Additional condition
elif isinstance(x, tuple) and len(x) == 3:
a, b, c = x
if a > b :
print("x is a tuple with length 3: (%s, %s, %s)" % (a, b, c))
print("The first element is greater than the second "
"element.")
# Complex case
elif isinstance(x, Foo) and hasattr(x, "c") and hasattr(x, "d"):
c, d = x.c, x.d
if isinstance(c, int) and d == 1:
print("x has type Foo")
print("x is an object with attributes 'c' and 'd'.")
print("'c' has type 'int', 'd' is equal to 1.")
print("c=%s, d=%s" % (c, d))
# Default case
else:
print("x can be anything")
One of the things I like about Python is it's readability. While the
OCAML inspired version is much more concise, I don't see it as
significantly easier to read -- and at this point I don't see any place
where I would make use of it myself.
Here's a bit of code that might be convertable:
result = []
for i, piece in enumerate(pieces):
if '-' in piece:
piece = piece.replace('-',' ')
piece = '-'.join(NameCase(piece).split())
elif alpha_num(piece) in ('i', 'ii', 'iii', 'iv', 'v', 'vi', \
'vii', 'viii', 'ix', 'x', 'pc', 'llc') \
or piece.upper() in job_titles \
or i and piece.upper() in deg_suffixi:
piece = piece.upper()
elif piece in ('and', 'de', 'del', 'der', 'el', 'la', 'van', ):
pass
elif piece[:2] == 'mc':
piece = 'Mc' + piece[2:].title()
else:
possible = mixed_case_names.get(piece, None)
if possible is not None:
piece = possible
else:
piece = piece.title()
if piece[-2:].startswith("'"):
piece = piece[:-1] + piece[-1].lower()
result.append(piece)
Ugly, I know -- but the question is: how would 'match' handle things like
'-' in piece
piece.upper() in ....
piece in (....)
piece[:2] = 'mc'
in other words, would match save me much in this circumstance, and would
it be easier to read?
-1
~Ethan~
-1 on adding anything like this to core Python.
In your example, it is
1. completely redundant with respect to current Python syntax;
2. look like chicken scratches;
3. limited by the chars availables to just a few of the infinity of
tests one might want to run.
4. gives special prominence to tuples, which is hardly appropriate to
list or iterable-oriented code.
The third point is why Python does not try to everything with syntax
symbols. How test that the input is a positive number?How test that the
input is a positive number? Type testing is somewhat contrary to
duck-typing. For instance, how would you test that the input is an
iterable?
> ML style pattern matching is syntactic sugar, that combines "if" statements
> with tuple unpacking, access to object attributes, and assignments. It is a
> compact, yet very readable syntax for algorithms, that would otherwise require
> nested "if" statements.
Your example does not use nesting.
> It is especially useful for writing interpreters, and
> processing complex trees.
Sounds like better suited to a special-purpose 3rd party module, like
pyparsing.
--
Terry Jan Reedy
@basecase
def fac(n):
return n * fac(n -1)
@f.equals(1):
def f(n):
return 1
@f.lessthan(1)
def f(n):
raise Error("n less than 1, operation not defined.")
It's not that pretty, but I don't see any need for a whole new syntax
for what is basically a glorified elif.
> I am unfamiliar with OCAML -- if x can match more than one condition,
> will it match all possible, or just the first one? If just the first
> one, the python code below can be simplified by ditching the while loop,
> removing the breaks, and using elif and else.
The match statement should indeed match (and execute) only the first
condition. However you can't simplify the code the way you do: If one of the
inner "if" statements fails, the algorithm should try the next match case.
Your example can't be easily simplified with the match statement. The match
statement isn't meant for string processing, but rather for nested tuples, or
objects. Additionally I didn't yet think about set operations (for "in").
The strength of the match statement is taking complex objects apart, and
testing some conditions on the pieces, at the same time.
Eike.
I've heard of pattern matching in other languages, but never had the
opportunity to play around with them. It seems to me though, that it's
just an enhanced case or switch statement. Python already has had a
proposal to add a case/switch to the language. Unfortunately, due to
lack of consensus on functionality and syntax, and lack of any pressing
need, it hasn't gone anywhere.
> ML style pattern matching is syntactic sugar, that combines "if" statements
> with tuple unpacking, access to object attributes, and assignments. It is a
> compact, yet very readable syntax for algorithms, that would otherwise require
> nested "if" statements. It is especially useful for writing interpreters, and
> processing complex trees.
