Data-Analytics/HW10/app.py at master · nickkeller21/Data-Analytics · GitHub

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import numpy as np

import sqlalchemy
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import Session
from sqlalchemy import create_engine, func

from flask import Flask, jsonify

import datetime as dt

### Constant
DAYS_PER_YR = 365

#################################################
# Database Setup
#################################################
engine = create_engine("sqlite:///Resources/hawaii.sqlite")

# reflect an existing database into a new model
Base = automap_base()
# reflect the tables
Base.prepare(engine, reflect=True)

# Save reference to the table
measurement = Base.classes.measurement
station = Base.classes.station
#################################################
# Flask Setup
#################################################
app = Flask(__name__)


#################################################
# Flask Routes
#################################################

@app.route("/")
def welcome():
    """List all available api routes."""
    return (
        f"Available Routes:<br/>"
        f"/api/v1.0/precipitation<br/>"
        f"/api/v1.0/stations<br/>"
        f"/api/v1.0/temp<br/>"
        f"/api/v1.0/<start><br/>"
        f"/api/v1.0/<start>/<end><br/>"
    )


@app.route("/api/v1.0/precipitation")
def precipitation():

    session = Session(engine)
    results = session.query(measurement.date, measurement.prcp ).all()

    session.close()

    data_dict = []

    for data in results:
         d = {'date': data.date , 'precipitation':data.prcp}
         data_dict.append(d)

    return jsonify(data_dict)

@app.route("/api/v1.0/stations")
def stations():

    session = Session(engine)

    results = session.query(station.station).all()

    session.close()

    all_names = list(np.ravel(results))

    return jsonify(all_names)

@app.route("/api/v1.0/temp")
def temp():

    session = Session(engine)

    tmp = session.query(measurement.date).order_by(measurement.date.desc()).first()
    last_date = str(tmp)[2:12]

    yr_last,mo_last,day_last = last_date.split("-")

    DAYS_PER_YR = 365
    last_date = dt.datetime(int(yr_last), int(mo_last), int(day_last))
    one_yr_b4_last_date = dt.datetime.date(last_date) - dt.timedelta(days= DAYS_PER_YR)

    results = session.query(measurement.date, measurement.tobs).\
    filter(measurement.date >= one_yr_b4_last_date).\
    order_by(measurement.date).all()

    session.close()
    data_dict = []

    for data in results:
        d = {'date': data.date ,
            'temp':data.tobs}
        data_dict.append(d)

    return jsonify(data_dict)

@app.route("/api/v1.0/<start_date>/<end_date>")
def temp_analysis(start_date,end_date):
    session = Session(engine)

    results = session.query(func.min(measurement.tobs), func.avg(measurement.tobs), func.max(measurement.tobs)).\
        filter(measurement.date >= start_date).filter(measurement.date <= end_date).all()

    session.close()
    data_dict = []

    data_dict = {'temp_min': results[0][0] ,
             'temp_max': results[0][2] ,
             'temp_average': results[0][1] }


    return jsonify(data_dict)

@app.route("/api/v1.0/<start_date>")
def temp_analysis2(start_date):
    session = Session(engine)

    tmp = session.query(measurement.date).order_by(measurement.date.desc()).first()
    end_date = str(tmp)[2:12]


    yr_last,mo_last,day_last = end_date.split("-")

    end_date = dt.datetime(int(yr_last), int(mo_last), int(day_last))


    results = session.query(func.min(measurement.tobs), func.avg(measurement.tobs), func.max(measurement.tobs)).\
        filter(measurement.date >= start_date).filter(measurement.date <= end_date).all()

    session.close()
    data_dict = []

    data_dict = {'temp_min': results[0][0] ,
             'temp_max': results[0][2] ,
             'temp_average': results[0][1] }


    return jsonify(data_dict)

if __name__ == '__main__':
    app.run(debug=True, port=5000)