[Python-Dev] Re: PEP 638: Syntactic macros
It looks like this hasn't gone anywhere in the past few years, which is a shame. Syntactic macros are one of the 2 or 3 "Killer features" that pushed me out of Python and into Julia (along with JITting inferred types and multiple dispatch). Math+data science code written in Julia is a lot more readable because of this. ___ Python-Dev mailing list -- [email protected] To unsubscribe send an email to [email protected] https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/[email protected]/message/PPCXZJYPNNT6XZ6EQ35OQE4SG2QBAZRT/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: PEP 638: Syntactic macros
Unfortunately, it's no longer being maintained. ___ Python-Dev mailing list -- [email protected] To unsubscribe send an email to [email protected] https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/[email protected]/message/UEPTBUIK67NLNE4JBNN6JNJON3BRGSUK/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: PEP 638: Syntactic macros
I think that's exactly the problem with a lack of Python macros. The full quote, of course, goes: "There should be one-- and preferably only one --*obvious* way to do it." Often, there's a mathematical notation for something, and *this* is the only obvious way to write anything out. But this doesn't work if you force every package to adopt the same syntax. For example, if you'd like a package to work with probabilities, it's very reasonable to want to write `x ~ Normal(0, 1)` to say x follows a normal distribution. This is the only syntax I consider natural for this problem; but packages can't do that, since `~` already has a meaning outside of probability. Not to mention, DSLs are forced to adopt all kinds of weird syntax when the behavior of base Python doesn't align with what the DSL needs to do. Obviously, the only way to write out a `for` loop should be to use the `for` keyword. This doesn't work in JAX. If you want to use a `for` loop in JAX, you have to use the `lax.fori_loop` function, or else `for` will end up being unrolled, because of various requirements of the JAX compiler. Having to use `lax.fori_loop` is, to put it mildly, *incredibly* unpythonic. This really is the biggest reason I switched to Julia: Python math is unpythonic. I don't want to be forced to learn lots of weird little functions like `np.matmul(x1, x2)` when there's already one obvious syntax I'm very familiar with: `x1 * x2`. ___ Python-Dev mailing list -- [email protected] To unsubscribe send an email to [email protected] https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/[email protected]/message/6QM4GMH5FDX2H5OZHCE33EOJHCV3TI2R/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: PEP 638: Syntactic macros
> Python has consistently refused to be turned into a platform for DSLs for
> almost 3 decades.
I think SymPy, PyMC, Pyomo, Pyro, and many more packages would all be very
surprised to hear they're no longer welcome in Python. Still, it seems like it
would be quite hard to kick them out, and would probably make the scientific
programming community pretty angry. If you don't like having DSLs in Python, I
think you're trying to close the barn door after the horse has bolted; you'd
have to go back in time to the creation of NumPy.
Syntactic macros aren't necessary for DSLs; it just makes them better. Without
syntactic macros, DSLs are forced to use clunky, complicated, and error-prone
string manipulation, rather than cleaner syntactic transformations. For
instance, here's NumPy's einsum, effectively behaving like a string macro:
```
X = np.einsum('ij,jk->ik', A, B, optimize='optimal')
```
And now here's the same thing in Julia:
```
@einsum X[i, k] := A[i, j] * B[j, k]
```
Which is more readable? Which is more Pythonic?
It's not that Python doesn't have DSLs (NumPy is effectively a DSL for linear
algebra). It's just that their syntax is sufficiently obscure that it's not at
all clear that's what they're doing.
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