Update src/streamlit_app.py

src/streamlit_app.py

@@ -19,7 +19,7 @@ def fetch_wnba_data():
         "LastNGames": "0",
         "LeagueID": "10",
         "Location": "",
-        "MeasureType": "Base",
+        "MeasureType": "Scoring",
         "Month": "0",
         "OpponentTeamID": "0",
         "Outcome": "",
@@ -37,23 +37,36 @@ def fetch_wnba_data():
         "VsDivision": ""
     }
     headers = {
-        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36",
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36",
         "Accept": "application/json, text/plain, */*",
-        "x-nba-stats-origin": "stats",
-        "x-nba-stats-token": "true",
-        "Referer": "https://stats.wnba.com/players/boxscores-traditional/",
         "Accept-Encoding": "gzip, deflate, br",
         "Accept-Language": "en-GB,en-US;q=0.9,en;q=0.8",
-        "sec-ch-ua": '"Not/A)Brand";v="99", "Google Chrome";v="126", "Chromium";v="126"',
+        "Connection": "keep-alive",
+        "Host": "stats.wnba.com",
+        "Referer": "https://stats.wnba.com/players/boxscores-scoring/",
+        "sec-ch-ua": '"Not_A Brand";v="99", "Google Chrome";v="109", "Chromium";v="109"',
         "sec-ch-ua-mobile": "?0",
         "sec-ch-ua-platform": '"Windows"',
-        "sec-fetch-dest": "empty",
-        "sec-fetch-mode": "cors",
-        "sec-fetch-site": "same-origin"
-        # Add cf_clearance cookie here if available, e.g.:
-        # "Cookie": "cf_clearance=your_cookie_value"
+        "Sec-Fetch-Dest": "empty",
+        "Sec-Fetch-Mode": "cors",
+        "Sec-Fetch-Site": "same-origin",
+        "x-nba-stats-origin": "stats",
+        "x-nba-stats-token": "true",
+        "X-NewRelic-ID": "VQECWF5UChABUVFUBwYEUVwD",
+        "newrelic": "eyJ2IjpbMCwxXSwiZCI6eyJ0eSI6IkJyb3dzZXIiLCJhYyI6IjE3NTk4NzIiLCJhcCI6IjE1ODkwMTY1OTQiLCJpZCI6ImQwMTY2YTBlYjJhNGU3NjEiLCJ0ciI6Ijc5OTcwZjg2YmRmMzFiODMwZDIyYjQ2OTNlZDViZjg2IiwidGkiOjE3NTEwMjUyNTAzMjQsInRrIjoiMjg5MDE5OSJ9fQ==",
+        "traceparent": "00-79970f86bdf31b830d22b4693ed5bf86-d0166a0eb2a4e761-01",
+        "tracestate": "2890199@nr=0-1-1759872-1589016594-d0166a0eb2a4e761----1751025250324",
+        "Cookie": (
+            "bm_sv=81F390751AEC1D1FB260953D398C5A4D~YAAQDwHARf6uj6+XAQAAAfA5sRzqRJgRh3B32ZqWy6it7Z6fxqJfhoJnTBNhXxLrad7PcTRelS3tWrr8UZ0igPSGq5RPSbx74Th8HRr7JesXhayd4S6iMSj9lY6iDW8DwtZMJ1VV6Z53UgrKLPJNYRNqrXvNW6HpUvolDeVs2DrB1QvWjgUsftRuNmgEb34LqKZKJS8Wb16Nl3Cnz/U5S451tH3wjHJmfEiW54wOIRtb/4mcmteH1Jeg6Lyrzg==~1;"
+            "bm_sz=2D0D6F1234C7ABD81BFA31A8E8436692~YAAQDwHARXoaj6+XAQAAK4TysBywZPNxEID0PIkx3xRXCUd0d/29PGKxBcY8BbfGpXK2mQmY4JFFo6jvaCg7oDKoFnuYpEvzSdS4P+HIoJ2YJT44TIRGGONf2u6YhkIdmN+7HML3CAVZbiqkhJrebrrcY0tDKb7oAmjcYbhZFaToEifUsi6Kzqg2/qjX5ZskYiX6HevYgvqKJG2enicqjp1g9BoYzLRKBualYuB8iafHN03nowT28yk86TjZpDVHdB6KZiRIkE/hOQHwY4+4lspWFjXyWZABbigixU4WduxUOieGFkuelkjSSTJCjMxugYyxZ5f5LNvKvDzYa7b8REHx4T4EMCB1CUF72yIJetJDWGptNPnrK7d2GAMsX7hBC4ot9t+rU+c9f7VqDnI=~4339254~3354693;"
+            "_abck=8EDF6F70F2EBD7C030552A7F17AE0613~-1~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~-1~||0||~1751023975;"
+            "ak_bmsc=B7BABDC398E92F1DF6650FC251EACFCF~000000000000000000000000000000~YAAQDwHARY0aj6+XAQAAvo/ysBwjFhKD1uQJMSb1wp40PfdvSnbuU85scjOO5zGLWbgaZDTozOc3oJpqfgUyNPOfunAmS964TA6cI3z9rwEzk/kP+ypn4b1wdhToyxyC0swmVj13Gj+09GTAhyXfnG/GW8lJBLMfmxOhQY4EzGGZwX6cY8eBxe8ZWgUUa3zZKo92fZEM5iLkdjyr5X5EoNsqIFHbEtNlWyJBvhyTxmv4n4q8Xr4+YtaDf/dW5xGITmfcSWzzcR1zQTUY6GgDW0NWsW5Zgz4RFqLu9d5fJkROwuaQwH2EHo9nZu5FXT5B3V+rmnGwPsCPRkYuxUc88u1clSTrZ3qpWXkBuBHdCLE/jGH91XelBfHZu00aDh18czfDmdSCiCVSIhKIIbKBMLO+wT4vLcjZjznyLN3wzY0XFGcZ8Bua0vzan0YhFNVR6+3kOO5HZLXjfSDwmw==;"
