One of the first python programs I wrote. For some reason, I chose to download the html and save to text files. I think I was having trouble working with the raw html with bs4. Anyway, I am leaving it 'as is' mostly for the sake of having a reference point in regards to how my python programming improve (or doesn't) over time.

SurfCheck.py

#-----------------------------------------------------------------------------#
# Parses the converted html files to find the swell heights and conditions
# and then prints these out into formatted tables
#-----------------------------------------------------------------------------#
 
import urllib2
from bs4 import BeautifulSoup
 
 
# Scarpe the site and convert html to text
def html_to_text(address, text_file):
     
    html = urllib2.urlopen(address).read() 
 
    soup = BeautifulSoup(html)
 
    s_doc = soup.prettify()
 
    target = open(text_file, 'w')
    target.truncate()
    target.write(html)
    target.close()
 
 
# Parse the text file to extract forecast data
def parse_txt(txt):
 
    # Open File
    in_file = open(txt)
 
    ## Search doc for a list of keywords and record the positions in the file
 
    # Define keywords
    word = ['Today', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 
        'Friday', 'Saturday', 'Sunday']
 
    # Initialize itr var to use to track file position
    i = 0
    l_pos = -99
 
    # Initialize arrays to use to store keyword and file poistion data
    pos_array = []
    word_array = []
    line1_array = []
    line2_array = []
    line3_array = []
 
    # Loop through doc, search for list of words, and record the line and line #
    for line in in_file:
        for w in word:
             
            if w in line:
                pos_array.append(i)
                word_array.append(w)
                line1_array.append(line)
                l_pos = i
        # Need to pull the extra lines to get the swell height and conditions
        if i == (l_pos + 3):
            line2_array.append(line)
        if i == (l_pos + 4):
            line3_array.append(line)
                 
        i += 1
         
    #Seems to be pulling in an extra line from time to time
    # - Remove last item from all arrays if len over 7
    if len(word_array) > 7:
        pos_array.pop()
        word_array.pop()
        line1_array.pop()
        line2_array.pop()
        line3_array.pop()
 
    # Grab the condition information from the respective lines
 
    am_cond = []
    am_swell = []
    pm_cond = []
    pm_swell = []
 
    # Pull AM condition information from line1_array
    for line in line1_array:
        lhs, rhs = line.split("AccordionPanelTab ")
        lhs, rhs = rhs.split("_")
        am_cond.append(lhs)
         
    # Pull AM swell height information from line2_array
    for line in line2_array:
        lhs, rhs = line.split(">", 1)
        lhs, rhs = rhs.split("<")
        am_swell.append(lhs)
         
    # Pull PM conditions and PM Swell from line3_array
    for line in line3_array:
        #Grab Swell Height
        lhs, rhs = line.split(">", 1)
        lhs, rhs = rhs.split("<")
        pm_swell.append(lhs)
        #Grab Conditions
        lhs, mid, rhs = line.split('"')
        pm_cond.append(mid)
         
    # Convert Condition values to readable values
 
    def conv_cond(cond):
        ret_array = []
        for val in cond:
            if val == 'cond1':
                ret_array.append("Good")
            elif val == 'cond2':
                ret_array.append("Fair")
            elif val == 'cond3':
                ret_array.append("Poor")
            else:
                ret_array.append("!Error!")
         
        return(ret_array)
         
    am_cond = conv_cond(am_cond)
    pm_cond = conv_cond(pm_cond)
     
    #Pull out the Beach Name from the txt file name
    beach, lhs = txt.split('.')
         
    # Print Swell Table
    print "\nSwell Report for %s" % beach
    print "----------------------------------------------"
    print "Day \t\t AM \t\t PM"
    print "----------------------------------------------"
    for j in range(len(word_array)):
        if j == 0:
            print "%s: \t\t %s %s \t %s %s" % (word_array[j], am_swell[j], am_cond[j],
                pm_swell[j], pm_cond[j])
        else:
            print "%s: \t %s %s \t %s %s" % (word_array[j], am_swell[j], am_cond[j],
                pm_swell[j], pm_cond[j])
             
    print "\n"
 
    in_file.close()
 
 
# Get the forecast
 
#Create list of spots we want to check
address = []
address.append('http://www.swellinfo.com/surf-forecast/ocean-beach-california-nw')
address.append('http://www.swellinfo.com/surf-forecast/ocean-beach-california')
address.append('http://www.swellinfo.com/surf-forecast/half-moon-bay-california')
address.append('http://www.swellinfo.com/surf-forecast/pescadero-california')
address.append('http://www.swellinfo.com/surf-forecast/davenport-california')
address.append('http://www.swellinfo.com/surf-forecast/santa-cruz-california')
 
# Create a list of text files to store the html in
txt = []
txt.append('Ocean Beach North.txt')
txt.append('Ocean Beach South.txt')
txt.append('Half Moon Bay.txt')
txt.append('Pescadero.txt')
txt.append('Davenport.txt')
txt.append('Santa Cruz.txt')
 
for i in range(len(address)):
    # Grab html and convert to text
    html_to_text(address[i], txt[i])
    # Set up the arrays to loop through the text files
    parse_txt(txt[i])