Add MRS Table

src/maximum_roster_strategy/data_loader.py

@@ -0,0 +1,11 @@
+import os
+import pandas as pd
+
+
+MRS_SHEET_ID = os.environ.get("MRS_SHEET_ID")
+
+
+def get_google_sheet_data() -> pd.DataFrame:
+    sheet_url = f"https://docs.google.com/spreadsheet/ccc?key={MRS_SHEET_ID}&output=csv"
+    df = pd.read_csv(sheet_url)
+    return df

src/page_selector.py

@@ -15,6 +15,7 @@ MODE_PAGE_EXCLUSION_MAP = {
         "Keepers",
         "ECR",
         "League_Simulation",
+        "Keep_Rules",
     ],
     OFFSEASON_MODE: [
         "Practice_Reports",

src/pages/4_Practice_Reports.py

@@ -5,6 +5,7 @@ from config import DEFAULT_ICON
 from shared_page import common_page_config
 
 from queries.nfl_teams.practice_reports import scrape_all_team_injury_report, CURRENT_SEASON, CURRENT_WEEK
+from streamlit_filter import filter_dataframe
 
 
 @st.cache_data(ttl=60 * 60 * 1)
@@ -42,14 +43,16 @@ def get_page():
     )
 
     with st.container():
-        filtered_data = data[
-            (
-                data.Team.isin(teams_selected)
-                & data.Position.isin(positions_selected)
-                & data.game_status.isin(status_selected)
-                & data["Last Practice Day"].isin(last_practice_day_selected)
-            )
-        ]
+        filtered_data = filter_dataframe(
+            data[
+                (
+                    data.Team.isin(teams_selected)
+                    & data.Position.isin(positions_selected)
+                    & data.game_status.isin(status_selected)
+                    & data["Last Practice Day"].isin(last_practice_day_selected)
+                )
+            ]
+        )
         st.dataframe(
             filtered_data,
             hide_index=True,

src/pages/80_Maximum_Roster_Strategy.py

@@ -0,0 +1,85 @@
+import pandas as pd
+import streamlit as st
+
+from config import DEFAULT_ICON
+from shared_page import common_page_config
+from maximum_roster_strategy import data_loader
+
+
+MINIMUM_WEEK = 6
+MAXIMUM_WEEK = 6
+
+MIN_TIER = 1
+MAX_TIER = 4
+
+POSITION_OPTIONS = ["RB", "WR", "TE", "QB"]
+
+POSITION_ABBR_FULL_NAME_MAP = {
+    "RB": "Running Backs",
+    "WR": "Wide Receivers",
+    "TE": "Tight Ends",
+    "QB": "Quarterbacks (Superflex / 2QB Leagues Only)",
+}
+
+
+@st.cache_data(ttl=60 * 60 * 24)
+def load_data():
+    return data_loader.get_google_sheet_data()
+
+
+def get_player_container(player_series: pd.Series):
+    with st.expander(label=player_series["Formatted"]):
+        st.write(player_series["Hold Condition"])
+        if isinstance(notes := player_series["Article Notes"], str):
+            st.write(notes)
+
+
+# https://github.com/alanjones2/alan-jones-article-code/blob/master/stgrid/app/gridapp.py
+def make_grid(cols, rows):
+    grid = [0] * cols
+    for i in range(cols):
+        with st.container():
+            grid[i] = st.columns(rows[i])
+    return grid
+
+
+def get_position_breakdown(df: pd.DataFrame, position_abbr: str, position_full_str: str):
+    with st.container():
+        st.header(position_full_str)
+        df_pos = df[df["Position"] == position_abbr]
+        time_slots = df.sort_values("WeekTimeSlotIndex")["TimeSlotName"].unique().tolist()
+        tier_list = list(range(MIN_TIER, MAX_TIER + 1))
+        num_time_slots = len(time_slots)
+        column_len_list = [num_time_slots] + [1, num_time_slots] * len(tier_list)
+        tier_time_grid = make_grid(len(tier_list) * 2 + 1, column_len_list)
+
+        for time_idx, time_slot in enumerate(time_slots):
+            with tier_time_grid[0][time_idx]:
+                st.markdown(f"<h3 style='text-align: center;'>{time_slot}</h3>", unsafe_allow_html=True)
+            for tier_idx, tier in enumerate(tier_list):
+                if time_idx == 0:
+                    with tier_time_grid[(tier_idx + 1) * 2 - 1][0]:
+                        st.markdown(f"<h4 style='text-align: center;'>Tier {tier}</h4>", unsafe_allow_html=True)
+                df_tier_slot = df_pos[(df_pos["TimeSlotName"] == time_slot) & (df_pos["Tier"] == tier)]
+                with tier_time_grid[(tier_idx + 1) * 2][time_idx]:
+                    df_tier_slot.apply(get_player_container, axis=1)
+
+
+def get_page():
+    page_title = "Maximum Roster Strategy"
+    st.set_page_config(page_title=page_title, page_icon=DEFAULT_ICON, layout="wide")
+    common_page_config()
+    st.title(page_title)
+    col_select, week_select = st.columns(2, gap="small")
+    with col_select:
+        position = st.selectbox(label="Position", options=POSITION_OPTIONS, index=0)
+    with week_select:
+        week = st.selectbox(label="Week", options=list(range(MAXIMUM_WEEK, MINIMUM_WEEK - 1, -1)), index=0)
+    df_mrs = load_data()
+    df_mrs = df_mrs[df_mrs["Week"] == week]
+
+    get_position_breakdown(df_mrs, position, POSITION_ABBR_FULL_NAME_MAP[position])
+
+
+if __name__ == "__main__":
+    get_page()

src/shared_page.py

@@ -1,7 +1,15 @@
+import streamlit as st
+
 from page_selector import remove_seasonal_pages
 from login_component import get_authorization_button
 
 
+def local_css(file_name):
+    with open(file_name) as f:
+        st.markdown("<style>{}</style>".format(f.read()), unsafe_allow_html=True)
+
+
 def common_page_config():
     get_authorization_button()
     remove_seasonal_pages()
+    local_css("style.css")

src/style.css

@@ -0,0 +1,14 @@
+div[data-testid="stVerticalBlock"] > div[data-testid="stHorizontalBlock"] > div[data-testid="column"] {
+    border-style: solid;
+    border-right-style: solid;
+    border-width: 1px;
+    border-color: grey;
+  }
+
+div[data-testid="stHorizontalBlock"] {
+  gap: 0;
+}
+
+div[data-testid="stVerticalBlock"] {
+  gap: 0;
+}