diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 2cdc6cf..cc8ee22 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -13,7 +13,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
       - name: Checkout github repo
@@ -26,12 +26,15 @@ jobs:
           cache: 'pip'
 
       - name: Install dependencies
-        run: | 
+        run: |
           python -m pip install -U pip
           python -m pip install .
           python -m pip install .[dev]
           python -m pip install git+https://github.com/GalSim-developers/JAX-GalSim.git
 
+      - name: Run Ruff
+        run: ruff check --output-format=github .
+
       - name: Run Tests
         run: |
           pytest --durations=0
diff --git a/bpd/diagnostics.py b/bpd/diagnostics.py
index ef5b418..8231c4b 100644
--- a/bpd/diagnostics.py
+++ b/bpd/diagnostics.py
@@ -16,7 +16,7 @@ def get_contour_plot(
     kde: bool | int | float = False,
 ) -> Figure:
     c = ChainConsumer()
-    for name, samples in zip(names, samples_list):
+    for name, samples in zip(names, samples_list, strict=False):
         df = pd.DataFrame.from_dict(samples)
         c.add_chain(Chain(samples=df, name=name, kde=kde))
     c.add_truth(Truth(location=truth))
@@ -24,7 +24,7 @@ def get_contour_plot(
 
 
 def get_gauss_pc_fig(
-    ax: Axes, samples: np.ndarray, truth: float, param_name: str = None
+    ax: Axes, samples: np.ndarray, truth: float, param_name: str | None = None
 ) -> None:
     """Get a marginal pc figure assuming Gaussian distribution of samples."""
     assert samples.ndim == 2  # (n_chains, n_samples)
@@ -49,7 +49,7 @@ def get_gauss_pc_fig(
 
 
 def get_pc_fig(
-    ax: Axes, samples: np.ndarray, truth: float, param_name: str = None
+    ax: Axes, samples: np.ndarray, truth: float, param_name: str | None = None
 ) -> None:
     """Get a marginal probability calibration figure using `hpdi` from `numpyro`."""
     assert samples.ndim == 2  # (n_chains, n_samples)
diff --git a/bpd/initialization.py b/bpd/initialization.py
index 1f406bd..e15a050 100644
--- a/bpd/initialization.py
+++ b/bpd/initialization.py
@@ -26,7 +26,7 @@ def init_with_ball(
     """Sample ball given offset of each parameter."""
     new = {}
     keys = random.split(rng_key, len(true_params.keys()))
-    rng_key_dict = {p: k for p, k in zip(true_params, keys)}
+    rng_key_dict = {p: k for p, k in zip(true_params, keys, strict=False)}
 
     for p, centr in true_params.items():
         offset = offset_dict[p]
diff --git a/bpd/io.py b/bpd/io.py
index 3d59190..aeca783 100644
--- a/bpd/io.py
+++ b/bpd/io.py
@@ -11,7 +11,6 @@
 def save_dataset(
     ds: dict[str, Array], fpath: str | Path, overwrite: bool = False
 ) -> None:
-
     if Path(fpath).exists() and not overwrite:
         raise IOError("overwriting existing ds")
     assert Path(fpath).suffix == ".npz"
@@ -22,6 +21,7 @@ def save_dataset(
 def load_dataset(fpath: str) -> dict[str, Array]:
     assert Path(fpath).exists(), "file path does not exists"
     assert Path(fpath).suffix == ".npz"
+
     ds = {}
 
     npzfile = jnp.load(fpath)
diff --git a/bpd/likelihood.py b/bpd/likelihood.py
index b778449..c1f55f6 100644
--- a/bpd/likelihood.py
+++ b/bpd/likelihood.py
@@ -17,7 +17,7 @@ def shear_loglikelihood_unreduced(
     # the priors are callables for now on only ellipticities
     # the interim_prior should have been used when obtaining e_obs from the chain (i.e. for now same sigma)
     # normalizatoin in priors can be ignored for now as alpha is fixed.
-    N, K, _ = e_post.shape
+    _, K, _ = e_post.shape  # (N, K, 2)
 
