diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
index 6ec1cfe8..e708fcb4 100644
--- a/.github/workflows/lint.yml
+++ b/.github/workflows/lint.yml
@@ -8,8 +8,8 @@ jobs:
       - uses: chartboost/ruff-action@v1
         with:
           src: './pyenzyme'
-          version: 0.15.22  # keep in sync with .pre-commit-config.yaml
+          version: 0.16.10  # keep in sync with .pre-commit-config.yaml
       - uses: chartboost/ruff-action@v1
         with:
           src: './tests'
-          version: 0.15.22
+          version: 0.16.10
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 6fc4ef38..75d7fdcd 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -7,7 +7,7 @@ repos:
       - id: uv-lock
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.15.22
+    rev: v0.16.10
     hooks:
       # Same lint gate CI runs (lint.yml lints ./pyenzyme and ./tests only).
       - id: ruff-check
diff --git a/pyenzyme/__init__.py b/pyenzyme/__init__.py
index 73ba22b5..7b0ba12a 100644
--- a/pyenzyme/__init__.py
+++ b/pyenzyme/__init__.py
@@ -28,23 +28,23 @@
 write_enzymeml = EnzymeMLHandler.write_enzymeml
 
 __all__ = [
+    "EnzymeMLHandler",
+    "EnzymeMLSuite",
     "UnitDefinition",
     "UnitType",
-    "EnzymeMLSuite",
-    "EnzymeMLHandler",
+    "compose",
     "from_csv",
     "from_dataframe",
     "from_excel",
     "from_sbml",
+    "group_measurements",
+    "plot",
+    "plot_interactive",
     "read_enzymeml",
+    "summary",
     "to_pandas",
     "to_sbml",
     "write_enzymeml",
-    "compose",
-    "plot",
-    "plot_interactive",
-    "summary",
-    "group_measurements",
 ]
 
 __version__ = version("pyenzyme")
diff --git a/pyenzyme/composer.py b/pyenzyme/composer.py
index 21db6789..9f8eedc4 100644
--- a/pyenzyme/composer.py
+++ b/pyenzyme/composer.py
@@ -1,4 +1,5 @@
-from typing import List, Optional, Tuple, Callable, Any
+from collections.abc import Callable
+from typing import Any
 
 from rich.console import Console
 
@@ -28,11 +29,11 @@
 
 def compose(
     name: str,
-    proteins: Optional[list[str]] = None,
-    small_molecules: Optional[list[str]] = None,
-    reactions: Optional[list[str]] = None,
-    vessel: Optional[v2.Vessel] = None,
-    id_mapping: Optional[dict[str, str]] = None,
+    proteins: list[str] | None = None,
+    small_molecules: list[str] | None = None,
+    reactions: list[str] | None = None,
+    vessel: v2.Vessel | None = None,
+    id_mapping: dict[str, str] | None = None,
 ) -> v2.EnzymeMLDocument:
     """
     Compose an EnzymeML document from proteins, small molecules, and reactions.
@@ -162,7 +163,7 @@ def _fetch_small_molecule(small_molecule_id: str) -> v2.SmallMolecule:
     )
 
 
-def _fetch_reaction(reaction_id: str) -> Tuple[v2.Reaction, List[v2.SmallMolecule]]:
+def _fetch_reaction(reaction_id: str) -> tuple[v2.Reaction, list[v2.SmallMolecule]]:
     """
     Fetch reaction information using available fetchers.
 
@@ -179,7 +180,7 @@ def _fetch_reaction(reaction_id: str) -> Tuple[v2.Reaction, List[v2.SmallMolecul
 
 
 def _fetch_with_fetchers(
-    entity_id: str, fetchers: List[Callable], entity_type: str
+    entity_id: str, fetchers: list[Callable], entity_type: str
 ) -> Any:
     """
     Generic function to attempt fetching with multiple fetchers.
@@ -210,7 +211,7 @@ def _fetch_with_fetchers(
     ) from last_error
 
 
-def _remove_duplicates(objects: List[Any]) -> List[Any]:
+def _remove_duplicates(objects: list[Any]) -> list[Any]:
     """
     Remove duplicate objects based on their ID attribute.
 
@@ -235,7 +236,7 @@ def _remove_duplicates(objects: List[Any]) -> List[Any]:
 
 
 def _apply_id_mapping(
-    objects: List[Any],
+    objects: list[Any],
     id_mapping: dict[str, str],
 ) -> dict[str, str]:
     """
diff --git a/pyenzyme/equations/__init__.py b/pyenzyme/equations/__init__.py
index 0965ff95..c1c420fc 100644
--- a/pyenzyme/equations/__init__.py
+++ b/pyenzyme/equations/__init__.py
@@ -1,4 +1,4 @@
-from .math import build_equation, build_equations  # noqa: F401
-from .chem import build_reaction, build_reactions  # noqa: F401
+from .chem import build_reaction, build_reactions
+from .math import build_equation, build_equations
 
 __all__ = ["build_equation", "build_equations", "build_reaction", "build_reactions"]
diff --git a/pyenzyme/equations/math.py b/pyenzyme/equations/math.py
index f5eea3be..ad694242 100644
--- a/pyenzyme/equations/math.py
+++ b/pyenzyme/equations/math.py
@@ -2,10 +2,10 @@
 
 import rich
 from loguru import logger
+from mdmodels.units.unit_definition import UnitDefinition
 from sympy import sympify
 
 from pyenzyme.logging import add_logger
-from mdmodels.units.unit_definition import UnitDefinition
 from pyenzyme.versions.v2 import (
     EnzymeMLDocument,
     Equation,
diff --git a/pyenzyme/fetcher/__init__.py b/pyenzyme/fetcher/__init__.py
index ed1ec769..2c82fe75 100644
--- a/pyenzyme/fetcher/__init__.py
+++ b/pyenzyme/fetcher/__init__.py
@@ -1,13 +1,13 @@
 from .chebi import fetch_chebi
 from .pdb import fetch_pdb
 from .pubchem import fetch_pubchem
-from .uniprot import fetch_uniprot
 from .rhea import fetch_rhea
+from .uniprot import fetch_uniprot
 
 __all__ = [
     "fetch_chebi",
     "fetch_pdb",
     "fetch_pubchem",
-    "fetch_uniprot",
     "fetch_rhea",
+    "fetch_uniprot",
 ]
diff --git a/pyenzyme/fetcher/chebi.py b/pyenzyme/fetcher/chebi.py
index 6e622965..60f312de 100644
--- a/pyenzyme/fetcher/chebi.py
+++ b/pyenzyme/fetcher/chebi.py
@@ -6,7 +6,6 @@
 """
 
 import re
-from typing import List, Optional
 
 import httpx
 from pydantic import BaseModel, ConfigDict, Field
@@ -19,7 +18,7 @@
 class ChEBIError(Exception):
     """Error class for ChEBI-specific errors."""
 
-    def __init__(self, message: str, cause: Optional[Exception] = None):
+    def __init__(self, message: str, cause: Exception | None = None):
         super().__init__(message)
         self.cause = cause
 
@@ -30,19 +29,19 @@ class ChebiSearchSource(BaseModel):
     model_config = ConfigDict(extra="ignore")
 
     chebi_accession: str
-    name: Optional[str] = None
+    name: str | None = None
     ascii_name: str
-    smiles: Optional[str] = None
-    inchi: Optional[str] = None
-    inchikey: Optional[str] = None
-    definition: Optional[str] = None
-    formula: Optional[str] = None
-    charge: Optional[int] = None
-    mass: Optional[float] = None
-    monoisotopicmass: Optional[float] = None
-    stars: Optional[int] = None
-    default_structure: Optional[int] = None
-    structures: Optional[List[int]] = None
+    smiles: str | None = None
+    inchi: str | None = None
+    inchikey: str | None = None
+    definition: str | None = None
+    formula: str | None = None
+    charge: int | None = None
+    mass: float | None = None
+    monoisotopicmass: float | None = None
+    stars: int | None = None
+    default_structure: int | None = None
+    structures: list[int] | None = None
 
 
 class ChebiSearchResult(BaseModel):
@@ -56,7 +55,7 @@ class ChebiSearchResult(BaseModel):
 class ChebiSearchResponse(BaseModel):
     """Search response structure from ChEBI search API."""
 
