advanced string formatting vs template strings

Templates are meant to be simpler than the the usual string formatting, at the cost of expressiveness. The rationale of PEP 292 compares templates to Python's %-style string formatting:

Python currently supports a string substitution syntax based on C's printf() '%' formatting character. While quite rich, %-formatting codes are also error prone, even for experienced Python programmers. A common mistake is to leave off the trailing format character, e.g. the s in %(name)s.

In addition, the rules for what can follow a % sign are fairly complex, while the usual application rarely needs such complexity. Most scripts need to do some string interpolation, but most of those use simple "stringification" formats, i.e. %s or %(name)s This form should be made simpler and less error prone.

While the new .format() improved the situation, it's still true that the format string syntax is rather complex, so the rationale still has its points.

One key advantage of string templates is that you can substitute only some of the placeholders using the safe_substitute method. Normal format strings will raise an error if a placeholder is not passed a value. For example:

"Hello, {first} {last}".format(first='Joe')

raises:

Traceback (most recent call last):  File "<stdin>", line 1, in <module>KeyError: 'last'

But:

from string import TemplateTemplate("Hello, $first $last").safe_substitute(first='Joe')

Produces:

'Hello, Joe $last'

Note that the returned value is a string, not a Template; if you want to substitute the $last you'll need to create a new Template object from that string.

For what it's worth, Template substitution from a dict appears to be 4 to 10 times slower than format substitution, depending on the length of the template. Here's a quick comparison I ran under OS X on a 2.3 GHz core i7 with Python 3.5.

from string import Templatelorem = "Lorem ipsum dolor sit amet {GIBBERISH}, consectetur adipiscing elit {DRIVEL}. Expectoque quid ad id, quod quaerebam, respondeas."loremtpl = Template("Lorem ipsum dolor sit amet $GIBBERISH, consectetur adipiscing elit $DRIVEL. Expectoque quid ad id, quod quaerebam, respondeas.")d = dict(GIBBERISH='FOOBAR', DRIVEL = 'RAXOOP')In [29]: timeit lorem.format(**d)1.07 µs ± 2.13 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)In [30]: timeit loremtpl.substitute(d)8.74 µs ± 12.9 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

The worst case I tested was about 10 times slower for a 13 character string. The best case I tested was about 4 times slower for a 71000 character string.