ENH Add `micropip.freeze`. This adds a function `micropip.freeze()` which creates a `packages.json`
lock file which includes all packages that were loaded by micropip in the
current Pyodide session. This can be used in subsequent sessions to load
the same set of packages with `pyodide.loadPackage`.

For example in our repl:

```py
from js.console import log
import micropip
await micropip.install("sphinx-version-warning") # Installs 19 wheels from pypi
log(micropip.freeze())
```
Then opening the browser console, we can copy the JSON and make a new `packages.json`
file out of it. (Our repl will just say "<Long output truncated>" but the browser
console truncates it and provides tools to make it easy to copy.) Reloading the page
with the new `packages.json`, `versionwarning` will autoload:
```py
import versionwarning # Automatically loads 19 wheels from PyPI
```
We detected that `versionwarning` is an export provided by the `sphinx-version-warning`
package via the `top_level.txt` file. Distressingly this file is part of the `egg-info`
spec but isn't mentioned anywhere in the `dist-info` spec. But wheels seem to include
it nonetheless.
### Description

### Checklists

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- [x] Add new / update outdated documentation

from pyodide_test_runner import run_in_pyodide


@run_in_pyodide(
    standalone=True,
    packages=["numcodecs", "numpy"],
    xfail_browsers={
        "chrome": "test_numcodecs triggers a recursion error in chrome",
    },
)
def test_blosc():
    import array

    import numpy as np
    from numcodecs.blosc import Blosc
    from numcodecs.compat import ensure_bytes, ensure_ndarray
    from numcodecs.lz4 import LZ4
    from numcodecs.zstd import Zstd
    from numpy.testing import assert_array_almost_equal, assert_array_equal

    def compare_arrays(arr, res, precision=None):
        # ensure numpy array with matching dtype
        res = ensure_ndarray(res).view(arr.dtype)

        # convert to correct shape
        if arr.flags.f_contiguous:
            order = "F"
        else:
            order = "C"
        res = res.reshape(arr.shape, order=order)

        # exact compare
        if precision is None:
            assert_array_equal(arr, res)

        # fuzzy compare
        else:
            assert_array_almost_equal(arr, res, decimal=precision)

    def check_encode_decode(arr, codec, precision=None):

        # N.B., watch out here with blosc compressor, if the itemsize of
        # the source buffer is different then the results of encoding
        # (i.e., compression) may be different. Hence we *do not* require that
        # the results of encoding be identical for all possible inputs, rather
        # we just require that the results of the encode/decode round-trip can
        # be compared to the original array.

        # encoding should support any object exporting the buffer protocol

        # test encoding of numpy array
        enc = codec.encode(arr)
        dec = codec.decode(enc)
        compare_arrays(arr, dec, precision=precision)

        # test encoding of bytes
        buf = arr.tobytes(order="A")
        enc = codec.encode(buf)
        dec = codec.decode(enc)
        compare_arrays(arr, dec, precision=precision)

        # test encoding of bytearray
        buf = bytearray(arr.tobytes(order="A"))
        enc = codec.encode(buf)
        dec = codec.decode(enc)
        compare_arrays(arr, dec, precision=precision)

        # test encoding of array.array
        buf = array.array("b", arr.tobytes(order="A"))
        enc = codec.encode(buf)
        dec = codec.decode(enc)
        compare_arrays(arr, dec, precision=precision)

        # decoding should support any object exporting the buffer protocol,

        # setup
        enc_bytes = ensure_bytes(enc)

        # test decoding of raw bytes
        dec = codec.decode(enc_bytes)
        compare_arrays(arr, dec, precision=precision)

        # test decoding of bytearray
        dec = codec.decode(bytearray(enc_bytes))
        compare_arrays(arr, dec, precision=precision)

        # test decoding of array.array
        buf = array.array("b", enc_bytes)
        dec = codec.decode(buf)
        compare_arrays(arr, dec, precision=precision)

        # test decoding of numpy array
        buf = np.frombuffer(enc_bytes, dtype="u1")
        dec = codec.decode(buf)
        compare_arrays(arr, dec, precision=precision)

        # test decoding directly into numpy array
        out = np.empty_like(arr)
        codec.decode(enc_bytes, out=out)
        compare_arrays(arr, out, precision=precision)

        # test decoding directly into bytearray
        out = bytearray(arr.nbytes)
        codec.decode(enc_bytes, out=out)
        # noinspection PyTypeChecker
        compare_arrays(arr, out, precision=precision)

