diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 5df1c376c8..176923763c 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -43,6 +43,7 @@ jobs:
       default_python: "3.12"
       envs: |
         - linux: check-dependencies
+        - linux: check-types
   latest_crds_contexts:
     uses: spacetelescope/crds/.github/workflows/contexts.yml@d96060f99a7ca75969f6652b050243592f4ebaeb  # 12.0.0
   crds_context:
diff --git a/changes/8852.general.rst b/changes/8852.general.rst
new file mode 100644
index 0000000000..0a584e8d63
--- /dev/null
+++ b/changes/8852.general.rst
@@ -0,0 +1 @@
+Added mypy type checking to CI checks
diff --git a/jwst/__init__.py b/jwst/__init__.py
index 8ec268c7e6..6fdd1e4afa 100644
--- a/jwst/__init__.py
+++ b/jwst/__init__.py
@@ -7,6 +7,6 @@
 _regex_git_hash = re.compile(r".*\+g(\w+)")
 __version_commit__ = ""
 if "+" in __version__:
-    commit = _regex_git_hash.match(__version__).groups()
+    commit = _regex_git_hash.match(__version__).groups()  # type: ignore
     if commit:
         __version_commit__ = commit[0]
diff --git a/jwst/ami/ami_analyze.py b/jwst/ami/ami_analyze.py
index dd7e24132c..631c780004 100644
--- a/jwst/ami/ami_analyze.py
+++ b/jwst/ami/ami_analyze.py
@@ -3,7 +3,7 @@
 import numpy as np
 import copy
 
-from jwst.datamodels import CubeModel, ImageModel
+from jwst.datamodels import CubeModel, ImageModel  # type: ignore[attr-defined]
 
 from .find_affine2d_parameters import find_rotation
 from . import instrument_data
diff --git a/jwst/ami/leastsqnrm.py b/jwst/ami/leastsqnrm.py
index fbbcd98b5f..d1c1a89524 100644
--- a/jwst/ami/leastsqnrm.py
+++ b/jwst/ami/leastsqnrm.py
@@ -613,7 +613,7 @@ def matrix_operations(img, model, flux=None, linfit=False, dqm=None):
 
     if linfit:
         try:
-            from linearfit import linearfit
+            from linearfit import linearfit  # type: ignore[import-not-found]
 
             # dependent variables
             M = np.asmatrix(flatimg)
diff --git a/jwst/ami/matrix_dft.py b/jwst/ami/matrix_dft.py
index 63ab8074b3..3f47a230c3 100644
--- a/jwst/ami/matrix_dft.py
+++ b/jwst/ami/matrix_dft.py
@@ -198,7 +198,7 @@ def matrix_idft(*args, **kwargs):
     return matrix_dft(*args, **kwargs)
 
 
-matrix_idft.__doc__ = matrix_dft.__doc__.replace(
+matrix_idft.__doc__ = matrix_dft.__doc__.replace(  # type: ignore
     'Perform a matrix discrete Fourier transform',
     'Perform an inverse matrix discrete Fourier transform'
 )
diff --git a/jwst/assign_wcs/util.py b/jwst/assign_wcs/util.py
index 1b30ce2320..b33620ed8b 100644
--- a/jwst/assign_wcs/util.py
+++ b/jwst/assign_wcs/util.py
@@ -99,7 +99,7 @@ def _reproject(x, y):
 
 
 def compute_scale(wcs: WCS, fiducial: Union[tuple, np.ndarray],
-                  disp_axis: int = None, pscale_ratio: float = None) -> float:
+                  disp_axis: int | None = None, pscale_ratio: float | None = None) -> float:
     """Compute scaling transform.
 
     Parameters
@@ -137,8 +137,8 @@ def compute_scale(wcs: WCS, fiducial: Union[tuple, np.ndarray],
     crval_with_offsets = wcs(*crpix_with_offsets, with_bounding_box=False)
 
     coords = SkyCoord(ra=crval_with_offsets[spatial_idx[0]], dec=crval_with_offsets[spatial_idx[1]], unit="deg")
-    xscale = np.abs(coords[0].separation(coords[1]).value)
-    yscale = np.abs(coords[0].separation(coords[2]).value)
+    xscale: float = np.abs(coords[0].separation(coords[1]).value)
+    yscale: float = np.abs(coords[0].separation(coords[2]).value)
 
     if pscale_ratio is not None:
         xscale *= pscale_ratio
@@ -149,7 +149,8 @@ def compute_scale(wcs: WCS, fiducial: Union[tuple, np.ndarray],
         # Assuming disp_axis is consistent with DataModel.meta.wcsinfo.dispersion.direction
         return yscale if disp_axis == 1 else xscale
 
-    return np.sqrt(xscale * yscale)
+    scale: float = np.sqrt(xscale * yscale)
+    return scale
 
 
 def calc_rotation_matrix(roll_ref: float, v3i_yang: float, vparity: int = 1) -> List[float]:
diff --git a/jwst/associations/__init__.py b/jwst/associations/__init__.py
index 0697dca651..da7b016279 100644
--- a/jwst/associations/__init__.py
+++ b/jwst/associations/__init__.py
@@ -9,7 +9,7 @@
 """
 
 # Take version from the upstream package
-from .. import __version__
+from jwst import __version__
 
 
 # Utility
diff --git a/jwst/associations/association.py b/jwst/associations/association.py
index e6edce4b75..6acfec5c17 100644
--- a/jwst/associations/association.py
+++ b/jwst/associations/association.py
@@ -79,12 +79,12 @@ class Association(MutableMapping):
     GLOBAL_CONSTRAINT = None
     """Global constraints"""
 
-    INVALID_VALUES = None
+    INVALID_VALUES: tuple | None = None
     """Attribute values that indicate the
     attribute is not specified.
     """
 
-    ioregistry = IORegistry()
+    ioregistry: IORegistry = IORegistry()
     """The association IO registry"""
 
     def __init__(
diff --git a/jwst/associations/association_io.py b/jwst/associations/association_io.py
index 5ce8c451a1..d768a20118 100644
--- a/jwst/associations/association_io.py
+++ b/jwst/associations/association_io.py
@@ -14,7 +14,7 @@
 logger = logging.getLogger(__name__)
 logger.addHandler(logging.NullHandler())
 
-__all__ = []
+__all__: list = []
 
 
 # Define JSON encoder to convert `Member` to `dict`
diff --git a/jwst/associations/lib/constraint.py b/jwst/associations/lib/constraint.py
index ed3c3d1c35..a3c270426f 100644
--- a/jwst/associations/lib/constraint.py
+++ b/jwst/associations/lib/constraint.py
@@ -56,7 +56,7 @@ class SimpleConstraintABC(abc.ABC):
     """
 
     # Attributes to show in the string representation.
-    _str_attrs = ('name', 'value')
+    _str_attrs: tuple = ('name', 'value')
 
     def __new__(cls, *args, **kwargs):
         """Force creation of the constraint attribute dict before anything else."""
diff --git a/jwst/associations/lib/rules_level3_base.py b/jwst/associations/lib/rules_level3_base.py
index a1da4f135b..944bc2b63b 100644
--- a/jwst/associations/lib/rules_level3_base.py
+++ b/jwst/associations/lib/rules_level3_base.py
@@ -97,7 +97,7 @@ class DMS_Level3_Base(DMSBaseMixin, Association):
     INVALID_VALUES = _EMPTY
 
     # Make sequences type-dependent
-    _sequences = defaultdict(Counter)
+    _sequences: defaultdict = defaultdict(Counter)
 
     def __init__(self, *args, **kwargs):
 
diff --git a/jwst/associations/tests/helpers.py b/jwst/associations/tests/helpers.py
index 11878d4dbe..82c77cc41a 100644
--- a/jwst/associations/tests/helpers.py
+++ b/jwst/associations/tests/helpers.py
@@ -56,11 +56,11 @@ class BasePoolRule():
 
     # Define the pools and testing parameters related to them.
     # Each entry is a tuple starting with the path of the pool.
-    pools = []
+    pools: list = []
 