     e_post_mag = jnp.sqrt(e_post[..., 0] ** 2 + e_post[..., 1] ** 2)
     denom = interim_prior(e_post_mag)  # (N, K), can ignore angle in prior as uniform
diff --git a/bpd/pipelines/image_ellips.py b/bpd/pipelines/image_ellips.py
index 7868c70..8492195 100644
--- a/bpd/pipelines/image_ellips.py
+++ b/bpd/pipelines/image_ellips.py
@@ -3,16 +3,14 @@
 
 import blackjax
 import jax.numpy as jnp
-from jax import Array
+from jax import Array, random
 from jax import jit as jjit
-from jax import random
 from jax._src.prng import PRNGKeyArray
 from jax.scipy import stats
 
 from bpd.chains import inference_loop
 from bpd.draw import draw_gaussian, draw_gaussian_galsim
 from bpd.noise import add_noise
-from bpd.pipelines.toy_ellips import do_inference
 from bpd.prior import ellip_mag_prior, sample_ellip_prior
 
 
@@ -122,7 +120,6 @@ def do_inference(
     target_acceptance_rate: float = 0.80,
     n_samples: int = 100,
 ):
-
     key1, key2 = random.split(rng_key)
 
     _logdensity = partial(logtarget_fnc, data=data)
@@ -164,7 +161,6 @@ def pipeline_image_interim_samples(
     background: float = 1.0,
     fft_size: int = 256,
 ):
-
     k1, k2 = random.split(rng_key)
 
     init_position = initialization_fnc(k1, true_params=true_params, data=target_image)
diff --git a/bpd/pipelines/shear_inference.py b/bpd/pipelines/shear_inference.py
index 3a5104c..c4b39bd 100644
--- a/bpd/pipelines/shear_inference.py
+++ b/bpd/pipelines/shear_inference.py
@@ -2,9 +2,8 @@
 from typing import Callable
 
 import blackjax
-from jax import Array
+from jax import Array, random
 from jax import jit as jjit
-from jax import random
 from jax._src.prng import PRNGKeyArray
 from jax.scipy import stats
 
diff --git a/bpd/pipelines/toy_ellips.py b/bpd/pipelines/toy_ellips.py
index 826cc5b..cbf8fb0 100644
--- a/bpd/pipelines/toy_ellips.py
+++ b/bpd/pipelines/toy_ellips.py
@@ -4,9 +4,8 @@
 import blackjax
 import jax.numpy as jnp
 import jax.scipy as jsp
-from jax import Array
+from jax import Array, random, vmap
 from jax import jit as jjit
-from jax import random, vmap
 from jax._src.prng import PRNGKeyArray
 
 from bpd.chains import inference_loop
@@ -73,7 +72,6 @@ def pipeline_toy_ellips_samples(
     k: int,
     n_warmup_steps: int = 500,
 ):
-
     k1, k2 = random.split(key)
 
     true_g = jnp.array([g1, g2])
diff --git a/pyproject.toml b/pyproject.toml
index 231b227..79cc4d0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -2,6 +2,7 @@
 requires = ["setuptools>=45"]
 build-backend = "setuptools.build_meta"
 
+
 [project]
 name = "BPD"
 authors = [{ name = "Ismael Mendoza" }]
@@ -9,35 +10,81 @@ description = "Bayesian Pixel Domain method for shear inference."
 version = "0.0.1"
 license = { file = "LICENSE" }
 readme = "README.md"
-dependencies = [
-    "numpy >=1.18.0",
-    "galsim >=2.3.0",
-    "jax >=0.4.30",
-    "jaxlib",
-    "blackjax >=1.2.0",
-    "numpyro >=0.15.0",
-]
+dependencies = ["numpy >=1.18.0", "galsim >=2.3.0", "jax >=0.4.30", "jaxlib", "blackjax >=1.2.0"]
+
 