    # mix of dtypes: integer, float, bool, string
    # mix of shapes: 1D, 2D, 3D
    # mix of orders: C, F
    arrays = [
        np.arange(1000, dtype="i4"),
        np.linspace(1000, 1001, 1000, dtype="f8"),
        np.random.normal(loc=1000, scale=1, size=(100, 10)),
        np.random.randint(0, 2, size=1000, dtype=bool).reshape(100, 10, order="F"),
        np.random.choice([b"a", b"bb", b"ccc"], size=1000).reshape(10, 10, 10),
        np.random.randint(0, 2**60, size=1000, dtype="u8").view("M8[ns]"),
        np.random.randint(0, 2**60, size=1000, dtype="u8").view("m8[ns]"),
        np.random.randint(0, 2**25, size=1000, dtype="u8").view("M8[m]"),
        np.random.randint(0, 2**25, size=1000, dtype="u8").view("m8[m]"),
        np.random.randint(-(2**63), -(2**63) + 20, size=1000, dtype="i8").view(
            "M8[ns]"
        ),
        np.random.randint(-(2**63), -(2**63) + 20, size=1000, dtype="i8").view(
            "m8[ns]"
        ),
        np.random.randint(-(2**63), -(2**63) + 20, size=1000, dtype="i8").view(
            "M8[m]"
        ),
        np.random.randint(-(2**63), -(2**63) + 20, size=1000, dtype="i8").view(
            "m8[m]"
        ),
    ]

    codecs = [
        LZ4(),
        LZ4(acceleration=-1),
        LZ4(acceleration=10),
        Zstd(),
        Zstd(level=-1),
        Zstd(level=10),
        Blosc(shuffle=Blosc.SHUFFLE),
        Blosc(clevel=0, shuffle=Blosc.SHUFFLE),
        Blosc(cname="lz4", shuffle=Blosc.SHUFFLE),
        Blosc(cname="lz4", clevel=1, shuffle=Blosc.NOSHUFFLE),
        Blosc(cname="lz4", clevel=5, shuffle=Blosc.SHUFFLE),
        Blosc(cname="lz4", clevel=9, shuffle=Blosc.BITSHUFFLE),
        Blosc(cname="zlib", clevel=1, shuffle=0),
        Blosc(cname="zstd", clevel=1, shuffle=1),
        Blosc(cname="blosclz", clevel=1, shuffle=2),
        Blosc(shuffle=Blosc.SHUFFLE, blocksize=0),
        Blosc(shuffle=Blosc.SHUFFLE, blocksize=2**8),
        Blosc(cname="lz4", clevel=1, shuffle=Blosc.NOSHUFFLE, blocksize=2**8),
    ]
    for codec in codecs:
        for arr in arrays:
            check_encode_decode(arr, codec)

from pyodide_test_runner import run_in_pyodide


@run_in_pyodide(
    standalone=True,
    packages=["numcodecs", "numpy"],
    xfail_browsers={
        "chrome": "test_numcodecs triggers a recursion error in chrome",
    },
)
def test_blosc():
    import array

    import numpy as np
    from numcodecs.blosc import Blosc
    from numcodecs.compat import ensure_bytes, ensure_ndarray
    from numcodecs.lz4 import LZ4
    from numcodecs.zstd import Zstd
    from numpy.testing import assert_array_almost_equal, assert_array_equal

    def compare_arrays(arr, res, precision=None):
        # ensure numpy array with matching dtype
        res = ensure_ndarray(res).view(arr.dtype)

        # convert to correct shape
        if arr.flags.f_contiguous:
            order = "F"
        else:
            order = "C"
        res = res.reshape(arr.shape, order=order)

        # exact compare
        if precision is None:
            assert_array_equal(arr, res)

        # fuzzy compare
        else:
            assert_array_almost_equal(arr, res, decimal=precision)

    def check_encode_decode(arr, codec, precision=None):

        # N.B., watch out here with blosc compressor, if the itemsize of
        # the source buffer is different then the results of encoding
        # (i.e., compression) may be different. Hence we *do not* require that
        # the results of encoding be identical for all possible inputs, rather
        # we just require that the results of the encode/decode round-trip can
        # be compared to the original array.

