Switch back to explicit arguments for get_dataframes()

Author: caleb531

README.md

@@ -146,7 +146,13 @@ def main() -> None:
     cli_args = ica.get_cli_parser().parse_args()
     # Retrieve the dataframes corresponding to the massaged contents of the
     # database; dataframes include `message` and `attachment`
-    dfs = ica.get_dataframes(**vars(cli_args))
+    dfs = ica.get_dataframes(
+        contact_name=cli_args.contact_name,
+        timezone=cli_args.timezone,
+        from_date=cli_args.from_date,
+        to_date=cli_args.to_date,
+        from_person=cli_args.from_person,
+    )
     # Send the results to stdout (or to file) in the given format
     ica.output_results(
         pd.DataFrame(

ica/analyzers/attachment_totals.py

@@ -18,7 +18,14 @@ def main() -> None:
     shared, YouTube videos, Apple Music, etc.
     """
     cli_args = ica.get_cli_parser().parse_args()
-    dfs = ica.get_dataframes(**vars(cli_args))
+    dfs = ica.get_dataframes(
+        contact_name=cli_args.contact_name,
+        timezone=cli_args.timezone,
+        from_date=cli_args.from_date,
+        to_date=cli_args.to_date,
+        from_person=cli_args.from_person,
+    )
+
     is_reaction = dfs.messages["is_reaction"]
     totals_map = {
         "gifs": dfs.attachments["mime_type"].eq("image/gif").sum(),

ica/analyzers/message_totals.py

@@ -81,7 +81,13 @@ def main() -> None:
     as well as other insightful metrics
     """
     cli_args = ica.get_cli_parser().parse_args()
-    dfs = ica.get_dataframes(**vars(cli_args))
+    dfs = ica.get_dataframes(
+        contact_name=cli_args.contact_name,
+        timezone=cli_args.timezone,
+        from_date=cli_args.from_date,
+        to_date=cli_args.to_date,
+        from_person=cli_args.from_person,
+    )
 
     all_datestrs = get_dates_between(
         get_first_message_date(dfs), str(datetime.date.today())

ica/analyzers/most_frequent_emojis.py

@@ -29,7 +29,14 @@ def main() -> None:
     entire conversation
     """
     cli_args = ica.get_cli_parser().parse_args()
-    dfs = ica.get_dataframes(**vars(cli_args))
+    dfs = ica.get_dataframes(
+        contact_name=cli_args.contact_name,
+        timezone=cli_args.timezone,
+        from_date=cli_args.from_date,
+        to_date=cli_args.to_date,
+        from_person=cli_args.from_person,
+    )
+
     emojis = get_emoji_list()
     text = dfs.messages[dfs.messages["is_reaction"].eq(False)].get("text")
     emoji_patt = re.compile(

ica/analyzers/totals_by_day.py

@@ -14,7 +14,13 @@ def main() -> None:
     the other person have been messaging in the conversation
     """
     cli_args = ica.get_cli_parser().parse_args()
-    dfs = ica.get_dataframes(**vars(cli_args))
+    dfs = ica.get_dataframes(
+        contact_name=cli_args.contact_name,
+        timezone=cli_args.timezone,
+        from_date=cli_args.from_date,
+        to_date=cli_args.to_date,
+        from_person=cli_args.from_person,
+    )
     ica.output_results(
         (
             dfs.messages[["text", "is_from_me", "datetime", "is_reaction"]]

ica/analyzers/transcript.py

@@ -18,7 +18,13 @@ def main() -> None:
     reactions, between you and the other person (attachment files not included)
     """
     cli_args = ica.get_cli_parser().parse_args()
-    dfs = ica.get_dataframes(**vars(cli_args))
+    dfs = ica.get_dataframes(
+        contact_name=cli_args.contact_name,
+        timezone=cli_args.timezone,
+        from_date=cli_args.from_date,
+        to_date=cli_args.to_date,
+        from_person=cli_args.from_person,
+    )
     ica.output_results(
         pd.DataFrame(
             {

ica/core.py

@@ -10,7 +10,7 @@
 from dataclasses import dataclass
 from io import BytesIO, StringIO
 from pathlib import Path
-from typing import Any, Callable, Union
+from typing import Callable, Union
 
 import pandas as pd
 import tzlocal
@@ -239,7 +239,6 @@ def get_dataframes(
     from_date: Union[str, None] = None,
     to_date: Union[str, None] = None,
     from_person: Union[str, None] = None,
-    **kwargs: Any,
 ) -> DataFrameNamespace:
     """
     Return all dataframes for a specific macOS Messages conversation