Mercurial > templog
annotate web/log.py @ 37:8da0fdadc8d7
- Getting there, update has problems
| author | Matt Johnston <matt@ucc.asn.au> |
|---|---|
| date | Sat, 16 Jun 2012 09:08:07 +0800 |
| parents | 024f5571df8c |
| children | 9b5b202129c3 |
| rev | line source |
|---|---|
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37
8da0fdadc8d7
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1 #:vim:et:ts=4:sts=4:sw=4: |
| 27 | 2 import rrdtool |
| 3 import os | |
| 29 | 4 import os.path |
| 27 | 5 import sys |
| 29 | 6 import glob |
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7 import hashlib |
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8 import tempfile |
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9 import time |
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10 import syslog |
| 29 | 11 from colorsys import hls_to_rgb |
| 27 | 12 |
| 28 | 13 import config |
| 27 | 14 |
| 15 def sensor_rrd_path(s): | |
| 28 | 16 return '%s/sensor_%s.rrd' % (config.DATA_PATH, s) |
| 27 | 17 |
| 29 | 18 # returns (path, sensor_name) tuples |
| 19 def all_sensors(): | |
| 20 return [(r, os.path.basename(r[:-4])) | |
| 21 for r in glob.glob('%s/*.rrd' % config.DATA_PATH)] | |
| 22 | |
| 27 | 23 def create_rrd(sensor_id): |
| 24 rrdtool.create(sensor_rrd_path(sensor_id), '-s', '300', | |
| 25 'DS:temp:GAUGE:600:-10:100', | |
| 26 'RRA:AVERAGE:0.5:1:1051200') | |
| 27 | |
| 29 | 28 |
| 29 # stolen from viewmtn, stolen from monotone-viz | |
| 30 def colour_from_string(str): | |
| 31 def f(off): | |
| 32 return ord(hashval[off]) / 256.0 | |
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33 hashval = hashlib.sha1(str).digest() |
| 29 | 34 hue = f(5) |
| 35 li = f(1) * 0.15 + 0.55 | |
| 36 sat = f(2) * 0.5 + .5 | |
| 37 return ''.join(["%.2x" % int(x * 256) for x in hls_to_rgb(hue, li, sat)]) | |
| 38 | |
| 39 def graph_png(start, length): | |
| 40 rrds = all_sensors() | |
| 41 | |
| 42 graph_args = [] | |
| 43 for n, (rrdfile, sensor) in enumerate(rrds): | |
| 44 vname = 'temp%d' % n | |
| 45 graph_args.append('DEF:%(vname)s=%(rrdfile)s:temp:AVERAGE' % locals()) | |
| 46 width = config.LINE_WIDTH | |
| 47 legend = config.SENSOR_NAMES.get(sensor, sensor) | |
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48 colour = config.SENSOR_COLOURS.get(legend, colour_from_string(sensor)) |
| 29 | 49 graph_args.append('LINE%(width)f:%(vname)s#%(colour)s:%(legend)s' % locals()) |
| 50 | |
| 51 tempf = tempfile.NamedTemporaryFile() | |
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52 args = [tempf.name, '-s', str(int(start)), |
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53 '-e', str(int(start+length)), |
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54 '-w', str(config.GRAPH_WIDTH), |
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55 '-h', str(config.GRAPH_HEIGHT), |
| 29 | 56 '--slope-mode', |
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57 '--border', '0', |
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58 '--color', 'BACK#ffffff', |
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59 '--imgformat', 'PNG'] \ |
| 29 | 60 + graph_args |
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61 if config.GRAPH_FONT: |
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62 args += ['--font', 'DEFAULT:0:%s' % config.GRAPH_FONT] |
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63 print>>sys.stderr, args |
| 29 | 64 rrdtool.graph(*args) |
| 65 return tempf.read() | |
| 66 | |
| 27 | 67 def sensor_update(sensor_id, measurements, first_real_time, time_step): |
| 68 try: | |
| 69 open(sensor_rrd_path(sensor_id)) | |
| 70 except IOError, e: | |
| 71 create_rrd(sensor_id) | |
| 72 | |
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73 print>>sys.stderr, sensor_id, measurements, first_real_time, time_step |
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74 |
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75 if measurements: |
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76 values = ['%d:%f' % p for p in |
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77 zip((first_real_time + time_step*t for t in xrange(len(measurements))), |
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78 measurements)] |
| 27 | 79 |
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80 rrdfile = sensor_rrd_path(sensor_id) |
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81 print>>sys.stderr, values |
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82 rrdtool.update(rrdfile, *values) |
| 33 | 83 |
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84 # be paranoid |
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85 f = file(rrdfile) |
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86 os.fsync(f.fileno()) |
| 27 | 87 |
| 33 | 88 def record_debug(lines): |
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89 f = open('%s/debug.log' % config.DATA_PATH, 'a+') |
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90 f.write('===== %s =====\n' % time.strftime('%a, %d %b %Y %H:%M:%S')) |
| 33 | 91 f.writelines(('%s\n' % s for s in lines)) |
| 92 f.flush() | |
| 93 return f | |
| 94 | |
| 27 | 95 def parse(lines): |
| 33 | 96 |
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97 debugf = record_debug(lines) |
| 33 | 98 |
| 27 | 99 entries = dict(l.split('=', 1) for l in lines) |
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100 if len(entries) != len(lines): |
| 27 | 101 raise Exception("Keys are not unique") |
| 102 | |
| 103 num_sensors = int(entries['sensors']) | |
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104 num_measurements = int(entries['measurements']) |
| 27 | 105 |
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106 sensors = [entries['sensor_id%d' % n] for n in xrange(num_sensors)] |
| 27 | 107 |
| 108 meas = [] | |
| 109 for s in sensors: | |
| 110 meas.append([]) | |
| 111 | |
| 28 | 112 def val_scale(v): |
| 113 # convert decidegrees to degrees | |
| 114 return 0.1 * v | |
| 115 | |
| 27 | 116 for n in xrange(num_measurements): |
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117 vals = [val_scale(int(x)) for x in entries["meas%d" % n].strip().split()] |
| 27 | 118 if len(vals) != num_sensors: |
| 119 raise Exception("Wrong number of sensors for measurement %d" % n) | |
| 120 # we make an array of values for each sensor | |
| 121 for s in xrange(num_sensors): | |
| 122 meas[s].append(vals[s]) | |
| 123 | |
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124 avr_now = float(entries['now']) |
| 27 | 125 avr_first_time = float(entries['first_time']) |
| 126 time_step = float(entries['time_step']) | |
| 127 | |
| 128 first_real_time = time.time() - (avr_now - avr_first_time) | |
| 129 | |
| 130 for sensor_id, measurements in zip(sensors, meas): | |
| 131 sensor_update(sensor_id, measurements, first_real_time, time_step) | |
| 33 | 132 |
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133 debugf.write("Updated %d sensors\n" % len(sensors)) |
| 33 | 134 debugf.flush() |