-    results: List[ChebiSearchResult]
+    results: list[ChebiSearchResult]
     total: int
     number_pages: int
 
@@ -105,14 +104,14 @@ def get_entry_by_id(self, chebi_id: str) -> ChebiSearchSource:
                 except Exception as e:
                     if isinstance(e, ChEBIError):
                         raise e
-                    raise ChEBIError(f"Failed to parse ChEBI response: {str(e)}", e)
+                    raise ChEBIError(f"Failed to parse ChEBI response: {e!s}", e)
             else:
                 raise ChEBIError(f"HTTP {response.status_code}: {response.text}")
 
         except httpx.HTTPStatusError as e:
-            raise ChEBIError(f"Failed to fetch ChEBI ID {chebi_id}: {str(e)}", e)
+            raise ChEBIError(f"Failed to fetch ChEBI ID {chebi_id}: {e!s}", e)
 
-    def get_entries_batch(self, chebi_ids: List[str]) -> List[ChebiSearchSource]:
+    def get_entries_batch(self, chebi_ids: list[str]) -> list[ChebiSearchSource]:
         """
         Fetch multiple ChEBI entries by their IDs using the search API.
 
@@ -136,13 +135,13 @@ def get_entries_batch(self, chebi_ids: List[str]) -> List[ChebiSearchSource]:
                 results.append(entry)
             except ChEBIError as e:
                 # Continue with other IDs even if one fails
-                raise ChEBIError(f"Failed to fetch ChEBI ID {chebi_id}: {str(e)}", e)
+                raise ChEBIError(f"Failed to fetch ChEBI ID {chebi_id}: {e!s}", e)
 
         return results
 
     def search_entries(
-        self, query: str, size: Optional[int] = None, page: int = 1
-    ) -> List[ChebiSearchSource]:
+        self, query: str, size: int | None = None, page: int = 1
+    ) -> list[ChebiSearchSource]:
         """
         Search for ChEBI entries by query string.
 
@@ -178,14 +177,14 @@ def search_entries(
                 except Exception as e:
                     if isinstance(e, ChEBIError):
                         raise e
-                    raise ChEBIError(f"Invalid search response format: {str(e)}", e)
+                    raise ChEBIError(f"Invalid search response format: {e!s}", e)
             else:
                 raise ChEBIError(
                     f"Search failed: HTTP {response.status_code}: {response.text}"
                 )
 
         except httpx.HTTPStatusError as e:
-            raise ChEBIError(f"Failed to search ChEBI: {str(e)}", e)
+            raise ChEBIError(f"Failed to search ChEBI: {e!s}", e)
 
 
 def process_search_result(source: ChebiSearchSource) -> v2.SmallMolecule:
@@ -227,8 +226,8 @@ def process_search_result(source: ChebiSearchSource) -> v2.SmallMolecule:
 
 def fetch_chebi(
     chebi_id: str,
-    smallmol_id: Optional[str] = None,
-    vessel_id: Optional[str] = None,
+    smallmol_id: str | None = None,
+    vessel_id: str | None = None,
 ) -> v2.SmallMolecule:
     """
     Fetch a ChEBI entry by ID and convert it to a SmallMolecule object.
@@ -264,7 +263,7 @@ def fetch_chebi(
             raise ValueError(str(e)) from e
 
 
-def fetch_chebi_batch(chebi_ids: List[str]) -> List[v2.SmallMolecule]:
+def fetch_chebi_batch(chebi_ids: list[str]) -> list[v2.SmallMolecule]:
     """
     Fetch multiple ChEBI entries by their IDs and convert them to SmallMolecule objects.
 
@@ -287,7 +286,7 @@ def fetch_chebi_batch(chebi_ids: List[str]) -> List[v2.SmallMolecule]:
     return [process_search_result(source) for source in chebi_sources]
 
 
-def search_chebi(query: str, size: Optional[int] = None) -> List[v2.SmallMolecule]:
+def search_chebi(query: str, size: int | None = None) -> list[v2.SmallMolecule]:
     """
     Search for ChEBI entries by query string.
 
diff --git a/pyenzyme/fetcher/pdb.py b/pyenzyme/fetcher/pdb.py
index 79146942..1075ec89 100644
--- a/pyenzyme/fetcher/pdb.py
+++ b/pyenzyme/fetcher/pdb.py
@@ -5,7 +5,7 @@
 Protein Data Bank by ID and map it to the PyEnzyme data model (v2).
 """
 
-from typing import Any, Dict, List, Optional
+from typing import Any
 
 import httpx
 from pydantic import BaseModel, Field
@@ -19,42 +19,42 @@
 class Citation(BaseModel):
     """Model for PDB citation data"""
 
-    title: Optional[str] = None
-    authors: Optional[List[str]] = None
-    journal_name: Optional[str] = Field(default=None, alias="journal_abbrev")
-    year: Optional[int] = None
-    doi: Optional[str] = None
-    pubmed_id: Optional[int] = Field(default=None, alias="pdbx_database_id_PubMed")
+    title: str | None = None
+    authors: list[str] | None = None
+    journal_name: str | None = Field(default=None, alias="journal_abbrev")
+    year: int | None = None
+    doi: str | None = None
+    pubmed_id: int | None = Field(default=None, alias="pdbx_database_id_PubMed")
 
 
 class StructInfo(BaseModel):
     """Model for PDB structure information"""
 
-    title: Optional[str] = None
-    experimental_method: Optional[str] = None
-    resolution: Optional[float] = None
+    title: str | None = None
+    experimental_method: str | None = None
+    resolution: float | None = None
 
 
 class EntityInfo(BaseModel):
     """Model for PDB entity information"""
 
-    description: Optional[str] = None
-    polymer_type: Optional[str] = None
-    ec_number: Optional[str] = None
-    sequence: Optional[str] = None
-    organism_scientific_name: Optional[str] = None
-    organism_taxid: Optional[int] = None
+    description: str | None = None
+    polymer_type: str | None = None
+    ec_number: str | None = None
+    sequence: str | None = None
+    organism_scientific_name: str | None = None
+    organism_taxid: int | None = None
 
 
 class PDBResponse(BaseModel):
     """Model for PDB API response"""
 
     pdb_id: str
-    citation: List[Citation] = []
-    struct: Optional[StructInfo] = None
-    polymer_entities: Optional[Dict[str, EntityInfo]] = None
-    rcsb_primary_citation: Optional[Dict[str, Any]] = None
-    rcsb_entry_info: Optional[Dict[str, Any]] = None
+    citation: list[Citation] = []
+    struct: StructInfo | None = None
+    polymer_entities: dict[str, EntityInfo] | None = None
+    rcsb_primary_citation: dict[str, Any] | None = None
+    rcsb_entry_info: dict[str, Any] | None = None
 
 
 class PDBClient:
@@ -62,7 +62,7 @@ class PDBClient:
 
     BASE_URL = "https://data.rcsb.org/rest/v1/core"
 
-    def get_entry_by_id(self, pdb_id: str) -> Optional[PDBResponse]:
+    def get_entry_by_id(self, pdb_id: str) -> PDBResponse | None:
         """
         Fetch a PDB entry by its ID.
 
