Tide Indicator Pi Project #8 - Calculation of Current Tide Completed

The program below seems to work!

Output:

('Next: ', (datetime.datetime(2016, 1, 3, 6, 18, 23, 116073), u'4.3'), ' is ', datetime.timedelta(0, 21180, 2472), ' away. /n Previous: ', (datetime.datetime(2016, 1, 2, 23, 49, 23, 115191), u'8.1'), ' was ', datetime.timedelta(0, 2159, 998410), ' ago.')
('Sum of both gaps is ', datetime.timedelta(0, 23340, 882))
('Tide is Currently: ', 'falling')
('tide difference = ', -3.8)
('lower tide value', 4.299999999999999)
('Normalised Time =', 2159, 23340, 0.29060405051843885)
0.958070971113
('Current tide : ', 7.940669690228617)

Code:

#version 1.0
#This program pulls tide data from the ports of Jersey Website
#Under a licence from the UKHO
#
#It then calculates the current tide using a simplified sinusoidal harmonic approximation
#By finding the two tide data points either side of now and working out the current tide height


import urllib2
from bs4 import BeautifulSoup
from time import sleep
import datetime as dt
import math

#open site and grab html

rawhtml = urllib2.urlopen("http://www.ports.je/Pages/tides.aspx").read(40000)
soup = BeautifulSoup(rawhtml, "html.parser")


#get the tide data (it's all in tags)

rawtidedata = soup.findAll('td')


#parse all data points (date, times, heights) to one big list
#format of the list is [day,tm,ht,tm,ht,tm,lt,tm,lt]

n=0
parsedtidedata=[]
for i in rawtidedata: 
 parsedtidedata.append(rawtidedata[n].get_text())
 n += 1

#extract each class of data (day, time , height) to a separate list (there are 10 data items for each day)

tidetimes=[]
tideheights=[]
tideday=[]
lastdayofmonth=int(parsedtidedata[-10])

for n in range(0,lastdayofmonth*10,10):

 tideday.append(parsedtidedata[n])
 tidetimes.extend([parsedtidedata[n+1],parsedtidedata[n+3],parsedtidedata[n+5],parsedtidedata[n+7]])
 tideheights.extend([parsedtidedata[n+2],parsedtidedata[n+4],parsedtidedata[n+6],parsedtidedata[n+8]])

#get time now:

currentTime = dt.datetime.now()


#create a list of all the tide times as datetime objects:

dtTideTimes=[]
tideDataList=[]

for j in range (0,lastdayofmonth*4):
 #print tidetimes[j][0:2], tidetimes[j][3:6]
 if tidetimes[j]=='**':
  dtTideTimes.append('**')
 else:

  dtTideTimes.append(dt.datetime.now().replace(day=int(j/4+1), hour=int(tidetimes[j][0:2]), minute=int(tidetimes[j][3:5])))

 #make a tuple for each data point and add it to a list
 tupleHolder =(dtTideTimes[j], tideheights[j])
 tideDataList.append(tupleHolder)
 
 #print what we've got so far
# print tideDataList[j]

#find the two closest times in the list to now:

gap1 = abs(tideDataList[0][0] - currentTime)
gap2 = abs(tideDataList[0][0] - currentTime)
nearest1 = tideDataList[0]

#print gap1 

for j in range (0,lastdayofmonth*4):

 if (tideDataList[j][0] !="**"):                      
  gapx = abs(tideDataList[j][0] - currentTime) 

#check if the data point is the first or second nearest to now. 
#Generates the datapoints either side of now

  if (gapx <= gap1):                            
   nearest1 = tideDataList[j]            
   gap1 = gapx
  if (gap1 < gapx and gapx <= gap2): 
   nearest2 = tideDataList[j]                   
   gap2 = gapx             

#print (nearest1, gap1)
#print (nearest2, gap2)
#print (gap1+gap2)    

#and now the maths begins
#print ('tide height 1 = ', nearest1[1])
#print ('tide height 2 = ', nearest2[1])

#need to get them in order of time: (this works)

if nearest1[0] > nearest2[0]:
 nextDataPoint = nearest1
 prevDataPoint = nearest2
 gapToNext = gap1
 gapToPrev = gap2

else:
 nextDataPoint = nearest2
 prevDataPoint = nearest1
 gapToNext = gap2
 gapToPrev = gap1

gapSum = gapToNext + gapToPrev

print('Next: ', nextDataPoint,' is ',gapToNext, ' away. /n Previous: ', prevDataPoint, ' was ', gapToPrev, ' ago.')
print('Sum of both gaps is ', gapSum) #this works

#is the tide rising or falling?
tideDifference = float(nextDataPoint[1])-float(prevDataPoint[1])

if (tideDifference<0 data-blogger-escaped-0="prev" data-blogger-escaped-:="" data-blogger-escaped-all="" data-blogger-escaped-code="" data-blogger-escaped-currently:="" data-blogger-escaped-currenttide="" data-blogger-escaped-data="" data-blogger-escaped-difference=", tideDifference) #this works


lowerTide = (float(nearest1[1]) + float(nearest2[1]) - abs(tideDifference))/2
print (" data-blogger-escaped-doesn="" data-blogger-escaped-else:="" data-blogger-escaped-falling="" data-blogger-escaped-for="" data-blogger-escaped-ide="" data-blogger-escaped-is="" data-blogger-escaped-lower="" data-blogger-escaped-lowertide="" data-blogger-escaped-math.cos="" data-blogger-escaped-math.pi="" data-blogger-escaped-normalisedtime="" data-blogger-escaped-ormalised="" data-blogger-escaped-pi="next" data-blogger-escaped-print="" data-blogger-escaped-scaled="" data-blogger-escaped-t="" data-blogger-escaped-this="" data-blogger-escaped-tide="" data-blogger-escaped-tidedifference="" data-blogger-escaped-tidestate="" data-blogger-escaped-time=", gapToPrev.seconds, gapSum.seconds, normalisedTime)

print (math.cos(normalisedTime))

if tideState == " data-blogger-escaped-to="" data-blogger-escaped-urrent="" data-blogger-escaped-value="" data-blogger-escaped-work="" data-blogger-escaped-works="">