Create app.py

app.py

@@ -0,0 +1,342 @@
+import streamlit as st
+import datetime
+import requests
+import pandas as pd
+from streamlit_calendar import calendar
+
+API_KEY = "b431ec171262073909ebf8c0c4afba71"
+
+def parse_time_field(date_str, time_str):
+    """
+    Convert a date string plus partial time info into date-time strings.
+    Example: date='2023-08-17', time='pre market' -> '2023-08-17T07:00:00'
+    """
+    if time_str and ":" in time_str:
+        return f"{date_str}T{time_str}:00", f"{date_str}T{time_str}:00"
+    else:
+        time_map = {
+            "bmo": "06:00:00",
+            "amc": "18:00:00",
+            "pre market": "07:00:00",
+            "post market": "16:00:00",
+            "during market": "10:00:00",
+        }
+        chosen_time = time_map.get(time_str.lower(), "00:00:00")
+        return f"{date_str}T{chosen_time}", f"{date_str}T{chosen_time}"
+
+def fetch_earnings(from_date, to_date, limit):
+    url = (
+        f"https://financialmodelingprep.com/api/v4/earning-calendar-confirmed"
+        f"?from={from_date}&to={to_date}&limit={limit}&apikey={API_KEY}"
+    )
+    resp = requests.get(url)
+    if resp.status_code == 200:
+        return resp.json()
+    return []
+
+def fetch_dividends(from_date, to_date):
+    url = (
+        f"https://financialmodelingprep.com/api/v3/stock_dividend_calendar"
+        f"?from={from_date}&to={to_date}&apikey={API_KEY}"
+    )
+    resp = requests.get(url)
+    if resp.status_code == 200:
+        return resp.json()
+    return []
+
+def fetch_splits(from_date, to_date):
+    url = (
+        f"https://financialmodelingprep.com/api/v3/stock_split_calendar"
+        f"?from={from_date}&to={to_date}&apikey={API_KEY}"
+    )
+    resp = requests.get(url)
+    if resp.status_code == 200:
+        return resp.json()
+    return []
+
+def fetch_earnings_ticker(symbol, limit):
+    url = (
+        f"https://financialmodelingprep.com/api/v3/historical/earning_calendar/"
+        f"{symbol}?limit={limit}&apikey={API_KEY}"
+    )
+    resp = requests.get(url)
+    if resp.status_code == 200:
+        return resp.json()
+    return []
+
+def fetch_dividends_ticker(symbol):
+    url = (
+        f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_dividend/"
+        f"{symbol}?apikey={API_KEY}"
+    )
+    resp = requests.get(url)
+    if resp.status_code == 200:
+        return resp.json()
+    return {}
+
+def fetch_splits_ticker(symbol):
+    url = (
+        f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_split/"
+        f"{symbol}?apikey={API_KEY}"
+    )
+    resp = requests.get(url)
+    if resp.status_code == 200:
+        return resp.json()
+    return {}
+
+def main():
+    # Updated title to reflect more events
+    st.set_page_config(page_title="Earnings, Dividends, and Splits Calendar", layout="wide")
+
+    # Initialize session state
+    if "general_data" not in st.session_state:
+        st.session_state["general_data"] = []
+    if "ticker_data" not in st.session_state:
+        st.session_state["ticker_data"] = []
+
+    st.title("Corporate Events Calendar")
+    st.write("This calendar shows earnings, dividends, and stock splits. "
+             "Use the selections on the sidebar to narrow results.")
+
+    st.sidebar.title("Input Parameters")
+    
+    with st.sidebar.expander("How to Use", expanded=False):
+        st.write(
+            """
+            1. Select "General Calendar" or "Ticker Calendar."
+            2. Check which event types you want (earnings, dividends, splits).
+            3. For the general view, choose a date range and limit.
+            4. For the ticker view, choose a symbol and limit.
+            5. Click the button to see results.
+            """
+        )
+    with st.sidebar.expander("", expanded=True):
+        page_choice = st.radio("Page", ["General Calendar", "Ticker Calendar"])
+
+    # Default date range
+    today = datetime.date.today()
+    one_month_later = today + datetime.timedelta(days=30)
+
+    if page_choice == "General Calendar":
+        with st.sidebar.expander("Event Type", expanded=True):
+            include_earnings = st.checkbox("Include Earnings", value=True, help="If checked, will fetch earnings within the date range.")