@@ -139,9 +139,9 @@ def get_entry_by_id(self, pdb_id: str) -> Optional[PDBResponse]:
             )
 
         except ValueError as e:
-            raise ValueError(f"Failed to retrieve PDB entry: {str(e)}")
+            raise ValueError(f"Failed to retrieve PDB entry: {e!s}")
         except ConnectionError as e:
-            raise ValueError(f"Connection to PDB server failed: {str(e)}")
+            raise ValueError(f"Connection to PDB server failed: {e!s}")
 
     def _fetch_json(self, url: str) -> dict:
         """
@@ -170,16 +170,16 @@ def _fetch_json(self, url: str) -> dict:
                 )
 
         except httpx.HTTPStatusError as e:
-            raise ConnectionError(f"Connection failed: {str(e)}")
+            raise ConnectionError(f"Connection failed: {e!s}")
         except ValueError as e:
-            raise ValueError(f"Failed to parse response: {str(e)}")
+            raise ValueError(f"Failed to parse response: {e!s}")
 
 
 def fetch_pdb(
     pdb_id: str,
-    protein_id: Optional[str] = None,
+    protein_id: str | None = None,
     entity_id: str = "1",
-    vessel_id: Optional[str] = None,
+    vessel_id: str | None = None,
 ) -> v2.Protein:
     """
     Fetch a PDB entry by ID and convert it to a Protein object.
diff --git a/pyenzyme/fetcher/pubchem.py b/pyenzyme/fetcher/pubchem.py
index d8be93e1..b4f409a3 100644
--- a/pyenzyme/fetcher/pubchem.py
+++ b/pyenzyme/fetcher/pubchem.py
@@ -1,4 +1,4 @@
-from typing import ClassVar, Optional
+from typing import ClassVar
 
 import httpx
 from pydantic import BaseModel, Field, field_validator
@@ -15,7 +15,7 @@ class PCUrn(BaseModel):
     """
 
     label: str
-    name: Optional[str] = Field(default=None)
+    name: str | None = Field(default=None)
 
 
 class PCProp(BaseModel):
@@ -104,7 +104,7 @@ def from_cid(cid: int) -> PubChemQuery:
     def extract_value(
         query: PCCompound,
         label: str,
-        name: Optional[str] = None,
+        name: str | None = None,
     ) -> float | int | str | None:
         """
         Extracts a specific property value from a PubChem compound.
@@ -149,8 +149,8 @@ def extract_by_preference(
 
 def fetch_pubchem(
     cid: str,
-    smallmol_id: Optional[str] = None,
-    vessel_id: Optional[str] = None,
+    smallmol_id: str | None = None,
+    vessel_id: str | None = None,
 ) -> v2.SmallMolecule:
     """
     Fetches a compound from PubChem by CID and converts it to a SmallMolecule object.
diff --git a/pyenzyme/fetcher/rhea.py b/pyenzyme/fetcher/rhea.py
index a205bf70..6ee225cf 100644
--- a/pyenzyme/fetcher/rhea.py
+++ b/pyenzyme/fetcher/rhea.py
@@ -7,7 +7,7 @@
 
 import re
 from io import StringIO
-from typing import ClassVar, List, Optional, Tuple
+from typing import ClassVar
 
 import httpx
 import pandas as pd
@@ -46,7 +46,7 @@ class RheaQuery(BaseModel):
     """
 
     count: int
-    results: List[RheaResult]
+    results: list[RheaResult]
 
 
 class RheaClient(BaseModel):
@@ -65,7 +65,7 @@ class RheaClient(BaseModel):
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
     json_content: RheaResult
-    chebi_ids: List[str]
+    chebi_ids: list[str]
 
     BASE_URL: ClassVar[str] = (
         "https://www.rhea-db.org/rhea/?query=RHEA:{0}&columns=rhea-id,equation,chebi-id&format={1}&limit=10"
@@ -147,8 +147,8 @@ def fetch_json(query: str) -> RheaQuery:
 
 def fetch_rhea(
     rhea_id: str,
-    vessel_id: Optional[str] = None,
-) -> Tuple[v2.Reaction, List[v2.SmallMolecule]]:
+    vessel_id: str | None = None,
+) -> tuple[v2.Reaction, list[v2.SmallMolecule]]:
     """
     Fetch a Rhea entry by ID and convert it to a Reaction object.
 
@@ -227,7 +227,7 @@ def fetch_rhea(
     return reaction, small_molecules
 
 
-def _split_chemical_equation_side(equation_side: str) -> List[str]:
+def _split_chemical_equation_side(equation_side: str) -> list[str]:
     """
     Split a chemical equation side on '+' while respecting parentheses.
 
diff --git a/pyenzyme/fetcher/uniprot.py b/pyenzyme/fetcher/uniprot.py
index fe76b7fb..aee6a83a 100644
--- a/pyenzyme/fetcher/uniprot.py
+++ b/pyenzyme/fetcher/uniprot.py
@@ -5,9 +5,10 @@
 UniProt database by ID and map it to the PyEnzyme data model (v2).
 """
 
+
 import requests
-from typing import List, Optional, Union
 from pydantic import BaseModel, Field, ValidationError
+
 from pyenzyme.fetcher.chebi import process_id
 from pyenzyme.versions import v2
 
@@ -28,21 +29,21 @@ class RecommendedName(BaseModel):
     """Model for a recommended or submitted protein name in UniProt API"""
 
     full_name: ProteinName = Field(alias="fullName")
-    ec_numbers: Optional[List[ECNumber]] = Field(default=None, alias="ecNumbers")
+    ec_numbers: list[ECNumber] | None = Field(default=None, alias="ecNumbers")
 
 
 class ProteinDescription(BaseModel):
     """Model for protein description in UniProt API"""
 
-    recommended_name: Optional[RecommendedName] = Field(
+    recommended_name: RecommendedName | None = Field(
         default=None, alias="recommendedName"
     )
-    submission_names: List[RecommendedName] = Field(
+    submission_names: list[RecommendedName] = Field(
         default_factory=list, alias="submissionNames"
     )
 
     @property
-    def name(self) -> Optional[RecommendedName]:
+    def name(self) -> RecommendedName | None:
         """Recommended name, or the first submission name for unreviewed (TrEMBL) entries."""
         if self.recommended_name:
             return self.recommended_name
@@ -52,8 +53,8 @@ def name(self) -> Optional[RecommendedName]:
 class Organism(BaseModel):
     """Model for organism in UniProt API"""
 
-    scientific_name: Optional[str] = Field(default=None, alias="scientificName")
-    taxon_id: Optional[int] = Field(default=None, alias="taxonId")
+    scientific_name: str | None = Field(default=None, alias="scientificName")
+    taxon_id: int | None = Field(default=None, alias="taxonId")
 
 
 class Sequence(BaseModel):
@@ -61,7 +62,7 @@ class Sequence(BaseModel):
 
     value: str
     length: int
-    mol_weight: Optional[int] = Field(default=None, alias="molWeight")
+    mol_weight: int | None = Field(default=None, alias="molWeight")
 
 
 class UniProtEntry(BaseModel):
@@ -71,10 +72,10 @@ class UniProtEntry(BaseModel):
 
     id: str = Field(alias="uniProtkbId")
     protein_description: ProteinDescription = Field(alias="proteinDescription")
-    organism: Optional[Organism] = None
-    sequence: Optional[Sequence] = None
+    organism: Organism | None = None
+    sequence: Sequence | None = None
     accession: str = Field(alias="primaryAccession")
-    annotation_score: Optional[float] = Field(default=None, alias="annotationScore")
+    annotation_score: float | None = Field(default=None, alias="annotationScore")
 
 
 class UniProtClient:
@@ -86,7 +87,7 @@ def __init__(self):
         """Initialize the UniProt client."""
         pass
 
-    def get_entry_by_id(self, uniprot_id: str) -> Union[UniProtEntry, None]:
+    def get_entry_by_id(self, uniprot_id: str) -> UniProtEntry | None:
         """
         Fetch a UniProt entry by its ID.
 
@@ -135,8 +136,8 @@ def get_entry_by_id(self, uniprot_id: str) -> Union[UniProtEntry, None]:
 
 def fetch_uniprot(
     uniprot_id: str,
-    protein_id: Optional[str] = None,
-    vessel_id: Optional[str] = None,
+    protein_id: str | None = None,
+    vessel_id: str | None = None,
 ) -> v2.Protein:
     """
     Fetch a UniProt entry by ID and convert it to a Protein object.
diff --git a/pyenzyme/logging.py b/pyenzyme/logging.py
index 781ef209..5ee333e1 100644
--- a/pyenzyme/logging.py
+++ b/pyenzyme/logging.py
@@ -1,4 +1,5 @@
 import sys
+
 from loguru import logger
 
 
@@ -31,11 +32,11 @@ def add_logger(
 
     """
     format = (
-        "  <cyan>%s</cyan>\t{module: >10}\t<level>{level}</level>: {message}" % name
+        f"  <cyan>{name}</cyan>\t{{module: >10}}\t<level>{{level}}</level>: {{message}}"
     )
 
     if isinstance(channel, str):
-        format = "{time:YYYY-MM-DD HH:mm:ss} %s {level}: {message}" % name
+        format = f"{{time:YYYY-MM-DD HH:mm:ss}} {name} {{level}}: {{message}}"
 
     logger.remove()
     logger.add(
diff --git a/pyenzyme/petab/baserow.py b/pyenzyme/petab/baserow.py
index cc982db3..2b6108cb 100644
--- a/pyenzyme/petab/baserow.py
+++ b/pyenzyme/petab/baserow.py
@@ -1,4 +1,5 @@
 from typing import Any
+
 from pydantic import BaseModel, ConfigDict
 
 
diff --git a/pyenzyme/petab/conditions.py b/pyenzyme/petab/conditions.py
index 0953c9b8..be77b1d2 100644
--- a/pyenzyme/petab/conditions.py
+++ b/pyenzyme/petab/conditions.py
@@ -1,7 +1,9 @@
-from typing import Dict, Any
+from typing import Any
+
 from pydantic import Field
 
 from pyenzyme.versions import v2
+
 from .baserow import BaseRow
 
 
@@ -22,7 +24,7 @@ class ConditionRow(BaseRow):
     condition_name: str = Field(alias="conditionName")
     species: dict[str, float] = Field(default_factory=dict)
 
-    def to_row(self) -> Dict[str, Any]:
+    def to_row(self) -> dict[str, Any]:
         """
         Converts the condition to a dictionary suitable for a PEtab conditions table row.
 
diff --git a/pyenzyme/petab/io.py b/pyenzyme/petab/io.py
index 8fea2dd7..2614d468 100644
--- a/pyenzyme/petab/io.py
+++ b/pyenzyme/petab/io.py
@@ -1,5 +1,4 @@
 from pathlib import Path
-from typing import Union
 
 import pandas as pd
 import yaml
@@ -21,7 +20,7 @@
 SBML_FILENAME = "model.xml"
 
 
-def to_petab(doc: v2.EnzymeMLDocument, path: Union[Path, str]) -> PEtab:
+def to_petab(doc: v2.EnzymeMLDocument, path: Path | str) -> PEtab:
     """
     Convert an EnzymeML document to a PEtab parameter estimation problem.
 
diff --git a/pyenzyme/petab/measurements.py b/pyenzyme/petab/measurements.py
index 586f46d6..ddc4a46a 100644
--- a/pyenzyme/petab/measurements.py
+++ b/pyenzyme/petab/measurements.py
@@ -1,7 +1,8 @@
-from typing import List, Union
+
 from pydantic import Field
 
 from pyenzyme.versions import v2
+
 from .baserow import BaseRow
 
 
@@ -46,11 +47,11 @@ class MeasurementRow(BaseRow):
     condition_id: str = Field(alias="simulationConditionId")
     measurement: float = Field(alias="measurement")
     time: float = Field(alias="time")
-    observable_parameters: Union[str, float, None] = Field(
+    observable_parameters: str | float | None = Field(
         default=None,
         alias="observableParameters",
     )
-    noise_parameters: Union[str, float, None] = Field(
+    noise_parameters: str | float | None = Field(
         default=None,
         alias="noiseParameters",
     )
@@ -60,7 +61,7 @@ class MeasurementRow(BaseRow):
     @classmethod
     def from_measurements(
         cls, measurements: list[v2.Measurement]
-    ) -> List["MeasurementRow"]:
+    ) -> list["MeasurementRow"]:
         """
         Convert a list of EnzymeML Measurement objects to a list of PEtab MeasurementRow objects.
         """
@@ -71,7 +72,7 @@ def from_measurements(
         ]
 
     @classmethod
-    def from_measurement(cls, measurement: v2.Measurement) -> List["MeasurementRow"]:
+    def from_measurement(cls, measurement: v2.Measurement) -> list["MeasurementRow"]:
         """
         Convert an EnzymeML Measurement object to a list of PEtab MeasurementRow objects.
 
diff --git a/pyenzyme/petab/observables.py b/pyenzyme/petab/observables.py
index 00a5afc1..c1e284fa 100644
--- a/pyenzyme/petab/observables.py
+++ b/pyenzyme/petab/observables.py
@@ -1,8 +1,9 @@
 from enum import Enum
-from typing import List, Optional
+
 from pydantic import ConfigDict, Field
 
 from pyenzyme.versions import v2
+
 from .baserow import BaseRow
 
 
@@ -21,24 +22,24 @@ class ObservableRow(BaseRow):
     model_config = ConfigDict(use_enum_values=True)
 
     observable_id: str = Field(alias="observableId")
-    observable_name: Optional[str] = Field(alias="observableName", default=None)
+    observable_name: str | None = Field(alias="observableName", default=None)
     observable_formula: str = Field(alias="observableFormula")
-    observable_noise: Optional[float] = Field(alias="observableNoise", default=0.0)
+    observable_noise: float | None = Field(alias="observableNoise", default=0.0)
     observable_transformation: Transformation = Field(
         alias="observableTransformation",
         default=Transformation.LIN,
     )
-    noise_formula: Optional[str] = Field(
+    noise_formula: str | None = Field(
         default=None,
         alias="noiseFormula",
     )
-    noise_distribution: Optional[NoiseDistribution] = Field(
+    noise_distribution: NoiseDistribution | None = Field(
         default=None,
         alias="noiseDistribution",
     )
 
     @classmethod
-    def from_enzymeml(cls, enzmldoc: v2.EnzymeMLDocument) -> List["ObservableRow"]:
+    def from_enzymeml(cls, enzmldoc: v2.EnzymeMLDocument) -> list["ObservableRow"]:
         """Extract observable rows from an EnzymeML document.
 
         Collects all species with data across measurements and creates observable rows.
diff --git a/pyenzyme/petab/parameters.py b/pyenzyme/petab/parameters.py
index 108ca9d4..181b6612 100644
--- a/pyenzyme/petab/parameters.py
+++ b/pyenzyme/petab/parameters.py
@@ -1,8 +1,9 @@
 from enum import Enum
-from typing import List, Optional
+
 from pydantic import ConfigDict, Field, field_serializer, field_validator
 
 from pyenzyme.versions import v2
+
 from .baserow import BaseRow
 
 
@@ -47,20 +48,20 @@ class ParameterRow(BaseRow):
     model_config = ConfigDict(use_enum_values=True)
 
     parameter_id: str = Field(alias="parameterId")
-    parameter_name: Optional[str] = Field(alias="parameterName", default=None)
+    parameter_name: str | None = Field(alias="parameterName", default=None)
     parameter_scale: ParameterScale = Field(
         default=ParameterScale.LIN,
         alias="parameterScale",
     )
     lower_bound: float = Field(alias="lowerBound")
     upper_bound: float = Field(alias="upperBound")
-    nominal_value: Optional[float] = Field(alias="nominalValue", default=None)
+    nominal_value: float | None = Field(alias="nominalValue", default=None)
     estimate: bool = Field(alias="estimate", default=True)
     initialization_prior_type: PriorType = Field(
         default=PriorType.PARAMETER_SCALE_UNIFORM,
         alias="initializationPriorType",
     )
-    initialization_prior_parameters: List[float] = Field(
+    initialization_prior_parameters: list[float] = Field(
         default_factory=list,
         alias="initializationPriorParameters",
     )
@@ -68,7 +69,7 @@ class ParameterRow(BaseRow):
         default=PriorType.PARAMETER_SCALE_UNIFORM,
         alias="objectivePriorType",
     )
-    objective_prior_parameters: List[float] = Field(
+    objective_prior_parameters: list[float] = Field(
         default_factory=list,
         alias="objectivePriorParameters",
     )
@@ -77,7 +78,7 @@ class ParameterRow(BaseRow):
         "objective_prior_parameters",
         "initialization_prior_parameters",
     )
-    def serialize_prior_parameters(self, v: List[float]) -> str:
+    def serialize_prior_parameters(self, v: list[float]) -> str:
         """
         Serializes a list of prior parameters into a semicolon-separated string.
 
