CODEWITHSUNDEEP
pythondatabasefoxprodbf
F.Motz
F.Motz

Reputation: 15

write dbf slice from dbf in python

I would like to use the DBF module to split a vfp dbf based on a value in a column, dist. I therefore extracted all necessary indices to use them for the export. Unfortunately, the original table does not allow a list of indices.

input_file = 'refrence.dbf'

table = dbf.Table(input_file)
l = []

for ind, record in enumerate(table.open(mode=dbf.READ_WRITE)):
    with record as r:
        if r.dist >= start and r.dist <= end:
            l.append(ind)

is there an easier way to get to n separate dbf files containing only the rows which satisfy the condition r.dist >= start and r.dist <= end ?

Upvotes: 1

Views: 1574

Answers (3)

A.Z. Soft
A.Z. Soft

Reputation: 546

You can access filtered table like this

table[l]["dist"]

or

table[l][fieldName]

or 

table[l][0]

You should make your dbf file with this filtered data.

Upvotes: 1

Paulo Scardine
Paulo Scardine

Reputation: 77399

I would try something like the following (untested):

def copy_range(source, destination, field_name, start, end):
    src = dbf.Table(source).open()
    dst = src.new(destination).open(dbf.READ_WRITE)  # copy structure
    for record in src:
        if start <= record[field_name] <= end:
            dst.append(record)
    src.close()
    dst.close()

Then call it like:

copy_range('refrence.dbf', 'result.dbf', 'dist', 100, 200)

Upvotes: 1

Ethan Furman
Ethan Furman

Reputation: 69298

Selecting the records can be done by:

target_records = [rec for rec in table if start <= rec.dist <= end]

Once you have the records, it's fairly easy to copy them into a new dbf:

new_table = old_table.new('some_file.dbf')
with new_table:
    for record in target_records:
        new_table.append(record)

Upvotes: 1

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