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 https://github.com/sklam/numba-example-wavephysics
# setup: N=100
# run: wave(N)
import numpy as np


def physics(masspoints, dt, plunk, which):
    ppos = masspoints[1]
    cpos = masspoints[0]
    N = cpos.shape[0]
    # apply hooke's law
    HOOKE_K = 2100000.0
    DAMPING = 0.0001
    MASS = 0.01

    force = np.zeros((N, 2))
    for i in range(1, N):
        dx, dy = cpos[i] - cpos[i - 1]
        dist = np.sqrt(dx**2 + dy**2)
        assert dist != 0
        fmag = -HOOKE_K * dist
        cosine = dx / dist
        sine = dy / dist
        fvec = np.array([fmag * cosine, fmag * sine])
        force[i - 1] -= fvec
        force[i] += fvec

    force[0] = force[-1] = 0, 0
    force[which][1] += plunk
    accel = force / MASS

    # verlet integration
    npos = (2 - DAMPING) * cpos - (1 - DAMPING) * ppos + accel * (dt**2)

    masspoints[1] = cpos
    masspoints[0] = npos


# pythran export wave(int)


def wave(PARTICLE_COUNT):
    SUBDIVISION = 300
    FRAMERATE = 60
    count = PARTICLE_COUNT
    width, height = 1200, 400

    masspoints = np.empty((2, count, 2), np.float64)
    initpos = np.zeros(count, np.float64)
    for i in range(1, count):
        initpos[i] = initpos[i - 1] + float(width) / count
    masspoints[:, :, 0] = initpos
    masspoints[:, :, 1] = height / 2
    f = 15
    plunk_pos = count // 2
    physics(masspoints, 1.0 / (SUBDIVISION * FRAMERATE), f, plunk_pos)
    return masspoints[0, count // 2]

# from https://github.com/sklam/numba-example-wavephysics
# setup: N=100
# run: wave(N)
import numpy as np


def physics(masspoints, dt, plunk, which):
    ppos = masspoints[1]
    cpos = masspoints[0]
    N = cpos.shape[0]
    # apply hooke's law
    HOOKE_K = 2100000.0
    DAMPING = 0.0001
    MASS = 0.01

    force = np.zeros((N, 2))
    for i in range(1, N):
        dx, dy = cpos[i] - cpos[i - 1]
        dist = np.sqrt(dx**2 + dy**2)
        assert dist != 0
        fmag = -HOOKE_K * dist
        cosine = dx / dist
        sine = dy / dist
        fvec = np.array([fmag * cosine, fmag * sine])
        force[i - 1] -= fvec
        force[i] += fvec

    force[0] = force[-1] = 0, 0
    force[which][1] += plunk
    accel = force / MASS

    # verlet integration
    npos = (2 - DAMPING) * cpos - (1 - DAMPING) * ppos + accel * (dt**2)

    masspoints[1] = cpos
    masspoints[0] = npos


# pythran export wave(int)


def wave(PARTICLE_COUNT):
    SUBDIVISION = 300
    FRAMERATE = 60
    count = PARTICLE_COUNT
    width, height = 1200, 400

    masspoints = np.empty((2, count, 2), np.float64)
    initpos = np.zeros(count, np.float64)
    for i in range(1, count):
        initpos[i] = initpos[i - 1] + float(width) / count
    masspoints[:, :, 0] = initpos
    masspoints[:, :, 1] = height / 2
    f = 15
    plunk_pos = count // 2
    physics(masspoints, 1.0 / (SUBDIVISION * FRAMERATE), f, plunk_pos)
    return masspoints[0, count // 2]
