prepare better DB interaction with reload

src/wce_crm/backend/initial_recording.py

@@ -34,6 +34,31 @@ class CompanyInfo(TypedDict):
     ma_archiviert: str
 
 
+class ContactPersonInfo(TypedDict):
+    an_id: str
+    ma_id: str
+    wce_id: str
+    st_id: str
+    an_sachgebiet: str
+    an_anrede: str
+    an_titel: str
+    an_nachname: str
+    an_vorname: str
+    an_position: str
+    an_mail: str
+    an_festnetz: str
+    an_mobil: str
+    an_faxnummer: str
+    an_hauptansprechpartner: str
+    an_anrede_anschrift: str
+    an_bemerkung: str
+    an_aktualisierung_datum: str
+    an_aktualisierung_nutzer: str
+    an_letztes_kontaktdatum: str
+    an_ersteintrag_datum: str
+    an_archiviert: str
+
+
 def _transform_for_gui_output(
     data: pl.DataFrame,
 ) -> pl.DataFrame:
@@ -53,18 +78,19 @@ def _transform_for_gui_output(
     return q.collect()
 
 
-def comp_search_choice_mapping() -> dict[str, int]:
+def comp_search_choices() -> tuple[tuple[str, int], ...]:
     # TODO no reload functionality
     q = db.df_crm_master.lazy()
     counter = pl.int_range(0, pl.len()).over(pl.col.ma_unternehmensname)
     q = q.with_columns(
-        ma_unternehmensname_dedupl=pl.when(counter == 0)
+        dedupl=pl.when(counter == 0)
         .then(pl.col.ma_unternehmensname)
         .otherwise(pl.format("{} ({})", pl.col.ma_unternehmensname, counter))
     )
     df = q.collect()
 
-    return dict(zip(df["ma_unternehmensname_dedupl"], df["ma_id"]))
+    # return dict(zip(df["dedupl"], df["ma_id"]))
+    return tuple(zip(df["dedupl"], df["ma_id"]))
 
 
 def comp_search_get_info(
@@ -76,3 +102,42 @@ def comp_search_get_info(
 
     df = _transform_for_gui_output(df)
     return cast(CompanyInfo, df.row(0, named=True))
+
+
+def contact_person_search_choices(
+    ma_id: int | None,
+    use_both_names: bool,
+) -> tuple[tuple[str, int], ...]:
+    # TODO no reload functionality
+    q = db.df_contact_person.lazy()
+    if ma_id is not None:
+        q = q.filter(pl.col.ma_id == ma_id)
+
+    dedupl_col = pl.col.an_nachname
+    if use_both_names:
+        q = q.with_columns(
+            name_search=(pl.format("{}, {}", pl.col.an_nachname, pl.col.an_vorname))
+        )
+        dedupl_col = pl.col.name_search
+
+    counter = pl.int_range(0, pl.len()).over(dedupl_col)
+    q = q.with_columns(
+        dedupl=pl.when(counter == 0)
+        .then(dedupl_col)
+        .otherwise(pl.format("{} ({})", dedupl_col, counter))
+    )
+    df = q.collect()
+
+    # return dict(zip(df["dedupl"], df["an_id"]))
+    return tuple(zip(df["dedupl"], df["an_id"]))
+
+
+def contact_person_search_get_info(
+    an_id: int,
+) -> ContactPersonInfo:
+    df = db.df_contact_person.filter(pl.col.an_id == an_id)
+    if df.height > 1 or df.height == 0:
+        raise ValueError(f"Größe des zurückgelieferten Datenpakets ungültig: {df.height}")
+
+    df = _transform_for_gui_output(df)
+    return cast(ContactPersonInfo, df.row(0, named=True))