'''

Records the maximum price, minimum price, and volume for all

commodities. This data will later be used to determine what

the promising commodities to trade. For example, we'd like to

trade on Mithril Ore because the volume is high and the price

fluctuates quite a bit, but we don't want to trade on

Steel Longsword because nobody trades it and the price doesn't

move that much.

Note: This function appends to the price_data/item_stats file.

Make sure you look through the file first before giving it

a start and end ID.

@param startId - the first ID for which to record commodity stats

@param endId - one greater than the last ID for which to record

commodity stats (the range includes the start, but does not include

the end ID)

'''

@staticmethod

def record_commodity_stats( startId , endId ):

for i in range( startId , endId ):

print "Processing " + str( i )

testData = PriceCrawler.get_price_data_from_html( i )

if ( not testData is None ):

maxPrice = 0

minPrice = 999999999

maxVolume = 0

minVolume = 999999999

allPoints = testData.get_all_datapoints()

#we do not include the last data point because

#that is today's data, which may be incomplete

#and so the volume may be much less than what it

#really is.

for datapoint in allPoints[1:len(allPoints)-1]:

#prices and volumes of 0 are invalid

if ( datapoint.get_price != 0 ):

maxPrice = max( datapoint.get_price() , maxPrice )

minPrice = min( datapoint.get_price() , minPrice )

if ( datapoint.get_volume() != 0 ):

maxVolume = max( datapoint.get_volume() , maxVolume )

minVolume = min( datapoint.get_volume() , minVolume )

out = open( "price_data/item_stats" , "a" )

out.write( str(i) + "," + str(maxPrice) + "," + str(minPrice) + \

"," + str(maxVolume) + "," + str(minVolume) + "\n" )

out.close()

else:

print str( i ) + " was not a valid id"

#let's not get blocked for too many requests

sleepInterval = randint( 1 , 2 )

sleepInterval = 2

print "Sleeping " + str( sleepInterval )

'''

If the DataManager has been initialized yet

'''

initialized = False

'''

Maps integer object IDs to their commodity string names

'''

idToName = {}

'''

Maps lowercase string names of commodities to their integer object IDs

'''

nameToId = {}

'''

Initializes the DataManager. You cannot perform any data operations

using the DataManager if init() has not yet been called.

'''

@staticmethod

def init():

#don't initialize twice and waste time

if ( DataManager.initialized ):

return

f = open( "price_data/item_ids" )

lines = f.readlines()

for line in lines :

pairing = line.split( "," )

objName = pairing[ 0 ]

objID = int( pairing[ 1 ] )

DataManager.idToName[ objID ] = objName

DataManager.nameToId[ objName.lower() ] = objID

DataManager.initialized = True

'''

Downloads the most recent data for the commodity with the given name

and id. The name IS CASE SENSITIVE and should appear with the same

capitalization as in the file price_data/item_ids. If you do not

know the correct capitalization, do not use this function!

@param name - the name of the commodity, as a string. It is CASE SENSITIVE!

@param id - the object id of the commodity, as an integer

'''

@staticmethod

def download_data_by_name_and_id( name , id ):

data = PriceCrawler.get_price_data_from_json( name , id )

if ( data != None ) :

PriceWriter.save_data( data )

else :

raise "Invalid commodity name or id."

'''

Downloads the most recent data for the commodity with the given name.

@param objectName - the name of the commodity, as a string. The name is

case insensitive

'''

@staticmethod

def download_data_by_name( objectName ):

name = objectName.lower()

id = DataManager.nameToId[ name ]

caseSensitiveName = DataManager.idToName[ id ]

DataManager.download_data_by_name_and_id( caseSensitiveName , id )

'''

Downloads the most recent data for all given commodities.

@param names - a list of names (as strings) of commodities for which to

download price data. The names are case insensitive.

'''

@staticmethod

def download_data_by_names( *names ):

for name in names:

DataManager.download_data_by_name( name )

'''

Downloads the most recent data for the commodity with the given ID.

@param objectId - the ID of the commodity, as an integer

'''

@staticmethod

def download_data_by_id( objectId ):

id = objectId

name = DataManager.idToName[ id ]

DataManager.download_data_by_name_and_id( name , id )

'''

Gets all known price data for the commodity with the given name.

The name is not case sensitive.

@param name - the name of a commodity, as a string

@return - the PriceData for the given commodity, or None if the commodity

was not found.

'''

@staticmethod

def get_data_by_name( name ):

id = DataManager.nameToId[ name.lower() ]

return PriceReader.get_price_data_from_csv( id )

'''

Gets all known price data for the commodity with the given ID.

@param id - the ID of a commodity, as an integer

@return - the PriceData for the given commodity, or None if the

ID was not found.

'''

@staticmethod

def get_data_by_id( id ):

return PriceReader.get_price_data_from_csv( id )

'''

Gets all price data for a given commodity starting at the given start

date and ending at the given end date. These dates are inclusive.

@param name - the name of a commodity. This is a case insensitive string.

@param startMonth - the month of the start date, as an integer.

@param startYear - the year of the start date, as an integer.

@param endMonth - the month of the end date, as an integer.

@param endYear - the year of the end date, as an integer.

'''

@staticmethod

def get_data_by_date_range( name , startMonth , startYear , endMonth , endYear ):

caseSensitiveName = DataManager.idToName[ DataManager.nameToId[ name.lower() ] ]

rtn = []

#iterate through month by month, year by year from the start to the

#end and add any nonzero datapoints to the list of data

currYear = startYear

currMonth = startMonth

while( currYear <= endYear ):

#if the current year is before the end year, then we just

#iterate through all months

if ( currYear < endYear ):

while( currMonth <= 12 ):

monthData = PriceReader.read_month_data( currMonth , currYear , caseSensitiveName )

for day in range( 1 , len( monthData.data ) ):

prices = monthData.get( day )

#we only add nonzero prices becauase prices of 0

#means that there was no price data for that given date

if ( prices[ 0 ] != 0 and prices[ 1 ] != 0 ):

rtn.append( (currYear , currMonth , day , prices[ 0 ] , prices[ 1 ] ) )

currMonth = currMonth + 1

#have to reset the month back to 1 after we've gone through

#all 12 months in the current year

currMonth = 1

#if the current year is the end year, then we can only iterate

#up to the end month

elif ( currYear == endYear ):

while( currMonth <= endMonth ):

monthData = PriceReader.read_month_data( currMonth , currYear , name )

for day in range( 1 , len( monthData.data ) ):

prices = monthData.get( day )

if ( prices[ 0 ] != 0 and prices[ 1 ] != 0 ):

rtn.append( (currYear , currMonth , day , prices[ 0 ] , prices[ 1 ] ) )

currMonth = currMonth + 1

#move on to the next year

currYear = currYear + 1

#DataManager.init()

#DataManager.download_data_by_names( "mithril ore" , "mithril bar" , "coal" , "iron ore" , "steel bar" )

#test = DataManager.get_data_by_date_range( "Mithril bar" , 12 , 2014 , 12 , 2015 )

#print test

#IDManager.record_commodity_stats( 12521 , 20001 )

#test = PriceCrawler.get_price_data_from_html( 12621 )

#print IDManager.is_interesting( test )