Update app

Dockerfile

@@ -1,25 +1,18 @@
-# app/Dockerfile
-
 FROM python:3.9-slim
 
-WORKDIR /app
-
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    software-properties-common \
-    git \
-    && rm -rf /var/lib/apt/lists/*
-
-#RUN git clone https://github.com/streamlit/streamlit-example.git .
-
-COPY . /app
-
-RUN pip3 install --upgrade pip
+COPY requirements.txt requirements.txt
 RUN pip3 install -r requirements.txt
 
+WORKDIR /data
+COPY /data /data
+
+WORKDIR /app
+COPY /app /app
+
+WORKDIR /
+
 EXPOSE 8501
 
 HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
 
-ENTRYPOINT ["streamlit", "run", "main.py", "--server.port=8501", "--server.address=0.0.0.0"]
+ENTRYPOINT ["streamlit", "run", "/app/main.py", "--server.port=8501", "--server.address=0.0.0.0"]

app/main.py

@@ -0,0 +1,40 @@
+import streamlit as st
+from streamlit_folium import st_folium
+import folium
+import glob
+import geopandas as gpd
+import pandas as pd
+import pathlib
+
+
+if __name__ == "__main__":
+    
+    """
+    # Lithos Carbon Shapefile Viewer
+    """
+
+    # glob shapefiles to load
+    current_dir = pathlib.Path().resolve()
+    data_dir = current_dir / "data"
+    shapefiles_list = sorted(data_dir.glob("*.shp"))
+
+    # user selects which shapefiels to plot
+    selected_shapefiles = st.pills("Choose shapefiles to view on the map", shapefiles_list, selection_mode="multi")
+
+    # load and merge shapefiles
+    if selected_shapefiles:
+        gdf = gpd.GeoDataFrame()    
+        gdf = gpd.GeoDataFrame(pd.concat([gpd.read_file(i) for i in selected_shapefiles], ignore_index=True), crs=gpd.read_file(selected_shapefiles[0]).crs)        
+
+
+        # Create a Folium map
+        m = folium.Map(location=[gdf.centroid.y.mean(), gdf.centroid.x.mean()], zoom_start=13)
+        folium.GeoJson(gdf.to_json()).add_to(m)
+
+
+        # Display the map in Streamlit
+        st_folium(m)
+
+        # Display data in table format
+        st.write(gdf)
+

app/readme.md

@@ -0,0 +1,53 @@
+## Requirements
+
+Build a simple application using ***existing technologies** (hint: we don’t need you to build a shapefile parser from scratch)* that will allow shapefiles to be visualized on a map. Shapefile data does not need to be persisted into a database, this application should be ephemeral and have the potential to be entirely offline.
+
+You’re free to use the framework of your choice. We want to understand how you approach this from a product perspective. Remember, we’re chasing ease of use!
+
+**Please don’t spend more than 1-2 hours on this exercise. Get something working, and we can have a discussion about features that would have followed.**
+
+---
+
+### Running the app via Docker:
+```
+chmod u+x build_and_run.sh
+./build_and_run_docker.sh
+```
+- Visit http://0.0.0.0:8501
+- Ctrl + c to quit
+
+### Running the app via Python with virtual env:
+```
+python3 -m venv venv
+. venv/bin/activate
+pip install -r requirements
+streamlit run main.py --server.port=8501 --server.address=0.0.0.0
+```
+- Visit http://0.0.0.0:8501
+- Ctrl + c to quit
+
+
+---
+
+### My dev log:
+- streamlit getting started (done)
+- display a shapefile
+  - streamlit plotting doesn't work out of the box for polygons
+  - geopandas has a geopandas dataframe, dartaframes required for st.map
+  - st.map is a st.pydeck_chart wrapper 
+    - st.pydeck_chart uses mapbox
+    - may need mapbox token - *Mapbox requires users to register and provide a token before users can request map tiles. Currently, Streamlit provides this token for you, but this could change at any time.*
+    - Can I plot polygons or just points?
+    - test data doesn't plot immediately    
+  - Folium can plot polygons in streamlit via geojson
+    - requires 3rd party plugin st_folium
+    - ok I have folium plotting test data
+  - easiest/least depedencies to convert shapefiles to geojson?
+    - easy/1-million dependencies: geopands+pandas
+      - already have that working so will leave it and discuss other options with Evan
+  - add sidebar for my notes and readme
+
+- things to add
+  - add a legend
+  - better theme
+  - deterministic map config toi prevent random width/height based on geo data etc

build_and_run.sh

@@ -1,2 +0,0 @@
-docker build -t lithos-app .
-docker run -p 8501:8501 lithos-app

build_and_run_docker.sh

@@ -0,0 +1,4 @@
+#!/usr/bin/sh
+
+docker build -t lithos-app .
+docker run -p 8501:8501 lithos-app

build_and_run_python.sh

@@ -0,0 +1,7 @@
+#!/usr/bin/sh
+
+rm -rf venv
+python3 -m venv venv
+. venv/bin/activate
+pip install -r requirements.txt
+streamlit run ./app/main.py --server.port=8501 --server.address=0.0.0.0

data/farm_fields.cpg

@@ -0,0 +1 @@
+UTF-8

data/farm_fields.prj

@@ -0,0 +1 @@
+GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

data/soil_samples.cpg

@@ -0,0 +1 @@
+UTF-8

data/soil_samples.prj

@@ -0,0 +1 @@
+GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

main.py

@@ -1,37 +0,0 @@
-from collections import namedtuple
-import altair as alt
-import math
-import pandas as pd
-import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:
-
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-with st.echo(code_location='below'):
-   total_points = st.slider("Number of points in spiral", 1, 5000, 2000)
-   num_turns = st.slider("Number of turns in spiral", 1, 100, 9)
-
-   Point = namedtuple('Point', 'x y')
-   data = []
-
-   points_per_turn = total_points / num_turns
-
-   for curr_point_num in range(total_points):
-      curr_turn, i = divmod(curr_point_num, points_per_turn)
-      angle = (curr_turn + 1) * 2 * math.pi * i / points_per_turn
-      radius = curr_point_num / total_points
-      x = radius * math.cos(angle)
-      y = radius * math.sin(angle)
-      data.append(Point(x, y))
-
-   st.altair_chart(alt.Chart(pd.DataFrame(data), height=500, width=500)
-      .mark_circle(color='#0068c9', opacity=0.5)
-      .encode(x='x:Q', y='y:Q'))

readme.md

@@ -1,21 +0,0 @@
-## Requirements
-
-Build a simple application using ***existing technologies** (hint: we don’t need you to build a shapefile parser from scratch)* that will allow shapefiles to be visualized on a map. Shapefile data does not need to be persisted into a database, this application should be ephemeral and have the potential to be entirely offline.
-
-You’re free to use the framework of your choice. We want to understand how you approach this from a product perspective. Remember, we’re chasing ease of use!
-
-**Please don’t spend more than 1-2 hours on this exercise. Get something working, and we can have a discussion about features that would have followed.**
-
-
-
-### Dev steps:
-- streamlit getting started (done)
-- display a shapefile
-- add a legend
-- add feature to select shape file
-
-
-### Running the app:
-- chmod u+x build_and_run.sh
-- ./build_and_run.sh
-- Visit http://0.0.0.0:8501

requirements.txt

@@ -1 +1,4 @@
-streamlit==1.41.1
+streamlit==1.41.1
+streamlit-folium==0.24.0
+pandas==2.2.3
+geopandas==1.0.1