On Mon, 19 Sep 2005, Bruno Desthuilliers wrote:
York a écrit :
(snip)
I love python. However, as a biologist, I like some high-levels
functions in R. I don't want to spend my time on parse a data file.
http://www.python.org/doc/current/lib/module-csv.html
Then in my python script, I call R to read data file and write them
into an MySQL table. If python can do this easily, I don't need R at
all.
So you don't need R at all.
Did you even read the OP's post? Specifically, this bit:
R language has very high-level IO functions, its read.table can read a
total .csv file and recogonize the types of each column.
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Python's csv module gives you tuples of strings; it makes no effort to
recognise the types of the data. AFAIK, python doesn't have any IO
facilities like this.
Larry's point that automagical type detection is risky because it can make
mistakes is a good one, but that doesn't mean that magic is useless - on
the contrary, for the majority of cases, it works fine, and is extremely
convenient.
The good news is that it's reasonably easy to write such a function: you
just need a function 'type_convert' which takes a string and returns an
object of the right type; then you can do:
import csv
def read_table(f):
for row in csv.reader(f):
yield map(type_convert, row)
This is a very, very rough cut - it doesn't do comment stripping, skipping
blank lines, dealing with the presence of a header line or the use of
different separators, etc, but all that's pretty easy to add. Also, note
that this returns an iterator rather than a list; use list(read_table(f))
if you want an actual list, or change the implementation of the function.
type_convert is itself fairly simple:
def _bool(s): # helper method for booleans
s = s.lower()
if (s == "true"): return True
elif (s == "false"): return False
else: raise ValueError, s
types = (int, float, complex, _bool, str)
def type_convert(s):
for type in types:
try:
return type(s)
except ValueError:
pass
raise ValueError, s
This whole thing isn't quite as sophisticated as R's table.convert; R
reads the whole table in, then tries to find a type for each column which
will fit all the values in that column, whereas i do each cell
individually. Again, it wouldn't be too hard to do this the other way
round.
Anyway, hope this helps. Bear in mind that there are python bindings for
the R engine, so you could just use R's version of read.table in python.
tom
--
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