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analyse-results.py
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#!/usr/bin/env python
import json
import sys
import os
import shutil
import math
import codecs
from collections import Counter
## this allows to pipe output to a file and have it be utf-8
# adapted from http://stackoverflow.com/questions/4545661/unicodedecodeerror-when-redirecting-to-file
sys.stdout = codecs.getwriter('utf-8')(sys.stdout)
BASEDIR=os.path.dirname( os.path.realpath(__file__) )
PROBE_BLACKLIST_FILE="%s/probe-blacklist.txt" % BASEDIR
# globally available
PROBES = []
with open('probeset.json','r') as probesin:
PROBES = json.load( probesin )
PROBES_BY_ID = {}
for p in PROBES:
PROBES_BY_ID[ p['probe_id'] ] = p
PROBE_BLACKLIST = set()
if os.path.isfile( PROBE_BLACKLIST_FILE ):
with open( PROBE_BLACKLIST_FILE ) as inf:
for line in inf:
line = line.rstrip('\n');
try:
prb_id,rest = line.split(None,1)
prb_id = int(prb_id)
PROBE_BLACKLIST.add( prb_id )
print "PROBE %s blacklisted" % prb_id
except:
print "can't parse this line in %s: %s" % ( PROBE_BLACKLIST_FILE, line )
sys.exit(1)
## filter probe list through blacklist
def data_line_generator():
infilename = 'measurementset.json'
proto = None
with open(infilename,'r') as infile:
msms = json.load( infile , encoding='utf-8')
for meas_proto in msms:
proto = meas_proto
for msm_entry in msms[meas_proto]:
if 'msm_id' in msm_entry:
with open('./results/msm.%s.json' % ( msm_entry['msm_id'] ),'r') as msmfile:
data = json.load( msmfile )
for entry in data:
if 'src_prb_id' in entry and entry['src_prb_id'] in PROBE_BLACKLIST:
continue
elif 'dst_prb_id' in entry and entry['dst_prb_id'] in PROBE_BLACKLIST:
continue
else:
yield proto, entry
else:
print >>sys.stderr," error on msm entry: %s " % ( msm_entry )
### common . For stuff general enough to apply to multiple analyses.
### example is text representation for traces, indexed by srcprb.dstprb
def init_common( basedata, probes ):
return {'v4': {}, 'v6': {}, 'timestamps': set() }
def do_common_entry( data, proto, data_entry ):
detail_key = '.'.join(map(str,[ data_entry['src_prb_id'] , data_entry['dst_prb_id'] ]))
if not detail_key in data[proto]:
data[proto][detail_key] = []
data[proto][detail_key].append( data_entry )
## support timestamps
data['timestamps'].add(data_entry['ts'])
def do_common_printresult( data ):
COMMONPATH='./analysis/common/details'
for proto in ('v4','v6'):
cpp = "%s/%s" % (COMMONPATH,proto)
for detail_key in data[ proto ].keys():
data_sorted = sorted( data[proto][detail_key], key=lambda x:x['ts'])
data_latest = data_sorted[-1]
src_prb,dst_prb = detail_key.split('.')
