Update pre commit

.pre-commit-config.yaml

@@ -1,22 +1,17 @@
 repos:
-  - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 23.9.1
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: "v0.12.3"
     hooks:
-      - id: black
-        language_version: python3.12
+      - id: ruff-format
+      - id: ruff-check
+        args: ["--fix", "--show-fixes"]
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.7.0
+    rev: 1.9.1
     hooks:
-      - id: nbqa-black
-        additional_dependencies: [black==23.9.1]
-      - id: nbqa-pyupgrade
-        additional_dependencies: [pyupgrade==2.7.3]
-  - repo: https://github.com/pycqa/flake8
-    rev: 6.1.0
-    hooks:
-      - id: flake8
-        args: ["--max-line-length=88", "--extend-ignore=E203"]
+      - id: nbqa-ruff-format
+        additional_dependencies: [ruff]
+
   - repo: https://github.com/kynan/nbstripout
-    rev: 0.6.0
+    rev: 0.8.1
     hooks:
       - id: nbstripout

README.md

@@ -60,8 +60,9 @@ mamba activate toolbox
 
 
 ## Working with git
-We are using `black` and `nbqa-black` as auto-formatters to ensure code quality.
-To make sure these tools are running every time you make a commit, set up our
+We are using `ruff` as auto-formatter and linter, and `nbqa-ruff-format` as auto-formatter
+for notebooks to ensure code quality. To make sure these tools are running every
+time you make a commit, set up our
 ``pre-commit hook`` via
 ```
 $ pre-commit install
@@ -71,10 +72,10 @@ reject a commit if any of the checks fail. Any failing checks can then be solved
 by fixing the issues reported by the `pre-commit hook`.
 
 
-We use the github workflow in this repository, see <https://guides.github.com/introduction/flow/>.
+We use the GitHub workflow in this repository, see <https://guides.github.com/introduction/flow/>.
 In short, to contribute:
 
 1. Create a new branch and switch to it using `git switch -c <name>`
 1. Make changes and commit
 1. Push the Branch using `git push -u origin <name>`
-1. Open a Pull Request on github.
+1. Open a Pull Request on GitHub.

common/crop.py

@@ -6,7 +6,7 @@
 from shlex import join
 
 if len(sys.argv) < 3:
-    print("Usage: {} in.crop out.pdf".format(sys.argv[0]))
+    print(f"Usage: {sys.argv[0]} in.crop out.pdf")
     exit(1)
 
 pdfcrop = os.path.dirname(os.path.abspath(__file__)) + "/pdfcrop2.pl"
@@ -15,8 +15,9 @@
 in_file = sys.argv[1]
 out_file = sys.argv[2]
 
-s = open(in_file, "r").read()
-s = s.splitlines()
+with open(in_file) as f:
+    s = f.read()
+    s = s.splitlines()
 
 source = s[0]
 page = s[1]
@@ -26,7 +27,7 @@
 if len(s) > 3:
     flags = s[3]
     flags = flags.split()
-    auto = not "noauto" in flags
+    auto = "noauto" not in flags
 
 cmd0 = ["pdfseparate", "-f", page, "-l", page, source, out_file]
 print(join(cmd0))

exercises-latex/13-python/loesung.py

@@ -1,13 +1,14 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import uncertainties.unumpy as unp
+from curve_fit import ucurve_fit
 from uncertainties.unumpy import (
     nominal_values as noms,
+)
+from uncertainties.unumpy import (
     std_devs as stds,
 )
 
-from curve_fit import ucurve_fit
-
 
 def make_qty(num, unit, exp="", figures=None):
     """Format an uncertainties ufloat as a \qty quantity"""
@@ -18,7 +19,7 @@ def make_qty(num, unit, exp="", figures=None):
     else:
         x = "{0:.{1:}f}".format(num, figures)
 
-    return r"\qty{{{}{}}}{{{}}}".format(x, exp, unit)
+    return rf"\qty{{{x}{exp}}}{{{unit}}}"
 
 
 t, U, U_err = np.genfromtxt("data.txt", unpack=True)
@@ -72,7 +73,7 @@ def f(t, a, b, c, d):
     t \mathbin{/} \unit{\milli\second} & \SetCell[c=2]{c} U \mathbin{/} \unit{\kilo\volt} & &
     t \mathbin{/} \unit{\milli\second} & \SetCell[c=2]{c} U \mathbin{/} \unit{\kilo\volt} & \\
