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Adicicao de Garbage Collector (GC) para economia de RAM #40

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Adicicao de Garbage Collector (GC) para economia de RAM #40

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12 changes: 11 additions & 1 deletion dados_cnpj_para_sqlite.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@

import pandas as pd, sqlite3, sqlalchemy
import glob, time, dask.dataframe as dd
import os, sys, zipfile
import os, sys, zipfile, gc

dataReferencia = 'xx/xx/2024' #input('Data de referência da base dd/mm/aaaa: ')
pasta_compactados = r"dados-publicos-zip" #local dos arquivos zipados da Receita
Expand Down Expand Up @@ -59,6 +59,11 @@ def carregaTabelaCodigo(extensaoArquivo, nomeTabela):
dtab = pd.read_csv(arquivo, dtype=str, sep=';', encoding='latin1', header=None, names=['codigo','descricao'])
dtab.to_sql(nomeTabela, engine, if_exists='replace', index=None)
engine.execute(f'CREATE INDEX idx_{nomeTabela} ON {nomeTabela}(codigo);')

#Coleta de lixo (liberar RAM)
del dtab
gc.collect()

if bApagaDescompactadosAposUso:
print('apagando arquivo '+arquivo)
os.remove(arquivo)
Expand Down Expand Up @@ -152,6 +157,11 @@ def carregaTipo(nome_tabela, tipo, colunas):
#dask possibilita usar curinga no nome de arquivo, por ex:
#ddf = dd.read_csv(pasta_saida+r'\*' + tipo, sep=';', header=None, names=colunas ...
ddf.to_sql(nome_tabela, engine_url, index=None, if_exists='append', dtype=sqlalchemy.sql.sqltypes.TEXT)

#Coleta de lixo (liberar RAM)
del ddf
gc.collect()

if bApagaDescompactadosAposUso:
print(f'apagando o arquivo {arq=}')
os.remove(arq)
Expand Down