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main.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
from datetime import timedelta, date
import pandas as pd
import numpy as np
import warnings
import requests
import sqlalchemy
import airports
def configure_engine():
DB_TYPE = 'mysql'
DB_DRIV = 'pymysql'
DB_USER = 'DBUSER'
DB_PASS = 'PASSWORD'
DB_HOST = 'IP'
DB_NAME = 'DBNAME'
SQLALCHEMY_DATABASE_URI = '%s+%s://%s:%s@%s/%s' % (DB_TYPE, DB_DRIV, DB_USER, DB_PASS, DB_HOST, DB_NAME)
return SQLALCHEMY_DATABASE_URI
def create_table():
POOL_SIZE = 50
metadata = sqlalchemy.MetaData()
TABLENAME = 'weather'
ENGINE = sqlalchemy.create_engine(
configure_engine(), pool_size=POOL_SIZE, max_overflow=0)
t = sqlalchemy.Table(TABLENAME, metadata,
sqlalchemy.Column('id', sqlalchemy.Integer, primary_key=True, autoincrement=True),
sqlalchemy.Column('DateTime', sqlalchemy.DATETIME),
sqlalchemy.Column('Airport-code', sqlalchemy.VARCHAR(10)),
sqlalchemy.Column('Temperature', sqlalchemy.DECIMAL(3,1)),
sqlalchemy.Column('Dew-Point', sqlalchemy.DECIMAL(3,1)),
sqlalchemy.Column('Humidity', sqlalchemy.VARCHAR(10)),
sqlalchemy.Column('Pressure-hPa', sqlalchemy.INTEGER),
sqlalchemy.Column('Visibility-km', sqlalchemy.DECIMAL(3,1)),
sqlalchemy.Column('Wind-Dir', sqlalchemy.VARCHAR(10)),
sqlalchemy.Column('Conditions', sqlalchemy.TEXT),
sqlalchemy.Column('Wind-Speed-kmh', sqlalchemy.DECIMAL(3,1)),
sqlalchemy.Column('Wind-Speed-ms', sqlalchemy.DECIMAL(3,1))
)
t.create(ENGINE)
def read_text(link):
page = requests.get(link)
return page.text
def get_data_between_texts(raw_text, text1, text2, include_texts=True):
index1 = raw_text.find(text1)
index2 = raw_text.find(text2)
if(include_texts):
filtered = raw_text[index1:index2+len(text2)]
else:
filtered = raw_text[index1+len(text1):index2]
return filtered
def get_weather_table(url):
full_html = read_text(url)
table_header = '<table cellspacing="0" cellpadding="0" id="obsTable" class="obs-table responsive">'
table_footer = '<div class="obs-table-footer">'
table = get_data_between_texts(full_html, table_header, table_footer)
return pd.read_html(table, header=0)[0]
def generate_weather_information(airport_code, year, month, day):
LINK = 'https://www.wunderground.com/history/airport/%s/%s/%s/%s/DailyHistory.html' % (airport_code, year, month, day)
try:
df = get_weather_table(LINK)
except:
return pd.DataFrame()
#Drop columns that not appair for all airports.
if unicode('Heat Index',"utf-8") in df.columns:
df = df.drop('Heat Index', 1)
if unicode('Windchill',"utf-8") in df.columns:
df = df.drop('Windchill', 1)
df = df.drop('Gust Speed', 1)
df = df.drop('Events', 1)
df = df.replace(np.nan, 'NA', regex=True)
df = df[df['Precip'] == 'NA']
df = df[df['Humidity'] != 'N/A%']
df = df.drop('Precip', 1)
df['Temp.'] = df['Temp.'].map(lambda x: x.rstrip(unicode(' °C',"utf-8")).replace('- ','0.0').replace(u'\xa0', u''))
df['Dew Point'] = df['Dew Point'].map(lambda x: x.rstrip(unicode(' °C',"utf-8")).replace('- ','0.0').replace(u'\xa0', u''))
df['Wind Speed'] = df['Wind Speed'].map(lambda x: x.replace('Calm','0.0 km/h / 0.0 m/s').replace('-','0.0 km/h / 0.0 m/s').replace(u'\xa0', u''))
df['Wind-Speed-kmh'] = df['Wind Speed'].map(lambda x: x.split(' / ')[0].rstrip(unicode(' km/h',"utf-8")).replace(u'\xa0', u''))
df['Wind-Speed-ms'] = df['Wind Speed'].map(lambda x: x.split(' / ')[1].rstrip(unicode(' m/s',"utf-8")).replace(u'\xa0', u''))
df = df.drop('Wind Speed', 1)
df['Pressure'] = df['Pressure'].map(lambda x: x.rstrip(unicode(' hPa',"utf-8")).replace('-','0.0').replace(u'\xa0', u''))
df['Visibility'] = df['Visibility'].map(lambda x: x.rstrip(unicode(' km',"utf-8")).replace('-','0.0').replace(u'\xa0', u''))
#Adjust the first column name to just Time
df.rename(columns={ df.columns[0]: 'Time' }, inplace=True)
measure_date = '%s-%s-%s ' % (year, month, day)
df['Time'] = pd.to_datetime(measure_date + df['Time'])
df['Airport-code'] = airport_code
cols = {}
cols['Temp.'] = 'Temperature'
cols['Time'] = 'DateTime'
cols['Dew Point'] = 'Dew-Point'
cols['Wind Dir'] = 'Wind-Dir'
cols['Pressure'] = 'Pressure-hPa'
cols['Visibility'] = 'Visibility-km'
df.rename(columns=cols, inplace=True)
return df
def send_to_sql(df):
TABLENAME = 'weather'
POOL_SIZE = 50
ENGINE = sqlalchemy.create_engine(
configure_engine(), pool_size=POOL_SIZE, max_overflow=0)
df.to_sql(TABLENAME, ENGINE, if_exists='append', index=False)
def daterange(start_date, end_date):
for n in range(int ((end_date - start_date).days)):
yield start_date + timedelta(n)
def run(start_date, end_date):
notLoaded = {}
airport_list = airports.get_airport_list()
for airport in airport_list:
notLoaded[airport['sigla']] = 0
for single_date in daterange(start_date, end_date):#The last day is not included, so the daterange is start_date to end_date-1
year = single_date.year
month = single_date.month
day = single_date.day
print("Reading data for %s-%s-%s"%(year,month,day))
for airport in airport_list:
df = generate_weather_information(airport['sigla'],year,month,day)
if df.empty == True:
notLoaded[airport['sigla']] = notLoaded[airport['sigla']] + 1
else:
send_to_sql(df)
print(notLoaded)
def test(airport_code,year,month,day):
df = generate_weather_information(airport_code,year,month,day)
print(df)
if __name__ == "__main__":
warnings.simplefilter(action='ignore', category=FutureWarning)
#test('SBCG',2017,10,2)
#create_table()
start_date = date(2018, 1, 1)
end_date = date(2018, 2, 1)
run(start_date, end_date)