It doesn't seem very readable to me. It looks like it is heavy on
"magic" characters... for example, what is the purpose of the leading |
character and the trailing -> digraph in this, and how does (| |) imply
attribute access given the rest of Python's syntax?
match x with
| {| a, b |} -> # Attribute existence and access
print("x is an object with attributes 'a' and 'b'.")
print("a=%s, b=%s" % (a, b))
It would require a new keyword "match", and overloading an existing
keyword "with" to have a second meaning. Python is *very* resistant to
adding new keywords. You would need to demonstrate that pattern matching
leads to significant benefits over if...elif...else in order to
compensate for the pain you cause to those who use "match" as a variable
name. This includes Python's own standard library, which has match
functions and methods in the re module.
It also uses special characters in a way that looks more like Perl than
Python. With few exceptions -- iterable slicing comes to mind -- Python
tends to avoid magic characters like that.
If you are serious about pursuing this idea, I suggest you need to
demonstrate some non-trivial gains from pattern matching. Perhaps you
should also look at how Haskell does it, and how functions in Haskell
can be written concisely. Here's a toy example:
factorial :: Integer -> Integer
factorial 0 = 1
factorial n = n * factorial (n - 1)
I'm interested in pattern matching, but I think the suggested syntax is
completely inappropriate for Python. I think that for this to have any
hope, its best bet would be as an enhancement of the case/switch PEP,
and it would need to look like Python code, not like Haskell or OCAML.
--
Steven
I don't object to the general idea, but syntax such as
> | {| a, b |} -> # Attribute existence and access
is far too cryptic and does nothing to improve readability.
--
Greg
def _check_call(f, x):
try:
return f(*x)
except TypeError:
return False
if x ==1:
pass
elif isinstance(x, int):
pass
elif isinstance(x, tuple) and len(x) == 2:
pass
elif hasattr(x, 'a') and hasattr(x, 'b'):
pass
elif _check_call((lambda a, b: a > b), x):
pass
elif isinstance(x, Foo) and isinstance(getattr(x, 'c', None), int) and
getattr(x, 'd', None) == 1:
pass
else:
pass
Cheers.
Nick.
--
Nick Coghlan | ncog...@gmail.com | Brisbane, Australia
> After learning a bit of Ocaml I started to like its pattern matching features.
> Since then I want to have a "match" statement in Python. I wonder if anybody
> else would like this too.
>
> ML style pattern matching is syntactic sugar, that combines "if" statements
> with tuple unpacking, access to object attributes, and assignments. It is a
> compact, yet very readable syntax for algorithms, that would otherwise require
> nested "if" statements. It is especially useful for writing interpreters, and
> processing complex trees.
While I generally like pattern matching in FP languages, I think it is not appropriate and not necessary for a general application language like Python. It is an important feature in FP because (1) it matches (!) FP's general point of view or paradigm (2) FP language example application are very much about algorithmics --far less about general designing/modelling.
> Instead of a specification in BNF, here is a function written with the
> proposed pattern matching syntax. It demonstrates the features that I find
> most important. The comments and the print statements explain what is done.
If ever pattern matching would be considered for inclusion in Python, it would have to fit Python's style, which your proposed syntax really does not. Actually, I find your current-python translation far more readable (except for the enclosing while true hack).
The syntax should look switch/case, probably. A keyword seems necessary to tell apart ordinary switch conditions from pattern matching ones. But it cannot be "match", so let's say "matching". Other changes inline below:
> Proposed Syntax
> ---------------
>
def foo(x):
> match x with
matching x:
> | 1 -> # Equality
case 1:
> print("x is equal to 1")
> | a:int -> # Type check
case int: # <=> isinstance(x, int) or x.__type__==int ???
> print("x has type int: %s" % a)
> | (a, b) -> # Tuple unpacking
case (a, b):
> print("x is a tuple with length 2: (%s, %s)" % (a, b))
> | {| a, b |} -> # Attribute existence and access
case (.a, .b):
> print("x is an object with attributes 'a' and 'b'.")
> print("a=%s, b=%s" % (a, b))
>
> # Additional condition
> | (a, b, c) with a > b ->
case (.a, .b, .c) and a > b:
> print("x is a tuple with length 3: (%s, %s, %s)" % (a, b, c))
> print("The first element is greater than the second element.")
>
> # Complex case
> | {| c:int, d=1 |}:Foo ->
case Foo(.c, .d) and isinstance(c,int) and d == 1:
case Foo(.c, .d) and c.__type__ == int and d == 1:
> print("x has type Foo")
> print("x is an object with attributes 'c' and 'd'.")
