Added Streamlit

.streamlit/config.toml

@@ -0,0 +1,5 @@
+[browser]
+gatherUsageStats = false
+
+[server]
+port = 8501

README.md

@@ -23,12 +23,23 @@ store these info in [rememberthemilk.ini](src/rememberthemilk.ini) (see [remembe
 pip install -r requirements.txt
 ```
 
-optionally:
+#### Dev Tools
+
+optionally: ruff and pre-commit
 
 ```sh
 pip install ruff pre-commit
 ```
 
+optionally: pytest coverage report
+
+```sh
+pip install pytest-cov
+pytest --cov
+# or
+pytest --cov --cov-report=html:coverage_report
+```
+
 ### Obtain API token
 
 run [auth.py](src/auth.py) once and add the resulting `token` to [rememberthemilk.ini](src/rememberthemilk.ini)
@@ -51,6 +62,16 @@ run [auth.py](src/auth.py) once and add the resulting `token` to [rememberthemil
 * ranked by product of overdue days x priority, to focus on most urgent ones
 * display time estimation in minutes to motivate you for solving the minor ones right away
 
+## Streamlit for interactive data analysis
+
+```sh
+pip install streamlit watchdog
+```
+
+```sh
+streamlit run src/app.py
+```
+
 ## My RTM lifehacks
 
 see original post at <https://www.rememberthemilk.com/forums/tips/31034/>

cspell-words.txt

@@ -2,13 +2,17 @@
 abcbazfegbaryxzfoo
 astype
 autouse
+DataFrame
 frob
 lifehacks
 Menke
 noqa
 prio
+pytest
 rememberthemilk
 rrule
+selectbox
+Streamlit
 Taschengeld
 taskseries
 todos

src/app.py

@@ -0,0 +1,10 @@
+"""Streamlit UI."""
+
+import streamlit as st
+
+from helper import delete_cache
+
+st.set_page_config(page_title="RTM Report", page_icon=None, layout="wide")
+st.title("RTM")
+
+delete_cache()

src/helper.py

@@ -51,6 +51,11 @@
 #
 
 
+def delete_cache() -> None:  # noqa: D103
+    for file_path in CACHE_DIR.glob("*.json"):  # pragma: no cover
+        file_path.unlink()
+
+
 def dict_to_url_param(d: dict[str, str]) -> str:
     """
     Convert a dictionary of parameter to url parameter string.

src/pages/Completed.py

@@ -0,0 +1,39 @@
+"""Completed Tasks."""  # noqa: INP001
+
+import altair as alt
+import streamlit as st
+
+from tasks_completed import completed_week, get_tasks_completed
+
+st.set_page_config(page_title="RTM Completed", page_icon=None, layout="wide")
+st.title("Completed")
+
+df = get_tasks_completed()
+st.dataframe(
+    df,
+    hide_index=True,
+    column_config={"url": st.column_config.LinkColumn("url", display_text="url")},
+)
+
+st.header("per Week")
+df = completed_week(df)
+df = df.reset_index()
+
+sel_param = st.selectbox(
+    label="Parameter",
+    options=("count", "sum_prio", "sum_overdue_prio", "sum_estimate"),
+)
+
+df["completed_week"] = df["completed_week"].astype(str)
+chart = (
+    alt.Chart(df)
+    .mark_bar()
+    .encode(
+        x=alt.X("completed_week:N", title=None),
+        y=alt.Y(f"{sel_param}:Q", title=None),
+        color="list:N",
+    )
+)
+st.altair_chart(chart, use_container_width=True)
+
+st.dataframe(df, hide_index=True)

src/pages/Overdue.py

@@ -0,0 +1,43 @@
+"""Completed Tasks."""  # noqa: INP001
+
+import altair as alt
+import streamlit as st
+
+from tasks_overdue import get_tasks_overdue, group_by_list
+
+st.set_page_config(page_title="RTM Overdue", page_icon=None, layout="wide")
+st.title("Overdue")
+
+df = get_tasks_overdue().sort_values(by=["overdue"], ascending=[True])
+lists = sorted(set(df["list"].to_list()))
+
+sel_list = st.selectbox(label="List", index=None, options=lists)
+
+st.dataframe(
+    df.query(f"list == '{sel_list}'") if sel_list else df,
+    hide_index=True,
+    column_config={"url": st.column_config.LinkColumn("url", display_text="url")},
+)
+
+st.header("by List")
+df = group_by_list(df)
+df = df.reset_index()
