67 lines
3.3 KiB
Python
Executable File
67 lines
3.3 KiB
Python
Executable File
#!/usr/bin/env python3
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from pathlib import Path
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import re
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import pandas
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# converts a cnrs geslab type t001 report to a single table
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def geslabt002_to_sheet(in_tsv_file_path: Path, out_tsv_file_path: Path):
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with open(in_tsv_file_path) as inf, open(out_tsv_file_path, 'wt') as outf:
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table_header_has_been_written = False
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for line in inf.readlines():
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# Entité dépensière : AESJULLIEN AES RENNES METROPOLE MC JULLIEN Crédits reçus : 40,000.00
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# Disponible : 24,743.14
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#
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#
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# N° commande Souche Libellé commande Date commande Raison sociale fournisseur Montant consommé sur exercice antérieur Montant consommé sur l'exercice Montant réservé Montant facturé Code origine Nature dépense Statut Cde groupée
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is_table_header = re.match(r'^N° com. GESLAB', line) is not None
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# for some strange reason, the column 'N° com. GESLAB''s contents are alternatively something like '1952-12-17 12:00:00 AM' and something like '19,855.00'
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if is_table_header and not table_header_has_been_written:
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outf.write('# %s' % line)
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table_header_has_been_written = True
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if re.match(r'^[0-9,.]+\t', line):
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outf.write(line)
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elif re.match(r'^[0-9][0-9][0-9][0-9]-[0-9]+-[0-9]+ [0-9][0-9]:[0-9][0-9]:[0-9][0-9] [AP]M\t', line):
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outf.write(line)
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else:
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print('ignoring line : %s' % line)
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def geslabt002_to_itorders(geslabt001_file_path: Path, itorders_file_path: Path):
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sheet_file_path = Path('./tmp/commandes-2019-cnrs.tsv')
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geslabt002_to_sheet(geslabt001_file_path, sheet_file_path)
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df = pandas.read_csv(sheet_file_path, sep='\t')
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# delete the colums for which the labve is of the form 'Unnamed: <n>'. They come from the csv export of libre office
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unnamed_columns = [column_label for column_label in df.keys() if re.match(r'^Unnamed', column_label) is not None]
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print(unnamed_columns)
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df = df.drop(columns=unnamed_columns)
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print(df.columns)
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print(df.keys())
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print(df)
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PETIT_MATERIEL_INFORMATIQUE = '1100'
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EQUIPEMENT_INFORMATIQUE = '2100'
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INFORMATIQUE_ACHAT = 'D3--'
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it_df = df[(df['Matière'] == PETIT_MATERIEL_INFORMATIQUE) | (df['Matière'] == EQUIPEMENT_INFORMATIQUE) | (df['Matière'] == INFORMATIQUE_ACHAT)]
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print(it_df)
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# to remove clutter, drop the columns that we don't need
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print(it_df.keys())
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it_df = it_df.drop(columns=['# N° com. GESLAB']) # this column seems to contain anything but ordering number
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it_df = it_df.drop(columns=['N° ligne']) # I don't know the meaning of this column
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it_df = it_df.drop(columns=['Code origine']) # I don't know the meaning of this column
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it_df = it_df.drop(columns=['Elément analytique']) # I don't know the meaning of this column
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it_df = it_df.drop(columns=['S']) # I don't know the meaning of this column
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print(it_df[['Facturé ligne', 'Raison sociale fournisseur', 'Libellé ligne']])
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it_df.to_csv(itorders_file_path, sep='\t')
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def main():
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geslabt002_to_itorders(Path('./achats-ipr/2019/cnrs/from_ngicquiaux_20230127/commandes-2019-cnrs-t002.tsv'), Path('./tmp/commandes-it-2019-cnrs-002.tsv'))
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main()
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