MNT: target py39 as new minimum, enable pyupgrade for ruff, bump min …

…dependencie versions (#614)

.github/workflows/selective_cache_persist.yml

@@ -14,7 +14,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [ '3.8-minver', '3.8', '3.9', '3.10', '3.11', '3.12']
+        python-version: [ '3.9-minver', '3.9', '3.10', '3.11', '3.12']
         #
     name: Persist cache for ${{ matrix.python-version }}
     steps:

.github/workflows/tests.yml

@@ -16,10 +16,9 @@ jobs:
       matrix:
         include:
           - name-suffix: "(Minimum Versions)"
-            python-version: "3.8"
+            python-version: "3.9"
             cache-suffix: "-minver"
             extra-requirements: "-c requirements/minver.txt"
-          - python-version: "3.8"
           - python-version: "3.9"
           - python-version: "3.10"
           - python-version: "3.11"

fastf1/_api.py

@@ -4,7 +4,6 @@
 import json
 import zlib
 from typing import (
-    Dict,
     Optional,
     Union
 )
@@ -29,15 +28,15 @@
 
 base_url = 'https://livetiming.formula1.com'
 
-headers: Dict[str, str] = {
+headers: dict[str, str] = {
     'Host': 'livetiming.formula1.com',
     'Connection': 'close',
     'TE': 'identity',
     'User-Agent': 'BestHTTP',
     'Accept-Encoding': 'gzip, identity',
 }
 
-pages: Dict[str, str] = {
+pages: dict[str, str] = {
     'session_data': 'SessionData.json',  # track + session status + lap count
     'session_info': 'SessionInfo.jsonStream',  # more rnd
     'archive_status': 'ArchiveStatus.json',  # rnd=1880327548
@@ -83,7 +82,7 @@ def make_path(wname, wdate, sname, sdate):
 
 
 # define all empty columns for timing data
-EMPTY_LAPS = {'Time': pd.NaT, 'Driver': str(), 'LapTime': pd.NaT,
+EMPTY_LAPS = {'Time': pd.NaT, 'Driver': '', 'LapTime': pd.NaT,
               'NumberOfLaps': np.nan, 'NumberOfPitStops': np.nan,
               'PitOutTime': pd.NaT, 'PitInTime': pd.NaT,
               'Sector1Time': pd.NaT, 'Sector2Time': pd.NaT,
@@ -92,7 +91,7 @@ def make_path(wname, wdate, sname, sdate):
               'SpeedI1': np.nan, 'SpeedI2': np.nan, 'SpeedFL': np.nan,
               'SpeedST': np.nan, 'IsPersonalBest': False}
 
-EMPTY_STREAM = {'Time': pd.NaT, 'Driver': str(), 'Position': np.nan,
+EMPTY_STREAM = {'Time': pd.NaT, 'Driver': '', 'Position': np.nan,
                 'GapToLeader': np.nan, 'IntervalToPositionAhead': np.nan}
 
 

fastf1/core.py

@@ -43,15 +43,13 @@
 import re
 import typing
 import warnings
+from collections.abc import Iterable
 from functools import cached_property
 from typing import (
     Any,
     Callable,
-    Iterable,
-    List,
     Literal,
     Optional,
-    Tuple,
     Union
 )
 
@@ -925,8 +923,8 @@ def add_driver_ahead(self, drop_existing: bool = True) -> "Telemetry":
         )
 
         if ((d['Date'].shape != dtd['Date'].shape)
-                or np.any((d['Date'].values
-                           != dtd['Date'].values))):
+                or np.any(d['Date'].values
+                          != dtd['Date'].values)):
             dtd = dtd.resample_channels(new_date_ref=d["Date"])
 
         # indices need to match as .join works index-on-index
@@ -1510,7 +1508,7 @@ def _load_laps_data(self, livedata=None):
             elif not len(d2):
                 result = d1.copy()
                 result.reset_index(drop=True, inplace=True)
-                result['Compound'] = str()
+                result['Compound'] = ''
                 result['TyreLife'] = np.nan
                 result['Stint'] = 0
                 result['New'] = False
@@ -3295,7 +3293,7 @@ def pick_accurate(self) -> "Laps":
         """
         return self[self['IsAccurate']]
 
-    def split_qualifying_sessions(self) -> List[Optional["Laps"]]:
+    def split_qualifying_sessions(self) -> list[Optional["Laps"]]:
         """Splits a lap object into individual laps objects for each
         qualifying session.
 
@@ -3354,7 +3352,7 @@ def split_qualifying_sessions(self) -> List[Optional["Laps"]]:
         return laps
 
     def iterlaps(self, require: Optional[Iterable] = None) \
-            -> Iterable[Tuple[int, "Lap"]]:
+            -> Iterable[tuple[int, "Lap"]]:
         """Iterator for iterating over all laps in self.
 