ldir = "%s/%s/%s/%s" % ( COMMONPATH, proto, src_prb, dst_prb )
if not os.path.exists( ldir ):
os.makedirs( ldir )
latest_file = "%s/latest.json" % (ldir)
# see ixpcountry template for example of how to use these latest.json files
with open(latest_file, 'w') as outfile:
json.dump( data_latest, outfile )
## CommonInit
CommonFormat = {}
## Timestamp period (Alex ixp tools codespring)
# Inits
ts_Start = sys.maxint
ts_End = -sys.maxint
from datetime import datetime
for time in data['timestamps']:
if time < ts_Start:
ts_Start = time
if time > ts_End:
ts_End = time
CommonFormat["StartTime"] = ts_Start
CommonFormat["EndTime"] = ts_End
CommonFormat["StartUTC"] = str(datetime.utcfromtimestamp(ts_Start))
CommonFormat["EndUTC"] = str(datetime.utcfromtimestamp(ts_End))
print "\nTimestamp period: %d - %d "%(CommonFormat["StartTime"],CommonFormat["EndTime"])
print "UTC time period : %s - %s "%(CommonFormat["StartUTC"],CommonFormat["EndUTC"])
## Unique AS list calculation (Alex ixp tools codespring)
ASV4 = set()
ASV6 = set()
for p in PROBES:
if p['asn_v4'] is not None:
ASV4.add(p['asn_v4'])
if p['asn_v6'] is not None:
ASV6.add(p['asn_v6'])
CommonFormat["ASV4"] = list(ASV4)
CommonFormat["ASV6"] = list(ASV6)
## Printing to file
with open(COMMONPATH+'/MsmDescr.json','w') as outfile:
json.dump( CommonFormat, outfile, indent=2 )
print "CommonInfo at: '%s'" % (COMMONPATH+'MsmDescr.json')
### perasn
def init_perasn( basedata, probes ):
d = {'asns': {}}
return d
def do_perasn_entry( asns_d , proto, data ):
terminal_asns = set()
try:
src_asn = PROBES_BY_ID[ data['src_prb_id'] ]['asn_%s' % proto ]
if src_asn != None:
terminal_asns.add( src_asn )
dst_asn = PROBES_BY_ID[ data['dst_prb_id'] ]['asn_%s' % proto ]
if dst_asn != None:
terminal_asns.add( dst_asn )
except:
# remove for now
pass
if len(terminal_asns) != 2:
return
for asn in terminal_asns:
other_asn = filter(lambda x: x != asn, terminal_asns)[0]
asns_d['asns'].setdefault( asn, {'facets': {
'out_of_country': {'asns': {}, 'path_count': 0},
'intermediates': {'asns': {}, 'path_count': 0}
} } )
## process the facet: 'out_of_country'
if data['in_country'] == False:
asns_d['asns'][ asn ]['facets']['out_of_country']['asns'].setdefault( other_asn, [] )
asns_d['asns'][ asn ]['facets']['out_of_country']['asns'][ other_asn ].append(
{
'src_prb_id': data['src_prb_id'],
'dst_prb_id': data['dst_prb_id'],
'proto': proto
}
)
asns_d['asns'][ asn ]['facets']['out_of_country']['path_count'] += 1
## process next facet. did we detect extra ASNs between src and dst
src_dst_with_intermediates = set() #need this because of duplicates
for intermediate in data['as_links']['nodes']:
if intermediate in terminal_asns:
continue
if intermediate.startswith('_'): # it's an IXP
continue
src_dst_with_intermediates.add( ( data['src_prb_id'], data['dst_prb_id'] ) )
for sdwi in src_dst_with_intermediates:
asns_d['asns'][ asn ]['facets']['intermediates']['asns'].setdefault( other_asn, [] )
asns_d['asns'][ asn ]['facets']['intermediates']['asns'][ other_asn ].append(
{
'src_prb_id': sdwi[0],
'dst_prb_id': sdwi[1],
'proto': proto
}
)
asns_d['asns'][ asn ]['facets']['intermediates']['path_count'] += 1
## process next facet, symmetry?
## hmmm. would need a lot of caching and put it in printresult?
## just show the probes then
def do_perasn_printresult( asns_d ):
DATAPATH='./analysis/perasn/'
if not os.path.exists( DATAPATH ):
os.makedirs( DATAPATH )
for asn,asn_data in asns_d['asns'].iteritems():
asn_file = "%s/%s.json" % ( DATAPATH, asn)
# see ixpcountry template for example of how to use these latest.json files
with open(asn_file, 'w') as outfile:
json.dump( asn_data, outfile, indent=2 )
### ixpcount
def init_ixpcount( basedata, probes ):
ixps = {
'ixps_per_path': {},
'seen': {'_none': 0, '_total': 0},
'seen_v4': {'_none': 0, '_total': 0},
'seen_v6': {'_none': 0, '_total': 0}
}
return ixps
def do_ixpcount_entry( ixps, proto, data ):
# proto_key (either 'seen_v4' or 'seen_v6')
pkey = 'seen_%s' % ( proto )
if not 'ixps' in data:
print "no ixp?!"
