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1 #!/usr/bin/env python3
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2
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3 import csv
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4 import sys
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5
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6
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7
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8 def main(files):
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9 header = []
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10 items = []
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11 possible_identity_headers = None
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12 for fi in files:
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13 with open(fi, 'rU') as table:
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14 reader = csv.DictReader(table, delimiter='\t', dialect='excel-tab')
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15 rows = list(reader)
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16 for field in reader.fieldnames:
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17 if field not in set(header):
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18 header.append(field)
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19 #try to find identity columns in the files, to use to join
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20 if possible_identity_headers is None:
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21 possible_identity_headers = set(reader.fieldnames)
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22 #winnow down the shared columns in each file by whether they're present in all, and all their values are unique in each file and not null
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23 #because these are the most likely to be shared keys
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24 possible_identity_headers = possible_identity_headers.intersection(filter(lambda f: len(set([r[f] for r in rows])) == len(rows) and all([r[f] is not None for r in rows]), reader.fieldnames))
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25 items.extend(rows)
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26
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27 # if len(possible_identity_headers) > 1:
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28 # #if there's more than one, we need to check that joining on any one of them produces the same results
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29
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30 # #finally
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31 # possible_identity_headers = set((possible_identity_headers.pop(), ))
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32
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33 #if we found an identity column, then try to join rows
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34 if possible_identity_headers:
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35 key_column = possible_identity_headers.pop()
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36 keys = set([r[key_column] for r in items])
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37 merged_rows = []
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38 for key in sorted(keys):
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39 new_row = {}
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40 for row in filter(lambda r: r[key_column] == key, items):
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41 new_row.update(row)
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42 merged_rows.append(new_row)
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43 items = merged_rows
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44
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45 wr = csv.DictWriter(sys.stdout, delimiter='\t', dialect='excel-tab', fieldnames=header)
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46 wr.writeheader()
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47 wr.writerows(items)
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48
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49
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50 if __name__ == '__main__':
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51 main(sys.argv[1:]) |