> print("'c' has type 'int', 'd' is equal to 1.")
> print("c=%s, d=%s" % (c, d))
>
> # Default case
> | _ ->
else:
> print("x can be anything")
> Equivalent Current Python
> -------------------------
>
> The first four cases could be handled more simply, but handling all cases in
> the same way leads IMHO to more simple code overall.
> [...]
Seems the only annoying aspect in current python is expressing secondary conditions. For instance, if x can be int and have either .a or .b, with different actions in sub-cases. Expressing this "naturally" in python is wrong because if x has neither .a nore .b other cases won't be matched. The only workaround is to have several top-level cases, repeating the top condition about x beeing an int. I guess.
> I left out dict and set, because I'm not sure how they should be handled. I
> think list should be handled like tuples. Probably there should be a universal
> matching syntax for all sequences, similarly to the already existing syntax:
> a, b, *c = s
This cannot be! Even less lists. Proposal:
case [] # check list
case [n] # ditto; n must be int telling length
case {a, b, c} # check set / elements
case {a:, b:, c:} # check dict / keys
An annoying thing is python has no syntax for structured objects. I find acceptable the above used workaround:
(.a, .b, .c)
to tell about attributes and
T(.a, .b, .c)
to additionally check the type.
> I don't really like the "->" digraph at the end of each match case. A colon
> would be much more consistent, but I use colons already for type checking
> (a:int).
Does a:int means isinstance(a,int) or a.__type__==int ?
I would like python to have an 'isa' operator for the latter.
> I generally think that Python should acquire more features from functional
> languages. In analogy to "RPython" it should ultimately lead to "MLPython", a
> subset of the Python language that can be type checked and reasoned about by
> external tools, similarly to what is possible with Ocaml.
I doubt about that for a handful of reasons.
ref to related feature, FWIW: OMeta general structural pattern matching http://tinlizzie.org/ometa/ (with implementation for python)
Denis
-- -- -- -- -- -- --
vit esse estrany ☣
List comprehensions are also cryptic if you see them for the first time. The
curly brackets with bars "{| |}" should symbolize that Python object are
glorified dicts. It is also quite close to Ocaml's syntax for records.
My secret agenda was however, to later introduce a new class and object syntax
for Python. I just didn't dare to propose a completely revised Python. But
here we go: :-)
Class Creation
--------------
Foo = class {| a, b |}
This should be equivalent to:
class Foo(object):
def __init__(self, a, b):
self.a = a
self.b = b
Inheritance is not so important in the context of classes that have no
methods. It could be expressed with a new method ("inherits") of the
metaclass. Like this:
Foo = class {| a, b |}.inherits(Bar, Baz)
How one would create methods, and if it should be possible to create method at
all, needs to be discussed.
Instance Creation
-----------------
foo = {| a=1, b=2 |}:Foo
This should be equivalent to:
foo = Foo(a=1, b=2)
In the usual case, it should not be necessary to specify the class name:
foo = {| a=1, b=2 |}
The run-time should search for a class with a matching "__init__" method. In
case of ambiguities an exception would be raised. You have to name object
attributes unambiguously for this to work. However it is more flexible than
Ocaml because you can disambiguate it by specifying the class name.
These constructions are expression, and can therefore be nested.
The next nice idea from Ocaml would be extending the class system ...
I'm getting a bit off topic though. I'll present a revised syntax for object
access later; generalized constructors.
Eike.
> Class Creation
> --------------
>
> Foo = class {| a, b |}
>
> This should be equivalent to:
>
> class Foo(object):
> def __init__(self, a, b):
> self.a = a
> self.b = b
>
> Inheritance is not so important in the context of classes that have no
> methods. It could be expressed with a new method ("inherits") of the
> metaclass. Like this:
>
> Foo = class {| a, b |}.inherits(Bar, Baz)
>
> How one would create methods, and if it should be possible to create method at
> all, needs to be discussed.
What advantage?
> Instance Creation
> -----------------
>
> foo = {| a=1, b=2 |}:Foo
>
> This should be equivalent to:
>
> foo = Foo(a=1, b=2)
>
> In the usual case, it should not be necessary to specify the class name:
>
> foo = {| a=1, b=2 |}
I want composite object literal notation as well. But certainly not {| a=1, b=2 |}. Rather (a=1, b=2) or (a:1, b:2).
Untyped case would created an instance of Object (but since as of now they can't have attrs, there should be another modif), or of a new FreeObject subtype of Object.
> The run-time should search for a class with a matching "__init__" method.
? conflicts?
