Update upstream source from tag 'upstream/0.19'

Update to upstream version '0.19'
with Debian dir 0cc2866dc4222e919db114429121a55eadb99c77

1 files changed, 0 insertions, 90 deletions

diff --git a/utils/ofx2xlsx.py b/utils/ofx2xlsx.py
deleted file mode 100644
index 32b19c6..0000000
--- a/utils/ofx2xlsx.py
+++ /dev/null
@@ -1,90 +0,0 @@
-from ofxparse import OfxParser
-import pandas as pd
-
-import argparse
-
-# TODO automatically extract from transactions
-fields = ['id','type', 'date', 'memo', 'payee', 'amount', 'checknum', 'mcc']
-
-parser = argparse.ArgumentParser(description='Convert multiple .qfx or .ofx to'
-                                             ' .xlsx.\n'
-                                             'Remove duplicate transactions '
-                                             'from different files.\n'
-                                             'use fixed columns:'
-                                             ' %s'%', '.join(fields))
-parser.add_argument('files', metavar='*.ofx *.qfx', type=str, nargs='+',
-                   help='.qfx or .ofx file names')
-parser.add_argument('--start', type=str, metavar='2014-01-01',
-                    default='2014-01-01',
-                   help="Don't take transaction before this date")
-parser.add_argument('--end', type=str, metavar='2014-12-31',
-                    default='2014-12-31',
-                    help="Don't take transaction after this date")
-parser.add_argument('--output', metavar='output.xlsx', type=str,
-                    default='output.xlsx', help='Were to store the xlsx')
-parser.add_argument('--id-length', metavar='24', type=int, default=24,
-                   help='Truncate the number of digits in a transaction ID.'
-                        ' This is important because this program remove'
-                        ' transactions with duplicate IDs (after verifing'
-                        ' that they are identical.'
-                        ' If you feel unsafe then use a large number but'
-                        'usually the last digits of the transaction ID are'
-                        'running numbers which change from download to download'
-                        ' as a result you will have duplicate transactions'
-                        ' unless you truncate the ID.')
-
-
-args = parser.parse_args()
-
-
-data = {}
-for fname in args.files:
-    ofx = OfxParser.parse(file(fname))
-    for account in ofx.accounts:
-        df = data.get(account.number, pd.DataFrame(columns=fields+['fname']))
-        for transaction in account.statement.transactions:
-            s = pd.Series([getattr(transaction,f) for f in fields], index=fields)
-            s['fname'] = fname.split('/')[-1]
-            df = df.append(s, ignore_index=True)
-        df['id'] = df['id'].str[:args.id_length]  # clip the last part of the ID which changes from download to download
-        data[account.number] = df
-
-print "Writing result to", args.output
-writer = pd.ExcelWriter(args.output)
-
-for account_number, df in data.iteritems():
-    # A transaction is identified using all `fields`
-    # collapse all repeated transactions from the same file into one row
-    # find the number of repeated transactions and
-    # put it in samedayrepeat column
-    df_count = df.groupby(fields+['fname']).size()
-    df_count = df_count.reset_index()
-    df_count.columns = list(df_count.columns[:-1]) + ['samedayrepeat']
-
-    # two transactions from the same file are always different
-    # but the same transaction can appear in multiple files if they overlap.
-    # check we have the same samedayrepeat for the same transaction on different files
-    df_size_fname_count = df_count.reset_index().groupby(fields).samedayrepeat.nunique()
-    assert (df_size_fname_count == 1).all(), "Different samedayrepeat in different files"
-
-    # take one file as an example
-    df1 = df_count.reset_index().groupby(fields+['samedayrepeat']).first()
-    df1 = df1.reset_index()
-
-    # expand back the collapsed transactions
-    # duplicate rows according to samedayrepeat value
-    df2 = df1.copy()
-    for i in range(2,df1.samedayrepeat.max()+1):
-        df2 = df2.append(df1[i<=df1.samedayrepeat])
-
-    # sort according to date
-    df2 = df2.reset_index().set_index('date').sort_index()
-    # filter dates
-    df2 = df2.ix[args.start:args.end]
-
-    #cleanup
-    df2 = df2.reset_index()[fields]
-
-    df2.to_excel(writer, account_number, index=False)
-
-writer.save()