+            include_dividends = st.checkbox("Include Dividends", value=True, help="If checked, will fetch dividends within the date range.")
+            include_splits = st.checkbox("Include Stock Splits", value=True, help="If checked, will fetch stock splits within the date range.")
+
+        with st.sidebar.expander("Parameters", expanded=True):
+            from_date = st.date_input("From Date", value=today, help="Start date range")
+            to_date = st.date_input("To Date", value=one_month_later, help="End date range")
+            limit_val = st.number_input("Limit", value=200, help="Number of earnings records to retrieve")
+
+        if st.sidebar.button("Retrieve Calendar", key="fetch_general"):
+            # Collect everything in one list
+            all_events = []
+
+            if include_earnings:
+                earnings_data = fetch_earnings(from_date, to_date, limit_val)
+                for item in earnings_data:
+                    date_str = item.get("date", "")
+                    time_str = item.get("time", "")
+                    start_dt, end_dt = parse_time_field(date_str, time_str)
+                    sym = item.get("symbol", "")
+                    event_title = f"[Earnings] {sym}"
+                    # Store entire item plus fields for the calendar
+                    event_entry = {
+                        "start": start_dt,
+                        "end": end_dt,
+                        "title": event_title,
+                        "color": "#3D9DF3",
+                        "eventType": "Earnings"
+                    }
+                    # Merge item fields directly
+                    event_entry.update(item)
+                    all_events.append(event_entry)
+
+            if include_dividends:
+                div_data = fetch_dividends(from_date, to_date)
+                for item in div_data:
+                    date_str = item.get("date", "")
+                    start_dt = f"{date_str}T00:00:00"
+                    end_dt = f"{date_str}T23:59:59"
+                    sym = item.get("symbol", "")
+                    event_title = f"[Dividend] {sym}"
+                    event_entry = {
+                        "start": start_dt,
+                        "end": end_dt,
+                        "title": event_title,
+                        "color": "#80C080",
+                        "eventType": "Dividend"
+                    }
+                    event_entry.update(item)
+                    all_events.append(event_entry)
+
+            if include_splits:
+                split_data = fetch_splits(from_date, to_date)
+                for item in split_data:
+                    date_str = item.get("date", "")
+                    start_dt = f"{date_str}T00:00:00"
+                    end_dt = f"{date_str}T23:59:59"
+                    sym = item.get("symbol", "")
+                    event_title = f"[Split] {sym}"
+                    event_entry = {
+                        "start": start_dt,
+                        "end": end_dt,
+                        "title": event_title,
+                        "color": "#FFC870",
+                        "eventType": "Split"
+                    }
+                    event_entry.update(item)
+                    all_events.append(event_entry)
+
+            st.session_state["general_data"] = all_events
+
+        st.subheader("General Calendar Results")
+
+        data_general = st.session_state["general_data"]
+        if data_general:
+            # Prepare events for calendar
+            calendar_events = []
+            for ev in data_general:
+                event_for_cal = {
+                    "title": ev["title"],
+                    "start": ev["start"],
+                    "end": ev["end"],
+                    "color": ev["color"],
+                }
+                calendar_events.append(event_for_cal)
+
+            cal_options = {
+                "initialView": "dayGridMonth",
+                "headerToolbar": {
+                    "left": "today prev,next",
+                    "center": "title",
+                    "right": "dayGridDay,dayGridWeek,dayGridMonth",
+                },
+                "navLinks": True,
+            }
+
+            # Show calendar
+            calendar(events=calendar_events, options=cal_options, key="general_cal")
+
+            # Show entire dataframe
+            st.write("Data Table")
+            df_g = pd.DataFrame(data_general)
+            st.dataframe(df_g, use_container_width=True)
+        else:
+            st.write("No data retrieved. Select event types and click the button.")
+
+    else:
+    
+        with st.sidebar.expander("Event Type", expanded=True):
+        # Ticker Calendar
+            include_earnings_t = st.checkbox("Include Earnings", value=True, help="If checked, will fetch historical earnings data.")
