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| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| import datetime | |
| import hopsworks | |
| from functions import figure, util | |
| import os | |
| import pickle | |
| import plotly.express as px | |
| import json | |
| # Set up | |
| api_key = os.getenv('HOPSWORKS_API_KEY') | |
| project_name = os.getenv('HOPSWORKS_PROJECT') | |
| project = hopsworks.login(project=project_name, api_key_value=api_key) | |
| fs = project.get_feature_store() | |
| secrets = util.secrets_api(project.name) | |
| feature_view = fs.get_feature_view( | |
| name='air_quality_fv', | |
| version=1, | |
| ) | |
| df = feature_view.get_batch_data(start_time=None, end_time=None, read_options=None).sort_values(by='date') | |
| today = datetime.datetime.now() - datetime.timedelta(0) | |
| st.set_page_config( | |
| page_title="Air Quality Prediction", | |
| page_icon="🧊", | |
| layout="wide", | |
| initial_sidebar_state="expanded", | |
| menu_items={ | |
| 'About': "# Air Quality Prediction" | |
| } | |
| ) | |
| st.title('Lahore Air Quality') | |
| st.subheader('Forecast and hindcast') | |
| st.subheader('Unit: PM25 - particle matter of diameter < 2.5 micrometers') | |
| #pickle_file_path = 'air_quality_df.pkl' | |
| # pickle_file_path = 'outcome_df.pkl' | |
| # with open(pickle_file_path, 'rb') as file: | |
| # st.session_state.df = pickle.load(file).sort_values(by="date") | |
| fig = figure.plot(df) | |
| # Render the chart in Streamlit | |
| st.plotly_chart(fig) |