     # Define the rules that SHOULD be present.
     # Each entry is the class name of the rule.
-    valid_rules = []
+    valid_rules: list = []
 
     def test_rules_exist(self):
         rules = registry_level3_only()
diff --git a/jwst/badpix_selfcal/badpix_selfcal.py b/jwst/badpix_selfcal/badpix_selfcal.py
index 0691926552..c2fd84bbfd 100644
--- a/jwst/badpix_selfcal/badpix_selfcal.py
+++ b/jwst/badpix_selfcal/badpix_selfcal.py
@@ -3,7 +3,7 @@
 
 import numpy as np
 
-import jwst.datamodels as dm
+from jwst.datamodels import IFUImageModel  # type: ignore[attr-defined]
 from stcal.outlier_detection.utils import medfilt
 from stdatamodels.jwst.datamodels.dqflags import pixel
 
@@ -12,7 +12,7 @@ def badpix_selfcal(minimg: np.ndarray,
                    flagfrac_lower: float = 0.001,
                    flagfrac_upper: float = 0.001,
                    kernel_size: int = 15,
-                   dispaxis=None) -> np.ndarray:
+                   dispaxis=None) -> tuple:
     """
     Flag residual artifacts as bad pixels in the DQ array of a JWST exposure
 
@@ -59,18 +59,17 @@ def badpix_selfcal(minimg: np.ndarray,
     flag_low, flag_high = np.nanpercentile(minimg_hpf, [flagfrac_lower * 100, (1 - flagfrac_upper) * 100])
     bad = (minimg_hpf > flag_high) | (minimg_hpf < flag_low)
     flagged_indices = np.where(bad)
-
     return flagged_indices
 
 
-def apply_flags(input_model: dm.IFUImageModel, flagged_indices: np.ndarray) -> dm.IFUImageModel:
+def apply_flags(input_model: IFUImageModel, flagged_indices: np.ndarray) -> IFUImageModel:
     """
     Apply the flagged indices to the input model. Sets the flagged pixels to NaN
     and the DQ flag to DO_NOT_USE + OTHER_BAD_PIXEL
 
     Parameters
     ----------
-    input_model : dm.IFUImageModel
+    input_model : IFUImageModel
         Input science data to be corrected
     flagged_indices : np.ndarray
         Indices of the flagged pixels,
@@ -78,7 +77,7 @@ def apply_flags(input_model: dm.IFUImageModel, flagged_indices: np.ndarray) -> d
 
     Returns
     -------
-    output_model : dm.IFUImageModel
+    output_model : IFUImageModel
         Flagged data model
     """
 
diff --git a/jwst/cube_skymatch/cube_skymatch_step.py b/jwst/cube_skymatch/cube_skymatch_step.py
index db61c79bb2..d8f6edb685 100644
--- a/jwst/cube_skymatch/cube_skymatch_step.py
+++ b/jwst/cube_skymatch/cube_skymatch_step.py
@@ -52,7 +52,7 @@ class CubeSkyMatchStep(Step):
         binwidth = float(min=0.0, default=0.1) # Bin width for 'mode' and 'midpt' `skystat`, in sigma
     """
 
-    reference_file_types = []
+    reference_file_types: list = []
 
     def process(self, input1, input2):
         cube_models = ModelContainer(input1)
diff --git a/jwst/datamodels/__init__.py b/jwst/datamodels/__init__.py
index 1d3e0b23d6..a3d64a70e3 100644
--- a/jwst/datamodels/__init__.py
+++ b/jwst/datamodels/__init__.py
@@ -34,7 +34,7 @@
 _deprecated_modules = ['schema']
 
 # Deprecated models in stdatamodels
-_deprecated_models = []
+_deprecated_models: list[str] = []
 
 # Import all submodules from stdatamodels.jwst.datamodels
 for attr in dir(stdatamodels.jwst.datamodels):
diff --git a/jwst/dq_init/dq_initialization.py b/jwst/dq_init/dq_initialization.py
index 9c67d16a35..424ef2dbe8 100644
--- a/jwst/dq_init/dq_initialization.py
+++ b/jwst/dq_init/dq_initialization.py
@@ -5,7 +5,7 @@
 from stdatamodels.jwst import datamodels
 
 from ..lib import reffile_utils
-from jwst.datamodels import dqflags
+from jwst.datamodels import dqflags  # type: ignore[attr-defined]
 
 log = logging.getLogger(__name__)
 log.setLevel(logging.DEBUG)
diff --git a/jwst/dq_init/tests/test_dq_init.py b/jwst/dq_init/tests/test_dq_init.py
index f4c5ac73f9..e18fae409c 100644
--- a/jwst/dq_init/tests/test_dq_init.py
+++ b/jwst/dq_init/tests/test_dq_init.py
@@ -259,12 +259,12 @@ def test_dq_add1_groupdq():
 
 # Set parameters for multiple runs of guider data
 args = "xstart, ystart, xsize, ysize, nints, ngroups, instrument, exp_type, detector"
-test_data = [(1, 1, 2048, 2048, 2, 2, 'FGS', 'FGS_ID-IMAGE', 'GUIDER1'),
+test_data_multiple = [(1, 1, 2048, 2048, 2, 2, 'FGS', 'FGS_ID-IMAGE', 'GUIDER1'),
              (1, 1, 1032, 1024, 1, 5, 'MIRI', 'MIR_IMAGE', 'MIRIMAGE')]
 ids = ["GuiderRawModel-Image", "RampModel"]
 
 
-@pytest.mark.parametrize(args, test_data, ids=ids)
+@pytest.mark.parametrize(args, test_data_multiple, ids=ids)
 def test_fullstep(xstart, ystart, xsize, ysize, nints, ngroups, instrument, exp_type, detector):
     """Test that the full step runs"""
 
diff --git a/jwst/extract_1d/apply_apcorr.py b/jwst/extract_1d/apply_apcorr.py
index daf9f67588..3618719f89 100644
--- a/jwst/extract_1d/apply_apcorr.py
+++ b/jwst/extract_1d/apply_apcorr.py
@@ -1,9 +1,6 @@
 import abc
 
-from typing import Tuple, Union, Type
 from scipy.interpolate import RectBivariateSpline, interp1d
-from astropy.io import fits
-from stdatamodels import DataModel
 from stdatamodels.jwst.datamodels import MultiSlitModel
 
 from ..assign_wcs.util import compute_scale
@@ -55,10 +52,8 @@ class ApCorrBase(abc.ABC):
         }
     }
 
-    size_key = None
-
-    def __init__(self, input_model: DataModel, apcorr_table: fits.FITS_rec, sizeunit: str,
-                 location: Tuple[float, float, float] = None, slit_name: str = None, **match_kwargs):
+    def __init__(self, input_model, apcorr_table, sizeunit,
+                 location = None, slit_name = None, **match_kwargs):
         self.correction = None
 
         self.model = input_model
@@ -75,6 +70,10 @@ def __init__(self, input_model: DataModel, apcorr_table: fits.FITS_rec, sizeunit
         self.apcorr_func = self.approximate()
         self.tabulated_correction = None
 
+    @property
+    def size_key(self):
+        return None
+
     def _convert_size_units(self):
         """If the SIZE or Radius column is in units of arcseconds, convert to pixels."""
         if self.apcorr_sizeunits.startswith('arcsec'):
@@ -102,7 +101,7 @@ def _convert_size_units(self):
                     'pixels.'
                 )
 
-    def _get_match_keys(self) -> dict:
+    def _get_match_keys(self):
         """Get column keys needed for reducing the reference table based on input."""
         instrument = self.model.meta.instrument.name.upper()
         exptype = self.model.meta.exposure.type.upper()
@@ -113,7 +112,7 @@ def _get_match_keys(self) -> dict:
             if key in exptype:
                 return relevant_pars[key]
 
-    def _get_match_pars(self) -> dict:
+    def _get_match_pars(self):
         """Get meta parameters required for reference table row-selection."""
         match_pars = {}
 
@@ -125,7 +124,7 @@ def _get_match_pars(self) -> dict:
 
         return match_pars
 
-    def _reduce_reftable(self) -> fits.FITS_record:
+    def _reduce_reftable(self):
         """Reduce full reference table to a single matched row."""
         table = self._reference_table.copy()
 
@@ -145,7 +144,7 @@ def approximate(self):
         """Generate an approximate aperture correction function based on input data."""
         pass
 
-    def apply(self, spec_table: fits.FITS_rec):
+    def apply(self, spec_table):
         """Apply interpolated aperture correction value to source-related extraction results in-place.
 