return
if not len(data['ixps']) in ixps['ixps_per_path']:
ixps['ixps_per_path'][ len( data['ixps'] )] = 0
ixps['ixps_per_path'][ len( data['ixps'] )] += 1
ixps['seen']['_total'] += 1
ixps[pkey]['_total'] += 1
if len(data['ixps']) == 0:
ixps['seen']['_none'] += 1
ixps[pkey]['_none'] += 1
else:
for ixp in data['ixps']:
if ixp not in ixps['seen']:
ixps['seen'][ixp] = 0
ixps['seen'][ixp] += 1
if ixp not in ixps[pkey]:
ixps[pkey][ixp] = 0
ixps[pkey][ixp] += 1
def do_ixpcount_printresult( ixps ):
print "Results for: IXPcount analysis"
print "=============================="
#print "%s" % ( ixps )
key2desc = [
['seen', "Overall"],
['seen_v4', "IPv4"],
['seen_v6', "IPv6"]
]
for kv in key2desc:
(key,desc) = kv
txt = "Results %s" % ( desc )
print txt
print '=' * len(txt)
for ixp in sorted( ixps[ key ], key=lambda x: ixps[ key ][x] , reverse=True ):
pct = 0
try:
pct = 100.0*ixps[key][ixp]/ixps[key]['_total']
except: pass
print "%02d\t%.1f%%\t%s" % ( ixps[key][ixp] , pct, ixp )
### incountry
def init_incountry( basedata, probes ):
data = {
'countries': basedata['countries'],
'routed_asns': 0,
'probes': PROBES,
}
for cc in basedata['country-stats']:
if 'routed_asns' in basedata['country-stats'][ cc ]:
data['routed_asns'] += basedata['country-stats'][ cc ]['routed_asns']
for proto in ('v4','v6'):
data[ proto ] = {
'path_count': 0,
'incountry_count': 0,
'abroad': {},
'ooc_probes': Counter() #tracks the probes that cause out of country paths (both src and dst)
}
return data
def do_incountry_entry( data, proto, entry ):
data[ proto ]['path_count'] += 1
if entry['in_country'] == True:
data[ proto ]['incountry_count'] += 1
elif entry['in_country'] == False:
data[ proto ]['ooc_probes'][ entry['src_prb_id'] ] += 1
data[ proto ]['ooc_probes'][ entry['dst_prb_id'] ] += 1
country_set = set()
for loc in entry['locations']:
country = None
try:
country = loc.split(',')[-1]
country_set.add( country )
except: pass
for country in country_set:
#TODO exclude guest country
if not country in data['countries']:
if not country in data[ proto ]['abroad']:
data[ proto ]['abroad'][ country ] = 0
data[ proto ]['abroad'][ country ] += 1
def do_incountry_printresult( data ):
DATAPATH='./analysis/incountry/'
if not os.path.exists( DATAPATH ):
os.makedirs( DATAPATH )
# ooc = out of country
ooc_pct = {'v4': None, 'v6': None}
ooc_pct_per_ooc = {'v4': Counter(), 'v6': Counter()}
print "Paths with out-of-country IP addresses"
print "========================================="
for proto in ('v4','v6'):
if data[ proto ]['path_count'] > 0:
ooc_pct[ proto ] = 100 - data[ proto ]['incountry_count'] * 100.0 / data[ proto ]['path_count']
print "IP%s : %.2f%%" % ( proto , ooc_pct[ proto ] )
for country in sorted( data[ proto ]['abroad'], key=lambda x:data[proto]['abroad'][x], reverse=True):
cnt = data[ proto ]['abroad'][ country ]
pct = cnt * 100.0 / data[ proto ]['path_count']
ooc_pct_per_ooc[ proto ][ country ] = pct
print " %s : %.2f%% (%d)" % ( country , pct, cnt)
## probes contributing most to out of country:
print "TOP 10 probes contributing to out-of-country-paths"
for prb_id,count in data[ proto ]['ooc_probes'].most_common(10):
