61 lines
1.9 KiB
Python
Executable File
61 lines
1.9 KiB
Python
Executable File
#!/usr/bin/python3
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#
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# This is a tool Josh uses on his box serving mailinabox.email to parse the nginx
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# access log to see how many people are installing Mail-in-a-Box each day, by
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# looking at accesses to the bootstrap.sh script.
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import re
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import glob
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import gzip
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import os.path
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import json
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import dateutil.parser
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outfn = "/home/user-data/www/mailinabox.email/install-stats.json"
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# Make a unique list of (date, ip address) pairs so we don't double-count
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# accesses that are for the same install.
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accesses = set()
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# Scan the current and rotated access logs.
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for fn in glob.glob("/var/log/nginx/access.log*"):
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# Gunzip if necessary.
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if fn.endswith(".gz"):
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f = gzip.open(fn)
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else:
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f = open(fn, "rb")
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# Loop through the lines in the access log.
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with f:
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for line in f:
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# Find lines that are GETs on /bootstrap.sh by either curl or wget.
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m = re.match(rb"(?P<ip>\S+) - - \[(?P<date>.*?)\] \"GET /bootstrap.sh HTTP/.*\" 200 \d+ .* \"(?:curl|wget)", line, re.I)
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if m:
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date, time = m.group("date").decode("ascii").split(":", 1)
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date = dateutil.parser.parse(date).date().isoformat()
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ip = m.group("ip").decode("ascii")
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accesses.add((date, ip))
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# Aggregate by date.
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by_date = {}
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for date, ip in accesses:
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by_date[date] = by_date.get(date, 0) + 1
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# Since logs are rotated, store the statistics permanently in a JSON file.
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# Load in the stats from an existing file.
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if os.path.exists(outfn):
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existing_data = json.load(open(outfn))
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for date, count in existing_data:
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if date not in by_date:
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by_date[date] = count
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# Turn into a list rather than a dict structure to make it ordered.
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by_date = sorted(by_date.items())
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# Pop the last one because today's stats are incomplete.
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by_date.pop(-1)
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# Write out.
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with open(outfn, "w") as f:
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json.dump(by_date, f, sort_keys=True, indent=True)
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