 [project.optional-dependencies]
-dev = ["pytest", "click"]
+dev = ["pytest", "click", "ruff", "ChainConsumer"]
+
 
 [project.urls]
 home = "https://github.com/LSSTDESC/BPD"
 
+
 [tool.setuptools.packages.find]
-include = ["bpd*", "scripts*"]
+include = ["bpd*"]
+
+[tool.ruff]
+exclude = [
+    ".bzr",
+    ".direnv",
+    ".eggs",
+    ".git",
+    ".git-rewrite",
+    ".hg",
+    ".ipynb_checkpoints",
+    ".mypy_cache",
+    ".nox",
+    ".pants.d",
+    ".pyenv",
+    ".pytest_cache",
+    ".pytype",
+    ".ruff_cache",
+    ".svn",
+    ".tox",
+    ".venv",
+    ".vscode",
+    "__pypackages__",
+    "_build",
+    "buck-out",
+    "build",
+    "dist",
+    "node_modules",
+    "site-packages",
+    "venv",
+]
+
+# Same as Black.
+line-length = 88
+indent-width = 4
+
+# Assume Python 3.8
+target-version = "py310"
+
+[tool.ruff.format]
+# Like Black, use double quotes for strings.
+quote-style = "double"
+
+# Like Black, indent with spaces, rather than tabs.
+indent-style = "space"
+
+# Like Black, respect magic trailing commas.
+skip-magic-trailing-comma = false
+
+# Like Black, automatically detect the appropriate line ending.
+line-ending = "auto"
+
+exclude = ["*.ipynb"]
 
 
-[tool.flake8]
-max-line-length = 88
-ignore = ["C901", "E203", "W503"]
-per-file-ignores = ["__init__.py:F401"]
+[tool.ruff.lint]
+select = ["E", "F", "I", "W", "B", "SIM", "PLE", "PLC", "PLW", "RUF"]
+ignore = ["C901", "E203", "E501", "E731", "PLC0206", "RUF027"]
+preview = true
+exclude = ["*.ipynb", "scripts/image_shear_gpu_one_galaxy.py", "scripts/benchmarks/*.py"]
 
 
-[tool.isort]
-profile = "black"
-multi_line_output = 3
-include_trailing_comma = true
-use_parentheses = true
-ensure_newline_before_comments = true
-line_length = 88
+[tool.pytest.ini_options]
+minversion = "6.0"
+addopts = "-rav"
+filterwarnings = ["ignore::DeprecationWarning:tensorflow.*"]
diff --git a/scripts/benchmarks/benchmark1.py b/scripts/benchmarks/benchmark1.py
index 805c05b..08c0f4d 100755
--- a/scripts/benchmarks/benchmark1.py
+++ b/scripts/benchmarks/benchmark1.py
@@ -82,7 +82,7 @@
 def sample_ball(rng_key, center_params: dict):
     new = {}
     keys = random.split(rng_key, len(center_params.keys()))
-    rng_key_dict = {p: k for p, k in zip(center_params, keys)}
+    rng_key_dict = {p: k for p, k in zip(center_params, keys, strict=False)}
     for p in center_params:
         centr = center_params[p]
         if p == "f":
@@ -128,7 +128,6 @@ def draw_gal(f, hlr, g1, g2, x, y):
 
 
 def _logprob_fn(params, data):
-
     # prior
     prior = jnp.array(0.0, device=GPU)
     for p in ("f", "hlr", "g1", "g2"):  # uniform priors
@@ -148,7 +147,7 @@ def _logprob_fn(params, data):
 
 
 def _log_setup(snr: float):
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
         print(file=f)
         print(
             f"""Running benchmark 1 with configuration as follows. Variable number of chains.
@@ -186,7 +185,6 @@ def _log_setup(snr: float):
 
