Best way to do data source abstraction

[Arthur Pemberton]

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...

[Sybren Stuvel]

Re: Best way to do data source abstraction

Arthur Pemberton enlightened us with:[color=blue]
> What is the best way to do data source abtraction?[/color]

That depends on your data source. For files, file-like objects are an
abstraction. For databases there is PEP 249.
[color=blue]
> 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.[/color]

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

[bruno at modulix]

Re: Best way to do data source abstraction

Arthur Pemberton wrote:[color=blue]
> 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.[/color]

Could you explain more accurately what you're trying to do ? FWIW, it
seems that a plain old factory function would do ?

class DatasourceAbstr action(object):
""" base class, factoring common stuff """
# implementation here

class JpegFile(Dataso urceAbstraction ):
# ....


class PdfFile(Datasou rceAbstraction) :
# ....

class TxtFile(Datasou rceAbstraction) :
# ....

# etc
_classes = {
'jpg' : JpegFile,
'txt' : TxtFile,
'pdf' : PdfFile,
# etc..
}

def Datasource(inpu tfile):
ext = os.path.splitex t(inputfile)
return _classes.get(ex t, <SomeDefaultCla ssHere>)(inputf ile)

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 'onurb@xiludom. gro'.split('@')])"

[Larry Bates]

Re: Best way to do data source abstraction

Arthur Pemberton wrote:[color=blue]
> 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.
>[/color]

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(fi lepath, 'r')
self.columnname s=columnnames
return

def __iter__(self):
return self

def next(self):
#
# Try to get the next line from file
#
try: line=self.fp.ne xt()
except StopIteration:
self.fp.close()
raise

#
# Decode the tab delimited line into its parts
#
line=line.rstri p()
if not line: raise StopIteration
values=line.spl it('\t')
print "values=", values
l=zip(self.colu mnnames, values)
print l
for column, value in l:
setattr(self, column, value)

return

if __name__ == "__main__":
obj=foo('abc.tx t', ['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

[Larry Bates]

Re: Best way to do data source abstraction

Arthur Pemberton wrote:[color=blue]
> 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.
>[/color]

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(fi lepath, 'r')
self.columnname s=columnnames
return

def __iter__(self):
return self

def next(self):
#
# Try to get the next line from file
#
try: line=self.fp.ne xt()
except StopIteration:
self.fp.close()
raise

#
# Decode the tab delimited line into its parts
#
line=line.rstri p()
if not line: raise StopIteration
values=line.spl it('\t')
print "values=", values
l=zip(self.colu mnnames, values)
print l
for column, value in l:
setattr(self, column, value)

return

if __name__ == "__main__":
obj=foo('abc.tx t', ['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