| 413 |
self.data[record] = values |
self.data[record] = values |
| 414 |
|
|
| 415 |
|
|
| 416 |
def table_to_dbf(table, filename): |
|
| 417 |
"""Create the dbf file filename from the table""" |
def _find_dbf_column_names(names): |
| 418 |
|
"""Determine the column names to use in a DBF file |
| 419 |
|
|
| 420 |
|
DBF files have a length limit of 10 characters on the column names |
| 421 |
|
so when writing an arbitrary Thuban table to a DBF file we may have |
| 422 |
|
we may have to rename some of the columns making sure that they're |
| 423 |
|
unique in the DBF file too. |
| 424 |
|
|
| 425 |
|
Names that are already short enough will stay the same. Longer names |
| 426 |
|
will be truncated to 10 characters or if that isn't unique it will |
| 427 |
|
be truncated more and filled up with digits. |
| 428 |
|
|
| 429 |
|
The parameter names should be a list of the column names. The return |
| 430 |
|
value will be a dictionary mapping the names in the input list to |
| 431 |
|
the names to use in the DBF file. |
| 432 |
|
""" |
| 433 |
|
# mapping from the original names in table to the names in the DBF |
| 434 |
|
# file |
| 435 |
|
name_map = {} |
| 436 |
|
|
| 437 |
|
# First, we keep all names that are already short enough |
| 438 |
|
for i in range(len(names) - 1, -1, -1): |
| 439 |
|
if len(names[i]) <= 10: |
| 440 |
|
name_map[names[i]] = names[i] |
| 441 |
|
del names[i] |
| 442 |
|
|
| 443 |
|
# dict used as a set of all names already used as DBF column names |
| 444 |
|
used = name_map.copy() |
| 445 |
|
|
| 446 |
|
# Go through all longer names. If the name truncated to 10 |
| 447 |
|
# characters is not used already, we use that. Otherwise we truncate |
| 448 |
|
# it more and append numbers until we get an unused name |
| 449 |
|
for name in names: |
| 450 |
|
truncated = name[:10] |
| 451 |
|
num = 0; numstr = "" |
| 452 |
|
#print "truncated", truncated, num |
| 453 |
|
while truncated in used and len(numstr) < 10: |
| 454 |
|
num += 1 |
| 455 |
|
numstr = str(num) |
| 456 |
|
truncated = name[:10 - len(numstr)] + numstr |
| 457 |
|
#print "truncated", truncated, num |
| 458 |
|
if len(numstr) >= 10: |
| 459 |
|
# This case should never happen in practice as tables with |
| 460 |
|
# 10^10 columns seem very unlikely :) |
| 461 |
|
raise ValueError("Can't find unique dbf column name") |
| 462 |
|
|
| 463 |
|
name_map[name] = truncated |
| 464 |
|
used[truncated] = 1 |
| 465 |
|
|
| 466 |
|
return name_map |
| 467 |
|
|
| 468 |
|
def table_to_dbf(table, filename, rows = None): |
| 469 |
|
"""Create the dbf file filename from the table. |
| 470 |
|
|
| 471 |
|
If rows is not None (the default) then it must be a list of row |
| 472 |
|
indices to be saved to the file, otherwise all rows are saved. |
| 473 |
|
""" |
| 474 |
|
|
| 475 |
dbf = dbflib.create(filename) |
dbf = dbflib.create(filename) |
| 476 |
|
|
| 477 |
dbflib_fieldtypes = {FIELDTYPE_STRING: dbflib.FTString, |
dbflib_fieldtypes = {FIELDTYPE_STRING: dbflib.FTString, |
| 478 |
FIELDTYPE_INT: dbflib.FTInteger, |
FIELDTYPE_INT: dbflib.FTInteger, |
| 479 |
FIELDTYPE_DOUBLE: dbflib.FTDouble} |
FIELDTYPE_DOUBLE: dbflib.FTDouble} |
| 480 |
|
|
| 481 |
|
|
| 482 |
|
name_map = _find_dbf_column_names([col.name for col in table.Columns()]) |
| 483 |
|
|
| 484 |
# Initialise the header. Distinguish between DBFTable and others. |
# Initialise the header. Distinguish between DBFTable and others. |
| 485 |
for col in table.Columns(): |
for col in table.Columns(): |
| 486 |
width = table.Width(col.name) |
width = table.Width(col.name) |
| 488 |
prec = getattr(col, "prec", 12) |
prec = getattr(col, "prec", 12) |
| 489 |
else: |
else: |
| 490 |
prec = 0 |
prec = 0 |
| 491 |
dbf.add_field(col.name, dbflib_fieldtypes[col.type], width, prec) |
dbf.add_field(name_map[col.name], dbflib_fieldtypes[col.type], |
| 492 |
|
width, prec) |
| 493 |
|
|
| 494 |
|
if rows is None: |
| 495 |
|
rows = range(table.NumRows()) |
| 496 |
|
|
| 497 |
for i in range(table.NumRows()): |
recNum = 0 |
| 498 |
record = table.ReadRowAsDict(i) |
for i in rows: |
| 499 |
dbf.write_record(i, record) |
record = {} |
| 500 |
|
for key, value in table.ReadRowAsDict(i).items(): |
| 501 |
|
record[name_map[key]] = value |
| 502 |
|
dbf.write_record(recNum, record) |
| 503 |
|
recNum += 1 |
| 504 |
dbf.close() |
dbf.close() |
| 505 |
|
|
| 506 |
def table_to_csv(table, filename): |
def table_to_csv(table, filename, rows = None): |
| 507 |
"""Export table to csv file.""" |
"""Export table to csv file. |
| 508 |
|
|
| 509 |
|
If rows is not None (the default) then it must be a list of row |
| 510 |
|
indices to be saved to the file, otherwise all rows are saved. |
| 511 |
|
""" |
| 512 |
|
|
| 513 |
file = open(filename,"w") |
file = open(filename,"w") |
| 514 |
columns = table.Columns() |
columns = table.Columns() |
| 519 |
header = header + "\n" |
header = header + "\n" |
| 520 |
file.write(header) |
file.write(header) |
| 521 |
|
|
| 522 |
for i in range(table.NumRows()): |
if rows is None: |
| 523 |
|
rows = range(table.NumRows()) |
| 524 |
|
|
| 525 |
|
for i in rows: |
| 526 |
record = table.ReadRowAsDict(i) |
record = table.ReadRowAsDict(i) |
| 527 |
if len(record): |
if len(record): |
| 528 |
line = "%s" % record[columns[0].name] |
line = "%s" % record[columns[0].name] |
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