CLN: Add additional typing information

Author: bashtage

pandas/io/stata.py

@@ -167,7 +167,7 @@
 stata_epoch = datetime.datetime(1960, 1, 1)
 
 
-def _stata_elapsed_date_to_datetime_vec(dates: Series, fmt: str) -> Series:
+def _stata_elapsed_date_to_datetime_vec(dates, fmt) -> Series:
     """
     Convert from SIF to datetime. http://www.stata.com/help.cgi?datetime
 
@@ -219,7 +219,7 @@ def _stata_elapsed_date_to_datetime_vec(dates: Series, fmt: str) -> Series:
     MIN_MS_DELTA = MIN_DAY_DELTA * 24 * 3600 * 1000
     MAX_MS_DELTA = MAX_DAY_DELTA * 24 * 3600 * 1000
 
-    def convert_year_month_safe(year: Series, month: Series) -> Series:
+    def convert_year_month_safe(year, month) -> Series:
         """
         Convert year and month to datetimes, using pandas vectorized versions
         when the date range falls within the range supported by pandas.
@@ -234,7 +234,7 @@ def convert_year_month_safe(year: Series, month: Series) -> Series:
                 [datetime.datetime(y, m, 1) for y, m in zip(year, month)], index=index
             )
 
-    def convert_year_days_safe(year: Series, days: Series) -> Series:
+    def convert_year_days_safe(year, days) -> Series:
         """
         Converts year (e.g. 1999) and days since the start of the year to a
         datetime or datetime64 Series
@@ -249,9 +249,7 @@ def convert_year_days_safe(year: Series, days: Series) -> Series:
             ]
             return Series(value, index=index)
 
-    def convert_delta_safe(
-        base: datetime.datetime, deltas: Series, unit: str
-    ) -> Series:
+    def convert_delta_safe(base, deltas, unit) -> Series:
         """
         Convert base dates and deltas to datetimes, using pandas vectorized
         versions if the deltas satisfy restrictions required to be expressed
@@ -298,21 +296,21 @@ def convert_delta_safe(
     # Delta days relative to base
     elif fmt.startswith(("%td", "td", "%d", "d")):
         base = stata_epoch
-        days: Series = dates
+        days = dates
         conv_dates = convert_delta_safe(base, days, "d")
     # does not count leap days - 7 days is a week.
     # 52nd week may have more than 7 days
     elif fmt.startswith(("%tw", "tw")):
-        year: Series = stata_epoch.year + dates // 52
+        year = stata_epoch.year + dates // 52
         days = (dates % 52) * 7
         conv_dates = convert_year_days_safe(year, days)
     elif fmt.startswith(("%tm", "tm")):  # Delta months relative to base
         year = stata_epoch.year + dates // 12
-        month: Series = (dates % 12) + 1
+        month = (dates % 12) + 1
         conv_dates = convert_year_month_safe(year, month)
     elif fmt.startswith(("%tq", "tq")):  # Delta quarters relative to base
         year = stata_epoch.year + dates // 4
-        quarter_month: Series = (dates % 4) * 3 + 1
+        quarter_month = (dates % 4) * 3 + 1
         conv_dates = convert_year_month_safe(year, quarter_month)
     elif fmt.startswith(("%th", "th")):  # Delta half-years relative to base
         year = stata_epoch.year + dates // 2
@@ -347,19 +345,19 @@ def _datetime_to_stata_elapsed_vec(dates: Series, fmt: str) -> Series:
     NS_PER_DAY = 24 * 3600 * 1000 * 1000 * 1000
     US_PER_DAY = NS_PER_DAY / 1000
 
-    def parse_dates_safe(
-        dates: Series, delta: bool = False, year: bool = False, days: bool = False
-    ):
-        d: Dict[str, Any] = {}
+    def parse_dates_safe(dates, delta=False, year=False, days=False):
+        d = {}
         if is_datetime64_dtype(dates.values):
             if delta:
-                time_delta: Series = dates - stata_epoch
+                time_delta = dates - stata_epoch
                 d["delta"] = time_delta.values.astype(np.int64) // 1000  # microseconds
             if days or year:
+                # ignore since mypy reports that DatetimeIndex has no year/month
                 date_index = DatetimeIndex(dates)
-                d["year"], d["month"] = date_index.year, date_index.month
+                d["year"] = date_index.year  # type: ignore
+                d["month"] = date_index.month  # type: ignore
             if days:
-                days_in_ns: Series = dates.astype(np.int64) - to_datetime(
+                days_in_ns = dates.astype(np.int64) - to_datetime(
                     d["year"], format="%Y"
                 ).astype(np.int64)
                 d["days"] = days_in_ns // NS_PER_DAY
@@ -588,10 +586,10 @@ def __init__(self, catarray: Series, encoding: str = "latin-1"):
         categories = catarray.cat.categories
         self.value_labels = list(zip(np.arange(len(categories)), categories))
         self.value_labels.sort(key=lambda x: x[0])
-        self.text_len = np.int32(0)
-        self.off = []
-        self.val = []
-        self.txt = []
+        self.text_len = 0
+        self.off: List[int] = []
+        self.val: List[int] = []
+        self.txt: List[bytes] = []
         self.n = 0
 
         # Compute lengths and setup lists of offsets and labels
@@ -2131,7 +2129,7 @@ def _prepare_categoricals(self, data: DataFrame) -> DataFrame:
 
         is_cat = [is_categorical_dtype(data[col]) for col in data]
         self._is_col_cat = is_cat
-        self._value_labels = []
+        self._value_labels: List[StataValueLabel] = []
         if not any(is_cat):
             return data
 
@@ -2290,8 +2288,8 @@ def _check_column_names(self, data: DataFrame) -> DataFrame:
         return data
 
     def _set_formats_and_types(self, dtypes: Series) -> None:
-        self.typlist = []
-        self.fmtlist = []
+        self.fmtlist: List[str] = []
+        self.typlist: List[int] = []
         for col, dtype in dtypes.items():
             self.fmtlist.append(_dtype_to_default_stata_fmt(dtype, self.data[col]))
             self.typlist.append(_dtype_to_stata_type(dtype, self.data[col]))