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🤓 Add type annotations (and related changes)

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This commit is contained in:
Mike Gerber 2025-06-12 07:02:23 +02:00
parent d685454c52
commit ebdded90d6
1 changed files with 11 additions and 9 deletions
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12
src/mods4pandas/lib.py
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@ -4,7 +4,7 @@ from itertools import groupby
import re import re
import warnings import warnings
import os import os
from typing import List, Sequence, MutableMapping, Dict from typing import Any, List, Sequence, MutableMapping, Dict
from collections import defaultdict from collections import defaultdict
import numpy as np import numpy as np
@ -229,12 +229,14 @@ class TagGroup:
Extract values using the given XPath expression, convert them to float and return descriptive Extract values using the given XPath expression, convert them to float and return descriptive
statistics on the values. statistics on the values.
""" """
def xpath_values():
values = [] values = []
for e in self.group: for e in self.group:
r = e.xpath(xpath_expr, namespaces=namespaces) r = e.xpath(xpath_expr, namespaces=namespaces)
values += r values += r
values = np.array([float(v) for v in values]) return np.array([float(v) for v in values])
values = xpath_values()
statistics = {} statistics = {}
if values.size > 0: if values.size > 0:
statistics[f'{xpath_expr}-mean'] = np.mean(values) statistics[f'{xpath_expr}-mean'] = np.mean(values)
@ -294,7 +296,7 @@ def flatten(d: MutableMapping, parent='', separator='_') -> dict:
It is assumed that d maps strings to either another dictionary (similarly structured) or some other value. It is assumed that d maps strings to either another dictionary (similarly structured) or some other value.
""" """
items = [] items: list[Any] = []
for k, v in d.items(): for k, v in d.items():
if parent: if parent:
@ -324,8 +326,8 @@ def column_names_csv(columns) -> str:
""" """
return ",".join('"' + c + '"' for c in columns) return ",".join('"' + c + '"' for c in columns)
current_columns: defaultdict = defaultdict(list) current_columns: dict[str, list] = defaultdict(list)
current_columns_types: dict[dict] = defaultdict(dict) current_columns_types: dict[str, dict] = defaultdict(dict)
def insert_into_db(con, table, d: Dict): def insert_into_db(con, table, d: Dict):
"""Insert the values from the dict into the table, creating columns if necessary""" """Insert the values from the dict into the table, creating columns if necessary"""