René's URL Explorer Experiment

{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"[Bug]: missing stubs for `plt.cm` (a.k.a. `matplotlib.pyplot.cm`)","articleBody":"### Bug summary\n\nIf I run `help(plt.cm)` I get a very nice runtime type info:\n\n\u003cdetails\u003e\n\u003csummary\u003e\u003cpre\u003ehelp(plt.cm)\u003c/pre\u003e\u003c/summary\u003e\n\u003cpre\u003e\nhelp(plt.cm)\nHelp on module matplotlib.cm in matplotlib:\nNAME\n    matplotlib.cm - Builtin colormaps, colormap handling utilities, and the `ScalarMappable` mixin.\nDESCRIPTION\n    .. seealso::\n      :doc:`/gallery/color/colormap_reference` for a list of builtin colormaps.\n      :ref:`colormap-manipulation` for examples of how to make\n      colormaps.\n      :ref:`colormaps` an in-depth discussion of choosing\n      colormaps.\n      :ref:`colormapnorms` for more details about data normalization.\nCLASSES\n    collections.abc.Mapping(collections.abc.Collection)\n        ColormapRegistry\n    class ColormapRegistry(collections.abc.Mapping)\n     |  ColormapRegistry(cmaps)\n     |\n     |  Container for colormaps that are known to Matplotlib by name.\n     |\n     |  The universal registry instance is `matplotlib.colormaps`. There should be\n     |  no need for users to instantiate `.ColormapRegistry` themselves.\n     |\n     |  Read access uses a dict-like interface mapping names to `.Colormap`\\s::\n     |\n     |      import matplotlib as mpl\n     |      cmap = mpl.colormaps['viridis']\n     |\n     |  Returned `.Colormap`\\s are copies, so that their modification does not\n     |  change the global definition of the colormap.\n     |\n     |  Additional colormaps can be added via `.ColormapRegistry.register`::\n     |\n     |      mpl.colormaps.register(my_colormap)\n     |\n     |  To get a list of all registered colormaps, you can do::\n     |\n     |      from matplotlib import colormaps\n     |      list(colormaps)\n     |\n     |  Method resolution order:\n     |      ColormapRegistry\n     |      collections.abc.Mapping\n     |      collections.abc.Collection\n     |      collections.abc.Sized\n     |      collections.abc.Iterable\n     |      collections.abc.Container\n     |      builtins.object\n     |\n     |  Methods defined here:\n     |\n     |  __call__(self)\n     |      Return a list of the registered colormap names.\n     |\n     |      This exists only for backward-compatibility in `.pyplot` which had a\n     |      ``plt.colormaps()`` method. The recommended way to get this list is\n     |      now ``list(colormaps)``.\n     |\n     |  __getitem__(self, item)\n     |\n     |  __init__(self, cmaps)\n     |      Initialize self.  See help(type(self)) for accurate signature.\n     |\n     |  __iter__(self)\n     |\n     |  __len__(self)\n     |\n     |  __str__(self)\n     |      Return str(self).\n     |\n     |  get_cmap(self, cmap)\n     |      Return a color map specified through *cmap*.\n     |\n     |      Parameters\n     |      ----------\n     |      cmap : str or `~matplotlib.colors.Colormap` or None\n     |\n     |          - if a `.Colormap`, return it\n     |          - if a string, look it up in ``mpl.colormaps``\n     |          - if None, return the Colormap defined in :rc:`image.cmap`\n     |\n     |      Returns\n     |      -------\n     |      Colormap\n     |\n     |  register(self, cmap, *, name=None, force=False)\n     |      Register a new colormap.\n     |\n     |      The colormap name can then be used as a string argument to any ``cmap``\n     |      parameter in Matplotlib. It is also available in ``pyplot.get_cmap``.\n     |\n     |      The colormap registry stores a copy of the given colormap, so that\n     |      future changes to the original colormap instance do not affect the\n     |      registered colormap. Think of this as the registry taking a snapshot\n     |      of the colormap at registration.\n     |\n     |      Parameters\n     |      ----------\n     |      cmap : matplotlib.colors.Colormap\n     |          The colormap to register.\n     |\n     |      name : str, optional\n     |          The name for the colormap. If not given, ``cmap.name`` is used.\n     |\n     |      force : bool, default: False\n     |          If False, a ValueError is raised if trying to overwrite an already\n     |          registered name. True supports overwriting registered colormaps\n     |          other than the builtin colormaps.\n     |\n     |  unregister(self, name)\n     |      Remove a colormap from the registry.\n     |\n     |      You cannot remove built-in colormaps.\n     |\n     |      If the named colormap is not registered, returns with no error, raises\n     |      if you try to de-register a default colormap.\n     |\n     |      .. warning::\n     |\n     |          Colormap names are currently a shared namespace that may be used\n     |          by multiple packages. Use `unregister` only if you know you\n     |          have registered that name before. In particular, do not\n     |          unregister just in case to clean the name before registering a\n     |          new colormap.\n     |\n     |      Parameters\n     |      ----------\n     |      name : str\n     |          The name of the colormap to be removed.\n     |\n     |      Raises\n     |      ------\n     |      ValueError\n     |          If you try to remove a default built-in colormap.\n     |\n     |  ----------------------------------------------------------------------\n     |  Data descriptors defined here:\n     |\n     |  __dict__\n     |      dictionary for instance variables\n     |\n     |  __weakref__\n     |      list of weak references to the object\n     |\n     |  ----------------------------------------------------------------------\n     |  Data and other attributes defined here:\n     |\n     |  __abstractmethods__ = frozenset()\n     |\n     |  ----------------------------------------------------------------------\n     |  Methods inherited from collections.abc.Mapping:\n     |\n     |  __contains__(self, key)\n     |\n     |  __eq__(self, other)\n     |      Return self==value.\n     |\n     |  get(self, key, default=None)\n     |      D.get(k[,d]) -\u003e D[k] if k in D, else d.  d defaults to None.\n     |\n     |  items(self)\n     |      D.items() -\u003e a set-like object providing a view on D's items\n     |\n     |  keys(self)\n     |      D.keys() -\u003e a set-like object providing a view on D's keys\n     |\n     |  values(self)\n     |      D.values() -\u003e an object providing a view on D's values\n     |\n     |  ----------------------------------------------------------------------\n     |  Data and other attributes inherited from collections.abc.Mapping:\n     |\n     |  __hash__ = None\n     |\n     |  __reversed__ = None\n     |\n     |  ----------------------------------------------------------------------\n     |  Class methods inherited from collections.abc.Collection:\n     |\n     |  __subclasshook__(C)\n     |      Abstract classes can override this to customize issubclass().\n     |\n     |      This is invoked early on by abc.ABCMeta.__subclasscheck__().\n     |      It should return True, False or NotImplemented.  If it returns\n     |      NotImplemented, the normal algorithm is used.  Otherwise, it\n     |      overrides the normal algorithm (and the outcome is cached).\n     |\n     |  ----------------------------------------------------------------------\n     |  Class methods inherited from collections.abc.Iterable:\n     |\n     |  __class_getitem__ = GenericAlias(args, /)\n     |      Represent a PEP 585 generic type\n     |\n     |      E.g. for t = list[int], t.__origin__ is list and t.__args__ is (int,).\nFUNCTIONS\n    get_cmap(name=None, lut=None)\n        [*Deprecated*] Get a colormap instance, defaulting to rc values if *name* is None.\n        Parameters\n        ----------\n        name : `~matplotlib.colors.Colormap` or str or None, default: None\n            If a `.Colormap` instance, it will be returned. Otherwise, the name of\n            a colormap known to Matplotlib, which will be resampled by *lut*. The\n            default, None, means :rc:`image.cmap`.\n        lut : int or None, default: None\n            If *name* is not already a Colormap instance and *lut* is not None, the\n            colormap will be resampled to have *lut* entries in the lookup table.\n        Returns\n        -------\n        Colormap\n        Notes\n        -----\n        .. deprecated:: 3.7\n           Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\nDATA\n    Accent = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Accent_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Blues = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Blues_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    BrBG = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    BrBG_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    BuGn = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    BuGn_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    BuPu = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    BuPu_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    CMRmap = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    CMRmap_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Dark2 = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Dark2_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    GnBu = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    GnBu_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Grays = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Grays_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Greens = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Greens_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Greys = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Greys_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    OrRd = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    OrRd_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Oranges = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Oranges_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PRGn = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PRGn_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Paired = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Paired_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Pastel1 = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Pastel1_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Pastel2 = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Pastel2_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    PiYG = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PiYG_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PuBu = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PuBuGn = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PuBuGn_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PuBu_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PuOr = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PuOr_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PuRd = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    PuRd_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Purples = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Purples_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdBu = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdBu_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdGy = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdGy_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdPu = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdPu_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdYlBu = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdYlBu_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdYlGn = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    RdYlGn_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Reds = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Reds_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Set1 = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Set1_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Set2 = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Set2_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Set3 = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Set3_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    Spectral = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Spectral_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Wistia = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    Wistia_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    YlGn = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    YlGnBu = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    YlGnBu_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    YlGn_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    YlOrBr = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    YlOrBr_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    YlOrRd = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    YlOrRd_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    afmhot = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    afmhot_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    autumn = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    autumn_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    berlin = \u003cmatplotlib.colors.ListedColormap object\u003e\n    berlin_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    binary = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    binary_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    bivar_cmaps = {'BiCone': \u003cmatplotlib.colors.SegmentedBivarColormap obj...\n    bone = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    bone_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    brg = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    brg_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    bwr = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    bwr_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    cividis = \u003cmatplotlib.colors.ListedColormap object\u003e\n    cividis_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    cmaps_listed = {'berlin': \u003cmatplotlib.colors.ListedColormap object\u003e, '...\n    cool = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    cool_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    coolwarm = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    coolwarm_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    copper = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    copper_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    cubehelix = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    cubehelix_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    datad = {'Accent': {'listed': ((0.4980392156862745, 0.788235294117647,...\n    flag = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    flag_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_earth = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_earth_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_gray = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_gray_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_grey = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_grey_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_heat = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_heat_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_ncar = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_ncar_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_rainbow = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_rainbow_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_stern = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_stern_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_yarg = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_yarg_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_yerg = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gist_yerg_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gnuplot = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gnuplot2 = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gnuplot2_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gnuplot_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gray = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    gray_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    grey = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    grey_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    hot = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    hot_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    hsv = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    hsv_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    inferno = \u003cmatplotlib.colors.ListedColormap object\u003e\n    inferno_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    jet = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    jet_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    magma = \u003cmatplotlib.colors.ListedColormap object\u003e\n    magma_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    managua = \u003cmatplotlib.colors.ListedColormap object\u003e\n    managua_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    multivar_cmaps = {'2VarAddA': \u003cmatplotlib.colors.MultivarColormap obje...\n    nipy_spectral = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    nipy_spectral_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    ocean = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    ocean_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    pink = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    pink_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    plasma = \u003cmatplotlib.colors.ListedColormap object\u003e\n    plasma_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    prism = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    prism_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    rainbow = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    rainbow_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    seismic = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    seismic_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    spring = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    spring_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    summer = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    summer_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    tab10 = \u003cmatplotlib.colors.ListedColormap object\u003e\n    tab10_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    tab20 = \u003cmatplotlib.colors.ListedColormap object\u003e\n    tab20_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    tab20b = \u003cmatplotlib.colors.ListedColormap object\u003e\n    tab20b_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    tab20c = \u003cmatplotlib.colors.ListedColormap object\u003e\n    tab20c_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    terrain = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    terrain_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    turbo = \u003cmatplotlib.colors.ListedColormap object\u003e\n    turbo_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    twilight = \u003cmatplotlib.colors.ListedColormap object\u003e\n    twilight_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    twilight_shifted = \u003cmatplotlib.colors.ListedColormap object\u003e\n    twilight_shifted_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    vanimo = \u003cmatplotlib.colors.ListedColormap object\u003e\n    vanimo_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    viridis = \u003cmatplotlib.colors.ListedColormap object\u003e\n    viridis_r = \u003cmatplotlib.colors.ListedColormap object\u003e\n    winter = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\n    winter_r = \u003cmatplotlib.colors.LinearSegmentedColormap object\u003e\nFILE\n    e:\\0sandbox\\archive.org-downloader\\.venv\\lib\\site-packages\\matplotlib\\cm.py\n\u003c/code\u003e\n\u003c/details\u003e\n\nBut the stub is quite sad:\nhttps://github.com/matplotlib/matplotlib/blob/1c3e0438cb890fe12e91c73b3782cae3b87060a5/lib/matplotlib/cm.pyi#L1-L22\n\nThis discrepancy leads to type-checker catching sadness\n\n\u003cimg width=\"332\" height=\"66\" alt=\"Image\" src=\"https://github.com/user-attachments/assets/476e1c13-50d7-4caf-9810-1d57e977054f\" /\u003e\n\nsnipet:\n```console\nr\u003e mypy -c \"import matplotlib.pyplot as plt; plt.cm.gray\"\n\u003cstring\u003e:1: error: Module has no attribute \"gray\"  [attr-defined]\nFound 1 error in 1 file (checked 1 source file)\n```\n\n\u003chr/\u003e\n\nI'm happy to help resolve this, but I'd like a few words of guidance as to what strategy should be used. Hardcoding? A cm.pyi codegen? Some sort of ignoring directive? Maybe even delete the current cm.pyi?\n\n### Code for reproduction\n\n```Python\nimport matplotlib.pyplot as plt\nplt.cm.gray\n```\n\n### Actual outcome\n\n\u003cstring\u003e:1: error: Module has no attribute \"gray\"  [attr-defined]\nFound 1 error in 1 file (checked 1 source file)\n\n### Expected outcome\n\n` `\n\n### Additional information\n\n_No response_\n\n### Operating system\n\n_No response_\n\n### Matplotlib Version\n\n3.10.5\n\n### Matplotlib Backend\n\n_No response_\n\n### Python version\n\n_No response_\n\n### Jupyter version\n\n_No response_\n\n### Installation\n\npip","author":{"url":"https://github.com/refack","@type":"Person","name":"refack"},"datePublished":"2025-08-16T23:10:58.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":1},"url":"https://github.com/30438/matplotlib/issues/30438"}