Download standard libraries in a zipfile. ### Description

This is a re-work of #3166. After this PR, the standard libraries are not vendored with `pyodide.asm.data`. Instead, it is now downloaded separately in a zip file similar to how we download pyodide_py.tar.

~~The hard part of this PR is to bootstrap Python without Python source codes. This requires deep-freezing all modules that are required during the bootstrap.~~

~~As mentioned in #3539, `encodings` module is needed during the bootstrap stage, but it is a large module (> 1.0MB) containing a bunch of encodings in the world, so I tried to freeze a subset of the encodings module that is used in the bootstrap (thanks for the idea from Hood), so the size increase of pyodide.asm.wasm is only 70KB.~~

~~However, the problem of freezing only part of the module is that the current Python import system does not support it. Therefore, I added some hacks to make it work, which is explained in a comment in pyodide.ts.~~

### File size change after this PR:

Before

```
- pyodide.asm.data:
    Original size: 4555 KB
    Gzip compressed size (level 1): 3062 KB
    Gzip compressed size (level 6): 2911 KB
    Gzip compressed size (level 9): 2911 KB
    Brotli compressed size: 2522 KB
- pyodide.asm.js:
    Original size: 1186 KB
    Gzip compressed size (level 1): 246 KB
    Gzip compressed size (level 6): 208 KB
    Gzip compressed size (level 9): 208 KB
    Brotli compressed size: 169 KB
- pyodide.asm.wasm:
    Original size: 8715 KB
    Gzip compressed size (level 1): 3142 KB
    Gzip compressed size (level 6): 2791 KB
    Gzip compressed size (level 9): 2791 KB
    Brotli compressed size: 2096 KB
```

After

```
- pyodide.asm.data:
    Original size: 4 KB
    Gzip compressed size (level 1): 0 KB
    Gzip compressed size (level 6): 0 KB
    Gzip compressed size (level 9): 0 KB
    Brotli compressed size: 0 KB
- pyodide.asm.js:
    Original size: 1086 KB
    Gzip compressed size (level 1): 213 KB
    Gzip compressed size (level 6): 177 KB
    Gzip compressed size (level 9): 177 KB
    Brotli compressed size: 145 KB
- pyodide.asm.wasm:
    Original size: 8775 KB
    Gzip compressed size (level 1): 3162 KB
    Gzip compressed size (level 6): 2806 KB
    Gzip compressed size (level 9): 2806 KB
    Brotli compressed size: 2105 KB
- python_stdlib.zip:
    Original size: 2230 KB
    Gzip compressed size (level 1): 2196 KB
    Gzip compressed size (level 6): 2194 KB
    Gzip compressed size (level 9): 2194 KB
    Brotli compressed size: 2181 KB
```


### Remaining works:

- remove pyodide.asm.data: the only remaining parts inside pyodide.asm.data is our [webbrowser.py](https://github.com/pyodide/pyodide/blob/main/src/py/lib/webbrowser.py) stub, I think we can either remove it or move it into pyodide_py.
- maybe merge pyodide_py.tar into the standard libraries zipfile.
- add option to use pycompiled standard libraries.

### Checklists

- [x] Add a [CHANGELOG](https://github.com/pyodide/pyodide/blob/main/docs/project/changelog.md) entry
- [x] Add / update tests

# from: http://continuum.io/blog/numba_performance
# setup: N = 10 ; import numpy as np ; image = np.random.rand(N, N, 3) ; state = np.zeros((N, N, 2)) ; state_next = np.empty_like(state) ; state[0, 0, 0] = state[0, 0, 1] = 1
# run: growcut(image, state, state_next, 2)

# pythran export growcut(float[][][], float[][][], float[][][], int)
import math


def window_floor(idx, radius):
    if radius > idx:
        return 0
    else:
        return idx - radius


def window_ceil(idx, ceil, radius):
    if idx + radius > ceil:
        return ceil
    else:
        return idx + radius


def growcut(image, state, state_next, window_radius):
    changes = 0
    sqrt_3 = math.sqrt(3.0)

    height = image.shape[0]
    width = image.shape[1]

    for j in range(width):
        for i in range(height):

            winning_colony = state[i, j, 0]
            defense_strength = state[i, j, 1]

            for jj in range(
                window_floor(j, window_radius), window_ceil(j + 1, width, window_radius)
            ):
                for ii in range(
                    window_floor(i, window_radius),
                    window_ceil(i + 1, height, window_radius),
                ):
                    if ii != i and jj != j:
                        d = image[i, j, 0] - image[ii, jj, 0]
                        s = d * d
                        for k in range(1, 3):
                            d = image[i, j, k] - image[ii, jj, k]
                            s += d * d
                        gval = 1.0 - math.sqrt(s) / sqrt_3

                        attack_strength = gval * state[ii, jj, 1]

                        if attack_strength > defense_strength:
                            defense_strength = attack_strength
                            winning_colony = state[ii, jj, 0]
                            changes += 1

            state_next[i, j, 0] = winning_colony
            state_next[i, j, 1] = defense_strength

    return changes

# from: http://continuum.io/blog/numba_performance
# setup: N = 10 ; import numpy as np ; image = np.random.rand(N, N, 3) ; state = np.zeros((N, N, 2)) ; state_next = np.empty_like(state) ; state[0, 0, 0] = state[0, 0, 1] = 1
# run: growcut(image, state, state_next, 2)

# pythran export growcut(float[][][], float[][][], float[][][], int)
import math


def window_floor(idx, radius):
    if radius > idx:
        return 0
    else:
        return idx - radius


def window_ceil(idx, ceil, radius):
    if idx + radius > ceil:
        return ceil
    else:
        return idx + radius


def growcut(image, state, state_next, window_radius):
    changes = 0
    sqrt_3 = math.sqrt(3.0)

    height = image.shape[0]
    width = image.shape[1]

    for j in range(width):
        for i in range(height):

            winning_colony = state[i, j, 0]
            defense_strength = state[i, j, 1]

            for jj in range(
                window_floor(j, window_radius), window_ceil(j + 1, width, window_radius)
            ):
                for ii in range(
                    window_floor(i, window_radius),
                    window_ceil(i + 1, height, window_radius),
                ):
                    if ii != i and jj != j:
                        d = image[i, j, 0] - image[ii, jj, 0]
                        s = d * d
                        for k in range(1, 3):
                            d = image[i, j, k] - image[ii, jj, k]
                            s += d * d
                        gval = 1.0 - math.sqrt(s) / sqrt_3

                        attack_strength = gval * state[ii, jj, 1]

                        if attack_strength > defense_strength:
                            defense_strength = attack_strength
                            winning_colony = state[ii, jj, 0]
                            changes += 1

            state_next[i, j, 0] = winning_colony
            state_next[i, j, 1] = defense_strength

    return changes