 # vmap only rng_key
 def do_warmup(rng_key, init_position: dict, data):
-
     _logdensity = partial(_logprob_fn, data=data)
 
     warmup = blackjax.window_adaptation(
@@ -258,7 +256,6 @@ def main():
         _init_positions = {p: q[:n_chains] for p, q in all_init_positions.items()}
 
         if ii == 0:
-
             # compilation times
             t1 = time.time()
             (_sts, _tp), _ = jax.block_until_ready(
@@ -310,7 +307,7 @@ def main():
     jnp.save(filepath, results)
 
     _log_setup(snr)
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
         print(file=f)
         print(f"results were saved to {filepath}", file=f)
 
diff --git a/scripts/benchmarks/benchmark2.py b/scripts/benchmarks/benchmark2.py
index 88e2a2d..2b7b761 100755
--- a/scripts/benchmarks/benchmark2.py
+++ b/scripts/benchmarks/benchmark2.py
@@ -84,7 +84,7 @@
 def sample_ball(rng_key, center_params: dict):
     new = {}
     keys = random.split(rng_key, len(center_params.keys()))
-    rng_key_dict = {p: k for p, k in zip(center_params, keys)}
+    rng_key_dict = {p: k for p, k in zip(center_params, keys, strict=False)}
     for p in center_params:
         centr = center_params[p]
         if p == "f":
@@ -130,7 +130,6 @@ def draw_gal(f, hlr, g1, g2, x, y):
 
 
 def _logprob_fn(params, data):
-
     # prior
     prior = jnp.array(0.0, device=GPU)
     for p in ("f", "hlr", "g1", "g2"):  # uniform priors
@@ -150,15 +149,15 @@ def _logprob_fn(params, data):
 
 
 def _log_setup(snr: float):
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding='utf-8') as f:
         print(file=f)
         print(
             f"""Running benchmark 2 with configuration as follows. Variable number of chains.
-    
+
     The sampler used is NUTS with standard warmup.
 
     TAG: {TAG}
-    SEED: {SEED} 
+    SEED: {SEED}
 
     Overall sampler configuration (fixed):
         max doublings: {MAX_DOUBLINGS}
@@ -188,7 +187,6 @@ def _log_setup(snr: float):
 
 # vmap only rng_key
 def do_warmup(rng_key, init_position: dict, data):
-
     _logdensity = partial(_logprob_fn, data=data)
 
     warmup = blackjax.window_adaptation(
@@ -271,7 +269,6 @@ def main():
         _data_ii = data_gpu[:n_obj]
 
         if ii == 0:
-
             # compilation times
             t1 = time.time()
             (_sts, _tp), _ = jax.block_until_ready(
@@ -323,7 +320,7 @@ def main():
     jnp.save(filepath, results)
 
     _log_setup(snr)
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding='utf-8') as f:
         print(file=f)
         print(f"results were saved to {filepath}", file=f)
 
diff --git a/scripts/benchmarks/benchmark2_7.py b/scripts/benchmarks/benchmark2_7.py
index d4b3854..893aa68 100755
--- a/scripts/benchmarks/benchmark2_7.py
+++ b/scripts/benchmarks/benchmark2_7.py
@@ -79,7 +79,7 @@
 def sample_ball(rng_key, center_params: dict):
     new = {}
     keys = random.split(rng_key, len(center_params.keys()))
-    rng_key_dict = {p: k for p, k in zip(center_params, keys)}
+    rng_key_dict = {p: k for p, k in zip(center_params, keys, strict=False)}
     for p in center_params:
         centr = center_params[p]
         if p == "f":
@@ -125,7 +125,6 @@ def draw_gal(f, hlr, g1, g2, x, y):
 
 
 def _logprob_fn(params, data):
-
     # prior
     prior = jnp.array(0.0, device=GPU)
     for p in ("f", "hlr", "g1", "g2"):  # uniform priors
@@ -147,7 +146,7 @@ def _logprob_fn(params, data):
 
 
 def _log_setup(snr: float):
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
         print(file=f)
         print(
             f"""Running benchmark 2.7 with configuration as follows
@@ -185,7 +184,6 @@ def _log_setup(snr: float):
 
 # vmap only rng_key
 def do_warmup(rng_key, init_position: dict, data):
-
     _logdensity = partial(_logprob_fn, data=data)
 
     warmup = blackjax.window_adaptation(
@@ -304,7 +302,7 @@ def main():
     filepath = SCRATCH_DIR.joinpath(filename)
     jnp.save(filepath, results)
 
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
         print(file=f)
         print(f"results were saved to {filepath}", file=f)
 
diff --git a/scripts/benchmarks/benchmark2_72.py b/scripts/benchmarks/benchmark2_72.py
index 8dded5f..367e8bc 100755
--- a/scripts/benchmarks/benchmark2_72.py
+++ b/scripts/benchmarks/benchmark2_72.py
@@ -73,7 +73,7 @@
 def sample_ball(rng_key, center_params: dict):
     new = {}
     keys = random.split(rng_key, len(center_params.keys()))
-    rng_key_dict = {p: k for p, k in zip(center_params, keys)}
+    rng_key_dict = {p: k for p, k in zip(center_params, keys, strict=False)}
     for p in center_params:
         centr = center_params[p]
         if p == "f":
@@ -119,7 +119,6 @@ def draw_gal(f, hlr, g1, g2, x, y):
 
 
 def _logprob_fn(params, data):
-
     # prior
     prior = jnp.array(0.0, device=GPU)
     for p in ("f", "hlr", "g1", "g2"):  # uniform priors
@@ -147,7 +146,6 @@ def _logprob_fn(params, data):
 
 # vmap only rng_key
 def do_warmup(rng_key, init_position: dict, data):
-
     _logdensity = partial(_logprob_fn, data=data)
 
     warmup = blackjax.window_adaptation(
diff --git a/scripts/benchmarks/benchmark2_8.py b/scripts/benchmarks/benchmark2_8.py
index ca4d725..2a1c5eb 100755
--- a/scripts/benchmarks/benchmark2_8.py
+++ b/scripts/benchmarks/benchmark2_8.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 
-"""Here we run multiple chains each on one galaxy, same noise realization. 
+"""Here we run multiple chains each on one galaxy, same noise realization.
 
 To get a sense of efficiency.
 
@@ -73,7 +73,7 @@
 def sample_ball(rng_key, center_params: dict):
     new = {}
     keys = random.split(rng_key, len(center_params.keys()))
-    rng_key_dict = {p: k for p, k in zip(center_params, keys)}
+    rng_key_dict = {p: k for p, k in zip(center_params, keys, strict=False)}
     for p in center_params:
         centr = center_params[p]
         if p == "f":
@@ -119,7 +119,6 @@ def draw_gal(f, hlr, g1, g2, x, y):
 
 
 def _logprob_fn(params, data):
-
     # prior
     prior = jnp.array(0.0, device=GPU)
     for p in ("f", "hlr", "g1", "g2"):  # uniform priors
@@ -150,7 +149,7 @@ def _logprob_fn(params, data):
 
 
 def _log_setup(snr: float):
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
         print(file=f)
         print(
             f"""Running benchmark 2.8 with configuration as follows
@@ -184,7 +183,6 @@ def _log_setup(snr: float):
 
 # vmap only rng_key
 def do_warmup(rng_key, init_position: dict, data):
-
     _logdensity = partial(_logprob_fn, data=data)
 
     warmup = blackjax.window_adaptation(
@@ -301,7 +299,7 @@ def main():
     filepath = SCRATCH_DIR.joinpath(filename)
     jnp.save(filepath, results)
 
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
         print(file=f)
         print(f"results were saved to {filepath}", file=f)
 
diff --git a/scripts/benchmarks/benchmark_chees1.py b/scripts/benchmarks/benchmark_chees1.py
index 61546a3..601fddd 100755
--- a/scripts/benchmarks/benchmark_chees1.py
+++ b/scripts/benchmarks/benchmark_chees1.py
@@ -19,7 +19,6 @@
 import jax_galsim as xgalsim
 import numpy as np
 import optax
-from jax import jit as jjit
 from jax import random, vmap
 from jax.scipy import stats
 