@@ -95,7 +96,7 @@ def serialize_prior_parameters(self, v: List[float]) -> str:
         mode="before",
     )
     @classmethod
-    def validate_prior_parameters(cls, v: str) -> List[float]:
+    def validate_prior_parameters(cls, v: str) -> list[float]:
         """
         Validates and converts a string of prior parameters into a list of floats.
 
@@ -108,7 +109,7 @@ def validate_prior_parameters(cls, v: str) -> List[float]:
         return [float(x) for x in v.split(";")]
 
     @classmethod
-    def from_parameters(cls, parameters: List[v2.Parameter]) -> List["ParameterRow"]:
+    def from_parameters(cls, parameters: list[v2.Parameter]) -> list["ParameterRow"]:
         """
         Creates a list of ParameterRow objects from a list of PyEnzyme Parameter objects.
         """
diff --git a/pyenzyme/petab/petab.py b/pyenzyme/petab/petab.py
index b0b36a49..b33a7d8b 100644
--- a/pyenzyme/petab/petab.py
+++ b/pyenzyme/petab/petab.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from pathlib import Path
-from typing import List, Union, Optional
+
 from pydantic import BaseModel, ConfigDict, Field
 
 
@@ -19,12 +19,12 @@ class PEtab(BaseModel):
         description="Version of the PEtab format. Only value 1 is supported.",
     )
 
-    parameter_file: Union[Path, List[Path]] = Field(
+    parameter_file: Path | list[Path] = Field(
         description="File name (absolute or relative) or URL to PEtab parameter table "
         "containing parameters of all models listed in `problems`. A single "
         "table may be split into multiple files and described as an array here."
     )
-    problems: List[Problem] = Field(
+    problems: list[Problem] = Field(
         default_factory=list,
         description="One or multiple PEtab problems (sets of model, condition, observable "
         "and measurement files). If different model and data files are "
@@ -35,11 +35,11 @@ class PEtab(BaseModel):
 
     def add_problem(
         self,
-        sbml_files: List[Path],
-        measurement_files: List[Path],
-        condition_files: List[Path],
-        observable_files: List[Path],
-        visualization_files: Optional[List[Path]] = None,
+        sbml_files: list[Path],
+        measurement_files: list[Path],
+        condition_files: list[Path],
+        observable_files: list[Path],
+        visualization_files: list[Path] | None = None,
     ) -> None:
         """
         Add a problem to the PEtab object.
@@ -60,13 +60,13 @@ class Problem(BaseModel):
     A set of PEtab model, condition, observable and measurement files and optional visualization files.
     """
 
-    sbml_files: List[Path] = Field(description="List of PEtab SBML files.")
-    measurement_files: List[Path] = Field(
+    sbml_files: list[Path] = Field(description="List of PEtab SBML files.")
+    measurement_files: list[Path] = Field(
         description="List of PEtab measurement files."
     )
-    condition_files: List[Path] = Field(description="List of PEtab condition files.")
-    observable_files: List[Path] = Field(description="List of PEtab observable files.")
-    visualization_files: Optional[List[Path]] = Field(
+    condition_files: list[Path] = Field(description="List of PEtab condition files.")
+    observable_files: list[Path] = Field(description="List of PEtab observable files.")
+    visualization_files: list[Path] | None = Field(
         default=None,
         description="List of PEtab visualization files.",
     )
diff --git a/pyenzyme/plotting/__init__.py b/pyenzyme/plotting/__init__.py
index 1d413c78..58896edc 100644
--- a/pyenzyme/plotting/__init__.py
+++ b/pyenzyme/plotting/__init__.py
@@ -1,4 +1,4 @@
-from .static import plot
 from .interactive import plot_interactive
+from .static import plot
 
 __all__ = ["plot", "plot_interactive"]
diff --git a/pyenzyme/plotting/interactive.py b/pyenzyme/plotting/interactive.py
index b5a36dc0..b6a55810 100644
--- a/pyenzyme/plotting/interactive.py
+++ b/pyenzyme/plotting/interactive.py
@@ -1,10 +1,10 @@
-from typing import List, Optional, Tuple, Dict
 
-from bokeh.models import TabPanel, Tabs, HoverTool, ColumnDataSource
-from bokeh.plotting import figure, show as show_bokeh
+import rich
 from bokeh.io import output_file, output_notebook
+from bokeh.models import ColumnDataSource, HoverTool, TabPanel, Tabs
 from bokeh.palettes import Category10, Category20
-import rich
+from bokeh.plotting import figure
+from bokeh.plotting import show as show_bokeh
 
 from pyenzyme.thinlayers.base import BaseThinLayer, SimResult, Time
 from pyenzyme.versions import v2
@@ -16,9 +16,9 @@
 
 def plot_interactive(
     enzmldoc: v2.EnzymeMLDocument,
-    measurement_ids: Optional[list[str]] = None,
-    thinlayer: Optional[BaseThinLayer] = None,
-    out: Optional[str] = None,
+    measurement_ids: list[str] | None = None,
+    thinlayer: BaseThinLayer | None = None,
+    out: str | None = None,
     width: int = DEFAULT_WIDTH,
     height: int = DEFAULT_HEIGHT,
     show: bool = True,
@@ -157,10 +157,10 @@ def _is_notebook() -> bool:
 def _create_measurement_tab(
     enzmldoc: v2.EnzymeMLDocument,
     measurement: v2.Measurement,
-    thinlayer: Optional[BaseThinLayer],
+    thinlayer: BaseThinLayer | None,
     width: int,
     height: int,
-    color_map: Dict[str, str],
+    color_map: dict[str, str],
     **kwargs,
 ) -> TabPanel:
     """
@@ -244,8 +244,8 @@ def _plot_species_bokeh(
     p: figure,
     species: v2.MeasurementData,
     pred: SimResult,
-    time: List[float],
-    color_map: Dict[str, str],
+    time: list[float],
+    color_map: dict[str, str],
     **kwargs,
 ) -> None:
     """
@@ -346,7 +346,7 @@ def _get_fit(
     enzmldoc: v2.EnzymeMLDocument,
     measurement: v2.Measurement,
     thinlayer: BaseThinLayer,
-) -> Tuple[SimResult, Time]:
+) -> tuple[SimResult, Time]:
     """
     Get model predictions for a measurement using a thinlayer.
 
@@ -391,7 +391,7 @@ def _get_fit(
     )
 
 
-def _collect_dataytypes(measurement_data: List[v2.MeasurementData]) -> List[str]:
+def _collect_dataytypes(measurement_data: list[v2.MeasurementData]) -> list[str]:
     """
     Extract and format unique measurement data types.
 
diff --git a/pyenzyme/plotting/static.py b/pyenzyme/plotting/static.py
index c192b661..68b3b151 100644
--- a/pyenzyme/plotting/static.py
+++ b/pyenzyme/plotting/static.py
@@ -1,10 +1,9 @@
 import math
-from typing import List, Optional, Tuple, Union
 
 import numpy as np
 from matplotlib import pyplot as plt
-from matplotlib.figure import Figure
 from matplotlib.axes import Axes
+from matplotlib.figure import Figure
 
 from pyenzyme.thinlayers.base import BaseThinLayer, SimResult, Time
 from pyenzyme.versions import v2
@@ -18,15 +17,15 @@ def plot(
     enzmldoc: v2.EnzymeMLDocument,
     columns: int = 2,
     show: bool = False,
-    measurement_ids: Optional[list[str]] = None,
+    measurement_ids: list[str] | None = None,
     marker_size: int = 6,
     marker_style: str = "o",
-    thinlayer: Optional[BaseThinLayer] = None,
-    out: Optional[str] = None,
+    thinlayer: BaseThinLayer | None = None,
+    out: str | None = None,
     img_format: str = "png",
     dpi: int = 300,
     **kwargs,
-) -> Tuple[Figure, Union[Axes, List[Axes]]]:
+) -> tuple[Figure, Axes | list[Axes]]:
     """
     Creates publication-quality plots of measurement data from an EnzymeML document.
 