     \midrule
-"""
+"""  # noqa: E501
 
 table_footer = r"""    \bottomrule
   \end{tblr}
@@ -84,7 +85,7 @@ def f(t, a, b, c, d):
 
 with open("build/loesung-table.tex", "w") as f:
     f.write(table_header)
-    for row in zip(t1, U1, t2, U2):
+    for row in zip(t1, U1, t2, U2, strict=False):
         f.write(row_template.format(*row))
         f.write("\n")
     f.write(table_footer)

exercises-latex/13-python/vorlage.py

@@ -1,13 +1,8 @@
-import matplotlib.pyplot as plt
 import numpy as np
-import uncertainties.unumpy as unp
 from uncertainties.unumpy import (
-    nominal_values as noms,
     std_devs as stds,
 )
 
-from curve_fit import ucurve_fit
-
 
 def make_qty(num, unit, exp="", figures=None):
     """Format an uncertainties ufloat as a \qty quantity"""
@@ -18,4 +13,4 @@ def make_qty(num, unit, exp="", figures=None):
     else:
         x = "{0:.{1:}f}".format(num, figures)
 
-    return r"\qty{{{}{}}}{{{}}}".format(x, exp, unit)
+    return rf"\qty{{{x}{exp}}}{{{unit}}}"

exercises-toolbox/1-python/5-readwrite/loesung1.py

@@ -6,6 +6,6 @@
 else:
     filename = "test.txt"
 
-with open(filename, "r") as f:
+with open(filename) as f:
     print(f.read())
 # end solution

exercises-toolbox/1-python/6-wordcount/loesung3.py

@@ -7,5 +7,5 @@
 counts = Counter(words)
 
 for key, count in counts.most_common(20):
-    print("{}: {}".format(key, count))
+    print(f"{key}: {count}")
 # end solution

exercises-toolbox/1-python/7-fstrings/loesung.py

@@ -36,7 +36,7 @@
 # begin solution
 print()  # Für den Abstand zur letzten Lösung
 # end solution
-for metal, mass in zip(metals, masses):
+for metal, mass in zip(metals, masses, strict=False):
     print()
     # begin solution
     print(f"{metal}: {mass}")
@@ -51,14 +51,14 @@
 # begin solution
 # Für die 4.Aufgabe:
 print()  # Für den Abstand zur letzten Lösung
-for metal, mass in zip(metals, masses):
+for metal, mass in zip(metals, masses, strict=False):
     print(f"{metal}: {mass:0.2f}")
 
 
 # Zum Knobeln für Interessierte:
 # Wie funktioniert das hier?
 print()  # Für den Abstand zur letzten Lösung
-for metal, mass in zip(metals, masses):
+for metal, mass in zip(metals, masses, strict=False):
     offset = 11 - len(metal)
     print(f"{metal}:", f"{mass:>{offset}.2f}")
 # end solution

exercises-toolbox/2-numpy/1-arrays/loesung.py

@@ -18,13 +18,13 @@
 arrays = [a, b, c, d, e, f, g0, g1, h]
 
 print("Aufgabe 1)")
-for name, array in zip(array_names, arrays):
+for name, array in zip(array_names, arrays, strict=False):
     print(f"Array {name}: {array}")
 
 
 # Aufgabe 2)
 print("\nAufgabe 2)")
-for name, array in zip(array_names, arrays):
+for name, array in zip(array_names, arrays, strict=False):
     print(f"Array {name}")
     print(f"\t len({name}): {len(array)}")
     print(f"\t {name}.shape: {array.shape}")

exercises-toolbox/2-numpy/2-indexing/loesung.py

@@ -1,8 +1,7 @@
 #! /usr/bin/env python
-# encoding: utf-8
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 field = np.array(
     [

exercises-toolbox/2-numpy/5-functions/loesung.py

@@ -1,5 +1,4 @@
 #! /usr/bin/env python
-# encoding: utf-8
 
 import numpy as np
 

exercises-toolbox/3-matplotlib/6/loesung.py

@@ -1,6 +1,6 @@
 # begin solution
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 x = np.linspace(0, 1, 100)
 

exercises-toolbox/3-matplotlib/7/loesung.py

@@ -1,6 +1,6 @@
 # begin solution
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 x = np.linspace(0, 2 * np.pi, 100)
 

exercises-toolbox/4-scipy/3-polyfit/loesung.py

@@ -1,6 +1,6 @@
 # begin solution
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 # Generate data
 rng = np.random.default_rng(210)
@@ -21,7 +21,7 @@ def f(x, a, b, c):