@@ -87,7 +86,7 @@
 def sample_ball(rng_key, center_params: dict):
     new = {}
     keys = random.split(rng_key, len(center_params.keys()))
-    rng_key_dict = {p: k for p, k in zip(center_params, keys)}
+    rng_key_dict = {p: k for p, k in zip(center_params, keys, strict=False)}
     for p in center_params:
         centr = center_params[p]
         if p == "f":
@@ -133,7 +132,6 @@ def draw_gal(f, hlr, g1, g2, x, y):
 
 
 def _logprob_fn(params, data):
-
     # prior
     prior = jnp.array(0.0, device=GPU)
     for p in ("f", "hlr", "g1", "g2"):  # uniform priors
@@ -153,15 +151,15 @@ def _logprob_fn(params, data):
 
 
 def _log_setup(snr: float):
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
         print(file=f)
         print(
             f"""Running benchmark chees 1 with configuration as follows. Variable number of chains.
-    
+
     The sampler used is NUTS with standard warmup.
 
     TAG: {TAG}
-    SEED: {SEED} 
+    SEED: {SEED}
 
     Overall sampler configuration (fixed):
         n_samples: {N_SAMPLES}
@@ -183,7 +181,7 @@ def _log_setup(snr: float):
     other parameters:
         slen: {SLEN}
         psf_hlr: {PSF_HLR}
-        background: {BACKGROUND}  
+        background: {BACKGROUND}
         snr: {snr}
     """,
             file=f,
@@ -292,7 +290,7 @@ def main():
     jnp.save(filepath, results)
 
     _log_setup(snr)
-    with open(LOG_FILE, "a") as f:
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
         print(file=f)
         print(f"results were saved to {filepath}", file=f)
 
diff --git a/scripts/get_shear_from_post_ellips.py b/scripts/get_shear_from_post_ellips.py
index 27c384d..5d5dcd2 100755
--- a/scripts/get_shear_from_post_ellips.py
+++ b/scripts/get_shear_from_post_ellips.py
@@ -35,7 +35,6 @@ def main(
     trim: int,
     overwrite: bool,
 ):
-
     # directory structure
     dirpath = DATA_DIR / "cache_chains" / tag
     assert dirpath.exists()
@@ -44,9 +43,8 @@ def main(
     old_seed = _extract_seed(e_samples_fname)
     fpath = DATA_DIR / "cache_chains" / tag / f"g_samples_{old_seed}_{seed}.npy"
 
-    if fpath.exists():
-        if not overwrite:
-            raise IOError("overwriting...")
+    if fpath.exists() and not overwrite:
+        raise IOError("overwriting...")
 
     samples_dataset = load_dataset(e_samples_fpath)
     e_post = samples_dataset["e_post"][:, ::trim, :]
diff --git a/scripts/image_shear_gpu_one_galaxy.py b/scripts/image_shear_gpu_one_galaxy.py
index 2376acd..0444337 100644
--- a/scripts/image_shear_gpu_one_galaxy.py
+++ b/scripts/image_shear_gpu_one_galaxy.py
@@ -1,6 +1,5 @@
 #!/usr/bin/env python3
 from functools import partial
-from math import ceil
 
 import click
 import jax.numpy as jnp
@@ -103,7 +102,6 @@ def main(
         slen=slen,
         pixel_scale=pixel_scale,
         fft_size=fft_size,
-        background=background,
     )
     vpipe1 = vmap(jjit(pipe1), (0, None, 0))
 
