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def _flatten_dict(dct: dict[str, Any]) -> list[str]:
    # for each key:
    # - find values
    # - if dict: recurse
    # - elif list: recurse for each item
    # - else: check if bool.
    # - if bool and True, compose a string that you pass around
    #   to join the param names.
    # This was coded for a specific use-case and YAML design; it should
    # be fairly straightforward to adapt to produce just the keys.

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# %%
import pyproj
import pyresample
import xarray
import numpy as np


def lon_lat_to_geostationary_area_coords(
    x: float,
    y: float,

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.editor-group-watermark > .letterpress{
  background-image: url("https://raw.githubusercontent.com/Aikoyori/ProgrammingVTuberLogos/main/VSCode/VSCode-Thick.png") !important;
  opacity: .75;
  aspect-ratio: 3/2 !important;
}

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.editor-group-watermark > .letterpress{
  background-image: url("https://raw.githubusercontent.com/Aikoyori/ProgrammingVTuberLogos/main/VSCode/VSCode-Thick.png") !important;
  opacity: .75;
  aspect-ratio: 3/2 !important;
}

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import xarray

variables = [
    'u_component_of_wind',
    'v_component_of_wind',
    'geopotential',
    'temperature',
    # ... full list of variables here: https://console.cloud.google.com/storage/browser/gcp-public-data-arco-era5/ar/1959-2022-full_37-1h-0p25deg-chunk-1.zarr-v2;tab=objects?pli=1&prefix=&forceOnObjectsSortingFiltering=false
]

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import json
import pyhf
from pyhf.contrib.utils import download
import cabinetry

download("https://www.hepdata.net/record/resource/1935437?view=true", "bottom-squarks")
ws = pyhf.Workspace(json.load(open("bottom-squarks/RegionC/BkgOnly.json")))
patchset = pyhf.PatchSet(json.load(open("bottom-squarks/RegionC/patchset.json")))
ws = patchset.apply(ws, "sbottom_600_280_150")
cabinetry.workspace.save(ws, "bottom-squarks.json")

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import jax.scipy as jsp
import equinox as eqx
import jax.numpy as jnp
from jax import Array
import jax

jax.config.update("jax_enable_x64", True)


@jax.jit

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import polars as pl
import os
import shutil


q = (
    pl.scan_csv("l.csv")
)

df = q.collect()

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import os
import glob
from re import sub
import subprocess

for fname in glob.glob("images/*.pdf"):
    subprocess.run(
        [
            "inkscape",
            "--pdf-poppler",

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from __future__ import annotations
from jax import numpy as jnp
from typing import Any

def convert_jax(spec: dict[str, Any]) -> None:
    for key, value in spec.items():
        value_type = type(value)
        if value_type == dict:
            convert_jax(value)