Best way to do data source abstraction
What is the best way to do data source abtraction? For example have different classes with the same interface, but different implementations. I was thinking of almost having classA as my main class, and have classA dynamically absorb classFood into to based on the extension of the input file received by classA. But this doesn't seem possible. Please advise. Thank you. -- To be updated... -- http://mail.python.org/mailman/listinfo/python-list
Re: Best way to do data source abstraction
Arthur Pemberton enlightened us with: What is the best way to do data source abtraction? That depends on your data source. For files, file-like objects are an abstraction. For databases there is PEP 249. I was thinking of almost having classA as my main class, and have classA dynamically absorb classFood into to based on the extension of the input file received by classA. But this doesn't seem possible. You don't explain the most important part - absorb. What does that mean? And what does it mean to have classA almost as your main class? Sybren -- The problem with the world is stupidity. Not saying there should be a capital punishment for stupidity, but why don't we just take the safety labels off of everything and let the problem solve itself? Frank Zappa -- http://mail.python.org/mailman/listinfo/python-list
Re: Best way to do data source abstraction
Arthur Pemberton wrote:
What is the best way to do data source abtraction? For example have
different classes with the same interface, but different
implementations.
I was thinking of almost having classA as my main class, and have
classA dynamically absorb classFood into to based on the extension
of the input file received by classA. But this doesn't seem possible.
Could you explain more accurately what you're trying to do ? FWIW, it
seems that a plain old factory function would do ?
class DatasourceAbstraction(object):
base class, factoring common stuff
# implementation here
class JpegFile(DatasourceAbstraction):
#
class PdfFile(DatasourceAbstraction):
#
class TxtFile(DatasourceAbstraction):
#
# etc
_classes = {
'jpg' : JpegFile,
'txt' : TxtFile,
'pdf' : PdfFile,
# etc..
}
def Datasource(inputfile):
ext = os.path.splitext(inputfile)
return _classes.get(ext, SomeDefaultClassHere)(inputfile)
The fact that there's no 'new' keyword in Python, and that classes are
callable objects acting as factories means that it's a no-brainer to use
a plain function (eventually disguised as a Class - the client code just
doesn't care !-) as factory...
Now if I missed the point, please give more explanations...
--
bruno desthuilliers
python -c print '@'.join(['.'.join([w[::-1] for w in p.split('.')]) for
p in '[EMAIL PROTECTED]'.split('@')])
--
http://mail.python.org/mailman/listinfo/python-list
Re: Best way to do data source abstraction
Arthur Pemberton wrote:
What is the best way to do data source abtraction? For example have
different classes with the same interface, but different
implementations.
I was thinking of almost having classA as my main class, and have
classA dynamically absorb classFood into to based on the extension
of the input file received by classA. But this doesn't seem possible.
Please advise.
Thank you.
The best method I've found is to have a class that abstracts
the data and presents the values from the data source via
class attributes. If you also implement it as an iterator
(e.g. give it __iter__ and __next__ methods), you can easily
iterate over the resultset from each data source. With this
method I've abstracted data in CSV files, fixed ASCII files,
SQL tables, Excel Spreadsheets, tab delimited files that are
members of a .ZIP archive, you name it.
Short example (not tested):
class foo:
'''
Class to abstract tab delimited files
'''
def __init__(self, filepath, columnnames):
self.fp=open(filepath, 'r')
self.columnnames=columnnames
return
def __iter__(self):
return self
def next(self):
#
# Try to get the next line from file
#
try: line=self.fp.next()
except StopIteration:
self.fp.close()
raise
#
# Decode the tab delimited line into its parts
#
line=line.rstrip()
if not line: raise StopIteration
values=line.split('\t')
print values=, values
l=zip(self.columnnames, values)
print l
for column, value in l:
setattr(self, column, value)
return
if __name__ == __main__:
obj=foo('abc.txt', ['name', 'address1', 'address2', 'city', 'state', 'zip'])
for entry in obj:
print
print Name, obj.name
print Address1, obj.address1
print Address2, obj.address2
print City, obj.city
print State..., obj.state
print Zip., obj.zip
-Larry Bates
--
http://mail.python.org/mailman/listinfo/python-list