+            "usprivacy=1---;"
+            "_ga=GA1.2.141871504.1751020378;"
+            "_gid=GA1.2.808457365.1751020378;"
+            "_ga_GELQE9ZCTK=GS2.2.s1751024075$o2$g1$t1751025052$j60$l0$h0"
+        )
     }
-
     try:
         st.write("Attempting API request with cloudscraper...")
         scraper = cloudscraper.create_scraper()
@@ -61,9 +74,8 @@ def fetch_wnba_data():
         response = scraper.get(url, params=params, headers=headers, timeout=60)
         response.raise_for_status()
         fetch_time = time.time() - start_time
-        st.success(f"API request successful. Fetched {len(response.json().get('resultSets', [])[0].get('rowSet', []))} records in {fetch_time:.2f} seconds.")
-        data = response.json()
-        game_logs = data.get("resultSets", [])[0].get("rowSet", [])
+        game_logs = response.json().get("resultSets", [])[0].get("rowSet", [])
+        st.success(f"API request successful. Fetched {len(game_logs)} records in {fetch_time:.2f} seconds.")
         if not game_logs:
             st.warning("No game logs found in the response.")
             return []
@@ -77,18 +89,17 @@ def fetch_wnba_data():
             response = session.get(url, params=params, headers=headers, timeout=60)
             response.raise_for_status()
             fetch_time = time.time() - start_time
-            st.success(f"API request successful (requests). Fetched {len(response.json().get('resultSets', [])[0].get('rowSet', []))} records in {fetch_time:.2f} seconds.")
-            data = response.json()
-            game_logs = data.get("resultSets", [])[0].get("rowSet", [])
+            game_logs = response.json().get("resultSets", [])[0].get("rowSet", [])
+            st.success(f"API request successful (requests). Fetched {len(game_logs)} records in {fetch_time:.2f} seconds.")
             if not game_logs:
                 st.warning("No game logs found in the response.")
                 return []
             return game_logs
         except requests.Timeout:
-            st.error("Request timed out after 60 seconds. Try uploading a local JSON file, checking your network, or adding a cf_clearance cookie.")
+            st.error("Request timed out after 60 seconds. Try uploading a local JSON file or checking your network.")
             return []
         except requests.HTTPError as e:
-            st.error(f"HTTP error: {e}. The API may require a cf_clearance cookie. See instructions below.")
+            st.error(f"HTTP error: {e}. Verify cookies and headers.")
             return []
         except requests.RequestException as e:
             st.error(f"Request failed: {e}. Possible API or network issue.")
@@ -107,7 +118,11 @@ def create_dataframe(game_logs):
         "TO_Rank", "PF_Rank", "PTS_Rank", "PLUS_MINUS_Rank", "Fantasy_Score_Rank",
         "Double_Double_Rank", "Triple_Double_Rank", "Minutes_Formatted"
     ]
-    return pd.DataFrame(game_logs, columns=columns)
+    try:
+        return pd.DataFrame(game_logs, columns=columns)
+    except ValueError:
+        st.error("Data structure mismatch. The API response for MeasureType=Scoring may have different columns. Please verify the response format.")
+        return pd.DataFrame()
 