Denis
-- -- -- -- -- -- --
vit esse estrany ☣
_______________________________________________
One other point that must be solved, is how to distinguish symbols that should
be assigned, from symbols that are specify conditions. Ocamls solution is that
all symbols are assigned. Conditions must be specified with literals. Here is
an example to illustrate it:
This is a simple function that compares its argument "x" to the integer one:
def foo(x):
match x with
| 1 ->
print("x is equal to 1")
| _ ->
print("x is not equal to 1")
In the code below we want to parametrize the value that we use for comparison.
The parameter "a" is introduced for this purpose. Now we need a way to tell
the compiler that "x" should be compared to "a"; and not assigned to "a". In
Ocaml this is impossible. The compiler would issue a warning ("Redundant case
in a pattern matching.").
def foo(x, a):
match x with
| a ->
print("x is equal to %s" % a)
| _ ->
print("x is not equal to %s" % a)
Maybe you come up with a nice notation for this problem.
By the way, why does no one like those "|" characters? They look good and take
up few space!
Eike.
No, I would do it like in OCaml, I think (but may be wrong) it fits the python-way, like having no formally qualified readonly or private slots.
> By the way, why does no one like those "|" characters? They look good and take
> up few space!
;-) It does not fit Python overall syntax look. And requires a magic id '_' for default case. And requires adding '->'. And we already have 'case x:' (and 'else') which fit perfectly. And are far more readable (no need to guess what given symbols mean, including the 'sense' of an arrow ;-).
> Eike.
Denis
-- -- -- -- -- -- --
vit esse estrany ☣
_______________________________________________
Really?
So Foobar = class {| 17, 'yellow' |}
means
class Foobar()
def __init__(self, 17, 'yellow'):
self.17 = 17
self.'yellow' = 'yellow'
Looks like I'm either stuck with always using a, b, c, etc for attribute
names, or I get compile errors.
This is *definitely* not Pythonic -- offers nothing for readability,
requires new strange symbols... yuck.
If you want a one-liner, make a function:
def Class(*args, **kwargs):
obj = type('Simple', (object, ), dict())
for i, arg in enumerate(args):
attr = chr(ord('a') + i)
setattr(obj, attr, arg)
for kw in kwargs:
setattr(obj, kw, kwargs[kw])
return obj
then
Foobar = Class( 17, 'yellow', this='that' )
and season to taste.
~Ethan~
> Instance Creation
> -----------------
>
> foo = {| a=1, b=2 |}:Foo
>
> This should be equivalent to:
>
> foo = Foo(a=1, b=2)
>
> In the usual case, it should not be necessary to specify the class name:
>
> foo = {| a=1, b=2 |}
>
> The run-time should search for a class with a matching "__init__" method.
I'm beginning to suspect this is an elaborate trolling attempt...
Yes, it's a bit of fun. This would never get into Python anyway, but I'd like
it nevertheless. (It is Ocaml's record syntax with some small tweaks.)
It would be possible to realize it though. With "inspect.getfullargspec" you
can see the a function's signature. There might be problems with efficiency,
because you'd have to search through globals and locals repeatedly. You you
could however store which class matched, somewhere in the code object.
Storing this kind of information would go against Python's nature as a dynamic
language, even though it would work as expected in 99% of the use cases. Oh
well ...
Eike
I don't have any real opinion on this, but this old experiment seems related to the discussion: http://svn.colorstudy.com/home/ianb/recipes/patmatch.py
--
Sent from a phone
On Dec 18, 2010 12:30 PM, "Eike Welk" <eike...@gmx.net> wrote:
On Saturday 18.12.2010 18:34:57 Georg Brandl wrote:
> Am 18.12.2010 12:23, schrieb Eike Welk:
> > In...
Yes, it's a bit of fun. This would never get into Python anyway, but I'd like
it nevertheless. (It is Ocaml's record syntax with some small tweaks.)
It would be possible to realize it though. With "inspect.getfullargspec" you
can see the a function's signature. There might be problems with efficiency,
because you'd have to search through globals and locals repeatedly. You you
could however store which class matched, somewhere in the code object.
Storing this kind of information would go against Python's nature as a dynamic
language, even though it would work as expected in 99% of the use cases. Oh
well ...
Eike
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Python-ideas mailing list
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ht...
On 12/17/2010 6:21 PM, Eike Welk wrote:
After learning a bit of Ocaml I started to like its pattern matching features.
Since then I want to have a "match" statement in Python. I wonder if anybody
else would like this too.
