src/cli.py

src/dev_streamlit.py

@@ -2,15 +2,22 @@
 
 import numpy as np
 import pandas as pd
+import sys
+from pathlib import Path
 import streamlit as st
+import pydeck as pdk
+
+sys.path.append(str(Path(__file__).parent.parent))
+
+from src import api, cli
 
 # NOTE: This file is for testing purposes. Do not use it in production.
 
 # Page Configuration ###
-title = "Sample Dashboard"
+title = "cli-surf"
 st.set_page_config(
     page_title=title,
-    page_icon="🌈",
+    page_icon="🌊",
     layout="wide",
 )
 st.title(title)
@@ -30,7 +37,7 @@
 )
 
 # progress bar
-st.write("Starting a long computation...")
+# st.write("Loading...")
 
 latest_iteration = st.empty()
 bar = st.progress(0)
@@ -40,68 +47,85 @@
     bar.progress(i + 1)
     time.sleep(0.01)
 
-st.write("...and now we're done!")
+# st.write("...and now we're done!")
 
 # Map
-st.title("My first app")
+# st.title("Surf Spot")
 
-map_data = pd.DataFrame(
-    np.random.randn(500, 2) / [50, 50] + [35.7, 139.67], columns=["lat", "lon"]
-)
-st.map(map_data)
+st.caption("Enter a surf spot to see the map and forecast!")
+
+# User input location
+location = st.text_input("Surf Spot", placeholder="Enter surf spot!")
+
+# Checks if location has been entered. 
+# If True, gathers surf report and displays map
+if location:
+    location = "location=" + location
+    surf_report = cli.run(args=["placeholder",f"{location}"])
+    lat, long = surf_report["Lat"], surf_report["Long"]
+    map_data = pd.DataFrame(
+        np.random.randn(500, 2) / [50, 50] + [lat, long], columns=["lat", "lon"]
+    )
+    st.map(map_data)
+    forecasted_dates = [forecast['date'] for forecast in surf_report['Forecast']]
+    forecasted_heights = [forecast['height'] for forecast in surf_report['Forecast']]
+    forecasted_periods = [forecast['period'] for forecast in surf_report['Forecast']]
+
+
+
+
+st.write("# Surf Conditions")
+
+# Checks if location has been inputted. Loads map if True 
+if location: 
+    # table
+    df = pd.DataFrame({
 
+    'date': forecasted_dates,
+    'heights': forecasted_heights,
+    'periods': forecasted_periods
+    })
 
-# test by markdown
-st.write("# title")
+    df
 
-# note
-st.caption("note")
+    st.line_chart(df.rename(columns={'date':'index'}).set_index('index'))
 
-# images
-st.image("https://ul.h3z.jp/tbfgZLSX.webp")
 
-# table
-df = pd.DataFrame({
-    "first column": [1, 2, 3, 4],
-    "second column": [10, 20, 30, 40],
-})
-st.write(df)
 
-# chart
-st.line_chart(df)
 
-# input text
-name = st.text_input("name")
+# DEFAULTS
+# # input text
+# name = st.text_input("name")
 
-# integer input
-age = st.number_input("age", step=1)
+# # integer input
+# age = st.number_input("age", step=1)
 
-st.write(f"name: {name}")
-st.write(f"age: {age}")
+# st.write(f"name: {name}")
+# st.write(f"age: {age}")
 
-# button
-if st.button("Push"):
-    st.write("Pushed")
+# # button
+# if st.button("Push"):
+#     st.write("Pushed")
 
-# pulldown
-select = st.selectbox("Fruits", options=["apple", "banana", "strawberry"])
-st.write(select)
+# # pulldown
+# select = st.selectbox("Fruits", options=["apple", "banana", "strawberry"])
+# st.write(select)
 
-# pulldown multiple
-multi_select = st.multiselect("Color", options=["red", "blue", "yellow"])
-st.write(multi_select)
+# # pulldown multiple
+# multi_select = st.multiselect("Color", options=["red", "blue", "yellow"])
+# st.write(multi_select)
 
-# checkbox
-if st.checkbox("Show dataframe"):
-    chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"])
-    st.line_chart(chart_data)
+# # checkbox
+# if st.checkbox("Show dataframe"):
+#     chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"])
+#     st.line_chart(chart_data)
 
-# radio button
-radio = st.radio("Select", ["cat", "dog"])
-st.write(f"radio: {radio}")
+# # radio button
+# radio = st.radio("Select", ["cat", "dog"])
+# st.write(f"radio: {radio}")
 
-# file upload
-uploaded_file = st.file_uploader("Upload", type=["csv"])
-if uploaded_file:
-    dataframe = pd.read_csv(uploaded_file)
-    st.write(dataframe)
+# # file upload
+# uploaded_file = st.file_uploader("Upload", type=["csv"])
+# if uploaded_file:
+#     dataframe = pd.read_csv(uploaded_file)
+#     st.write(dataframe)

src/helper.py

@@ -239,9 +239,9 @@ def forecast_to_json(data, decimal):
     for i in range(len(dates)):
         forecast = {
             "date": str(dates[i].date()),
-            "surf height": round(float(surf_height[i]), decimal),
-            "swell direction": round(float(swell_direction[i]), decimal),
-            "swell period": round(float(swell_period[i]), decimal),
+            "height": round(float(surf_height[i]), decimal),
+            "direction": round(float(swell_direction[i]), decimal),
+            "period": round(float(swell_period[i]), decimal),
         }
         forecasts.append(forecast)