![]() You might want to de-duplicate these and print the number of unique pages with 404s: s = set()ĭave and I have been working on expanding piwheels' logger to include web-page hits, package searches, and more, and it's been a piece of cake, thanks to lars. If you wanted to show only the 404s, you could do: with open('ssl_access.log') as f: The entry has become a namedtuple with attributes relating to the entry data, so for example, you can access the status code with row.status and the path with _str: with open('ssl_access.log') as f: It's parsed the log entry and put the data into a structured format. This example will open a single log file and print the contents of every row: with open('ssl_access.log') as f: To get any sensible data out of your logs, you need to parse, filter, and sort the entries. Your log files will be full of entries like this, not just every single page hit, but every file and resource served-every CSS stylesheet, JavaScript file and image, every 404, every redirect, every bot crawl. This is a request showing the IP address of the origin of the request, the timestamp, the requested file path (in this case /, the homepage, the HTTP status code, the user agent (Firefox on Ubuntu), and so on. On a typical web server, you'll find Apache logs in /var/log/apache2/ then usually access.log, ssl_access.log (for HTTPS), or gzipped rotated logfiles like access-20200101.gz or ssl_access-20200101.gz. I'm using Apache logs in my examples, but with some small (and obvious) alterations, you can use Nginx or IIS. You'll want to download the log file onto your computer to play around with it. To get started, find a single web access log and make a copy of it. On some systems, the right route will be pip3 install lars. You can install lars with: $ pip install lars Since it's a relational database, we can join these results on other tables to get more contextual information about the file. In real time, as Raspberry Pi users download Python packages from, we log the filename, timestamp, system architecture (Arm version), distro name/version, Python version, and so on. Then a few years later, we started using it in the piwheels project to read in the Apache logs and insert rows into our Postgres database. I first saw Dave present lars at a local Python user group. Lars is another hidden gem written by Dave Jones. That means you can use Python to parse log files retrospectively (or in real time) using simple code, and do whatever you want with the data-store it in a database, save it as a CSV file, or analyze it right away using more Python. Lars is a web server-log toolkit for Python.
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