 # Function to convert DataFrame to CSV for download
 def convert_to_csv(df):
@@ -116,15 +131,16 @@ def convert_to_csv(df):
     return csv_buffer.getvalue()
 
 # Streamlit app
-st.title("WNBA 2025 Player Game Logs")
+st.title("WNBA 2025 Player Game Logs (Scoring)")
 
-# Instructions for cf_clearance cookie
+# Instructions for troubleshooting
 st.markdown("""
 **Troubleshooting API Access**:
-If the API request fails, you may need a `cf_clearance` cookie:
-1. Open `https://stats.wnba.com/players/boxscores-traditional/` in Chrome.
-2. Press F12, go to Network tab, refresh, and find the `playergamelogs` request.
-3. Copy the `Cookie` header (e.g., `cf_clearance=...`) and add it to the `headers` in the code.
+If the API request fails:
+1. Verify the `Cookie` header in the code matches a recent browser request.
+2. Open `https://stats.wnba.com/players/boxscores-scoring/` in Chrome, press F12, go to Network tab, refresh, and find the `playergamelogs` request.
+3. Copy the `Cookie` header and update the `headers` in the code.
+4. Upload a local JSON file as a fallback.
 """)
 
 # Option to upload local JSON file
@@ -154,44 +170,45 @@ if game_logs:
     with st.spinner("Converting data to DataFrame..."):
         df = create_dataframe(game_logs)
 
-    # Display total number of records
-    st.write(f"Total records fetched: {len(df)}")
-
-    # Display filters
-    st.subheader("Filter Data")
-    player_filter = st.selectbox("Select Player", options=["All"] + sorted(df["Player_Name"].unique()))
-    team_filter = st.selectbox("Select Team", options=["All"] + sorted(df["Team_Abbreviation"].unique()))
-
-    # Apply filters
-    filtered_df = df
-    if player_filter != "All":
-        filtered_df = filtered_df[filtered_df["Player_Name"] == player_filter]
-    if team_filter != "All":
-        filtered_df = filtered_df[filtered_df["Team_Abbreviation"] == team_filter]
-
-    # Display first 1000 records
-    st.subheader("Game Log Data (First 1000 Records)")
-    display_df = filtered_df.iloc[:1000]
-    st.write(f"Displaying {len(display_df)} records (out of {len(filtered_df)} after filtering)")
-    st.dataframe(display_df, use_container_width=True)
-
-    # Download button for all records
-    st.subheader("Download Data")
-    csv_data = convert_to_csv(filtered_df)
-    st.download_button(
-        label=f"Download All {len(filtered_df)} Records as CSV",
-        data=csv_data,
-        file_name="wnba_player_gamelogs_2025_filtered.csv",
-        mime="text/csv"
-    )
-
-    # Visualization
-    if player_filter != "All":
-        st.subheader(f"Points Scored by {player_filter}")
-        player_data = filtered_df[["Game_Date", "PTS"]].copy()
-        player_data["Game_Date"] = pd.to_datetime(player_data["Game_Date"])
-        player_data = player_data.sort_values("Game_Date")
-        st.line_chart(player_data.set_index("Game_Date")["PTS"])
+    if not df.empty:
+        # Display total number of records
+        st.write(f"Total records fetched: {len(df)}")
+
+        # Display filters
+        st.subheader("Filter Data")
+        player_filter = st.selectbox("Select Player", options=["All"] + sorted(df["Player_Name"].unique()))
+        team_filter = st.selectbox("Select Team", options=["All"] + sorted(df["Team_Abbreviation"].unique()))
+
+        # Apply filters
+        filtered_df = df
+        if player_filter != "All":
+            filtered_df = filtered_df[filtered_df["Player_Name"] == player_filter]
+        if team_filter != "All":
+            filtered_df = filtered_df[filtered_df["Team_Abbreviation"] == team_filter]
+
+        # Display first 1000 records
+        st.subheader("Game Log Data (First 1000 Records)")
+        display_df = filtered_df.iloc[:1000]
+        st.write(f"Displaying {len(display_df)} records (out of {len(filtered_df)} after filtering)")
+        st.dataframe(display_df, use_container_width=True)
+
+        # Download button for all records
+        st.subheader("Download Data")
+        csv_data = convert_to_csv(filtered_df)
+        st.download_button(
+            label=f"Download All {len(filtered_df)} Records as CSV",
+            data=csv_data,
+            file_name="wnba_player_gamelogs_2025_filtered.csv",
+            mime="text/csv"
+        )
+
+        # Visualization
+        if player_filter != "All":
+            st.subheader(f"Points Scored by {player_filter}")
+            player_data = filtered_df[["Game_Date", "PTS"]].copy()
+            player_data["Game_Date"] = pd.to_datetime(player_data["Game_Date"])
+            player_data = player_data.sort_values("Game_Date")
+            st.line_chart(player_data.set_index("Game_Date")["PTS"])
 else:
     st.warning("No data available to display. Check error messages above or upload a JSON file.")