 parameters, covariance_matrix = np.polyfit(x, y, deg=2, cov=True)
 uncertainties = np.sqrt(np.diag(covariance_matrix))
 
-for name, value, unc in zip("abc", parameters, uncertainties):
+for name, value, unc in zip("abc", parameters, uncertainties, strict=False):
     print(f"{name} = {value:.3f} ± {unc:.3f}")
 
 fig = plt.figure(layout="constrained")

exercises-toolbox/4-scipy/4-curve_fit/loesung.py

@@ -1,5 +1,5 @@
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 from scipy.optimize import curve_fit
 
 # begin solution

exercises-toolbox/4-scipy/5-peakdetect/loesung.py

@@ -1,7 +1,7 @@
+import matplotlib.pyplot as plt
 import numpy as np
 from scipy.optimize import curve_fit
 from scipy.signal import find_peaks
-import matplotlib.pyplot as plt
 
 # begin solution
 

exercises-toolbox/4-scipy/6-beugung/loesung.py

@@ -1,6 +1,6 @@
+import matplotlib.pyplot as plt
 import numpy as np
 from scipy.optimize import curve_fit
-import matplotlib.pyplot as plt
 
 
 def theory(phi, A0, b):

exercises-toolbox/5-uncertainties/1-formel/loesung.py

@@ -1,7 +1,7 @@
 # begin solution
+from sympy import sin, var
 from uncertainties import ufloat
 from uncertainties.unumpy import sin as usin
-from sympy import var, sin
 
 x = ufloat(4.56, 0.2)
 y = ufloat(2.11, 0.3)

exercises-toolbox/5-uncertainties/3-curve_fit/loesung.py

@@ -39,7 +39,7 @@ def f(x, a, b, c):
 y = unp.uarray(y_0, y_err)
 params = ucurve_fit(f, x, y)
 print("a * cos(x * b) + c")
-for char, p in zip("abc", params):
+for char, p in zip("abc", params, strict=False):
     print(f"{char} = {p}")
 
 fig = plt.figure(layout="constrained")

exercises-toolbox/5-uncertainties/4-linleastsquares/loesung.py

@@ -28,7 +28,7 @@ def linleastsquares(functions, x_values, y_values):
 
 
 def linear_combination(x, functions, params):
-    return np.sum([p * f(x) for p, f in zip(params, functions)], axis=0)
+    return np.sum([p * f(x) for p, f in zip(params, functions, strict=False)], axis=0)
 
 
 if __name__ == "__main__":

exercises-toolbox/7-make/auswertung-bonus-loesung.py

@@ -1,6 +1,6 @@
+import matplotlib.pyplot as plt
 import numpy as np
 from scipy.optimize import curve_fit
-import matplotlib.pyplot as plt
 
 
 def theory(phi, A0, b):

exercises-toolbox/7-make/auswertung.py

@@ -1,6 +1,6 @@
+import matplotlib.pyplot as plt
 import numpy as np
 from scipy.optimize import curve_fit
-import matplotlib.pyplot as plt
 
 
 def theory(phi, A0, b):

exercises-toolbox/8-all/303_Der_Lock-In-Verstaerker/loesung.py

@@ -1,9 +1,8 @@
 # begin solution
-import numpy as np
-from uncertainties.unumpy import nominal_values as noms
 import matplotlib.pyplot as plt
-
+import numpy as np
 from curve_fit import ucurve_fit
+from uncertainties.unumpy import nominal_values as noms
 
 
 def Ur(r, A, B, C):

exercises-toolbox/8-all/354_Gedaempfte_und_erzwungene_Schwingungen/loesung.py

@@ -1,6 +1,6 @@
 # begin solution
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 L, C, R = np.genfromtxt("geraetedaten.txt", unpack=True)
 L *= 1e-3

exercises-toolbox/8-all/702_Aktivierung_mit_Neutronen/loesung.py

@@ -1,11 +1,12 @@
-from linregress import ulinregress
+import matplotlib.pyplot as plt
 
 # begin solution
 import numpy as np
 import uncertainties as unc
 import uncertainties.unumpy as unp
-from uncertainties.unumpy import nominal_values as noms, std_devs as stds
-import matplotlib.pyplot as plt
+from linregress import ulinregress
+from uncertainties.unumpy import nominal_values as noms
+from uncertainties.unumpy import std_devs as stds
 
 Delta_t_0 = np.genfromtxt("Delta_t_0.txt")
 N_0 = np.genfromtxt("N_0.txt")

exercises-toolbox/8-all/corona/loesung.py

@@ -1,5 +1,5 @@
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 data = np.genfromtxt(
     "./FB53-Coronafallzahlen.csv",