<commit_before>from csvdb import CsvMetadata, CsvDatabase
from energyPATHWAYS.generated.text_mappings import MappedCols

_Metadata = [
    CsvMetadata('BlendNodeBlendMeasures',
                key_col='name',
                df_cols=['gau', 'demand_sector', 'value', 'year']),
    CsvMetadata('CO2PriceMeasures',
                key_col='name',
                lowcase_cols=['sensitivity'],
                df_cols=['gau', 'sensitivity', 'value', 'year']),
    CsvMetadata('CurrenciesConversion',
                data_table=True),
    CsvMetadata('DemandCO2CaptureMeasures',
                data_table=True),
    CsvMetadata('DemandDrivers',
                key_col='name',
                lowcase_cols=['sensitivity'],
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year', 'sensitivity']),
    CsvMetadata('DemandEnergyDemands',
                key_col='subsector',
                lowcase_cols=['sensitivity'],
                df_cols=['gau', 'demand_technology', 'value', 'oth_2', 'oth_1', 'year', 'final_energy', 'sensitivity']),
    CsvMetadata('DemandEnergyEfficiencyMeasures',
                key_col='name',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year', 'final_energy']),
    CsvMetadata('DemandEnergyEfficiencyMeasuresCost',
                key_col='parent',
                df_cols=['vintage', 'gau', 'value', 'oth_2', 'oth_1', 'final_energy']),
    CsvMetadata('DemandFlexibleLoadMeasures',
                key_col='subsector',
                df_cols=['gau', 'demand_technology', 'value', 'oth_1', 'year']),
    CsvMetadata('DemandFuelSwitchingMeasures',
                data_table=True),
    CsvMetadata('DemandFuelSwitchingMeasuresCost',
                key_col='parent',
                df_cols=['vintage', 'gau', 'value', 'oth_2', 'oth_1']),
    CsvMetadata('DemandFuelSwitchingMeasuresEnergyIntensity',
                key_col='parent',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year']),
    CsvMetadata('DemandFuelSwitchingMeasuresImpact',
                key_col='parent',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year']),
    CsvMetadata('DemandSales',
                key_col='demand_technology',
                df_cols=['vintage', 'gau', 'value', 'oth_2', 'oth_1']),
    CsvMetadata('DemandSalesShareMeasures',
                key_col='name',
                df_cols=['vintage', 'gau', 'oth_1', 'value']),
    CsvMetadata('DemandSectors',
                key_col='name'),
    CsvMetadata('DemandServiceDemandMeasures',
                key_col='name',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year']),
    CsvMetadata('DemandServiceDemandMeasuresCost',
                key_col='parent',
                df_cols=['vintage', 'gau', 'value', 'oth_2', 'oth_1']),
    CsvMetadata('DemandServiceDemands',
                key_col='subsector',
                lowcase_cols=['sensitivity'],
                df_cols=['gau', 'demand_technology', 'value', 'oth_2', 'oth_1', 'year', 'final_energy', 'sensitivity']),
    CsvMetadata('DemandServiceEfficiency',
                key_col='subsector',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year', 'final_energy']),
    CsvMetadata('DemandServiceLink',
                data_table=True),
    CsvMetadata('DemandStock',
                key_col='subsector',
                df_cols=['gau', 'demand_technology', 'value', 'oth_2', 'oth_1', 'year']),<commit_msg>changes to db tables<commit_after>from csvdb import CsvMetadata, CsvDatabase
from energyPATHWAYS.generated.text_mappings import MappedCols

_Metadata = [
    CsvMetadata('BlendNodeBlendMeasures',
                key_col='name',
                df_cols=['gau', 'demand_sector', 'value', 'year']),
    CsvMetadata('CO2PriceMeasures',
                key_col='name',
                lowcase_cols=['sensitivity'],
                df_cols=['gau', 'sensitivity', 'value', 'year']),
    CsvMetadata('CurrenciesConversion',
                data_table=True),
    CsvMetadata('DemandCO2CaptureMeasures',
                data_table=True),
    CsvMetadata('DemandDrivers',
                key_col='name',
                lowcase_cols=['sensitivity'],
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year', 'sensitivity']),
    CsvMetadata('DemandEnergyDemands',
                key_col='subsector',
                lowcase_cols=['sensitivity'],
                df_cols=['gau', 'demand_technology', 'value', 'oth_2', 'oth_1', 'year', 'final_energy', 'sensitivity']),
    CsvMetadata('DemandEnergyEfficiencyMeasures',
                key_col='name',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year', 'final_energy']),
    CsvMetadata('DemandEnergyEfficiencyMeasuresCost',
                key_col='parent',
                df_cols=['vintage', 'gau', 'value', 'oth_2', 'oth_1', 'final_energy']),
    CsvMetadata('DemandFlexibleLoadMeasures',
                key_col='subsector',
                df_cols=['gau', 'demand_technology', 'value', 'oth_1', 'year']),
    CsvMetadata('DemandFuelSwitchingMeasures',
                data_table=True),
    CsvMetadata('DemandFuelSwitchingMeasuresCost',
                key_col='parent',
                df_cols=['vintage', 'gau', 'value', 'oth_2', 'oth_1']),
    CsvMetadata('DemandFuelSwitchingMeasuresEnergyIntensity',
                key_col='parent',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year']),
    CsvMetadata('DemandFuelSwitchingMeasuresImpact',
                key_col='parent',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year']),
    CsvMetadata('DemandSales',
                key_col='demand_technology',
                df_cols=['vintage', 'gau', 'value', 'oth_2', 'oth_1']),
    CsvMetadata('DemandSalesShareMeasures',
                key_col='name',
                df_cols=['vintage', 'gau', 'oth_1', 'value']),
    CsvMetadata('DemandSectors',
                key_col='name'),
    CsvMetadata('DemandServiceDemandMeasures',
                key_col='name',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year']),
    CsvMetadata('DemandServiceDemandMeasuresCost',
                key_col='parent',
                df_cols=['vintage', 'gau', 'value', 'oth_2', 'oth_1']),
    CsvMetadata('DemandServiceDemands',
                key_col='subsector',
                lowcase_cols=['sensitivity'],
                df_cols=['gau', 'demand_technology', 'value', 'oth_2', 'oth_1', 'year', 'final_energy', 'sensitivity']),
    CsvMetadata('DemandServiceEfficiency',
                key_col='subsector',
                df_cols=['gau', 'value', 'oth_2', 'oth_1', 'year', 'final_energy']),
    CsvMetadata('DemandServiceLink',
                key_col='name'),
    CsvMetadata('DemandStock',
                key_col='subsector',
                df_cols=['gau', 'demand_technology', 'value', 'oth_2', 'oth_1', 'year']),
{'fraction_non_alphanumeric': 0.16155419222903886, 'fraction_numerical': 0.008764241893076249, 'mean_word_length': 2.6693461950696675, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2479943', 'n_tokens_mistral': 2292, 'n_tokens_neox': 2125, 'n_words': 304}