ddrs/src/geslabt002_to_itorders.py

#!/usr/bin/env python3
from pathlib import Path
import re
import pandas


# converts a cnrs geslab type t001 report to a single table
def geslabt002_to_sheet(in_tsv_file_path: Path, out_tsv_file_path: Path):
    with open(in_tsv_file_path) as inf, open(out_tsv_file_path, 'wt') as outf:
        table_header_has_been_written = False
        for line in inf.readlines():
            # Entité dépensière : 				AESJULLIEN		AES RENNES METROPOLE MC JULLIEN									Crédits reçus : 								40,000.00
            # 															Disponible : 								24,743.14
            #
            #
            # 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
            is_table_header = re.match(r'^N° com. GESLAB', line) is not None
            # 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'
            if is_table_header and not table_header_has_been_written:
                outf.write('# %s' % line)
                table_header_has_been_written = True
            if re.match(r'^[0-9,.]+\t', line):
                outf.write(line)
            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):
                outf.write(line)
            else:
                print('ignoring line : %s' % line)


def geslabt002_to_itorders(geslabt001_file_path: Path, itorders_file_path: Path):
    sheet_file_path = Path('./tmp/commandes-2019-cnrs.tsv')
    geslabt002_to_sheet(geslabt001_file_path, sheet_file_path)

    df = pandas.read_csv(sheet_file_path, sep='\t')

    # delete the colums for which the labve is of the form 'Unnamed: <n>'. They come from the csv export of libre office
    unnamed_columns = [column_label for column_label in df.keys() if re.match(r'^Unnamed', column_label) is not None]
    print(unnamed_columns)
    df = df.drop(columns=unnamed_columns)

    print(df.columns)
    print(df.keys())
    print(df)
    PETIT_MATERIEL_INFORMATIQUE = '1100'
    EQUIPEMENT_INFORMATIQUE = '2100'
    INFORMATIQUE_ACHAT = 'D3--'
    it_df = df[(df['Matière'] == PETIT_MATERIEL_INFORMATIQUE) | (df['Matière'] == EQUIPEMENT_INFORMATIQUE) | (df['Matière'] == INFORMATIQUE_ACHAT)]
    print(it_df)

    # to remove clutter, drop the columns that we don't need
    print(it_df.keys())
    it_df = it_df.drop(columns=['# N° com. GESLAB'])  # this column seems to contain anything but ordering number
    it_df = it_df.drop(columns=['N° ligne'])  # I don't know the meaning of this column
    it_df = it_df.drop(columns=['Code origine'])  # I don't know the meaning of this column
    it_df = it_df.drop(columns=['Elément analytique'])  # I don't know the meaning of this column
    it_df = it_df.drop(columns=['S'])  # I don't know the meaning of this column

    print(it_df[['Facturé ligne', 'Raison sociale fournisseur', 'Libellé ligne']])
    it_df.to_csv(itorders_file_path, sep='\t')


def main():
    geslabt002_to_itorders(Path('./achats-ipr/2019/cnrs/from_ngicquiaux_20230127/commandes-2019-cnrs-t002.tsv'), Path('./tmp/commandes-it-2019-cnrs-002.tsv'))


main()