@@ -146,7 +145,7 @@ def _plot_measurement(
     ax: Axes,
     enzmldoc: v2.EnzymeMLDocument,
     measurement: v2.Measurement,
-    thinlayer: Optional[BaseThinLayer],
+    thinlayer: BaseThinLayer | None,
     marker_size: int,
     marker_style: str,
     **kwargs,
@@ -205,7 +204,7 @@ def _plot_species(
     ax: Axes,
     species: v2.MeasurementData,
     pred: SimResult,
-    time: List[float],
+    time: list[float],
     marker_size: int,
     marker_style: str,
     **kwargs,
@@ -264,7 +263,7 @@ def _plot_species(
 
 
 def _configure_plot(
-    ax: Axes, measurement: v2.Measurement, dataytypes: List[str]
+    ax: Axes, measurement: v2.Measurement, dataytypes: list[str]
 ) -> None:
     """
     Configure plot appearance with titles, labels, and styling.
@@ -305,7 +304,7 @@ def _get_fit(
     enzmldoc: v2.EnzymeMLDocument,
     measurement: v2.Measurement,
     thinlayer: BaseThinLayer,
-) -> Tuple[SimResult, Time]:
+) -> tuple[SimResult, Time]:
     """
     Get model predictions for a measurement using a thinlayer.
 
@@ -350,7 +349,7 @@ def _get_fit(
     )
 
 
-def _collect_dataytypes(measurement_data: List[v2.MeasurementData]) -> List[str]:
+def _collect_dataytypes(measurement_data: list[v2.MeasurementData]) -> list[str]:
     """
     Extract and format unique measurement data types.
 
diff --git a/pyenzyme/pretty.py b/pyenzyme/pretty.py
index ff6e98af..4670b415 100644
--- a/pyenzyme/pretty.py
+++ b/pyenzyme/pretty.py
@@ -1,8 +1,9 @@
 from typing import TYPE_CHECKING
+
+from rich.columns import Columns
 from rich.console import Console
 from rich.panel import Panel
 from rich.table import Table
-from rich.columns import Columns
 
 if TYPE_CHECKING:
     from pyenzyme.versions.v2 import EnzymeMLDocument
diff --git a/pyenzyme/sbml/__init__.py b/pyenzyme/sbml/__init__.py
index ab163b1d..0c769fec 100644
--- a/pyenzyme/sbml/__init__.py
+++ b/pyenzyme/sbml/__init__.py
@@ -3,8 +3,8 @@
 from .serializer import to_sbml
 
 __all__ = [
-    "to_sbml",
-    "read_sbml",
     "create_sbml_omex",
+    "read_sbml",
     "read_sbml_omex",
+    "to_sbml",
 ]
diff --git a/pyenzyme/sbml/ldutils.py b/pyenzyme/sbml/ldutils.py
index e61a54a7..12cbba42 100644
--- a/pyenzyme/sbml/ldutils.py
+++ b/pyenzyme/sbml/ldutils.py
@@ -1,7 +1,8 @@
-import rdflib
 import json
 import xml.etree.ElementTree as ET
 
+import rdflib
+
 
 def parse_sbml_rdf_annotation(sbml_obj, enzml_obj):
     """
diff --git a/pyenzyme/sbml/parser.py b/pyenzyme/sbml/parser.py
index 592c5f23..d194dc53 100644
--- a/pyenzyme/sbml/parser.py
+++ b/pyenzyme/sbml/parser.py
@@ -10,14 +10,13 @@
 from loguru import logger
 
 import pyenzyme as pe
-
 from pyenzyme import xmlutils
 from pyenzyme.logging import add_logger
 
 from . import read_sbml_omex
 from .ldutils import parse_sbml_rdf_annotation
-from .versions.handler import VersionHandler, SupportedVersions
 from .utils import _get_unit
+from .versions.handler import SupportedVersions, VersionHandler
 
 
 def read_sbml(cls, path: Path | str):
diff --git a/pyenzyme/sbml/serializer.py b/pyenzyme/sbml/serializer.py
index 67f47e69..20e8327f 100644
--- a/pyenzyme/sbml/serializer.py
+++ b/pyenzyme/sbml/serializer.py
@@ -1,8 +1,8 @@
 from __future__ import annotations
 
+from collections.abc import Callable
 from copy import deepcopy
 from pathlib import Path
-from typing import Callable, List
 
 import libsbml
 import pandas as pd
@@ -629,7 +629,7 @@ def _validate_sbml(sbmldoc: libsbml.SBMLDocument) -> None:
             )
 
 
-def _assign_ids_to_units(doc_units: List[UnitDefinition]) -> List[UnitDefinition]:
+def _assign_ids_to_units(doc_units: list[UnitDefinition]) -> list[UnitDefinition]:
     """
     Assign unique IDs to units.
 
diff --git a/pyenzyme/sbml/versions/__init__.py b/pyenzyme/sbml/versions/__init__.py
index fe805738..5f4c36e3 100644
--- a/pyenzyme/sbml/versions/__init__.py
+++ b/pyenzyme/sbml/versions/__init__.py
@@ -1,15 +1,15 @@
 from .v2 import (
+    ComplexAnnot,
     DataAnnot,
-    SpeciesDataAnnot,
-    ProteinAnnot,
     ParameterAnnot,
-    ComplexAnnot,
+    ProteinAnnot,
+    SpeciesDataAnnot,
 )
 
 __all__ = [
+    "ComplexAnnot",
     "DataAnnot",
-    "SpeciesDataAnnot",
-    "ProteinAnnot",
     "ParameterAnnot",
-    "ComplexAnnot",
+    "ProteinAnnot",
+    "SpeciesDataAnnot",
 ]
diff --git a/pyenzyme/tabular.py b/pyenzyme/tabular.py
index 2d9ff46d..8d98855f 100644
--- a/pyenzyme/tabular.py
+++ b/pyenzyme/tabular.py
@@ -3,13 +3,12 @@
 import pathlib as pl
 
 import pandas as pd
-
 from mdmodels.units.unit_definition import UnitDefinition
 
 from .versions.v2 import (
     DataTypes,
-    Measurement,
     EnzymeMLDocument,
+    Measurement,
     MeasurementData,
 )
 
diff --git a/pyenzyme/thinlayers/__init__.py b/pyenzyme/thinlayers/__init__.py
index c8b79104..1a0d02f6 100644
--- a/pyenzyme/thinlayers/__init__.py
+++ b/pyenzyme/thinlayers/__init__.py
@@ -1,5 +1,6 @@
 from .base import BaseThinLayer
 
+
 def _get_pysces():
     global ThinLayerPysces
     try:
@@ -30,4 +31,4 @@ def __getattr__(name):
     raise AttributeError(f"module '{__name__}' has no attribute '{name}'")
 
 
-__all__ = ["BaseThinLayer", "ThinLayerPysces", "ThinLayerCopasi"]
+__all__ = ["BaseThinLayer", "ThinLayerCopasi", "ThinLayerPysces"]
diff --git a/pyenzyme/thinlayers/base.py b/pyenzyme/thinlayers/base.py
index 9eb63464..375a7ed5 100644
--- a/pyenzyme/thinlayers/base.py
+++ b/pyenzyme/thinlayers/base.py
@@ -1,6 +1,6 @@
 from abc import ABC, abstractmethod
 from functools import cached_property
-from typing import Dict, List, Optional, Set, Tuple, TypeAlias
+from typing import TypeAlias
 
 import pandas as pd
 from sympy import Symbol, sympify
@@ -10,9 +10,9 @@
 
 # Type aliases for usage across the thinlayers
 # Easier to read and understand than using type hints
-InitCondDict: TypeAlias = Dict[str, float]
-SimResult: TypeAlias = Dict[str, List[float]]
-Time: TypeAlias = List[float]
+InitCondDict: TypeAlias = dict[str, float]
+SimResult: TypeAlias = dict[str, list[float]]
+Time: TypeAlias = list[float]
 
 
 class BaseThinLayer(ABC):
@@ -30,13 +30,13 @@ class BaseThinLayer(ABC):
     """
 
     enzmldoc: v2.EnzymeMLDocument
-    measurement_ids: List[str]
+    measurement_ids: list[str]
     exclude_unmodeled_species: bool = True
 
     def __init__(
         self,
         enzmldoc: v2.EnzymeMLDocument,
-        measurement_ids: Optional[List[str]] = None,
+        measurement_ids: list[str] | None = None,
         df_per_measurement: bool = False,
         exclude_unmodeled_species: bool = True,
     ):
@@ -149,7 +149,7 @@ def _remove_unmodeled_species(enzmldoc: v2.EnzymeMLDocument) -> v2.EnzymeMLDocum
         return enzmldoc
 
