Thank you, Tom.
-York Tom Anderson wrote: > 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 > -- http://mail.python.org/mailman/listinfo/python-list
