Hello --
Is there a convention, library or Pythonic idiom for performing
lightweight relational operations on flatfiles? I frequently find
myself writing code to do simple SQL-like operations between flat
files, such as appending columns from one file to another, linked
through a common id. For example, take a list of addresses and append
a 'district' field by looking up a congressional district from a
second file that maps zip codes to districts.
Conceptually this is a simple database operation with a join on a
common field (zip code in the above example). Other case use other
relational operators (projection, cross-product, etc) so I'm really
looking for something SQL-like in functionality. However, the data is
in flat-files, the file structure changes frequently, the files are
dynamically generated from a range of sources, are short-lived in
nature, and otherwise not warrant the hassle of a database setup. So
I've been looking around for a nice, Pythonic, zero-config (no
parsers, no setup/teardown, etc) solution for simple queries that
handles a database of csv-files-with-headers automatically. There are
number of solutions that are close, but in the end come up short:
- KirbyBase 1.9 (latest Python version) is the closest that I could
find, as it lets you keep your data in flatfiles and perform
operations using the field names from those text-based tables, but it
doesn't support joins (the more recent Ruby version seems to).
- Buzhug and Sqlite have their data structures w no automatic .tab
or .csv parsing (unless sqlite includes a way to map flatfiles to
sqlite virtual tables that I don't know about).
- http://aspn.activestate.com/ASPN/Coo.../Recipe/159974 is
heading in the right direction, as it shows how to perform relational
operations on lists and are index based rather than field-name based.
- http://aspn.activestate.com/ASPN/Coo.../Recipe/498130 and
provide ways of automatically populating DBs but not the reverse
(persist changes back out to the data files)
The closest alternatives I've found are the GNU textutils that support
join, cut, merge, etc but I need to add additional logic they don't
support, nor do they allow field-level write operations from Python
(UPDATE ... WHERE ...). Normally I'd jump right in and start coding
but this seems like something so common that I would have expected
someone else to have solved, so in the interest of not re-inventing
the wheel I thought I'd see if anyone had any other suggestions. Any
thoughts?
Thanks!
Ramon
Is there a convention, library or Pythonic idiom for performing
lightweight relational operations on flatfiles? I frequently find
myself writing code to do simple SQL-like operations between flat
files, such as appending columns from one file to another, linked
through a common id. For example, take a list of addresses and append
a 'district' field by looking up a congressional district from a
second file that maps zip codes to districts.
Conceptually this is a simple database operation with a join on a
common field (zip code in the above example). Other case use other
relational operators (projection, cross-product, etc) so I'm really
looking for something SQL-like in functionality. However, the data is
in flat-files, the file structure changes frequently, the files are
dynamically generated from a range of sources, are short-lived in
nature, and otherwise not warrant the hassle of a database setup. So
I've been looking around for a nice, Pythonic, zero-config (no
parsers, no setup/teardown, etc) solution for simple queries that
handles a database of csv-files-with-headers automatically. There are
number of solutions that are close, but in the end come up short:
- KirbyBase 1.9 (latest Python version) is the closest that I could
find, as it lets you keep your data in flatfiles and perform
operations using the field names from those text-based tables, but it
doesn't support joins (the more recent Ruby version seems to).
- Buzhug and Sqlite have their data structures w no automatic .tab
or .csv parsing (unless sqlite includes a way to map flatfiles to
sqlite virtual tables that I don't know about).
- http://aspn.activestate.com/ASPN/Coo.../Recipe/159974 is
heading in the right direction, as it shows how to perform relational
operations on lists and are index based rather than field-name based.
- http://aspn.activestate.com/ASPN/Coo.../Recipe/498130 and
provide ways of automatically populating DBs but not the reverse
(persist changes back out to the data files)
The closest alternatives I've found are the GNU textutils that support
join, cut, merge, etc but I need to add additional logic they don't
support, nor do they allow field-level write operations from Python
(UPDATE ... WHERE ...). Normally I'd jump right in and start coding
but this seems like something so common that I would have expected
someone else to have solved, so in the interest of not re-inventing
the wheel I thought I'd see if anyone had any other suggestions. Any
thoughts?
Thanks!
Ramon
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