     @staticmethod
-    def _get_all_species(enzmldoc: v2.EnzymeMLDocument) -> Set[str]:
+    def _get_all_species(enzmldoc: v2.EnzymeMLDocument) -> set[str]:
         """
         Gets all species from the EnzymeML document.
         """
@@ -168,7 +168,7 @@ def integrate(
         t0: float,
         t1: float,
         nsteps: int = 100,
-    ) -> Tuple[SimResult, Time]:
+    ) -> tuple[SimResult, Time]:
         """
         Integrates the model from t0 to t1 with the given initial conditions.
 
diff --git a/pyenzyme/thinlayers/basico.py b/pyenzyme/thinlayers/basico.py
index dd011a0e..20517dc4 100644
--- a/pyenzyme/thinlayers/basico.py
+++ b/pyenzyme/thinlayers/basico.py
@@ -6,15 +6,14 @@
 
 from __future__ import annotations
 
+import os
 from dataclasses import dataclass
 from pathlib import Path
+
 import numpy as np
 import pandas as pd
-import os
-
-from typing import Dict, List, Optional, Tuple
 
-from pyenzyme.thinlayers.base import BaseThinLayer, SimResult, Time, InitCondDict
+from pyenzyme.thinlayers.base import BaseThinLayer, InitCondDict, SimResult, Time
 from pyenzyme.versions import v2
 
 try:
@@ -54,7 +53,7 @@ def __init__(
         self,
         enzmldoc: v2.EnzymeMLDocument,
         model_dir: Path | str = "./copasi_models",
-        measurement_ids: Optional[List[str]] = None,
+        measurement_ids: list[str] | None = None,
     ):
         """
         Initialize the ThinLayerCopasi instance.
@@ -113,7 +112,7 @@ def integrate(
         t0: float,
         t1: float,
         nsteps: int = 100,
-    ) -> Tuple[SimResult, Time]:
+    ) -> tuple[SimResult, Time]:
         """
         Integrates the model from t0 to t1 with the given initial conditions.
 
@@ -397,7 +396,7 @@ def _create_sbml_file(self, model_dir: str) -> str:
 
     def _simulate_condition(
         self, init_concs: InitMap
-    ) -> Tuple[List[np.ndarray], List[str]]:
+    ) -> tuple[list[np.ndarray], list[str]]:
         """
         Simulates a single experimental condition.
 
@@ -438,11 +437,11 @@ class InitMap:
         species (Dict[str, float]): Dictionary mapping species IDs to initial concentrations.
     """
 
-    time: List[float]
-    species: Dict[str, float]
+    time: list[float]
+    species: dict[str, float]
 
     @classmethod
-    def from_measurement(cls, meas: v2.Measurement, df: pd.DataFrame) -> "InitMap":
+    def from_measurement(cls, meas: v2.Measurement, df: pd.DataFrame) -> InitMap:
         """
         Create an InitMap instance from a measurement and its dataframe.
 
diff --git a/pyenzyme/thinlayers/psyces.py b/pyenzyme/thinlayers/psyces.py
index caacf79a..c69e6e4e 100644
--- a/pyenzyme/thinlayers/psyces.py
+++ b/pyenzyme/thinlayers/psyces.py
@@ -11,7 +11,6 @@
 import os
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Dict, List, Optional, Tuple
 
 import dill
 import numpy as np
@@ -63,7 +62,7 @@ def __init__(
         self,
         enzmldoc: v2.EnzymeMLDocument,
         model_dir: Path | str = "./pysces_models",
-        measurement_ids: Optional[List[str]] = None,
+        measurement_ids: list[str] | None = None,
     ):
         """
         Initialize the ThinLayerPysces instance.
@@ -128,7 +127,7 @@ def integrate(
         t0: float,
         t1: float,
         nsteps: int = 100,
-    ) -> Tuple[SimResult, Time]:
+    ) -> tuple[SimResult, Time]:
         """
         Integrates the model from t0 to t1 with the given initial conditions.
 
@@ -469,7 +468,7 @@ def _simulate_experiment(self, parameters):
 
     def _simulate_condition(
         self, init_concs: InitMap
-    ) -> Tuple[List[np.ndarray], List[str]]:
+    ) -> tuple[list[np.ndarray], list[str]]:
         """
         Simulates a single experimental condition.
 
@@ -502,11 +501,11 @@ class InitMap:
         species (Dict[str, float]): Dictionary mapping species IDs to initial concentrations.
     """
 
-    time: List[float]
-    species: Dict[str, float]
+    time: list[float]
+    species: dict[str, float]
 
     @classmethod
-    def from_measurement(cls, meas: v2.Measurement, df: pd.DataFrame) -> "InitMap":
+    def from_measurement(cls, meas: v2.Measurement, df: pd.DataFrame) -> InitMap:
         """
         Create an InitMap instance from a measurement and its dataframe.
 
diff --git a/pyenzyme/versions/io.py b/pyenzyme/versions/io.py
index d97abcb1..3ab84aee 100644
--- a/pyenzyme/versions/io.py
+++ b/pyenzyme/versions/io.py
@@ -1,6 +1,5 @@
 import json
 from pathlib import Path
-from typing import Optional
 
 import pandas as pd
 import rich
@@ -24,7 +23,7 @@ class EnzymeMLHandler:
     """
 
     @classmethod
-    def read_enzymeml(cls, path: str) -> v2.EnzymeMLDocument:  # noqa: F405
+    def read_enzymeml(cls, path: str) -> v2.EnzymeMLDocument:
         """Read an EnzymeML document from a file.
 
         Attempts to read the document using different version parsers until successful.
@@ -47,7 +46,7 @@ def read_enzymeml(cls, path: str) -> v2.EnzymeMLDocument:  # noqa: F405
                     continue
             elif version == "v2":
                 try:
-                    with open(path, "r") as f:
+                    with open(path) as f:
                         data = json.load(f)
 
                     return v2.EnzymeMLDocument.model_validate(data)
@@ -58,7 +57,7 @@ def read_enzymeml(cls, path: str) -> v2.EnzymeMLDocument:  # noqa: F405
         raise ValueError(f"Invalid EnzymeML version: {path}") from error
 
     @classmethod
-    def read_enzymeml_from_string(cls, data: str) -> v2.EnzymeMLDocument:  # noqa: F405
+    def read_enzymeml_from_string(cls, data: str) -> v2.EnzymeMLDocument:
         """Read an EnzymeML document from a string.
 
         Attempts to read the document using different version parsers until successful.
@@ -87,7 +86,7 @@ def from_dataframe(
         df: pd.DataFrame,
         data_unit: str,
         time_unit: str,
-    ) -> list[v2.Measurement]:  # noqa: F405
+    ) -> list[v2.Measurement]:
         """Parse a pandas DataFrame into a list of measurements.
 
         This function expects the DataFrame to have the following structure:
@@ -120,7 +119,7 @@ def write_enzymeml(
         cls,
         enzmldoc: v2.EnzymeMLDocument,
         path: Path | str | None = None,
-    ) -> Optional[str]:  # noqa: F405
+    ) -> str | None:
         """Write an EnzymeML document to a file or return as a string.
 
         Args:
@@ -154,7 +153,7 @@ def to_sbml(
         enzmldoc: v2.EnzymeMLDocument,
         path: Path | str | None = None,
         verbose: bool = False,
-    ) -> tuple[str, pd.DataFrame | None]:  # noqa: F405
+    ) -> tuple[str, pd.DataFrame | None]:
         """Convert an EnzymeML document to SBML format and write it to a file.
 
         The systems biology markup language (SBML) is a machine-readable format for
@@ -186,7 +185,7 @@ def to_petab(
         cls,
         enzmldoc: v2.EnzymeMLDocument,
         path: Path | str,
-    ) -> PEtab:  # noqa: F405
+    ) -> PEtab:
         """
         Convert an EnzymeML document to a PEtab parameter estimation problem and write to file.
 
@@ -226,7 +225,7 @@ def to_petab(
     def from_sbml(
         cls,
         path: Path | str,
-    ) -> v2.EnzymeMLDocument:  # noqa: F405
+    ) -> v2.EnzymeMLDocument:
         """
         Read an SBML file and initialize an EnzymeML document.
 
@@ -249,7 +248,7 @@ def to_pandas(
         cls,
         enzmldoc: v2.EnzymeMLDocument,
         per_measurement: bool = False,
-    ) -> pd.DataFrame | dict[str, pd.DataFrame]:  # noqa: F405
+    ) -> pd.DataFrame | dict[str, pd.DataFrame]:
         """Convert an EnzymeML document to a pandas DataFrame.
 
         The resulting DataFrame contains the following columns:
@@ -285,7 +284,7 @@ def from_csv(
         time_unit: str,
         data_type: v2.DataTypes = v2.DataTypes.CONCENTRATION,
         sep: str = "\t",
-    ) -> list[v2.Measurement]:  # noqa: F405
+    ) -> list[v2.Measurement]:
         """Reads a CSV file from the specified path into a measurement.
 
         This function expects the CSV file to have the following structure:
@@ -322,7 +321,7 @@ def from_excel(
         data_unit: str,
         time_unit: str,
         data_type: v2.DataTypes = v2.DataTypes.CONCENTRATION,
-    ) -> list[v2.Measurement]:  # noqa: F405
+    ) -> list[v2.Measurement]:
         """Reads an Excel file from the specified path into Measurement objects.
 
         This function expects the Excel file to have the following structure:
diff --git a/pyenzyme/widgets.py b/pyenzyme/widgets.py
index accb45af..587a98fa 100644
--- a/pyenzyme/widgets.py
+++ b/pyenzyme/widgets.py
@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING, Any, get_origin, get_args
+from typing import TYPE_CHECKING, Any, get_args, get_origin
 
 if TYPE_CHECKING:
     from pyenzyme.versions.v2 import EnzymeMLDocument
diff --git a/pyproject.toml b/pyproject.toml
index b57b4599..41c6306f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -47,6 +47,14 @@ copasi = ["copasi-basico>=0.85"]
 [tool.pytest.ini_options]
 markers = ["remote: tests that require network access to external services"]
 
+[tool.ruff]
+# Generated by md-models ("do not edit") and the legacy v1 package.
+extend-exclude = ["pyenzyme/versions/v2.py", "pyenzyme/v1"]
+
+[tool.ruff.lint]
+# Ruff <0.16 defaults plus the rule families ruff can autofix.
+select = ["E4", "E7", "E9", "F", "I", "UP", "RUF010", "RUF022", "RUF100"]
+
 [tool.uv]
 
 [build-system]
diff --git a/tests/conftest.py b/tests/conftest.py
index 34f3d1b8..92c7e160 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,4 +1,5 @@
 import pytest
+
 import pyenzyme as pe
 
 
diff --git a/tests/integration/test_basico.py b/tests/integration/test_basico.py
index f6c83aa5..be13e2c0 100644
--- a/tests/integration/test_basico.py
+++ b/tests/integration/test_basico.py
@@ -1,6 +1,7 @@
 import tempfile
 
 import pytest
+
 import pyenzyme as pe
 from pyenzyme.thinlayers.basico import ThinLayerCopasi
 from pyenzyme.versions import v2
diff --git a/tests/integration/test_composer.py b/tests/integration/test_composer.py
index 96479f16..a5c82f8e 100644
--- a/tests/integration/test_composer.py
+++ b/tests/integration/test_composer.py
@@ -1,4 +1,5 @@
 import pytest
+
 import pyenzyme as pe
 from pyenzyme.tools import to_dict_wo_json_ld
 
diff --git a/tests/integration/test_petab.py b/tests/integration/test_petab.py
index bd5b4994..ae1a52d0 100644
--- a/tests/integration/test_petab.py
+++ b/tests/integration/test_petab.py
@@ -1,5 +1,6 @@
 import re
 import tempfile
+
 import pytest
 
 import pyenzyme as pe
diff --git a/tests/integration/test_psyces.py b/tests/integration/test_psyces.py
index 1a98c4b0..069303c0 100644
--- a/tests/integration/test_psyces.py
+++ b/tests/integration/test_psyces.py
@@ -1,6 +1,7 @@
 import tempfile
 
 import pytest
+
 import pyenzyme as pe
 from pyenzyme.thinlayers.psyces import ThinLayerPysces
 from pyenzyme.versions import v2
diff --git a/tests/integration/test_suite.py b/tests/integration/test_suite.py
index 46dadfa8..4ea3f688 100644
--- a/tests/integration/test_suite.py
+++ b/tests/integration/test_suite.py
@@ -1,8 +1,9 @@
 import json
-import pyenzyme as pe
-from pyenzyme.suite import EnzymeMLSuite
+
 from pytest_httpx import HTTPXMock
 
+import pyenzyme as pe
+from pyenzyme.suite import EnzymeMLSuite
 from pyenzyme.tools import to_dict_wo_json_ld
 from pyenzyme.versions import v2
 
@@ -10,7 +11,7 @@
 class TestSuite:
     def test_fetch_current(self, httpx_mock: HTTPXMock):
         # Arrange
-        with open("tests/fixtures/sbml/ode_example_enzml.json", "r") as f:
+        with open("tests/fixtures/sbml/ode_example_enzml.json") as f:
             data = json.load(f)
             httpx_mock.add_response(json={"data": {"content": data}})
 
@@ -24,7 +25,7 @@ def test_fetch_current(self, httpx_mock: HTTPXMock):
 
     def test_update_current(self, httpx_mock: HTTPXMock):
         # Arrange
-        with open("tests/fixtures/sbml/ode_example_enzml.json", "r") as f:
+        with open("tests/fixtures/sbml/ode_example_enzml.json") as f:
             data = pe.read_enzymeml_from_string(json.load(f))
             httpx_mock.add_response(
                 match_json=json.loads(data.model_dump_json()),
diff --git a/tests/unit/test_equations.py b/tests/unit/test_equations.py
index a43df460..8e9d3337 100644
--- a/tests/unit/test_equations.py
+++ b/tests/unit/test_equations.py
@@ -1,8 +1,8 @@
 import pytest
 
+from pyenzyme import EnzymeMLDocument, EquationType
 from pyenzyme.equations.chem import build_reaction, build_reactions
 from pyenzyme.equations.math import build_equation, build_equations
-from pyenzyme import EquationType, EnzymeMLDocument
 
 
 class TestMathEquations:
diff --git a/tests/unit/test_sbml_annot_v1.py b/tests/unit/test_sbml_annot_v1.py
index ff6ee602..4dbf553c 100644
--- a/tests/unit/test_sbml_annot_v1.py
+++ b/tests/unit/test_sbml_annot_v1.py
@@ -1,11 +1,11 @@
 import pandas as pd
-
 from mdmodels.units.converter import convert_unit
+
 from pyenzyme.sbml.versions.v1 import (
-    DataAnnot,
-    ReactantAnnot,
     ComplexAnnot,
+    DataAnnot,
     ProteinAnnot,
+    ReactantAnnot,
 )
 
 
diff --git a/tests/unit/test_sbml_annot_v2.py b/tests/unit/test_sbml_annot_v2.py
index 3a132f05..73f7187a 100644
--- a/tests/unit/test_sbml_annot_v2.py
+++ b/tests/unit/test_sbml_annot_v2.py
@@ -1,15 +1,15 @@
 from pyenzyme.sbml.versions.v2 import (
+    ConditionsAnnot,
     DataAnnot,
     MeasurementAnnot,
-    ConditionsAnnot,
-    SpeciesDataAnnot,
-    TemperatureAnnot,
+    ParameterAnnot,
     PHAnnot,
-    SmallMoleculeAnnot,
     ProteinAnnot,
-    ParameterAnnot,
-    VariablesAnnot,
+    SmallMoleculeAnnot,
+    SpeciesDataAnnot,
+    TemperatureAnnot,
     VariableAnnot,
+    VariablesAnnot,
 )