1. completely redundant with respect to current Python syntax;
2. look like chicken scratches;
3. limited by the chars availables to just a few of the infinity of tests one might want to run.
4. gives special prominence to tuples, which is hardly appropriate to list or iterable-oriented code.
x = (3, 4)if x matches (&a, &b):print(a, b)
x = (3, 4)
if isinstance(x, tuple) and len(x) == 2:a, b = x
print(a, b)
x = [3, 4]if x matches [3, &b, *]:print(b)
x = [3, 4]if isinstance(x, list) and x[0] == 3:_, b, *_ = xprint(b)
if x matches {j : &k}:print(k)
if isinstance(x, dict) and j in x and len(x) == 1:k = a[j]print(k)
x matches {'account': (&username, &domain),'type': 'administrator','password': &hash,'friends': (&best_friend, *&other_friends),*}
x matches Foo(a=&alpha, b=&beta)
x matches (3 * 14 + big_complicated_expression, &y)
x matches (f(&y), g(&z))
On Saturday 18.12.2010 22:26:05 Bruce Leban wrote:
> x = (3, 4)
> if x matches (&a, &b):
> print(a, b)
>
>
> is equivalent to
>
> x = (3, 4)
> if isinstance(x, tuple) and len(x) == 2:
> a, b = x
> print(a, b)
...
> Whether or not this is useful at all is a big question, but I think it's at
> least more interesting. This isn't perfect. For example
>
> x matches Foo(a=&alpha, b=&beta)
>
For this case I prose that the class "Foo" should implement a special function
"__rinit__" that breaks an instance apart, into components that can be
matched. These components should be chosen so that they could be given to
"__init__" as its arguments.
"__rinit__" should return the following objects:
* a tuple of objects, corresponding to the regular arguments of "__init__".
* a tuple of strings that contains the argument names.
* a dict of string:object that represents the keyword only attributes.
A simple class would look like this:
class Foo(object):
def __init__(self, c, d):
self.c = c
self.d = d
def __rinit__(self):
return (self.c, self.d), ("c", "d"), {}
The example from above:
x matches Foo(c=&gamma, d=&delta)
would work like this:
if isinstance(x, Foo):
vals, names, kwargs = x.__rinit__()
gamma = vals[names.index("c")]
delta = vals[names.index("d")]
Positional arguments are also possible:
x matches Foo(&gamma, &delta)
would work like this:
if isinstance(x, Foo):
vals, names, kwargs = x.__rinit__()
gamma = vals[0]
delta = vals[0]
A type check would be expressed like this:
x matches Foo(&*_)
> could mean checking x.hasattr('a') but there's no guarantee that Foo(a=1,
> b=2) will produce that result. Maybe that's OK.
>
> Also, any values on the right hand side not marked by & are matched for
> equality, so you could write
>
> x matches (3 * 14 + big_complicated_expression, &y)
It's really neat, but maybe too much visual clutter. It should be discussed if
the following looks better:
x matches (x, y) and x == 3 * 14 + big_complicated_expression
I'm unsure about it.
> which is pretty ugly. And that suggests:
>
> x matches (f(&y), g(&z))
It can only work with the few functions that are bijective. Many algorithms
destroy information and can therefore not be run backwards.
> which either doesn't make sense or is messy. We could add a __matches__
> attribute to functions so they could support this, but now this is getting
> pretty complicated for unclear benefit.
Eike
Not really. A list comp looks like a cross between a list and a
for-loop, which is exactly what a list comp is.
[2*x for x in sequence]
I believe that people -- at least some people -- could intuit the
meaning of this from context. But even if they can't, it's a simple
extension to existing Python syntax they should already know. And best
of all, you can easily experiment on it by copying and pasting a list
comp into the interactive interpreter and seeing what it does.
Your proposed syntax {| |} could be related to sets, or dicts, or both.
Or it could be related to the | operator. If you don't know which, it's
hard to guess. It looks more like a set than a dict:
{a, b} # set
{a: value, b: value} # dict
{|a, b|} # looks like a set with extra symbols
and there's probably nothing you can do with it in isolation from a full
pattern match block.