+            include_dividends_t = st.checkbox("Include Dividends", value=True, help="If checked, will fetch historical dividends data.")
+            include_splits_t = st.checkbox("Include Splits", value=True, help="If checked, will fetch historical stock splits data.")
+            
+        with st.sidebar.expander("Parameters", expanded=True):
+            symbol = st.text_input("Symbol", value="AAPL", help="Enter a stock ticker")
+            limit_val_ticker = st.number_input("Limit", value=50, help="Number of earnings records to retrieve")
+
+        if st.sidebar.button("Retrieve Ticker Calendar", key="fetch_ticker"):
+            ticker_events = []
+
+            if include_earnings_t:
+                data_earnings_t = fetch_earnings_ticker(symbol, limit_val_ticker)
+                for item in data_earnings_t:
+                    date_str = item.get("date", "")
+                    time_str = item.get("time", "")
+                    start_dt, end_dt = parse_time_field(date_str, time_str)
+                    event_title = f"[Earnings] {symbol}"
+                    event_info = {
+                        "start": start_dt,
+                        "end": end_dt,
+                        "title": event_title,
+                        "color": "#3D9DF3",
+                        "eventType": "Earnings"
+                    }
+                    event_info.update(item)
+                    ticker_events.append(event_info)
+
+            if include_dividends_t:
+                data_div_t = fetch_dividends_ticker(symbol)
+                # The response is a dict with keys like "symbol" and "historical"
+                historical_divs = data_div_t.get("historical", [])
+                for item in historical_divs:
+                    date_str = item.get("date", "")
+                    start_dt = f"{date_str}T00:00:00"
+                    end_dt = f"{date_str}T23:59:59"
+                    event_title = f"[Dividend] {symbol}"
+                    event_info = {
+                        "start": start_dt,
+                        "end": end_dt,
+                        "title": event_title,
+                        "color": "#80C080",
+                        "eventType": "Dividend"
+                    }
+                    event_info.update(item)
+                    ticker_events.append(event_info)
+
+            if include_splits_t:
+                data_split_t = fetch_splits_ticker(symbol)
+                # The response is a dict with keys like "symbol" and "historical"
+                historical_splits = data_split_t.get("historical", [])
+                for item in historical_splits:
+                    date_str = item.get("date", "")
+                    start_dt = f"{date_str}T00:00:00"
+                    end_dt = f"{date_str}T23:59:59"
+                    event_title = f"[Split] {symbol}"
+                    event_info = {
+                        "start": start_dt,
+                        "end": end_dt,
+                        "title": event_title,
+                        "color": "#FFC870",
+                        "eventType": "Split"
+                    }
+                    event_info.update(item)
+                    ticker_events.append(event_info)
+
+            st.session_state["ticker_data"] = ticker_events
+
+        st.subheader("Ticker Calendar Results")
+
+        data_ticker = st.session_state["ticker_data"]
+        if data_ticker:
+            # Prepare events
+            calendar_events_t = []
+            for ev in data_ticker:
+                calendar_events_t.append({
+                    "title": ev["title"],
+                    "start": ev["start"],
+                    "end": ev["end"],
+                    "color": ev["color"]
+                })
+
+            cal_options_ticker = {
+                "initialView": "dayGridMonth",
+                "headerToolbar": {
+                    "left": "today prev,next",
+                    "center": "title",
+                    "right": "dayGridDay,dayGridWeek,dayGridMonth",
+                },
+                "navLinks": True,
+            }
+
+            calendar(events=calendar_events_t, options=cal_options_ticker, key="ticker_cal")
+
+            st.write("Data Table")
+            df_t = pd.DataFrame(data_ticker)
+            st.dataframe(df_t, use_container_width=True)
+        else:
+            st.write("No data retrieved. Check your options and press the button.")
+
+if __name__ == "__main__":
+    main()
+    
+    
+hide_streamlit_style = """
+<style>
+#MainMenu {visibility: hidden;}
+footer {visibility: hidden;}
+</style>
+"""
+st.markdown(hide_streamlit_style, unsafe_allow_html=True)