         Parameters
@@ -181,14 +180,14 @@ class ApCorrPhase(ApCorrBase):
     """
     size_key = 'size'
 
-    def __init__(self, *args, pixphase: float = 0.5, **kwargs):
+    def __init__(self, *args, pixphase = 0.5, **kwargs):
         self.phase = pixphase  # In the future we'll attempt to measure the pixel phase from inputs.
 
         super().__init__(*args, **kwargs)
 
     def approximate(self):
         """Generate an approximate function for interpolating apcorr values to input wavelength and size."""
-        def _approx_func(wavelength: float, size: float, pixel_phase: float) -> RectBivariateSpline:
+        def _approx_func(wavelength, size, pixel_phase):
             """Create a 'custom' approximation function that approximates the aperture correction in two stages based on
             input data.
 
@@ -228,7 +227,7 @@ def _approx_func(wavelength: float, size: float, pixel_phase: float) -> RectBiva
     def measure_phase(self):  # Future method in determining pixel phase
         pass
 
-    def tabulate_correction(self, spec_table: fits.FITS_rec):
+    def tabulate_correction(self, spec_table):
         """Tabulate the interpolated aperture correction value.
         
          This will save time when applying it later, especially if it is to be applied to multiple integrations.  
@@ -255,7 +254,7 @@ def tabulate_correction(self, spec_table: fits.FITS_rec):
 
         self.tabulated_correction = np.asarray(coefs)
 
-    def apply(self, spec_table: fits.FITS_rec, use_tabulated=False):
+    def apply(self, spec_table, use_tabulated=False):
         """Apply interpolated aperture correction value to source-related extraction results in-place.
 
         Parameters
@@ -297,8 +296,8 @@ def apply(self, spec_table: fits.FITS_rec, use_tabulated=False):
 class ApCorrRadial(ApCorrBase):
     """Aperture correction class used with spectral data produced from an extraction aperture radius."""
 
-    def __init__(self, input_model: DataModel, apcorr_table,
-                 location: Tuple[float, float, float] = None):
+    def __init__(self, input_model, apcorr_table,
+                 location = None):
 
         self.correction = None
         self.model = input_model
@@ -329,7 +328,7 @@ def _convert_size_units(self):
                     'pixels.'
                 )
 
-    def apply(self, spec_table: fits.FITS_rec):
+    def apply(self, spec_table):
         """Apply interpolated aperture correction value to source-related extraction results in-place.
 
         Parameters
@@ -410,7 +409,7 @@ def approximate(self):
         return RectBivariateSpline(size, wavelength, apcorr.T, ky=1, kx=1)
 
 
-def select_apcorr(input_model: DataModel) -> Union[Type[ApCorr], Type[ApCorrPhase], Type[ApCorrRadial]]:
+def select_apcorr(input_model):
     """Select appropriate Aperture correction class based on input DataModel.
 
     Parameters
diff --git a/jwst/extract_1d/extract.py b/jwst/extract_1d/extract.py
index 7c0198bad7..bd7cda6d8c 100644
--- a/jwst/extract_1d/extract.py
+++ b/jwst/extract_1d/extract.py
@@ -5,14 +5,11 @@
 import math
 import numpy as np
 
-from typing import Union, Tuple, NamedTuple, List
+from dataclasses import dataclass
 from astropy.modeling import polynomial
 from astropy.io import fits
-from gwcs import WCS
-from stdatamodels import DataModel
-from stdatamodels.properties import ObjectNode
 from stdatamodels.jwst import datamodels
-from stdatamodels.jwst.datamodels import dqflags, SlitModel, SpecModel
+from stdatamodels.jwst.datamodels import dqflags
 from stdatamodels.jwst.datamodels.apcorr import (
     MirLrsApcorrModel, MirMrsApcorrModel, NrcWfssApcorrModel, NrsFsApcorrModel,
     NrsMosApcorrModel, NrsIfuApcorrModel, NisWfssApcorrModel
@@ -88,11 +85,12 @@
 EXACT = "exact match"
 
 
-class Aperture(NamedTuple):  # When python 3.6 is no longer supported, consider converting to DataClass
-    xstart: Union[int, float]
-    xstop: Union[int, float]
-    ystart: Union[int, float]
-    ystop: Union[int, float]
+@dataclass
+class Aperture:
+    xstart: float
+    xstop: float
+    ystart: float
+    ystop: float
 
 
 class Extract1dError(Exception):
@@ -109,7 +107,7 @@ class ContinueError(Exception):
     pass
 
 
-def open_extract1d_ref(refname: str, exptype: str) -> dict:
+def open_extract1d_ref(refname, exptype):
     """Open the extract1d reference file.
 
     Parameters
@@ -174,7 +172,7 @@ def open_extract1d_ref(refname: str, exptype: str) -> dict:
     return ref_dict
 
 
-def open_apcorr_ref(refname: str, exptype: str) -> DataModel:
+def open_apcorr_ref(refname, exptype):
     """Determine the appropriate DataModel class to use when opening the input APCORR reference file.
 
     Parameters
@@ -212,16 +210,16 @@ def open_apcorr_ref(refname: str, exptype: str) -> DataModel:
 
 
 def get_extract_parameters(
-        ref_dict: Union[dict, None],
-        input_model: DataModel,
-        slitname: str,
-        sp_order: int,
-        meta: ObjectNode,
-        smoothing_length: Union[int, None],
-        bkg_fit: str,
-        bkg_order: Union[int, None],
-        use_source_posn: Union[bool, None]
-) -> dict:
+        ref_dict,
+        input_model,
+        slitname,
+        sp_order,
+        meta,
+        smoothing_length,
+        bkg_fit,
+        bkg_order,
+        use_source_posn
+):
     """Get extract1d reference file values.
 
     Parameters
@@ -449,7 +447,7 @@ def get_extract_parameters(
     return extract_params
 
 
-def log_initial_parameters(extract_params: dict):
+def log_initial_parameters(extract_params):
     """Log some of the initial extraction parameters.
 
     Parameters
@@ -477,9 +475,7 @@ def log_initial_parameters(extract_params: dict):
     log.debug(f"use_source_posn = {extract_params['use_source_posn']}")
 
 
-def get_aperture(
-        im_shape: tuple, wcs: WCS, extract_params: dict
-) -> Union[Aperture, dict]:
+def get_aperture(im_shape, wcs, extract_params):
     """Get the extraction limits xstart, xstop, ystart, ystop.
 
     Parameters
@@ -521,7 +517,7 @@ def get_aperture(
     return ap_ref
 
 
-def aperture_from_ref(extract_params: dict, im_shape: Tuple[int]) -> Aperture:
+def aperture_from_ref(extract_params, im_shape):
     """Get extraction region from reference file or image shape.
 
     Parameters
@@ -560,9 +556,7 @@ def aperture_from_ref(extract_params: dict, im_shape: Tuple[int]) -> Aperture:
     return ap_ref
 
 
-def update_from_width(
-        ap_ref: Aperture, extract_width: Union[int, None], direction: int
-) -> Aperture:
+def update_from_width(ap_ref, extract_width, direction):
     """Update XD extraction limits based on extract_width.
 
     If extract_width was specified, that value should override
@@ -623,9 +617,7 @@ def update_from_width(
     return ap_width
 
 
-def update_from_shape(
-        ap: Aperture, im_shape: Tuple[int]
-) -> Tuple[Aperture, bool]:
+def update_from_shape(ap, im_shape):
     """Truncate extraction region based on input image shape.
 
     Parameters
@@ -675,7 +667,7 @@ def update_from_shape(
     return ap_shape, truncated
 
 
-def aperture_from_wcs(wcs: WCS) -> Union[NamedTuple, None]:
+def aperture_from_wcs(wcs):
     """Get the limits over which the WCS is defined.
 
     Parameters
@@ -685,7 +677,7 @@ def aperture_from_wcs(wcs: WCS) -> Union[NamedTuple, None]:
 
     Returns
     -------
-    ap_wcs : namedtuple or None
+    ap_wcs : Aperture or None
         Keys are 'xstart', 'xstop', 'ystart', and 'ystop'.  These are the
         limits copied directly from wcs.bounding_box.
     """
@@ -722,12 +714,7 @@ def aperture_from_wcs(wcs: WCS) -> Union[NamedTuple, None]:
     return ap_wcs
 
 
-def update_from_wcs(
-        ap_ref: Aperture,
-        ap_wcs: Union[Aperture, None],
-        extract_width: int,
-        direction: int,
-) -> Aperture:
+def update_from_wcs(ap_ref, ap_wcs, extract_width, direction,):
     """Limit the extraction region to the WCS bounding box.
 
     Parameters
@@ -783,9 +770,7 @@ def update_from_wcs(
     return ap
 
 
-def sanity_check_limits(
-        ap_ref: Aperture, ap_wcs: Aperture,
-) -> bool:
+def sanity_check_limits(ap_ref, ap_wcs,):
     """Sanity check.
 
     Parameters
@@ -818,9 +803,7 @@ def sanity_check_limits(
     return flag
 
 
-def compare_start(
-        aperture_start: Union[int, float], wcs_bb_lower_lim: Union[int, float]
-) -> Union[int, float]:
+def compare_start(aperture_start, wcs_bb_lower_lim):
     """Compare the start limit from the aperture with the WCS lower limit.
 
     Extended summary
@@ -855,9 +838,7 @@ def compare_start(
         return math.ceil(wcs_bb_lower_lim)
 
 
-def compare_stop(
-        aperture_stop: Union[int, float], wcs_bb_upper_lim: Union[int, float]
-) -> Union[int, float]:
+def compare_stop(aperture_stop, wcs_bb_upper_lim):
     """Compare the stop limit from the aperture with the WCS upper limit.
 
     The more restrictive (i.e. smaller) limit is the one upon which the
@@ -890,7 +871,7 @@ def compare_stop(
         return math.floor(wcs_bb_upper_lim)
 
 
-def create_poly(coeff: List[float]) -> Union[polynomial.Polynomial1D, None]:
+def create_poly(coeff):
     """Create a polynomial model from coefficients.
 
     Parameters
@@ -1035,27 +1016,27 @@ class ExtractBase(abc.ABC):
 
     def __init__(
             self,
-            input_model: DataModel,
-            slit: Union[DataModel, None] = None,
-            ref_image: Union[DataModel, None] = None,
-            dispaxis: int = HORIZONTAL,
-            spectral_order: int = 1,
-            xstart: int = None,
-            xstop: int = None,
-            ystart: int = None,
-            ystop: int = None,
-            extract_width: int = None,
-            src_coeff: Union[List[List[float]], None] = None,
-            bkg_coeff: Union[List[List[float]], None] = None,
-            independent_var: str = "pixel",
-            smoothing_length: int = 0,
-            bkg_fit: str = "poly",
-            bkg_order: int = 0,
-            position_correction: float = 0.,
-            subtract_background: Union[bool, None] = None,
-            use_source_posn: Union[bool, None] = None,
-            match: Union[str, None] = None,
-            ref_file_type: Union[str, None] = None
+            input_model,
+            slit = None,
+            ref_image = None,
+            dispaxis = HORIZONTAL,
+            spectral_order = 1,
+            xstart = None,
+            xstop = None,
+            ystart = None,
+            ystop = None,
+            extract_width = None,
+            src_coeff = None,
+            bkg_coeff = None,
+            independent_var = "pixel",
+            smoothing_length = 0,
+            bkg_fit = "poly",
+            bkg_order = 0,
+            position_correction = 0.,
+            subtract_background = None,
+            use_source_posn = None,
+            match = None,
+            ref_file_type = None
     ):
         """
         Parameters
@@ -1222,9 +1203,7 @@ def assign_polynomial_limits(self):
         pass
 
     @staticmethod
-    def get_target_coordinates(
-            input_model: DataModel, slit: Union[DataModel, None]
-    ) -> Tuple[Union[float, None], Union[float, None]]:
+    def get_target_coordinates(input_model, slit):
         """Get the right ascension and declination of the target.
 
         For MultiSlitModel (or similar) data, each slit has the source
@@ -1277,9 +1256,7 @@ def get_target_coordinates(
 
         return targ_ra, targ_dec
 
-    def offset_from_offset(
-            self, input_model: DataModel, slit: DataModel,
-    ) -> Tuple[float, Union[float, None]]:
+    def offset_from_offset(self, input_model, slit):
         """Get position offset from the target coordinates.
 
         Parameters
@@ -1347,13 +1324,7 @@ def offset_from_offset(
 
         return offset, locn
 
-    def locn_from_wcs(
-            self,
-            input_model: DataModel,
-            slit: Union[DataModel, None],
-            targ_ra: Union[float, None],
-            targ_dec: Union[float, None],
-    ) -> Union[Tuple[int, float, float], None]:
+    def locn_from_wcs(self, input_model, slit, targ_ra, targ_dec):
         """Get the location of the spectrum, based on the WCS.
 
         Parameters
@@ -1544,7 +1515,7 @@ def __init__(self, *base_args, **base_kwargs):
                     log.debug("Background subtraction was specified in the reference file,")
                     log.debug("but has been overridden by the step parameter.")
 
-    def nominal_locn(self, middle: int, middle_wl: float) -> Union[float, None]:
+    def nominal_locn(self, middle, middle_wl):
         """Find the nominal cross-dispersion location of the target spectrum.
 
         This version is for the case that the reference file is a JSON file,
@@ -1604,7 +1575,7 @@ def nominal_locn(self, middle: int, middle_wl: float) -> Union[float, None]:
 
         return location
 
-    def add_position_correction(self, shape: tuple):
+    def add_position_correction(self, shape):
         """Add the position offset to the extraction location (in-place).
 
         Extended summary
@@ -1666,7 +1637,7 @@ def _apply_position_corr(self, coeffs):
             coeff_list[0] += self.position_correction
             coeffs[i] = copy.copy(coeff_list)
 
-    def update_extraction_limits(self, ap: Aperture):
+    def update_extraction_limits(self, ap):
         """Update start and stop limits.
 
         Extended summary
@@ -1796,19 +1767,7 @@ def _poly_per_region(self, coeffs):
 
         return result
 
-    def extract(
-            self,
-            data: np.ndarray,
-            var_poisson: np.ndarray,
-            var_rnoise: np.ndarray,
-            var_flat: np.ndarray,
-            wl_array: Union[np.ndarray, None],
-    ) -> Tuple[
-        float, float, np.ndarray,
-        np.ndarray, np.ndarray, np.ndarray, np.ndarray,
-        np.ndarray, np.ndarray, np.ndarray, np.ndarray,
-        np.ndarray, np.ndarray
-    ]:
+    def extract(self, data, var_poisson, var_rnoise, var_flat, wl_array):
         """Do the extraction.
 
         Extended summary
@@ -2048,9 +2007,7 @@ def __init__(self, *base_args, **base_kwargs):
         """
         super().__init__(*base_args, **base_kwargs)
 
-    def nominal_locn(
-            self, middle: float, middle_wl: float
-    ) -> Union[float, None]:
+    def nominal_locn(self, middle, middle_wl):
         """Find the nominal cross-dispersion location of the target spectrum.
 
         This version is for the case that the reference file is an image.
@@ -2106,7 +2063,7 @@ def nominal_locn(
 
         return location
 
-    def add_position_correction(self, shape: tuple):
+    def add_position_correction(self, shape):
         """Shift the reference image (in-place).
 
         Parameters
@@ -2163,18 +2120,7 @@ def log_extraction_parameters(self):
         log.debug(f"smoothing_length = {self.smoothing_length}")
         log.debug(f"position_correction = {self.position_correction}")
 
-    def extract(self,
-                data: np.ndarray,
-                var_poisson: np.ndarray,
-                var_rnoise: np.ndarray,
-                var_flat: np.ndarray,
-                wl_array: np.ndarray,
-                ) -> \
-            Tuple[
-                float, float, np.ndarray,
-                np.ndarray, np.ndarray, np.ndarray, np.ndarray,
-                np.ndarray, np.ndarray, np.ndarray, np.ndarray,
-                np.ndarray, np.ndarray]:
+    def extract(self, data, var_poisson, var_rnoise, var_flat, wl_array):
         """
         Do the actual extraction, for the case that the extract1d reference file
         is an image.
@@ -2455,7 +2401,7 @@ def extract(self,
                 background, b_var_poisson, b_var_rnoise, b_var_flat,
                 npixels, dq)
 
-    def match_shape(self, shape: tuple) -> np.ndarray:
+    def match_shape(self, shape):
         """Truncate or expand reference image to match the science data.
 
         Extended summary
@@ -2495,9 +2441,7 @@ def match_shape(self, shape: tuple) -> np.ndarray:
         return buf
 
     @staticmethod
-    def separate_target_and_background(
-            ref
-    ) -> Tuple[np.ndarray, Union[np.ndarray, None]]:
+    def separate_target_and_background(ref):
         """Create masks for target and background.
 
         Parameters
@@ -2533,24 +2477,24 @@ def separate_target_and_background(
 
 
 def run_extract1d(
-        input_model: DataModel,
-        extract_ref_name: str,
-        apcorr_ref_name: Union[str, None],
-        smoothing_length: Union[int, None],
-        bkg_fit: str,
-        bkg_order: Union[int, None],
-        bkg_sigma_clip: float,
-        log_increment: int,
-        subtract_background: Union[bool, None],
-        use_source_posn: Union[bool, None],
-        center_xy: Union[float, None],
-        ifu_autocen: Union[bool, None],
-        ifu_rfcorr: Union[bool, None],
-        ifu_set_srctype: str,
-        ifu_rscale: float,
-        ifu_covar_scale: float,
-        was_source_model: bool = False,
-) -> DataModel:
+        input_model,
+        extract_ref_name,
+        apcorr_ref_name,
+        smoothing_length,
+        bkg_fit,
+        bkg_order,
+        bkg_sigma_clip,
+        log_increment,
+        subtract_background,
+        use_source_posn,
+        center_xy,
+        ifu_autocen,
+        ifu_rfcorr,
+        ifu_set_srctype,
+        ifu_rscale,
+        ifu_covar_scale,
+        was_source_model,
+):
     """Extract 1-D spectra.
 
     This just reads the reference files (if any) and calls do_extract1d.
@@ -2688,7 +2632,7 @@ def run_extract1d(
     return output_model
 
 
-def ref_dict_sanity_check(ref_dict: Union[dict, None]) -> Union[dict, None]:
+def ref_dict_sanity_check(ref_dict):
     """Check for required entries.
 
     Parameters
@@ -2723,24 +2667,24 @@ def ref_dict_sanity_check(ref_dict: Union[dict, None]) -> Union[dict, None]:
 
 
 def do_extract1d(
-        input_model: DataModel,
-        extract_ref_dict: Union[dict, None],
-        apcorr_ref_model=None,
-        smoothing_length: Union[int, None] = None,
-        bkg_fit: str = "poly",
-        bkg_order: Union[int, None] = None,
-        bkg_sigma_clip: float = 0,
-        log_increment: int = 50,
-        subtract_background: Union[int, None] = None,
-        use_source_posn: Union[bool, None] = None,
-        center_xy: Union[int, None] = None,
-        ifu_autocen: Union[bool, None] = None,
-        ifu_rfcorr: Union[bool, None] = None,
-        ifu_set_srctype: str = None,
-        ifu_rscale: float = None,
-        ifu_covar_scale: float = 1.0,
-        was_source_model: bool = False
-) -> DataModel:
+        input_model,
+        extract_ref_dict,
+        apcorr_ref_model = None,
+        smoothing_length = None,
+        bkg_fit = "poly",
+        bkg_order = None,
+        bkg_sigma_clip = 0,
+        log_increment = 50,
+        subtract_background = None,
+        use_source_posn = None,
+        center_xy = None,
+        ifu_autocen = None,
+        ifu_rfcorr = None,
+        ifu_set_srctype = None,
+        ifu_rscale = None,
+        ifu_covar_scale = 1.0,
+        was_source_model = False
+):
     """Extract 1-D spectra.
 
     In the pipeline, this function would be called by run_extract1d.
@@ -3067,9 +3011,7 @@ def do_extract1d(
     return output_model
 
 
-def populate_time_keywords(
-        input_model: DataModel, output_model: DataModel
-) -> Union[DataModel, None]:
+def populate_time_keywords(input_model, output_model):
     """Copy the integration times keywords to header keywords.
 
     Parameters
@@ -3212,7 +3154,7 @@ def populate_time_keywords(
             n += 1
 
 
-def get_spectral_order(slit: DataModel) -> int:
+def get_spectral_order(slit):
     """Get the spectral order number.
 
     Parameters
@@ -3241,7 +3183,7 @@ def get_spectral_order(slit: DataModel) -> int:
     return sp_order
 
 
-def is_prism(input_model: DataModel) -> bool:
+def is_prism(input_model):
     """Determine whether the current observing mode used a prism.
 
     Extended summary
@@ -3289,9 +3231,7 @@ def is_prism(input_model: DataModel) -> bool:
     return prism_mode
 
 
-def copy_keyword_info(
-        slit: SlitModel, slitname: Union[str, None], spec: SpecModel
-):
+def copy_keyword_info(slit, slitname, spec):
     """Copy metadata from the input to the output spectrum.
 
     Parameters
@@ -3343,16 +3283,7 @@ def copy_keyword_info(
         spec.shutter_state = slit.shutter_state
 
 
-def extract_one_slit(
-        input_model: DataModel,
-        slit: SlitModel,
-        integ: int,
-        prev_offset: Union[float, str],
-        extract_params: dict
-) -> Tuple[float, float, np.ndarray,
-           np.ndarray, np.ndarray, np.ndarray, np.ndarray,
-           np.ndarray, np.ndarray, np.ndarray, np.ndarray,
-           np.ndarray, np.ndarray, float]:
+def extract_one_slit(input_model, slit, integ, prev_offset, extract_params):
     """Extract data for one slit, or spectral order, or plane.
 
     Parameters
@@ -3567,11 +3498,7 @@ def extract_one_slit(
             extraction_values)
 
 
-def replace_bad_values(
-        data: np.ndarray,
-        input_dq: Union[np.ndarray, None],
-        wl_array: np.ndarray
-) -> np.ndarray:
+def replace_bad_values(data, input_dq, wl_array):
     """Replace values flagged with DO_NOT_USE or that have NaN wavelengths.
 
     Parameters
@@ -3611,10 +3538,7 @@ def replace_bad_values(
     return data
 
 
-def nans_at_endpoints(
-        wavelength: np.ndarray,
-        dq: np.ndarray,
-) -> Tuple[np.ndarray, np.ndarray, slice]:
+def nans_at_endpoints(wavelength, dq):
     """Flag NaNs in the wavelength array.
 
     Extended summary
@@ -3684,7 +3608,8 @@ def create_extraction(extract_ref_dict,
                       output_model,
                       apcorr_ref_model,
                       log_increment,
-                      is_multiple_slits):
+                      is_multiple_slits
+):
     if slit is None:
         meta_source = input_model
     else:
diff --git a/jwst/fits_generator/generators.py b/jwst/fits_generator/generators.py
index f7f8499a60..8e217a79f5 100644
--- a/jwst/fits_generator/generators.py
+++ b/jwst/fits_generator/generators.py
@@ -41,10 +41,10 @@
 from . import util
 from jwst import __version__
 
-bool = __builtins__['bool']
-str = __builtins__['str']
-int = __builtins__['int']
-float = __builtins__['float']
+bool = __builtins__['bool']  # type: ignore[index]
+str = __builtins__['str']  # type: ignore[index]
+int = __builtins__['int']  # type: ignore[index]
+float = __builtins__['float']  # type: ignore[index]
 
 def date_and_time_to_cds(date_str, time_str):
     """
diff --git a/jwst/fits_generator/input_file_types.py b/jwst/fits_generator/input_file_types.py
index 163ea9dd28..c0333a572c 100644
--- a/jwst/fits_generator/input_file_types.py
+++ b/jwst/fits_generator/input_file_types.py
@@ -453,8 +453,8 @@ def is_niriss_spec_horiz(hdulist):
     InputAPTFile
     ]
 
-file_type_names = [
+type_names = [
     x.type_name for x in input_file_types]
 
-file_type_names[-1] = 'or ' + file_type_names[-1]
-file_type_names = ', '.join(file_type_names)
+type_names[-1] = 'or ' + type_names[-1]
+file_type_names = ', '.join(type_names)
diff --git a/jwst/lib/engdb_direct.py b/jwst/lib/engdb_direct.py
index 39ddf977ce..906e9b1200 100644
--- a/jwst/lib/engdb_direct.py
+++ b/jwst/lib/engdb_direct.py
@@ -80,7 +80,7 @@ def __init__(self, base_url=None, default_format='dict', **service_kwargs):
         ]), timeout=self.timeout)
         response.raise_for_status()
 
-    @property
+    @property  # type: ignore[no-redef]
     def default_format(self):  # noqa: F811
         return self._default_format
 
diff --git a/jwst/lib/progress.py b/jwst/lib/progress.py
index 4091b62569..c0c9067fce 100644
--- a/jwst/lib/progress.py
+++ b/jwst/lib/progress.py
@@ -32,7 +32,7 @@ def next(self):
 
 # Stub the Bar functionality if the actual module does not exist.
 try:
-    from progress.bar import Bar as _Bar
+    from progress.bar import Bar as _Bar  # type: ignore[import-not-found]
 except ModuleNotFoundError:
     _Bar = _BarStub
 
diff --git a/jwst/lib/set_telescope_pointing.py b/jwst/lib/set_telescope_pointing.py
index 4f46a443ab..e3c8ac4ea5 100644
--- a/jwst/lib/set_telescope_pointing.py
+++ b/jwst/lib/set_telescope_pointing.py
@@ -63,7 +63,7 @@
 from enum import Enum
 import logging
 from math import (cos, sin, sqrt)
-import typing
+from typing import Callable
 
 from astropy import units as U
 from astropy.table import Table
@@ -205,7 +205,7 @@ class Methods(Enum):
     #: Default algorithm under PCS_MODE TRACK/FINEGUIDE/MOVING.
     TRACK = TRACK_TR_202111
 
-    def __new__(cls: object, value: str, func_name: str, calc_func: str, mnemonics: dict):
+    def __new__(cls, value, func_name, calc_func, mnemonics):
         obj = object.__new__(cls)
         obj._value_ = value
         obj._func_name = func_name
@@ -306,39 +306,43 @@ def __str__(self):
 GuideStarPosition.__new__.__defaults__ = ((None,) * 3)
 
 
+def NoneFactory():
+    """Set default of any field in the dataclass to None without mypy getting angry"""
+    return dataclasses.field(default_factory=lambda: None)
+
 # Transforms
 @dataclasses.dataclass
 class Transforms:
     """The matrices used in calculation of the M_eci2siaf transformation
     """
     #: ECI to FGS1
-    m_eci2fgs1: np.array = None
+    m_eci2fgs1: np.ndarray = NoneFactory()
     #: ECI to Guide Star
-    m_eci2gs: np.array = None
+    m_eci2gs: np.ndarray = NoneFactory()
     #: ECI to J-Frame
-    m_eci2j: np.array = None
+    m_eci2j: np.ndarray = NoneFactory()
     #: ECI to SIAF
-    m_eci2siaf: np.array = None
+    m_eci2siaf: np.ndarray = NoneFactory()
     #: ECI to SIFOV
-    m_eci2sifov: np.array = None
+    m_eci2sifov: np.ndarray = NoneFactory()
     #: ECI to V
-    m_eci2v: np.array = None
+    m_eci2v: np.ndarray = NoneFactory()
     #: FGSX to Guide Stars transformation
-    m_fgsx2gs: np.array = None
+    m_fgsx2gs: np.ndarray = NoneFactory()
     #: FGS1 to SIFOV
-    m_fgs12sifov: np.array = None
+    m_fgs12sifov: np.ndarray = NoneFactory()
     #: Velocity aberration
-    m_gs2gsapp: np.array = None
+    m_gs2gsapp: np.ndarray = NoneFactory()
     #: J-Frame to FGS1
-    m_j2fgs1: np.array = None
+    m_j2fgs1: np.ndarray = NoneFactory()
     #: FSM correction
-    m_sifov_fsm_delta: np.array = None
+    m_sifov_fsm_delta: np.ndarray = NoneFactory()
     #: SIFOV to V1
-    m_sifov2v: np.array = None
+    m_sifov2v: np.ndarray = NoneFactory()
     #: V to SIAF
-    m_v2siaf: np.array = None
+    m_v2siaf: np.ndarray = NoneFactory()
     #: Override values. Either another Transforms or dict-like object
-    override: object = None
+    override: object = NoneFactory()
 
     @classmethod
     def from_asdf(cls, asdf_file):
@@ -426,50 +430,50 @@ class TransformParameters:
     #: The V3 position angle to use if the pointing information is not found.
     default_pa_v3: float = 0.
     #: Detector in use.
-    detector: str = None
+    detector: str = NoneFactory()
     #: Do not write out the modified file.
     dry_run: bool = False
     #: URL of the engineering telemetry database REST interface.
-    engdb_url: str = None
+    engdb_url: str = NoneFactory()
     #: Exposure type
-    exp_type: str = None
+    exp_type: str = NoneFactory()
     #: FGS to use as the guiding FGS. If None, will be set to what telemetry provides.
-    fgsid: int = None
+    fgsid: int = NoneFactory()
     #: The version of the FSM correction calculation to use. See `calc_sifov_fsm_delta_matrix`
     fsmcorr_version: str = 'latest'
     #: Units of the FSM correction values. Default is 'arcsec'. See `calc_sifov_fsm_delta_matrix`
     fsmcorr_units: str = 'arcsec'
     #: Guide star WCS info, typically from the input model.
-    guide_star_wcs: WCSRef = WCSRef()
+    guide_star_wcs: WCSRef = WCSRef(None, None, None)
     #: Transpose the `j2fgs1` matrix.
     j2fgs_transpose: bool = True
     #: The [DX, DY, DZ] barycentri velocity vector
-    jwst_velocity: np.array = None
+    jwst_velocity: np.ndarray = NoneFactory()
     #: The method, or algorithm, to use in calculating the transform. If not specified, the default method is used.
     method: Methods = Methods.default
     #: Observation end time
-    obsend: float = None
+    obsend: float = NoneFactory()
     #: Observation start time
-    obsstart: float = None
+    obsstart: float = NoneFactory()
     #: If set, matrices that should be used instead of the calculated one.
-    override_transforms: Transforms = None
+    override_transforms: Transforms = NoneFactory()
     #: The tracking mode in use.
-    pcs_mode: str = None
+    pcs_mode: str = NoneFactory()
     #: The observatory orientation, represented by the ECI quaternion, and other engineering mnemonics
-    pointing: Pointing = None
+    pointing: Pointing = NoneFactory()
     #: Reduction function to use on values.
-    reduce_func: typing.Callable = None
+    reduce_func: Callable = NoneFactory()
     #: The SIAF information for the input model
-    siaf: SIAF = None
+    siaf: SIAF = NoneFactory()
     #: The SIAF database
-    siaf_db: SiafDb = None
+    siaf_db: SiafDb = NoneFactory()
     #: If no telemetry can be found during the observation,
     #: the time, in seconds, beyond the observation time to search for telemetry.
     tolerance: float = 60.
     #: The date of observation (`jwst.datamodels.JwstDataModel.meta.date`)
-    useafter: str = None
+    useafter: str = NoneFactory()
     #: V3 position angle at Guide Star (`jwst.datamodels.JwstDataModel.meta.guide_star.gs_v3_pa_science`)
-    v3pa_at_gs: float = None
+    v3pa_at_gs: float = NoneFactory()
 
     def as_reprdict(self):
         """Return a dict where all values are REPR of their values"""
@@ -878,7 +882,6 @@ def update_wcs_from_telem(model, t_pars: TransformParameters):
             logger.warning('Exception is %s', exception)
             logger.info("Setting ENGQLPTG keyword to PLANNED")
             model.meta.visit.engdb_pointing_quality = "PLANNED"
-            t_pars.pointing = None
     else:
         logger.info('Successful read of engineering quaternions:')
         logger.info('\tPointing: %s', t_pars.pointing)
@@ -2987,7 +2990,7 @@ def gs_ideal_to_subarray(gs_position, aperture, flip=False):
     return x, y
 