> My secret agenda was however, to later introduce a new class and object syntax
> for Python. I just didn't dare to propose a completely revised Python. But
> here we go: :-)
>
>
> Class Creation
> --------------
>
> Foo = class {| a, b |}
>
> This should be equivalent to:
>
> class Foo(object):
> def __init__(self, a, b):
> self.a = a
> self.b = b
What's so special about Foo that it needs special syntax just to make it
easier? In any case, these days I'd suggest that's probably best written
as a namedtuple:
>>> from collections import namedtuple
>>> Spam = namedtuple('Spam', 'a b c')
>>> x = Spam(a=23, b=42, c=None)
>>> x
Spam(a=23, b=42, c=None)
> Inheritance is not so important in the context of classes that have no
> methods. It could be expressed with a new method ("inherits") of the
> metaclass. Like this:
>
> Foo = class {| a, b |}.inherits(Bar, Baz)
>
> How one would create methods, and if it should be possible to create method at
> all, needs to be discussed.
I don't think it does :)
I think you're falling into the trap of thinking that everything needs
to be a one-liner. It doesn't.
> Instance Creation
> -----------------
>
> foo = {| a=1, b=2 |}:Foo
>
> This should be equivalent to:
>
> foo = Foo(a=1, b=2)
Why do you think you need two ways of spelling Foo(a=1, b=2)? What's
wrong with the Python syntax for it? It seems to me that you want the
obfuscation of OCAML's syntax with the slowness of Python, a strange
choice...
> In the usual case, it should not be necessary to specify the class name:
>
> foo = {| a=1, b=2 |}
>
> The run-time should search for a class with a matching "__init__" method. In
Oh wow. Just ... wow.
You want the Python virtual machine to do a search through N objects in
K scopes, checking each one to see if it is a class, then checking the
signature of the __init__ method, just to allow the caller to
*implicitly* specify the class of an instance instead of explicitly.
-1000 on that.
> case of ambiguities an exception would be raised. You have to name object
> attributes unambiguously for this to work. However it is more flexible than
> Ocaml because you can disambiguate it by specifying the class name.
>
> These constructions are expression, and can therefore be nested.
*cries*
--
Steven
I would love to see this implemented! Off course I like my syntax better. :-)
On Saturday 18.12.2010 22:26:05 Bruce Leban wrote:
> Whether or not this is useful at all is a big question, but I think it's at> least more interesting. This isn't perfect. For exampleFor this case I prose that the class "Foo" should implement a special function
>
> x matches Foo(a=&alpha, b=&beta)
"__rinit__" that breaks an instance apart, into components that can be
matched. These components should be chosen so that they could be given to
"__init__" as its arguments.
"__rinit__" should return the following objects:
* a tuple of objects, corresponding to the regular arguments of "__init__".
* a tuple of strings that contains the argument names.
* a dict of string:object that represents the keyword only attributes.
A type check would be expressed like this:
x matches Foo(&*_)
x matches Foo(*)
> could mean checking x.hasattr('a') but there's no guarantee that Foo(a=1,It's really neat, but maybe too much visual clutter. It should be discussed if
> b=2) will produce that result. Maybe that's OK.
>
> Also, any values on the right hand side not marked by & are matched for
> equality, so you could write
>
> x matches (3 * 14 + big_complicated_expression, &y)
the following looks better:
x matches (x, y) and x == 3 * 14 + big_complicated_expression
x matches (&k, &y) and k == some_expression
k = some_expressionx matches (k, &y)
I'm unsure about it.
It can only work with the few functions that are bijective. Many algorithms
> which is pretty ugly. And that suggests:
>
> x matches (f(&y), g(&z))
destroy information and can therefore not be run backwards.
> > List comprehensions are also cryptic if you see them for the first time. The
> > curly brackets with bars "{| |}" should symbolize that Python object are
> > glorified dicts. It is also quite close to Ocaml's syntax for records.
>
> Not really. A list comp looks like a cross between a list and a
> for-loop, which is exactly what a list comp is.
And actually python (composite) objects, conceptually, are closer to named tuples than to dicts; composite objects are _not_ collections. That they are based on dicts is, imo, an implementation detail. For this reason, I'm pleased their dict attr is weirdly called "__dict__".
Denis
-- -- -- -- -- -- --
vit esse estrany ☣
_______________________________________________
I like this argument. This might lead to a design decision for the pattern
matching syntax: A pattern that matches an object should look closely like the
code that creates that object.
> > Class Creation
> > --------------
> >
> > Foo = class {| a, b |}
> What's so special about Foo that it needs special syntax just to make it
> easier? In any case, these days I'd suggest that's probably best written
>
> as a namedtuple:
> >>> from collections import namedtuple
> >>> Spam = namedtuple('Spam', 'a b c')
> >>> x = Spam(a=23, b=42, c=None)
> >>> x
>
> Spam(a=23, b=42, c=None)
Yes you are right. namedtuple is rely a perfect substitute for for Ocaml's
records. The only thing which it is missing, is optional type checking in the
constructor. Not only as a consistency test, but also as a terse form of
documentation.