involvepct = 100.0 * count / math.sqrt( data[ proto ]['path_count'] ) # roughly correct
print " prb_id:%s / AS%s / %d/%d paths / involvepct:%.1f" % ( prb_id, PROBES_BY_ID[prb_id]['asn_%s' % proto] , count, data[proto]['path_count'], involvepct )
print "Country stats based on this"
print "---------------------------"
probe_asns = {'v4': set(), 'v6': set()}
for prb_info in data['probes']:
if 'asn_v4' in prb_info and prb_info['asn_v4'] != None:
probe_asns['v4'].add( prb_info['asn_v4'] )
if 'asn_v6' in prb_info and prb_info['asn_v6'] != None:
probe_asns['v6'].add( prb_info['asn_v6'] )
print " ASNs in routing: %s" % ( data['routed_asns'] )
probe_asn_counts = {'v4': None, 'v6': None}
for proto in ('v4','v6'):
cnt = len(probe_asns[ proto ])
print " ASNs with public probes: %s (%s)" % ( cnt, proto )
probe_asn_counts[ proto ] = cnt
inc_data = {
'routed_asn_count': data['routed_asns'],
'probe_asn_count': probe_asn_counts,
'out_of_country_pct': ooc_pct,
'out_of_country_country_pct': {
'v4': ooc_pct_per_ooc['v4'].most_common(),
'v6': ooc_pct_per_ooc['v6'].most_common()
}
}
inc_json_file = "%s/incountry.json" % ( DATAPATH )
with open( inc_json_file,'w') as outf:
json.dump( inc_data, outf )
print "INCOUNTRY data file at: '%s'" % (inc_json_file)
### ixpcountry
def init_ixpcountry( basedata, probes ):
rows = { 'v4' : list(), 'v6' : list() }
for probe in PROBES:
if('address_v4' in probe and probe['address_v4'] != None and "system-ipv4-works" in probe['tags']):
rows['v4'].append({
'id': probe['probe_id'],
'asn_v4': probe['asn_v4'],
'asn_v6': probe['asn_v6']
})
if('address_v6' in probe and probe['address_v6'] != None and "system-ipv6-works" in probe['tags']):
rows['v6'].append({
'id': probe['probe_id'],
'asn_v4': probe['asn_v4'],
'asn_v6': probe['asn_v6']
})
## can do data reduction step here if data is too big
d = {'summary':{},'details':{}}
for proto in ('v4','v6'):
d['summary'][proto] = {
'rows': rows[proto],
'cols': rows[proto],
'cells': [],
}
d['details'][proto] = {}
return d
def do_ixpcountry_entry( ixpcountry, proto, data ):
my_cells = ixpcountry['summary'][proto]['cells']
my_cells.append({
'row': data['src_prb_id'],
'col': data['dst_prb_id'],
'data': {'in_country': data['in_country'], 'via_ixp': data['via_ixp']}
})
details = ixpcountry['details'][proto]
detail_key = '.'.join(map(str,[ data['src_prb_id'] , data['dst_prb_id'] ]))
details[ detail_key ] = data
def do_ixpcountry_printresult( ixpcountry ):
VIZPATH='./analysis/ixpcountry/'
VIZDETAILSPATH='./analysis/ixpcountry/details'
if not os.path.exists( VIZPATH ):
os.makedirs( VIZPATH )
if not os.path.exists( VIZDETAILSPATH ):
os.makedirs( VIZDETAILSPATH )
for proto in ('v4','v6'):
with open('%s/ixpcountry.%s.json' % (VIZPATH,proto), 'w') as outfile:
json.dump( ixpcountry['summary'][ proto ], outfile )
for detail_key in ixpcountry['details'][ proto ].keys():
with open('%s/%s.%s.json' % ( VIZDETAILSPATH, detail_key, proto ), 'w') as outfile:
json.dump( ixpcountry['details'][ proto ][ detail_key ], outfile )
print "IXPCOUNTRY viz results available in %s" % ( VIZPATH )
### aspath
def init_asgraph( basedata, probes ):