 
-def calc_wcs_guiding(model, t_pars, default_roll_ref=0.0, default_vparity=1, default_v3yangle=0.0):
+def calc_wcs_guiding(model, t_pars: TransformParameters, default_roll_ref=0.0, default_vparity=1, default_v3yangle=0.0):
     """Calculate WCS info for FGS guiding
 
     For Fine Guidance guiding observations, nearly everything
@@ -3028,7 +3031,7 @@ def calc_wcs_guiding(model, t_pars, default_roll_ref=0.0, default_vparity=1, def
     # Retrieve the appropriate mnemonics that represent the X/Y position of guide star
     # in the image.
     if t_pars.exp_type in ['fgs_acq1', 'fgs_acq2']:
-        mnemonics_to_read = FGS_ACQ_MNEMONICS
+        mnemonics_to_read = set(FGS_ACQ_MNEMONICS.keys())
     elif t_pars.exp_type in ['fgs_fineguide', 'fgs_track']:
         mnemonics_to_read = FGS_GUIDED_MNEMONICS
     elif t_pars.exp_type in FGS_ID_EXP_TYPES:
diff --git a/jwst/lib/set_velocity_aberration.py b/jwst/lib/set_velocity_aberration.py
index 4e05f42ed9..7fcff79ffa 100644
--- a/jwst/lib/set_velocity_aberration.py
+++ b/jwst/lib/set_velocity_aberration.py
@@ -23,7 +23,7 @@
 from gwcs.geometry import SphericalToCartesian, CartesianToSpherical
 from scipy.constants import speed_of_light
 import jwst.datamodels as dm
-from jwst.datamodels import Level1bModel
+from jwst.datamodels import Level1bModel  # type: ignore[attr-defined]
 
 # Configure logging
 logger = logging.getLogger(__name__)
diff --git a/jwst/lib/siafdb.py b/jwst/lib/siafdb.py
index a90b74d205..4c9691498a 100644
--- a/jwst/lib/siafdb.py
+++ b/jwst/lib/siafdb.py
@@ -76,7 +76,7 @@ def __init__(self, source=None, prd=None):
             log_level = logging.ERROR
         try:
             with LoggingContext(logger_pysiaf, level=log_level):
-                import pysiaf
+                import pysiaf # type: ignore[import-not-found]
         except ImportError:
             raise ValueError('Package "pysiaf" is not installed. Cannot use the pysiaf api')
         self.pysiaf = pysiaf
diff --git a/jwst/lib/tests/test_siafdb.py b/jwst/lib/tests/test_siafdb.py
index 2cf0357850..f070140105 100644
--- a/jwst/lib/tests/test_siafdb.py
+++ b/jwst/lib/tests/test_siafdb.py
@@ -7,7 +7,7 @@
 from jwst.lib import siafdb
 
 pytest.importorskip('pysiaf')
-import pysiaf  # noqa: E402
+import pysiaf  # type: ignore[import-not-found]  # noqa: E402
 
 # Database paths
 DATA_PATH = Path(__file__).parent / 'data'
diff --git a/jwst/mrs_imatch/mrs_imatch_step.py b/jwst/mrs_imatch/mrs_imatch_step.py
index 543da7b208..3abf11aa12 100644
--- a/jwst/mrs_imatch/mrs_imatch_step.py
+++ b/jwst/mrs_imatch/mrs_imatch_step.py
@@ -31,7 +31,7 @@ class MRSIMatchStep(Step):
         skip = boolean(default=True) # Step must be turned on by parameter reference or user
     """
 
-    reference_file_types = []
+    reference_file_types: list = []
 
     def process(self, images):
 
diff --git a/jwst/outlier_detection/tests/test_fileio.py b/jwst/outlier_detection/tests/test_fileio.py
index 6e01557c8e..41ef2c1b2f 100644
--- a/jwst/outlier_detection/tests/test_fileio.py
+++ b/jwst/outlier_detection/tests/test_fileio.py
@@ -1,6 +1,6 @@
 import pytest
 from jwst.outlier_detection._fileio import _save_intermediate_output
-from jwst.datamodels import ImageModel
+from jwst.datamodels import ImageModel  # type: ignore[attr-defined]
 from jwst.step import OutlierDetectionStep
 import os
 import numpy as np
diff --git a/jwst/outlier_detection/tso.py b/jwst/outlier_detection/tso.py
index d0161dffe7..2c0020986f 100644
--- a/jwst/outlier_detection/tso.py
+++ b/jwst/outlier_detection/tso.py
@@ -49,7 +49,7 @@ def detect_outliers(
     # Save median model if pars['save_intermediate_results'] is True
     # this will be a CubeModel with rolling median values.
     if save_intermediate_results:
-        median_model = dm.CubeModel(data=medians)
+        median_model = dm.CubeModel(data=medians)  # type: ignore[name-defined]
         with dm.open(weighted_cube) as dm0:
             median_model.update(dm0)
         save_median(median_model, make_output_path)
@@ -89,7 +89,11 @@ def weight_no_resample(input_model, good_bits):
     return weighted_cube
 
 
-def compute_rolling_median(model: dm.CubeModel, weight_threshold: np.ndarray, w: int=25) -> np.ndarray:
+def compute_rolling_median(
+        model: dm.CubeModel,  # type: ignore[name-defined]
+        weight_threshold: np.ndarray,
+        w: int=25
+) -> np.ndarray:
     '''
     Set bad and low-weight data to NaN, then compute the rolling median over the time axis.
 
@@ -159,7 +163,7 @@ def moving_median_over_zeroth_axis(x: np.ndarray, w: int) -> np.ndarray:
     for idx in range(w - 1):
         shifted[idx:-w + idx + 1, idx] = x
     shifted[idx + 1:, idx + 1] = x
-    medians = np.median(shifted, axis=1)
+    medians: np.ndarray = np.median(shifted, axis=1)
     for idx in range(w - 1):
         medians[idx] = np.median(shifted[idx, :idx + 1])
         medians[-idx - 1] = np.median(shifted[-idx - 1, -idx - 1:])
diff --git a/jwst/pipeline/tests/test_calwebb_image2.py b/jwst/pipeline/tests/test_calwebb_image2.py
index e0389f42e3..0e24cc6768 100644
--- a/jwst/pipeline/tests/test_calwebb_image2.py
+++ b/jwst/pipeline/tests/test_calwebb_image2.py
@@ -2,7 +2,7 @@
 import os
 import shutil
 from jwst.stpipe import Step
-from jwst.datamodels import ImageModel
+from jwst.datamodels import ImageModel  # type: ignore[attr-defined]
 
 
 INPUT_FILE = "dummy_rate.fits"
diff --git a/jwst/pipeline/tests/test_calwebb_image3.py b/jwst/pipeline/tests/test_calwebb_image3.py
index 8531674664..3c7f813ac6 100644
--- a/jwst/pipeline/tests/test_calwebb_image3.py
+++ b/jwst/pipeline/tests/test_calwebb_image3.py
@@ -3,7 +3,7 @@
 import shutil
 from jwst.stpipe import Step
 from jwst.assign_wcs import AssignWcsStep
-from jwst.datamodels import ImageModel
+from jwst.datamodels import ImageModel  # type: ignore[attr-defined]
 
 
 INPUT_FILE = "dummy_cal.fits"
diff --git a/jwst/pipeline/tests/test_calwebb_spec2.py b/jwst/pipeline/tests/test_calwebb_spec2.py
index 71a39232f3..1baf57ac9d 100644
--- a/jwst/pipeline/tests/test_calwebb_spec2.py
+++ b/jwst/pipeline/tests/test_calwebb_spec2.py
@@ -3,7 +3,7 @@
 import shutil
 from jwst.pipeline.calwebb_spec2 import Spec2Pipeline
 from jwst.stpipe import Step
-from jwst.datamodels import IFUImageModel
+from jwst.datamodels import IFUImageModel  # type: ignore[attr-defined]
 