+
+
+sel_list = st.selectbox(
+    label="Parameter",
+    options=("count", "sum_prio", "sum_overdue_prio", "sum_estimate"),
+)
+
+chart = (
+    alt.Chart(df)
+    .mark_bar()
+    .encode(
+        x=alt.X("list:N", title=None),
+        y=alt.Y(f"{sel_list}:Q", title=None),
+        color="list:N",
+    )
+)
+st.altair_chart(chart, use_container_width=True)
+
+st.dataframe(df, hide_index=True)

src/tasks_completed.py

@@ -6,6 +6,8 @@
 
 import datetime as dt
 
+from pandas import DataFrame
+
 from helper import (
     DATE_TODAY,
     df_name_url_to_html,
@@ -20,11 +22,8 @@
 AND NOT list:Taschengeld"""
 
 
-if __name__ == "__main__":
+def get_tasks_completed() -> DataFrame:  # noqa: D103
     lists_dict = get_lists_dict()
-
-    print("# RTM tasks completed this year")
-
     df = get_tasks_as_df(
         my_filter=FILTER_COMPLETED,
         lists_dict=lists_dict,
@@ -34,7 +33,6 @@
     )
     df = df.reset_index()
 
-    df = df_name_url_to_html(df)
     cols = [
         "name",
         "list",
@@ -46,20 +44,41 @@
         "overdue_prio",
         "postponed",
         "estimate",
+        "url",
     ]
+    df = df[cols]
+
+    return df
+
+
+def completed_week(df: DataFrame) -> DataFrame:  # noqa: D103
+    df = (
+        df.groupby(["completed_week", "list"])
+        .agg(
+            count=("completed_week", "count"),
+            sum_prio=("prio", "sum"),
+            sum_overdue_prio=("overdue_prio", "sum"),
+            sum_estimate=("estimate", "sum"),
+        )
+        .sort_values(by=["completed_week", "list"], ascending=[False, True])
+    )
+    return df
+
+
+if __name__ == "__main__":
+    df = get_tasks_completed()
+
+    print("# RTM tasks completed this year")
+
+    df = df_name_url_to_html(df)
 
     df_to_html(
-        df[cols],
+        df,
         "out-completed.html",
     )
     # df.to_excel(output_dir/"out-done-year.xlsx", index=False)
 
-    df2 = df.groupby(["completed_week", "list"]).agg(
-        count=("completed_week", "count"),
-        sum_prio=("prio", "sum"),
-        sum_overdue_prio=("overdue_prio", "sum"),
-        sum_estimate=("estimate", "sum"),
-    )
+    df2 = completed_week(df)
     print(df2)
 
     df_to_html(df2, "out-completed-week.html", index=True)

src/tasks_overdue.py

@@ -4,6 +4,8 @@
 by Dr. Torben Menke https://entorb.net
 """
 
+from pandas import DataFrame
+
 from helper import (
     df_name_url_to_html,
     df_to_html,
@@ -18,9 +20,8 @@
 """
 
 
-if __name__ == "__main__":
+def get_tasks_overdue() -> DataFrame:  # noqa: D103
     lists_dict = get_lists_dict()
-    print("# RTM tasks overdue")
 
     df = get_tasks_as_df(
         my_filter=FILTER_OVERDUE,
@@ -29,12 +30,34 @@
     df = df.sort_values(by=["overdue_prio"], ascending=False)
     df = df.reset_index()
 
-    cols = ["name", "list", "due", "overdue", "prio", "overdue_prio", "estimate"]
+    cols = ["name", "list", "due", "overdue", "prio", "overdue_prio", "estimate", "url"]
+    df = df[cols]
+
+    return df
+
+
+def group_by_list(df: DataFrame) -> DataFrame:  # noqa: D103
+    df = (
+        df.groupby(["list"])
+        .agg(
+            count=("list", "count"),
+            sum_prio=("prio", "sum"),
+            sum_overdue_prio=("overdue_prio", "sum"),
+            sum_estimate=("estimate", "sum"),
+        )
+        .sort_values(by=["list"], ascending=[True])
+    )
+    return df
+
+
+if __name__ == "__main__":
+    print("# RTM tasks overdue")
+    df = get_tasks_overdue()
 
-    print(df[cols])
+    print(df)
 
     df = df_name_url_to_html(df)
     df_to_html(
-        df[cols],
+        df,
         "out-overdue.html",
     )