>
> > Inheritance is not so important in the context of classes that have no
> > methods. It could be expressed with a new method ("inherits") of the
> > metaclass. Like this:
> >
> > Foo = class {| a, b |}.inherits(Bar, Baz)
> >
> > How one would create methods, and if it should be possible to create
> > method at all, needs to be discussed.
>
> I don't think it does :)
>
> I think you're falling into the trap of thinking that everything needs
> to be a one-liner. It doesn't.
Yes, in a "real" program you would want to document the attributes, and soon
the class definition would be no longer a one liner.
On the other hand: If the code is short (and readable), you can get an
overview much more easily.
My positive attitude towards this syntax comes from the only weakness that
Python IMHO has: You can't easily see which data attributes an instance has.
This information is hidden in __init__, and sometimes elsewhere. I think a
mechanism like slots should be the norm, and dynamism the exception.
>
> > Instance Creation
> > -----------------
> >
> > foo = {| a=1, b=2 |}:Foo
> >
> > This should be equivalent to:
> >
> > foo = Foo(a=1, b=2)
>
> Why do you think you need two ways of spelling Foo(a=1, b=2)? What's
> wrong with the Python syntax for it? It seems to me that you want the
> obfuscation of OCAML's syntax with the slowness of Python, a strange
> choice...
I would like to combine the nice aspects of Ocaml, with the unproblematic
nature of Python. In Ocaml I like the syntax for records, the match
expression, and some aspects of the file system. Most other things are IMHO
rather horrible.
Eike.
> My positive attitude towards this syntax comes from the only weakness that
> Python IMHO has: You can't easily see which data attributes an instance has.
> This information is hidden in __init__, and sometimes elsewhere.
Agreed.
Rather commonly elsewhere, I guess.
> I think a
> mechanism like slots should be the norm, and dynamism the exception.
I wish we could put in front place the set of intended data attributes, including ones w/o defaults and optional ones. Even better, instanciation with the same param names would automagically set those attributes.
class Point(Object):
x = 0
y = 0
d
color
def __init__(self, HLSColor=None):
if color is not None:
self.color = toRGB(color)
self.d = self.x + self.y
p = Point(x=1, y=2, color=HLS(0,0,50)
assert (p.d == 3)
(untested)
I find those loads of "self.x=x" in constructors sooo stupid --I want the machine to do it for me. __init__ should only define the essential part of obj construction; while the final constructor would do some mechanical job in addition.
Denis
-- -- -- -- -- -- --
vit esse estrany ☣
_______________________________________________
> My positive attitude towards this syntax comes from the only weakness that
> Python IMHO has: You can't easily see which data attributes an instance has.
What's wrong with dir(obj) and vars(obj)?
>>> class Spam:
... x = 1
... def __init__(self):
... self.y = 2
...
>>> obj = Spam()
>>> vars(obj)
{'y': 2}
>>> dir(obj)
['__doc__', '__init__', '__module__', 'x', 'y']
Python has *awesome* self-inspection abilities -- there's very little
you can't easily find out about an object, so much so that people
sometimes complain that you can't really hide information from the
caller in Python -- there are no truly private attributes, only private
by convention. See also the inspect module.
> This information is hidden in __init__, and sometimes elsewhere. I think a
> mechanism like slots should be the norm, and dynamism the exception.
Such a language would no longer be Python. Perhaps it will be a better
language, perhaps a worse one, but it won't be Python.
By the way, __slots__ is intended as a memory optimization, not as a
mechanism for defeating Python's dynamic nature.
--
Steven
On 19 Dec 2010, at 21:26, Steven D'Aprano <st...@pearwood.info> wrote:
> Eike Welk wrote:
>
>> My positive attitude towards this syntax comes from the only weakness that Python IMHO has: You can't easily see which data attributes an instance has.
>
> What's wrong with dir(obj) and vars(obj)?
>
>
> >>> class Spam:
> ... x = 1
> ... def __init__(self):
> ... self.y = 2
> ...
> >>> obj = Spam()
> >>> vars(obj)
> {'y': 2}
> >>> dir(obj)
> ['__doc__', '__init__', '__module__', 'x', 'y']
>
I think the issue that Elke is pointing out is that dir(Spam) knows nothing about y (whereas it would if you used __slots__).
One answer is to have class member defaults for all instance members.
Michael
I should have expressed it more clearly, I was referring to the source text.
