Top all-time · #5884
Billets (Logilab
Company blog · logilab.org/blogentryprogrammingsystems
Billets (Logilab is the company blog at logilab.org, writing about programming and systems. Since 2010, 14 different Hacker News readers have linked it 14 times, most often “Introduction To Mercurial (hg) Phases”. It is still writing: the last post was on 2025-11-28, and you can follow it by feed.
Too few sampled comments (9) to say how often HN recommends it.?
Why HN links it
HN commenters link Logilab's blog posts as references for Python tooling, mainly pylint, Pyreverse UML diagrams and xmldiff, plus a post on Mercurial phases. The comments cite these posts without judging the writing.
Summarised by Claude from a sample of 9 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Logilab est une société spécialisée dans le développement de logiciels, le conseil, et la formation en web sémantique et informatique scientifique. Découvrez nos services et expertises pour vos projets.
Most-linked posts?
- /8574 people · 4 mentions · first linked 2010-05-06
- Introduction To Mercurial (hg) Phases2 people · 2 mentions · first linked 2012-02-02
- /blogentry/68832 people · 2 mentions · first linked 2020-03-22
What Hacker News says?
Have you tried Pyreverse[1]? I used it for my Software Engineering course. From the documentation - Pyreverse analyses Python code and extracts UML class diagrams and package dependencies. [1] https://www.logilab.org/blogentry/6883
Comment linking /blogentry/6883
on “Technical Writing Courses”Submitted Pylint 1.0 released as a story · 5 points
HN discussionCarmack's article inspired me greatly. For the past month I have been churning a product idea for a code analysis & program transformation tool for Python. Seeing someone like Carmack recommend tools like these feels like substantial validation of their usefulness. While investigating the feasibility of my product idea, I have run across 3 interesting Python analysis tools that are often overshadowed by pyflakes & p…
Comment linking /card/pylintfeatures
on “John Carmack on the importance of Static Code Analysis”Submitted Introduction To Mercurial (hg) Phases as a story · 3 points
HN discussionpylint is probably the most commonly used: http://www.logilab.org/857
Comment linking /857
on “Python 3.3.0 released”Submitted Virtualenv - Play safely with a Python as a story · 2 points
HN discussionAs long as we're on an open source kick here (since I prefer open source over proprietary): http://checkstyle.sourceforge.net/ http://cppcheck.sourceforge.net/ http://google-styleguide.googlecode.com/svn/trunk/cpplint/cp... http://www.dwheeler.com/flawfinder/ http://www.dsm.fordham.edu/~ftnchek/ http://community.haskell.org/~ndm/hlint/ http://jlint.sourceforge.net/ http://search.cpan.org/dist/Perl-Critic/bin/perlcri…
Comment linking /857
on “John Carmack on Static Code Analysis”Submitted Python Profiling tools and visualizer as a story · 1 points
HN discussionMercurial tries to avoid the "rebasing public changes" problem with a new hg 2.1 feature called "phases" that tracks whether a changeset has been shared. Unfortunately, it is a little simple-minded because pushing to any other hg repo, even on your same machine, will mark the changeset as "public". http://www.logilab.org/blogentry/88203
Comment linking /blogentry/88203
on “A Rebase Workflow for Git”Submitted Guide to Virtualenv (like rvm for Python) as a story · 1 points
HN discussionFor python: pylint is nice http://www.logilab.org/857
Comment linking /857
on “Perl::Critic - Automatically review your code”"You wonder why it hasn't been done before," one said. To cite some previous work: sgrep (structured grep): http://www.cs.helsinki.fi/u/jjaakkol/sgrep.html xmlstarlet (including xpath): http://xmlstar.sourceforge.net/ xmldiff: http://www.logilab.org/859 jsawk (including jsonquery): https://github.com/micha/jsawk
Comment linking /859
on “Dartmouth researchers working on variants of diff and grep”Since you mention you're using Flask. Before diving into data intensive stuff if need be, a lot can be done by profiling, refactoring, and improving the actual code: - Profiling and refactoring Python code in general: Using yappi[^1] to profile and generate profile data, and KCachegrind[^2] to visualize that data in the form of call graphs, number of cycles, etc. can yield great results. You can find which functions…
Comment linking /blogentry/6883
on “Ask HN: What do I need to learn how to write a scalable app?”>No; The line has to be executed for the error to show up in a dynamic language. This is a common misperception: http://pychecker.sourceforge.net/ http://www.logilab.org/857 (pylint) http://www.jslint.com/ And to head off the common "But but but it's not the compiler", I contend you're doing something wrong if you're not also running lint against a C program, as C compilers do not catch tons of things that people do…
Comment linking /857
on “I like strong typing and compilation errors”