d = {'nodes': Counter(),
'links': Counter()
}
return d
def do_asgraph_entry( d, proto, entry ):
# print entry['as_links']['nodes']
# print entry['as_links']['links']
for n in entry['as_links']['nodes']:
d['nodes'][ n ] += 1
for l in entry['as_links']['links']:
## {u'src': u'NETNOD-MMO-B-1500', u'dst': u'AS29518', u'type': u'd'}
link_key = '>'.join([ l['src'], l['dst'], l['type'] ])
d['links'][ link_key ] += 1
def do_asgraph_printresult( d ):
result = {'nodes': [], 'edges': []}
VIZPATH='./analysis/asgraph/'
if not os.path.exists( VIZPATH ):
os.makedirs( VIZPATH )
name2idx={}
idx=0
for n in d['nodes']:
count = d['nodes'][n]
name2idx[ n ] = idx
typ = 'asn'
if n.startswith('_'):
typ = 'ixp'
n = n.lstrip('_');
result['nodes'].append({'id': idx, 'name': n, 'type': typ, 'count': count })
idx += 1
for l in d['links']:
src,dst,typ = l.split('>',2)
result['edges'].append({'source': name2idx[src], 'target': name2idx[dst], 'type': typ})
with open('%s/asgraph.json' % ( VIZPATH), 'w') as outfile:
json.dump( result , outfile )
print "ASGRAPH viz results in '%s'" % ( VIZPATH )
## geopath stuff
def init_geopath( basedata, probes ):
return {'v4':[], 'v6':[]}
def do_geopath_entry( data, proto, data_entry ):
geojson_pieces = data_entry['geojson']
for piece in geojson_pieces:
# {u'type': u'LineString', u'properties': {u'dloc': u'Stockholm,Stockholm,SE', u'is_direct': False, u'dasn': u'', u'sloc': u'Probe', u'sasn': u'59521', u'asn': None}, u'coordinates': [[u'18.0385', u'59.3305'], [u'18.0649', u'59.33258']]}
# leaflet is picky on it's GeoJson?
prop = piece['properties']
del( piece['properties'] )
data[ proto ].append({
'geometry': piece,
'properties': prop,
'type': 'Feature'
})
def do_geopath_printresult( data ):
VIZPATH='./analysis/geopath/'
if not os.path.exists( VIZPATH ):
os.makedirs( VIZPATH )
for proto in ('v4','v6'):
geojson = {'type':'FeatureCollection', 'features': data[ proto ] }
with open('%s/geopath.%s.json' % ( VIZPATH, proto ), 'w') as outfile:
json.dump( geojson , outfile )
print "GEOPATH viz results in '%s'" % ( VIZPATH )
### ixplans (ixp-lans, not ix-plans ;) )
def init_ixplans( basedata, probes ):
# group by IP
struct = {}
for proto in ('v4','v6'):
struct[ proto ] = {
'nodes': set(),
'links': set(),
'ixps': Counter()
}
return struct
def do_ixplans_entry( data, proto, data_entry ):
src_prb_id = data_entry['src_prb_id']
dst_prb_id = data_entry['dst_prb_id']
data[ proto ]['nodes'].add( src_prb_id )
data[ proto ]['nodes'].add( dst_prb_id )
if 'ixps' in data_entry:
for ixp in data_entry['ixps']:
link_key = u'{}>{}>{}'.format(src_prb_id, dst_prb_id, ixp)
data[ proto ]['links'].add( link_key )
data[ proto ]['ixps'][ ixp ] += 1
def do_ixplans_printresult( data ):
VIZPATH='./analysis/ixplans/'
if not os.path.exists( VIZPATH ):
os.makedirs( VIZPATH )
for proto in ('v4','v6'):
name2idx={}
idx=0
result = {'nodes': [], 'links': [], 'ixps': []}
for n in data[proto]['nodes']:
lat = PROBES_BY_ID[ n ]['lat']
lon = PROBES_BY_ID[ n ]['lon']
asn = PROBES_BY_ID[ n ]['asn_%s' % ( proto ) ]
result['nodes'].append({'probe_id': n, 'asn': asn, 'lat': lat, 'lon': lon})
name2idx[ n ] = idx