        # encoding should support any object exporting the buffer protocol

        # test encoding of numpy array
        enc = codec.encode(arr)
        dec = codec.decode(enc)
        compare_arrays(arr, dec, precision=precision)

        # test encoding of bytes
        buf = arr.tobytes(order="A")
        enc = codec.encode(buf)
        dec = codec.decode(enc)
        compare_arrays(arr, dec, precision=precision)

        # test encoding of bytearray
        buf = bytearray(arr.tobytes(order="A"))
        enc = codec.encode(buf)
        dec = codec.decode(enc)
        compare_arrays(arr, dec, precision=precision)

        # test encoding of array.array
        buf = array.array("b", arr.tobytes(order="A"))
        enc = codec.encode(buf)
        dec = codec.decode(enc)
        compare_arrays(arr, dec, precision=precision)

        # decoding should support any object exporting the buffer protocol,

        # setup
        enc_bytes = ensure_bytes(enc)

        # test decoding of raw bytes
        dec = codec.decode(enc_bytes)
        compare_arrays(arr, dec, precision=precision)

        # test decoding of bytearray
        dec = codec.decode(bytearray(enc_bytes))
        compare_arrays(arr, dec, precision=precision)

        # test decoding of array.array
        buf = array.array("b", enc_bytes)
        dec = codec.decode(buf)
        compare_arrays(arr, dec, precision=precision)

        # test decoding of numpy array
        buf = np.frombuffer(enc_bytes, dtype="u1")
        dec = codec.decode(buf)
        compare_arrays(arr, dec, precision=precision)

        # test decoding directly into numpy array
        out = np.empty_like(arr)
        codec.decode(enc_bytes, out=out)
        compare_arrays(arr, out, precision=precision)

        # test decoding directly into bytearray
        out = bytearray(arr.nbytes)
        codec.decode(enc_bytes, out=out)
        # noinspection PyTypeChecker
        compare_arrays(arr, out, precision=precision)

    # mix of dtypes: integer, float, bool, string
    # mix of shapes: 1D, 2D, 3D
    # mix of orders: C, F
    arrays = [
        np.arange(1000, dtype="i4"),
        np.linspace(1000, 1001, 1000, dtype="f8"),
        np.random.normal(loc=1000, scale=1, size=(100, 10)),
        np.random.randint(0, 2, size=1000, dtype=bool).reshape(100, 10, order="F"),
        np.random.choice([b"a", b"bb", b"ccc"], size=1000).reshape(10, 10, 10),
        np.random.randint(0, 2**60, size=1000, dtype="u8").view("M8[ns]"),
        np.random.randint(0, 2**60, size=1000, dtype="u8").view("m8[ns]"),
        np.random.randint(0, 2**25, size=1000, dtype="u8").view("M8[m]"),
        np.random.randint(0, 2**25, size=1000, dtype="u8").view("m8[m]"),
        np.random.randint(-(2**63), -(2**63) + 20, size=1000, dtype="i8").view(
            "M8[ns]"
        ),
        np.random.randint(-(2**63), -(2**63) + 20, size=1000, dtype="i8").view(
            "m8[ns]"
        ),
        np.random.randint(-(2**63), -(2**63) + 20, size=1000, dtype="i8").view(
            "M8[m]"
        ),
        np.random.randint(-(2**63), -(2**63) + 20, size=1000, dtype="i8").view(
            "m8[m]"
        ),
    ]

    codecs = [
        LZ4(),
        LZ4(acceleration=-1),
        LZ4(acceleration=10),
        Zstd(),
        Zstd(level=-1),
        Zstd(level=10),
        Blosc(shuffle=Blosc.SHUFFLE),
        Blosc(clevel=0, shuffle=Blosc.SHUFFLE),
        Blosc(cname="lz4", shuffle=Blosc.SHUFFLE),
        Blosc(cname="lz4", clevel=1, shuffle=Blosc.NOSHUFFLE),
        Blosc(cname="lz4", clevel=5, shuffle=Blosc.SHUFFLE),
        Blosc(cname="lz4", clevel=9, shuffle=Blosc.BITSHUFFLE),
        Blosc(cname="zlib", clevel=1, shuffle=0),
        Blosc(cname="zstd", clevel=1, shuffle=1),
        Blosc(cname="blosclz", clevel=1, shuffle=2),
        Blosc(shuffle=Blosc.SHUFFLE, blocksize=0),
        Blosc(shuffle=Blosc.SHUFFLE, blocksize=2**8),
        Blosc(cname="lz4", clevel=1, shuffle=Blosc.NOSHUFFLE, blocksize=2**8),
    ]
    for codec in codecs:
        for arr in arrays:
            check_encode_decode(arr, codec)
