I just helped a friend troubleshoot a DNS problem he was having on oneof his home Linux machines. The specific problem was that Firefox wastaking a long time to start connecting to web sites; he believed itwas DNS problems.

I ran down some standard guesses:

• maybe one or more nameservers in /etc/resolv.conf weren'tresponding, and Firefox was having to wait for lookups against eachto time out. But straight lookups with dig weren't delayed, so itwasn't that.

In the comments on the other day's' minimizing object churn ' entry, it wasnoted that Python string concatenation had been optimized some in therecent 2.4 release of the CPython interpreter. The 2.4 release notessay (from here ):

• String concatenations in statements of the form s = s + "abc" and s += "abc" are now performed more efficiently in certaincircumstances.

But what is 'more efficiently' and what are the 'certaincircumstances'? What does it

This week we received 12,872 email messages from 229 different IPaddresses. Our SMTP server handled 22,584 sessions from 1,544different IP addresses, which is significantly down from last week .

To go with it, overall connections are down a lot from last week : we only saw 93,950 connections from at least 31,000different IP addresses. I believe this is the lowest connection rateI've seen since

One of the interesting things about writing code in high level garbagecollected languages is how your optimization concerns can change. Oneoptimization in all GC'd languages, Python included, is minimizing thecreation of new objects and maximizing the reuse of old ones; thefewer new objects you create, the fewer cycles garbage collectioneats, the less memory gets fragmented, and you often even use lessmemory overall.

Minimizing object churn is behind several well-known Python(anti-)patterns, such as 'avoid repeated string