 
 INPUT_FILE = "dummy_rate.fits"
diff --git a/jwst/pixel_replace/pixel_replace_step.py b/jwst/pixel_replace/pixel_replace_step.py
index 7aa07b3dfd..b76260d0a0 100644
--- a/jwst/pixel_replace/pixel_replace_step.py
+++ b/jwst/pixel_replace/pixel_replace_step.py
@@ -3,7 +3,7 @@
 
 from ..stpipe import Step
 from jwst.stpipe import record_step_status
-from .. import datamodels
+from jwst import datamodels
 from .pixel_replace import PixelReplacement
 
 __all__ = ["PixelReplaceStep"]
diff --git a/jwst/regtest/test_associations_sdp_pools.py b/jwst/regtest/test_associations_sdp_pools.py
index 3cbe4afe08..bda356691d 100644
--- a/jwst/regtest/test_associations_sdp_pools.py
+++ b/jwst/regtest/test_associations_sdp_pools.py
@@ -22,11 +22,11 @@
 
 # Mark expected failures. Key is the pool name
 # and value is the reason message.
-EXPECTED_FAILS = {
+EXPECTED_FAILS: dict = {
 }
 
 # Pools that require special handling
-SPECIAL_DEFAULT = {
+SPECIAL_DEFAULT: dict = {
     'args': [],
     'xfail': None,
     'slow': False,
diff --git a/jwst/regtest/test_associations_standards.py b/jwst/regtest/test_associations_standards.py
index b8ba75c0b6..6f103385ed 100644
--- a/jwst/regtest/test_associations_standards.py
+++ b/jwst/regtest/test_associations_standards.py
@@ -34,7 +34,7 @@
 ]
 
 # Produce general associations
-DEF_ARGS = []
+DEF_ARGS: list = []
 
 # Define the standards
 
diff --git a/jwst/regtest/test_fgs_pointing.py b/jwst/regtest/test_fgs_pointing.py
index f905da5f6b..ba90dce043 100644
--- a/jwst/regtest/test_fgs_pointing.py
+++ b/jwst/regtest/test_fgs_pointing.py
@@ -9,7 +9,7 @@
 from numpy import array                             # noqa: E402
 from numpy import allclose, isclose                 # noqa: E402
 
-from jwst.datamodels import Level1bModel            # noqa: E402
+from jwst.datamodels import Level1bModel            # type: ignore[attr-defined] # noqa: E402
 from jwst.lib import engdb_mast                     # noqa: E402
 from jwst.lib import engdb_tools                    # noqa: E402
 from jwst.lib import set_telescope_pointing as stp  # noqa: E402
diff --git a/jwst/resample/resample_step.py b/jwst/resample/resample_step.py
index 5790fb4f58..4132850918 100755
--- a/jwst/resample/resample_step.py
+++ b/jwst/resample/resample_step.py
@@ -4,7 +4,7 @@
 
 import asdf
 
-from jwst.datamodels import ModelLibrary, ImageModel
+from jwst.datamodels import ModelLibrary, ImageModel  # type: ignore[attr-defined]
 from jwst.lib.pipe_utils import match_nans_and_flags
 
 from . import resample
@@ -56,7 +56,7 @@ class ResampleStep(Step):
         in_memory = boolean(default=True)  # Keep images in memory
     """
 
-    reference_file_types = []
+    reference_file_types: list = []
 
     def process(self, input):
 
diff --git a/jwst/skymatch/skymatch_step.py b/jwst/skymatch/skymatch_step.py
index c64b63c00d..9762a72048 100644
--- a/jwst/skymatch/skymatch_step.py
+++ b/jwst/skymatch/skymatch_step.py
@@ -63,7 +63,7 @@ class SkyMatchStep(Step):
         in_memory = boolean(default=True) # If False, preserve memory using temporary files
     """  # noqa: E501
 
-    reference_file_types = []
+    reference_file_types: list = []
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
diff --git a/jwst/stpipe/core.py b/jwst/stpipe/core.py
index 21efa00ef0..0c3df08d71 100644
--- a/jwst/stpipe/core.py
+++ b/jwst/stpipe/core.py
@@ -11,7 +11,7 @@
 from stpipe import Step
 from stpipe import Pipeline
 
-from .. import __version_commit__, __version__
+from jwst import __version_commit__, __version__
 from ..lib.suffix import remove_suffix
 
 
diff --git a/jwst/tests/test_import.py b/jwst/tests/test_import.py
index 5df92128d5..63cd440361 100644
--- a/jwst/tests/test_import.py
+++ b/jwst/tests/test_import.py
@@ -8,7 +8,7 @@
 import jwst
 
 
-def dependencies(package, exclude: [str]):
+def dependencies(package, exclude: list[str]):
     return [
         module[1]
         for module in pkgutil.walk_packages(
diff --git a/jwst/tweakreg/tweakreg_step.py b/jwst/tweakreg/tweakreg_step.py
index 0d8363771b..1638189daf 100644
--- a/jwst/tweakreg/tweakreg_step.py
+++ b/jwst/tweakreg/tweakreg_step.py
@@ -126,7 +126,7 @@ class TweakRegStep(Step):
         in_memory = boolean(default=True)  # If False, preserve memory using temporary files at expense of runtime
     """
 
-    reference_file_types = []
+    reference_file_types: list = []
 
     def process(self, input):
         if isinstance(input, ModelLibrary):
diff --git a/jwst/wfss_contam/tests/test_observations.py b/jwst/wfss_contam/tests/test_observations.py
index 71228f6479..422b2900ec 100644
--- a/jwst/wfss_contam/tests/test_observations.py
+++ b/jwst/wfss_contam/tests/test_observations.py
@@ -12,7 +12,7 @@
 from jwst.wfss_contam.observations import background_subtract
 from jwst.wfss_contam.disperse import dispersed_pixel
 from jwst.wfss_contam.tests import data
-from jwst.datamodels import SegmentationMapModel, ImageModel
+from jwst.datamodels import SegmentationMapModel, ImageModel  # type: ignore[attr-defined]
 
 data_path = os.path.split(os.path.abspath(data.__file__))[0]
 DIR_IMAGE = "direct_image.fits"
diff --git a/pyproject.toml b/pyproject.toml
index c73a69fef9..bbe52dca46 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -264,6 +264,8 @@ line-length = 130
 lint.ignore = [
     "E741", # ambiguous variable name (O/0, l/I, etc.)
     "E722", # Do not use bare `except`
+    "ANN101", # Missing type annotation for self in method
+    "ANN102", # Missing type annotation for cls in classmethod    
 ]
 
 [tool.ruff.lint.per-file-ignores]
@@ -286,6 +288,24 @@ lint.ignore = [
     "E402", # module-level import not at top of file
 ]
 
+[tool.mypy]
+python_version = "3.12"
+warn_return_any = true
+warn_unused_configs = true
+disable_error_code = "import-untyped" # do not check imports
+exclude = ["build"]
+
+[[tool.mypy.overrides]]
+# don't complain about the installed c parts of this library
+module = [
+    "jwst.cube_build.cube_match_internal",
+    "jwst.cube_build.cube_match_sky_driz",
+    "jwst.cube_build.cube_match_sky_pointcloud",
+    "jwst.lib.winclip",
+    "jwst.straylight.calc_xart",
+]
+ignore_missing_imports = true
+
 [tool.towncrier]
 filename = "CHANGES.rst"
 directory = "changes"
diff --git a/tox.ini b/tox.ini
index 8813c9998a..77df7bbe27 100644
--- a/tox.ini
+++ b/tox.ini
@@ -13,6 +13,14 @@ envlist =
 #     tox -l -v
 #
 
+[testenv:check-types]
+description = check type hints, e.g. with mypy
+deps =
+    mypy
+    types-requests
+commands =
+    mypy jwst --config-file pyproject.toml
+
 [testenv:check-dependencies]
 description = verify that install_requires in setup.cfg has correct dependencies
 # `extras` needs to be empty to check modules without additional dependencies