idx += 1
for l in data[proto]['links']:
src,dst,ixp = l.split('>',2)
result['links'].append({'source': name2idx[ int(src)], 'target': name2idx[ int(dst)], 'ixp': ixp})
#for i in sorted( data[proto]['ixps'], key=lambda x:data[proto]['ixps'][x], reverse=True ):
for i in sorted( data[proto]['ixps'], reverse=True ):
result['ixps'].append( i )
with open('%s/ixplans.%s.json' % ( VIZPATH, proto ), 'w') as outfile:
json.dump( result , outfile )
print "IXP LANs: viz results in '%s'" % ( VIZPATH )
### probetags
def init_probetags( basedata, probes ):
return {}
def do_probetags_entry( data, proto, data_entry ):
pass
def do_probetags_printresult( data ):
print "PROBETAGS"
VIZPATH="./analysis/probetags/"
if not os.path.exists( VIZPATH ):
os.makedirs( VIZPATH )
tags = {
'system': Counter(),
'user': Counter()
}
json_out = {
'system': [],
'user': [],
}
for p in PROBES:
if 'tags' in p:
for t in p['tags']:
if t.startswith('system-'):
t = t[7:]
tags['system'][ t ] += 1
else:
tags['user'][ t ] += 1
for tagtype in tags:
for tag in sorted( tags[tagtype].keys() ):
json_out[tagtype].append({'text': tag, 'count': tags[tagtype][tag]})
with open("%s/tags.json" % ( VIZPATH ), 'w') as outfile:
json.dump( json_out, outfile )
print "PROBE TAGS: viz results in '%s'" % ( VIZPATH )
### viaanchor
def init_viaanchor( basedata, probes ):
data = {}
for proto in ('v4','v6'):
data[ proto ] = {
'probeset': set(),
'rtts': {}
}
return data
def do_viaanchor_entry( data, proto, data_entry ):
#if data_entry['via_ixp'] == False and len( data_entry['dst_rtts'] ) > 0:
if len( data_entry['dst_rtts'] ) > 0:
key = '|'.join(map(str,[data_entry['src_prb_id'],data_entry['dst_prb_id']]))
if not key in data[ proto ]:
data[proto][ key ]['rtts'] = data_entry['dst_rtts']
else:
# in case of multiple intervals measured
for rtt in data_entry['dst_rtts']:
data[proto][ key ]['rtts'].append( rtt )
def do_viaanchor_printresult( data ):
VIZPATH='./analysis/viaanchor';
MIN_RESPONSE_COUNT=3
## anchors are 6XXX
anchors = set( filter( lambda x:x>=6000 and x<7000, PROBES_BY_ID.keys() ) )
for anchor_id in anchors:
ANCHORPATH= "%s/%s/" % ( VIZPATH, anchor_id )
if not os.path.exists( ANCHORPATH ):
os.makedirs( ANCHORPATH )
for proto in ('v4','v6'):
result = {'cells':[], 'probeset': set()}
for pair,rtts in data[ proto ].iteritems():
if len( rtts ) < MIN_RESPONSE_COUNT: continue
direct_minrtt = min(rtts)
src_prb, dst_prb = pair.split('|')
if anchor_id in (src_prb, dst_prb):
continue
pair1 = "%s|%s" % ( src_prb, anchor_id )
pair2 = "%s|%s" % ( anchor_id, dst_prb )
if not pair1 in data[ proto ]: continue
if not pair2 in data[ proto ]: continue
if len( data[ proto ][ pair1 ] ) < MIN_RESPONSE_COUNT: continue
if len( data[ proto ][ pair2 ] ) < MIN_RESPONSE_COUNT: continue
stitch_minrtt = min( data[ pair1 ] ) + min( data[ pair2 ] )
result['probeset'].add( src_prb )
result['probeset'].add( dst_prb )
result['cells'].append({
'src_prb': src_prb,
'dst_prb': dst_prb,
'direct_minrtt': direct_minrtt,
'stitch_minrtt': stitch_minrtt,
'stitch_rtt_gain': direct_minrtt - stitch_minrtt
})
result['probes'] = []
for prb_id in result['probeset']:
result['probes'].append({
})
with open("%s/stitching.%s.json" % ( ANCHORPATH, proto ) ,'w') as f:
print >>f, json.dumps( result, indent=2 )
print "VIAANCHOR viz results for anchor %s in '%s'" % ( anchor_id, ANCHORPATH )
def init_cities( basedata, probes ):
return {'v4': Counter(), 'v6': Counter()}
def do_cities_entry( data, proto, data_entry ):
for city in data_entry['locations']:
data[proto][city] += 1
def do_cities_printresult( data ):
print "CITIES"
print "======"
for proto in ('v4','v6'):
print "IP%s" % ( proto )
for city,count in data[ proto ].most_common():
print " %s (%s)" % (city, count)
### below might be easy to copy-paste for additional analyses
### stub
def init_stub( basedata, probes ):
return {}
def do_stub_entry( data, proto, data_entry ):
pass
def do_stub_printresult( data ):
pass
## http://stackoverflow.com/a/13814557/1520581
def copytree(src, dst, symlinks=False, ignore=None):
if not os.path.exists(dst):
os.makedirs(dst)
for item in os.listdir(src):
s = os.path.join(src, item)
d = os.path.join(dst, item)
if os.path.isdir(s):
copytree(s, d, symlinks, ignore)
else:
if not os.path.exists(d) or os.stat(src).st_mtime - os.stat(dst).st_mtime > 1:
shutil.copy2(s, d)
def main():
## ixps
### analysis types available
# maybe can make a nice dispatch table out of this
### and/or specify this at command line, ie. ./analyse-results.py <analysis-name> <analysis-name>
# 'ixp_county'
# 'ixpcountry'
basedata = None
with open("basedata.json") as inf:
basedata = json.load( inf )
probes = None
#with open("probeset.json") as inf:
# probes = json.load( inf )
defs={
'ixpcount': True,
'incountry': True,
'ixpcountry': True,
'cities': True,
'asgraph': True,
'geopath': True,
'ixplans': True,
'probetags': True,
'viaanchor': False, ## buggy
'perasn': True
}
#defs={'perasn': True}
if len( sys.argv ) > 1:
# take defs from stdin arguments
# so you can say: analyse-results.py incountry
defs = {}
for df in sys.argv[1:]:
defs[df]=True
defs['common']=True ## always true
### initialise all analyses
data = {}
### copy template viz stuff
copytree('%s/template/' % BASEDIR ,'./analysis')
## only the analyses that are 'True'
analysis_list = sorted( filter(lambda x: defs[x], defs.keys() ) )
for analysis in analysis_list:
## this is a fancy way of saying:
#data['ixpcount'] = init_ixpcount( basedata, probes )
#data['incountry'] = init_incountryy( basedata, probes )
data[ analysis ] = globals()['init_%s' % analysis]( basedata , PROBES )
### loop over all traceroutes
for proto,data_entry in data_line_generator():
for analysis in analysis_list:
## this calls:
# do_ixpcountry_entry( data['ixpcountry'], proto, data_entry )
globals()["do_%s_entry" % analysis]( data[ analysis ], proto, data_entry )
### print analyses results
for analysis in analysis_list:
globals()["do_%s_printresult" % analysis]( data[analysis] )
if __name__ == '__main__':
#try:
main()
#except UnicodeEncodeError, e:
# print e
# print "If you encounter errors like described here:"
# print " http://stackoverflow.com/questions/4545661/unicodedecodeerror-when-redirecting-to-file"
# print "Consider setting the env var: PYTHONIOENCODING=UTF-8"