gistfile1.txt

import requests
import datetime
from dateutil import parser
import pandas as pd
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
# plt.style.use('ggplot')
from bs4 import BeautifulSoup
import StringIO
import base64
import json

import warnings
warnings.filterwarnings("ignore")

def get_plot_as_b64_png(ax):
    fig = ax.figure
    imgdata = StringIO.StringIO()
    fig.savefig(imgdata, format='png')
    imgdata.seek(0)  # rewind the data
    fin_dta = base64.b64encode(imgdata.buf)
    return fin_dta

def apply(input):
    global df
    city = input.get('city','arb').upper()
    try:
        url = "http://w1.weather.gov/obhistory/K%s.html"%city
        r = requests.get(url)
        html_data = r.text
        rows = [row for row in BeautifulSoup(html_data)("tr")][::-1]
        plist = []
        for row in rows:
            cols = row('td')
            if len(cols) > 4:
                pressure = cols[13].text 
                time = cols[1].text
                dt = parser.parse(time)
                plist.append({'time': dt, 'pressure':float(pressure)})
        df = pd.DataFrame(plist)
        plt.xlabel('Hourly reading')
        plt.ylabel('Air Pressure')
        plt.title('Air Pressure in %s'%city)
        ax = df.pressure.plot()
        fin_dta = get_plot_as_b64_png(ax)
        res = {'png':fin_dta, 'city': city}
        return res
    except Exception as e:
        print "Error ",e
        return "error"