app copy.py

import streamlit as st
import warnings
warnings.filterwarnings('ignore')
import pandas as pd
import geopandas as gpd
from difflib import get_close_matches
import tempfile


from io import BytesIO



def convert_to_gdf(uploaded_file):
    # Read the file using BytesIO
    file_buffer = BytesIO(uploaded_file.read())

    # Detect file type and load accordingly
    if uploaded_file.name.endswith('.shp'):
        gdf = gpd.read_file(file_buffer)
    elif uploaded_file.name.endswith(('.geojson', '.json')):
        gdf = gpd.read_file(file_buffer, driver='GeoJSON')
    else:
        raise ValueError("Unsupported file format")

    return gdf

# add logo D:\Terradot\repos\crea-carbon-model\app\logo.jpg

st.sidebar.image('logo.jpg', width=200)
st.sidebar.title('Proyecto Crea')
st.sidebar.write('Solo uso interno')
# add sidebar with 2 upload buttons
st.sidebar.header('Upload Files')
uploaded_file = st.sidebar.file_uploader('Upload your shapefile', type=['shp', 'geojson', 'json'], disabled = True)
uploaded_file2 = st.sidebar.file_uploader('Upload your csv file', type=['csv'], disabled = True)

if uploaded_file is not None:
        lotes_gdf = convert_to_gdf(uploaded_file)
        st.write(lotes_gdf)

if uploaded_file2 is not None:
    # read csv and create dataframe
    obs_df_2023 = pd.read_csv(uploaded_file2)


# add Test button
test = True #st.sidebar.button('Test')

if 'key' not in st.session_state:
    st.session_state['key'] = None

if 'lote_gdf' not in st.session_state:
    st.session_state['lote_gdf'] = None

if test:

    lotes_gdf = gpd.read_file('data/lotes espacio crea_empresa.shp', encoding='utf-8')
    obs_df_2023 = pd.read_csv('data/obs_df_2023_12_1.csv')
    obs_df_2023.fillna('-', inplace=True)
    obs_df_2023.Campo = obs_df_2023.Campo.astype('str')

    empresa_obs = obs_df_2023.EMPRESA.unique().tolist()
    # create a state variable to hold the current value of key variable



    col1, col2,col3 = st.columns(3)

    with col1:
        st.header('EMPRESA')
        selected_company = st.selectbox(f'Seleccione empresa', empresa_obs, index= 0)

    # filter dataframe by selected company
    obs_df_2023 = obs_df_2023[obs_df_2023['EMPRESA'] == selected_company]
    
    if st.session_state['lote_gdf'] is not None:
        lotes_gdf = st.session_state['lote_gdf']
    else:
        lotes_gdf = lotes_gdf[lotes_gdf['empresa'] == selected_company]
        st.session_state['lote_gdf'] = lotes_gdf
    

    campo_obs = obs_df_2023.Campo.unique().tolist()
    campo_gdf = lotes_gdf.campo.unique().tolist()
    # Initialize an empty dictionary
    similar_dict = {}
    N = 3
    CUTOFF = 0.72
    # Loop through each item in the template list
    for item in campo_gdf:
        # normalize the stings to lowercase and remove punctuation in campo_obs
        campo_obs_norm = [str(c).lower() for c in campo_obs]
        campo_obs_norm = [c.replace('.', ' ') for c in campo_obs_norm]

        # Find the most similar item in df_columns list
        similar_items = get_close_matches(item, campo_obs_norm, N, CUTOFF)

        # get the index of the most similar item
        similar_items_idx = [campo_obs_norm.index(i) for i in similar_items]

        # get the most similar item in the original list
        similar_items = [campo_obs[i] for i in similar_items_idx]

        # If a similar item is found, add to the dictionary
        if similar_items:
            similar_dict[item] = similar_items[0]
        else:
            # If no similar item is found, set value as "no match"
            similar_dict[item] = "no match"



    similar_dict_df = pd.DataFrame.from_dict(similar_dict, orient='index').reset_index()
    similar_dict_df.columns = ['gdf','obs']
    # campo_obs = [str(c) for c in campo_obs]


    # campo_obs.sort(key=str.lower)
    campo_obs.insert(0, 'no match')

    all_keys = similar_dict_df['gdf'].unique().tolist()

    # Fields

    lotes_gdf['campo_obs'] = lotes_gdf['campo'].map(similar_dict)

    cutoff = 0.3

    def on_click_field(*args):
        # key, field, selected_value = key
        def inner():
            # st.session_state['key'] = key
            print(args)
            
        return inner

    def show_field(key):
        key, selected_value = key
        lote_obs = obs_df_2023[obs_df_2023['Campo'] == selected_value]['Lote'].unique().tolist()
        lote_obs.insert(0, 'no match')
        with col3:
            # st.header(st.session_state['key'])
            st.header('Lote')
            df_field = lotes_gdf[lotes_gdf['campo'] == key]
            fields = df_field['lote'].unique().tolist()
               
            for j,field in enumerate(fields):
                similar_items = get_close_matches(field, lote_obs, 3, 0.70)
                default = similar_items[0] if similar_items else 0
                # selected_value = st.multiselect(f'{field} (.shp):', lote_obs, default=default, key='field'+str(j))
                selected_value = st.selectbox(f'{field} (.shp):', lote_obs, index = lote_obs.index(default)  , key='field'+str(j), on_change=on_click_field(key, field, selected_value))

                lotes_gdf.loc[(lotes_gdf['campo'] == key) & (lotes_gdf['lote'] == field), 'lote_obs'] = selected_value
            
                # st.session_state['lote_gdf'] = lotes_gdf



    def on_click(key):
        def inner():
            st.session_state['key'] = key
            show_field(key)
        return inner

    with col2:
        st.header('Campo')
        for i, key in enumerate(all_keys):
            selected_value = st.selectbox(f'{key}:', campo_obs, index=campo_obs.index(similar_dict_df[similar_dict_df['gdf'] == key]['obs'].values[0]))
            # selected_value = st.multiselect(f'{key} (.shp):', campo_obs, default=similar_dict_df[similar_dict_df['gdf'] == key]['obs'].values[0], key=i)
            lotes_gdf.loc[(lotes_gdf['campo'] == key) & (lotes_gdf['empresa'] == selected_company), 'campo_obs'] = similar_dict_df[similar_dict_df['gdf'] == key]['obs'].values[0]

            if selected_value:
                similar_dict_df.loc[similar_dict_df['gdf'] == key, 'obs'] = selected_value
                value = selected_value
                lotes_gdf.loc[(lotes_gdf['campo'] == key) & (lotes_gdf['empresa'] == selected_company), 'campo_obs'] = selected_value
                
            else:
                # similar_dict_df.loc[similar_dict_df['gdf'] == key, 'obs'] = 'no match'
                value = similar_dict_df.loc[similar_dict_df['gdf'] == key, 'obs']
                lotes_gdf.loc[(lotes_gdf['campo'] == key) & (lotes_gdf['empresa'] == selected_company), 'campo_obs'] = value

            st.session_state['lote_gdf'] = lotes_gdf
            st.button('Show Fields', key=key, on_click=on_click([key,value]))


        # st.dataframe(similar_dict_df)
        # if st.button('Show Fields'):
        #     st.dataframe(similar_dict_df)

    # add download button
            

            

st.sidebar.download_button(
        label="Download GeoJSON",
        data=lotes_gdf.to_json().encode('utf-8'),
        file_name=f'{selected_company}.geojson',
        # mime='text/csv',
        mime = 'application/json',
    )