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Browse files- README.md +5 -4
- app.py +64 -0
- requirements.txt +3 -0
README.md
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---
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title: Electricity
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sdk: gradio
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sdk_version: 3.
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app_file: app.py
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pinned: false
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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title: Electricity
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emoji: π
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colorFrom: purple
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colorTo: yellow
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sdk: gradio
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sdk_version: 3.5
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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import pandas as pd
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from pandas.tseries.holiday import USFederalHolidayCalendar as calendar
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import hopsworks
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import joblib
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import datetime
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import os
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import requests
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project = hopsworks.login()
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fs = project.get_feature_store()
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mr = project.get_model_registry()
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model = mr.get_model("ny_elec_model", version=1)
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model_dir = model.download()
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model = joblib.load(model_dir + "/ny_elec_model.pkl")
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def predict():
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today = get_date()
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temp = get_temp(today)
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df = pd.DataFrame({"date": [today], "temperature": [temp]})
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df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True)
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df['day'] = df['date'].dt.dayofweek
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df['month'] = df['date'].dt.month
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holidays = calendar().holidays(start=df['date'].min(), end=df['date'].max())
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df['holiday'] = df['date'].isin(holidays).astype(int)
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demand = model.predict(df.drop(columns=['date']))[0]
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return [today, temp, demand]
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def get_date():
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today = datetime.datetime.today()
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return today.date()
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def get_temp(date):
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weather_api_key = os.environ.get('WEATHER_API_KEY')
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weather_url = ('http://api.weatherapi.com/v1/history.json'
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'?key={}'
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'&q=New%20York,%20USA'
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'&dt={}').format(weather_api_key, date)
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return requests.get(weather_url).json()['forecast']['forecastday'][0]['day']['avgtemp_c']
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demo = gr.Interface(
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fn = predict,
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title = "NY Electricity Demand Prediction",
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description ="Daily NY Electricity Demand Prediction",
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allow_flagging = "never",
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inputs = [],
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outputs = [
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gr.Textbox(label="Date"),
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gr.Textbox(label="Temperature forecast [β]"),
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gr.Textbox(label="Predicted demand [MWh]"),
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]
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)
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# TODO: we have only the demand predictions for two days ago, so we have two options
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# - skip EIA demand forecast (no comparison)
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# - show prediction for two days ago
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demo.launch()
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requirements.txt
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hopsworks
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joblib
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pandas
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