In the declaration of a class in C++ you can see the data attributes that its
instances use. In a Python class you have to look at the "__init__" method,
and possibly into other methods, to see which data attributes are used. It's
much harder to get an overview over the data attributes in Python.
Python's introspection features are off course great.
Eike
P.S.: In my last mail, I also wanted to express that "I like Ocaml's type
system", not its "file system".
These days, a nice solution to that problem is to define a named tuple
and inherit from it (see the 3.2 version of urllib.parse for a number
of examples).
Cheers,
Nick.
--
Nick Coghlan | ncog...@gmail.com | Brisbane, Australia
Then he should have said -- he explicitly said:
"You can't easily see which data attributes an INSTANCE has."
[emphasis added]
As a general rule, you can't expect the class to know what attributes an
instance has. This is a deliberate design choice. If you want to find
out what attributes an object has, you ask the object, not the object's
parent class.
Think of this as a variation on the Law of Demeter: if you want to know
how many fleas a dog has, inspect the dog, not the dog's owner.
> One answer is to have class member defaults for all instance members.
Well, that's an answer, but I'm not sure what the question is. From time
to time I create a class which includes default class attributes, which
then get optionally overridden by instance attributes. But that's much
rarer than the usual case, where the instance has the attributes and the
class doesn't.
I would find it very disturbing to see classes declare meaningless class
attributes (probably set to None) just to make it easier to predict what
attributes the instances will get. That's pretty close to this horror:
def spam():
# Declare all local variables which will be used.
a = None
b = None
c = None
# Now use them.
a = 1
b = function(a, 23, -2)
c = another_func(b)
return a+b+c
Personally, I've never found this to be a problem in practice. If I want
to find out what attributes an instance of a class will have, I
instantiate the class and inspect the instance. Or I read the docs.
Looking at the source code is also an option (if the source code is
available). For most classes, any attributes will be set in the __init__
method. If you have to read the source to determine what attributes
exist, there's not much difference between:
class Spam:
a = 1
b = 2
c = 3
and
class Spam:
def __init(self):
self.a = 1
self.b = 2
self.c = 3
But normally I just care about methods, not data attributes, and for
that dir(cls) is perfectly adequate. (There may be the odd object that
includes instance methods, but they'll be rare.)
Michael wrote:[...]
On 19 Dec 2010, at 21:26, Steven D'Aprano <st...@pearwood.info> wrote:
Eike Welk wrote:
My positive attitude towards this syntax comes from the only weakness that Python IMHO has: You can't easily see which data attributes an instance has.What's wrong with dir(obj) and vars(obj)?
Then he should have said -- he explicitly said:
I think the issue that Elke is pointing out is that dir(Spam) knows nothing about y (whereas it would if you used __slots__).
"You can't easily see which data attributes an INSTANCE has."
[emphasis added]
As a general rule, you can't expect the class to know what attributes an instance has. This is a deliberate design choice. If you want to find out what attributes an object has, you ask the object, not the object's parent class.
Think of this as a variation on the Law of Demeter: if you want to know how many fleas a dog has, inspect the dog, not the dog's owner.Well, that's an answer, but I'm not sure what the question is. From time to time I create a class which includes default class attributes, which then get optionally overridden by instance attributes. But that's much rarer than the usual case, where the instance has the attributes and the class doesn't.
One answer is to have class member defaults for all instance members.
I would find it very disturbing to see classes declare meaningless class attributes (probably set to None) just to make it easier to predict what attributes the instances will get. That's pretty close to this horror:
[snip...]
Personally, I've never found this to be a problem in practice.
If I want to find out what attributes an instance of a class will have, I instantiate the class and inspect the instance. Or I read the docs. Looking at the source code is also an option (if the source code is available). For most classes, any attributes will be set in the __init__ method. If you have to read the source to determine what attributes exist, there's not much difference between:
class Spam:
a = 1
b = 2
c = 3
and
class Spam:
def __init(self):
self.a = 1
self.b = 2
self.c = 3
But normally I just care about methods, not data attributes, and for that dir(cls) is perfectly adequate. (There may be the odd object that includes instance methods, but they'll be rare.)
--
Steven
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May you find forgiveness for yourself and forgive others
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-- the sqlite blessing http://www.sqlite.org/different.html
Automating that is quite easy with keyword arguments:
>>> class Foo(object):
... def __init__(self, **kwargs):
... self.__dict__.update(kwargs)
...
>>> f = Foo(a=1, b=2)
>>> f.a
1
>>> f.b
2
If you want to play safe, filter out keys that start with '__'.
Best regards and a happy new year!
Mart Sõmermaa