@@ -125,7 +123,6 @@ def main(
 
 
 def main():
-
     pipe1 = partial(
         pipeline_toy_ellips_samples,
         g1=g1,
diff --git a/scripts/mp_toy_shear_cpu.py b/scripts/mp_toy_shear_cpu.py
index 101fffb..05b3392 100755
--- a/scripts/mp_toy_shear_cpu.py
+++ b/scripts/mp_toy_shear_cpu.py
@@ -66,7 +66,7 @@ def main(
         sigma_e=shape_noise,
         n_samples=n_samples_shear,
     )
-    g_samples_list = pool.starmap(task2, zip(seeds, e_post_list))
+    g_samples_list = pool.starmap(task2, zip(seeds, e_post_list, strict=False))
     print("INFO: Shear samples obtained")
 
     print("INFO: Saving shear samples to disk...")
diff --git a/scripts/slurm/slurm_job.py b/scripts/slurm/slurm_job.py
index 967d693..c35b7ba 100755
--- a/scripts/slurm/slurm_job.py
+++ b/scripts/slurm/slurm_job.py
@@ -27,7 +27,7 @@ def setup_sbatch_job_gpu(
     job_dir = Path(JOB_DIR)
     jobfile = job_dir.joinpath(jobfile_name)
 
-    with open(jobfile, "w") as f:
+    with open(jobfile, "w", encoding="utf-8") as f:
         f.writelines(
             "#!/bin/bash\n"
             f"#SBATCH --job-name={jobname}\n"
diff --git a/scripts/slurm/slurm_toy_shear_gpu.py b/scripts/slurm/slurm_toy_shear_gpu.py
index c5148a9..3a386a4 100755
--- a/scripts/slurm/slurm_toy_shear_gpu.py
+++ b/scripts/slurm/slurm_toy_shear_gpu.py
@@ -44,7 +44,6 @@ def main(
     add_extra: bool,
     qos: str,
 ):
-
     tagpath = DATA_DIR / "cache_chains" / jobname
     if not add_extra:
         assert not tagpath.exists()
@@ -66,7 +65,7 @@ def main(
     )
 
     # append to jobfile the  commands.
-    with open(jobfile, "a") as f:
+    with open(jobfile, "a", encoding="utf-8") as f:
         f.write("\n")
 
     for ii in range(4):
@@ -74,13 +73,13 @@ def main(
         cmd = base_cmd.format(seed=cmd_seed)
         srun_cmd = f"srun --exact -u -n 1 -c 1 --gpus-per-task 1 --mem-per-gpu={mem_per_gpu} {cmd}  &\n"
 
-        with open(jobfile, "a") as f:
+        with open(jobfile, "a", encoding="utf-8") as f:
             f.write(srun_cmd)
 
-    with open(jobfile, "a") as f:
+    with open(jobfile, "a", encoding="utf-8") as f:
         f.write("\nwait")
 
-    subprocess.run(f"sbatch {jobfile.as_posix()}", shell=True)
+    subprocess.run(f"sbatch {jobfile.as_posix()}", shell=True, check=False)
 
 
 if __name__ == "__main__":
diff --git a/tests/test_shear_inference.py b/tests/test_shear_inference.py
index bb5f497..1c9786f 100644
--- a/tests/test_shear_inference.py
+++ b/tests/test_shear_inference.py
@@ -4,13 +4,12 @@
 import pytest
 from jax import random
 
-from scripts.get_shear_from_post_ellips import pipeline_shear_inference
-from scripts.get_toy_ellip_samples import pipeline_toy_ellips_samples
+from bpd.pipelines.shear_inference import pipeline_shear_inference
+from bpd.pipelines.toy_ellips import pipeline_toy_ellips_samples
 
 
 @pytest.mark.parametrize("seed", [1234, 4567])
 def test_shear_inference_toy_ellipticities(seed):
-
     key = random.key(seed)
     k1, k2 = random.split(key)
 
diff --git a/tests/test_shear_trans.py b/tests/test_shear_trans.py
index b0641fe..93726f3 100644
--- a/tests/test_shear_trans.py
+++ b/tests/test_shear_trans.py
@@ -14,7 +14,6 @@
 
 
 def test_scalar_inverse():
-
     # scalar version
     ellips = (0.0, 0.1, 0.2, -0.1, -0.2)
     shears = (0.0, -0.01, 0.01, -0.02, 0.02)