#!/usr/bin/python
# Given a URL or filename, extract things that look like radio frequencies from
# it and produce a CSV file suitable for feeding to tk500.
# Adam Sampson <ats@offog.org>

import urllib, re, optparse

unit_scale = {
	"hz": 1,
	"khz": 1E3,
	"mhz": 1E6,
	"ghz": 1E9,
	}
min_plausible = 100 * 1E3
max_plausible = 2 * 1E9

def mode(f):
	return "NFM"

def find_freqs(url, found):
	f = urllib.urlopen(url)
	data = f.read()
	f.close()

	for number, unit in re.findall(r'(?i)([0-9.]+)\s*([kmg]?hz)', data):
		try:
			f = float(number)
		except ValueError:
			continue
		unit = unit.lower()
		if unit not in unit_scale:
			continue
		f *= unit_scale[unit]
		found.add(f)

def main():
	parser = optparse.OptionParser(usage="%prog [OPTIONS] URL ...")
	parser.add_option("-n", dest="start", type="int", help="first channel number", default=500)
	parser.add_option("-p", dest="prefix", help="prefix for channel names", default="Chan")
	(opts, args) = parser.parse_args()

	found = set()
	for url in args:
		find_freqs(url, found)

	freqs = [f for f in found if f >= min_plausible and f <= max_plausible]
	freqs.sort()
	n = 0
	for f in freqs:
		print '%d,%.5f,%s,,"%s%d"' % (n + opts.start, f / 1E6, mode(f), opts.prefix, n + 1)
		n += 1

if __name__ == "__main__":
	main()