         This method wraps :meth:`pandas.DataFrame.iterrows`.
@@ -3762,16 +3760,13 @@ class NoLapDataError(Exception):
     after processing the result.
     """
     def __init__(self, *args):
-        super(NoLapDataError, self).__init__("Failed to load session because "
-                                             "the API did not provide any "
-                                             "usable data.")
+        super().__init__("Failed to load session because the API did not "
+                         "provide any usable data.")
 
 
 class InvalidSessionError(Exception):
     """Raised if no session for the specified event name, type and year
     can be found."""
 
     def __init__(self, *args):
-        super(InvalidSessionError, self).__init__(
-            "No matching session can be found."
-        )
+        super().__init__("No matching session can be found.")

fastf1/ergast/interface.py

@@ -1,10 +1,8 @@
 import copy
 import json
 from typing import (
-    List,
     Literal,
     Optional,
-    Type,
     Union
 )
 
@@ -252,7 +250,7 @@ class ErgastSimpleResponse(ErgastResponseMixin, ErgastResultFrame):
     _internal_names_set = set(_internal_names)
 
     @property
-    def _constructor(self) -> Type["ErgastResultFrame"]:
+    def _constructor(self) -> type["ErgastResultFrame"]:
         # drop from ErgastSimpleResponse to ErgastResultFrame, removing the
         # ErgastResponseMixin because a slice of the data is no longer a full
         # response and pagination, ... is therefore not supported anymore
@@ -363,7 +361,7 @@ def description(self) -> ErgastResultFrame:
         return self._description
 
     @property
-    def content(self) -> List[ErgastResultFrame]:
+    def content(self) -> list[ErgastResultFrame]:
         """A ``list`` of :class:`ErgastResultFrame` that contain the main
         response data.
 

fastf1/events.py

@@ -194,7 +194,6 @@
 from typing import (
     Literal,
     Optional,
-    Type,
     Union
 )
 
@@ -624,7 +623,7 @@ def _get_schedule_ff1(year):
             data[f'session{j+1}_date'][i] = pd.Timestamp(date)
             data[f'session{j+1}_date_Utc'][i] = pd.Timestamp(date_utc)
 
-    str().capitalize()
+    ''.capitalize()
 
     df = pd.DataFrame(data)
     # change column names from snake_case to UpperCamelCase
@@ -885,7 +884,7 @@ def __init__(self, *args, year: int = 0,
             self[col] = self[col].astype(_type)
 
     @property
-    def _constructor_sliced_horizontal(self) -> Type["Event"]:
+    def _constructor_sliced_horizontal(self) -> type["Event"]:
         return Event
 
     def is_testing(self):

fastf1/internals/fuzzy.py

@@ -1,5 +1,4 @@
 import warnings
-from typing import List
 
 import numpy as np
 
@@ -15,7 +14,7 @@
 
 def fuzzy_matcher(
         query: str,
-        reference: List[List[str]],
+        reference: list[list[str]],
         abs_confidence: float = 0.0,
         rel_confidence: float = 0.0
 ) -> (int, bool):

fastf1/internals/pandas_extensions.py

@@ -1,5 +1,3 @@
-from typing import List
-
 import numpy as np
 from pandas import (
     DataFrame,
@@ -35,7 +33,7 @@
 
 def create_df_fast(
         *,
-        arrays: List[np.ndarray],
+        arrays: list[np.ndarray],
         columns: list,
         fallback: bool = True
 ) -> DataFrame:
@@ -71,7 +69,7 @@ def create_df_fast(
 
 
 def _fallback_create_df(
-        arrays: List[np.ndarray],
+        arrays: list[np.ndarray],
         columns: list
 ) -> DataFrame:
     data = {col: arr for col, arr in zip(columns, arrays)}
@@ -87,7 +85,7 @@ def _fallback_if_unsupported(func):
 
 @_fallback_if_unsupported
 def _unsafe_create_df_fast(
-        arrays: List[np.ndarray],
+        arrays: list[np.ndarray],
         columns: list
 ) -> DataFrame:
     # Implements parts of pandas' internal DataFrame creation mechanics

fastf1/livetiming/__main__.py

@@ -15,7 +15,7 @@ def save(args):
 
 
 def convert(args):
-    with open(args.input, 'r') as infile:
+    with open(args.input) as infile:
         messages = infile.readlines()
     data, ec = messages_from_raw(messages)
     with open(args.output, 'w') as outfile:

fastf1/livetiming/client.py

@@ -3,10 +3,8 @@
 import json
 import logging
 import time
-from typing import (
-    Iterable,
-    Optional
-)
+from collections.abc import Iterable
+from typing import Optional
 
 import requests
 

fastf1/livetiming/data.py

@@ -95,7 +95,7 @@ def load(self):
                 next_data = None
             else:
                 # read a new file as next file
-                with open(next_file, 'r') as fobj:
+                with open(next_file) as fobj:
                     next_data = fobj.readlines()
 
             if current_data is None:

fastf1/plotting/__init__.py

@@ -1,8 +1,4 @@
 import warnings
-from typing import (
-    Dict,
-    List
-)
 
 from fastf1.plotting._constants import \
     LEGACY_DRIVER_COLORS as _LEGACY_DRIVER_COLORS
@@ -91,11 +87,11 @@ def __getattr__(name):
     raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
 
 
-_DEPR_COMPOUND_COLORS: Dict[str, str] = {
+_DEPR_COMPOUND_COLORS: dict[str, str] = {
     key: val for key, val
     in _Constants['2024'].CompoundColors.items()
 }
-COMPOUND_COLORS: Dict[str, str]
+COMPOUND_COLORS: dict[str, str]
 """
 Mapping of tyre compound names to compound colors (hex color codes).
 (current season only)
@@ -107,8 +103,8 @@ def __getattr__(name):
 """
 
 
-_DEPR_DRIVER_COLORS: Dict[str, str] = _LEGACY_DRIVER_COLORS.copy()
-DRIVER_COLORS: Dict[str, str]
+_DEPR_DRIVER_COLORS: dict[str, str] = _LEGACY_DRIVER_COLORS.copy()
+DRIVER_COLORS: dict[str, str]
 """
 Mapping of driver names to driver colors (hex color codes).
 
@@ -123,8 +119,8 @@ def __getattr__(name):
 """
 
 
-_DEPR_DRIVER_TRANSLATE: Dict[str, str] = _LEGACY_DRIVER_TRANSLATE.copy()
-DRIVER_TRANSLATE: Dict[str, str]
+_DEPR_DRIVER_TRANSLATE: dict[str, str] = _LEGACY_DRIVER_TRANSLATE.copy()
+DRIVER_TRANSLATE: dict[str, str]
 """
 Mapping of driver names to theirs respective abbreviations.
 
@@ -138,13 +134,13 @@ def __getattr__(name):
     future version. Use :func:`~fastf1.plotting.get_driver_name` instead.
 """
 
-_DEPR_TEAM_COLORS: Dict[str, str] = {
+_DEPR_TEAM_COLORS: dict[str, str] = {
     # str(key.value): val for key, val
     # in _Constants['2024'].Colormaps[_Colormaps.Default].items()
     name.replace("kick ", ""): team.TeamColor.FastF1 for name, team
     in _Constants['2024'].Teams.items()
 }
-TEAM_COLORS: Dict[str, str]
+TEAM_COLORS: dict[str, str]
 """
 Mapping of team names to team colors (hex color codes).
 (current season only)
@@ -154,8 +150,8 @@ def __getattr__(name):
     future version. Use :func:`~fastf1.plotting.get_team_color` instead.
 """
 
-_DEPR_TEAM_TRANSLATE: Dict[str, str] = _LEGACY_TEAM_TRANSLATE.copy()
-TEAM_TRANSLATE: Dict[str, str]
+_DEPR_TEAM_TRANSLATE: dict[str, str] = _LEGACY_TEAM_TRANSLATE.copy()
+TEAM_TRANSLATE: dict[str, str]
 """
 Mapping of team names to theirs respective abbreviations.
 
@@ -164,8 +160,8 @@ def __getattr__(name):
     future version. Use :func:`~fastf1.plotting.get_team_name` instead.
 """
 
-_DEPR_COLOR_PALETTE: List[str] = _COLOR_PALETTE.copy()
-COLOR_PALETTE: List[str]
+_DEPR_COLOR_PALETTE: list[str] = _COLOR_PALETTE.copy()
+COLOR_PALETTE: list[str]
 """
 The default color palette for matplotlib plot lines in fastf1's color scheme.
 

fastf1/plotting/_backend.py

@@ -1,8 +1,4 @@
 import dataclasses
-from typing import (
-    Dict,
-    List
-)
 
 import fastf1._api
 from fastf1.plotting._base import (
@@ -16,12 +12,12 @@
 
 def _load_drivers_from_f1_livetiming(
         *, api_path: str, year: str
-) -> List[_Team]:
+) -> list[_Team]:
     # load the driver information for the determined session
     driver_info = fastf1._api.driver_info(api_path)
 
     # parse the data into the required format
-    teams: Dict[str, _Team] = dict()
+    teams: dict[str, _Team] = dict()
 
     # Sorting by driver number here will directly guarantee that drivers
     # are sorted by driver number within each team. This has two advantages: