reader = csv.reader(arquivo_csv, delimiter=',')
year = 2013
month = 1
collection = 'historical_data_daily'
for colunm in reader:
if year < 2021:
for week in calendar.monthcalendar(year, month):
for day in week:
if day != 0:
date = utils.format_number(
day, 2) + '.' + utils.format_number(
month, 2) + '.' + str(year)
date = utils.string_to_date(date)
if server.db_select(collection, ['date'],
[date]) == None:
server.db_insert(
collection, ['date', 'br_production'],
[date, utils.string_to_float(colunm[1])])
else:
server.db_update(collection, {"date": date}, {
'br_production':
utils.string_to_float(colunm[1])
})
if server.db_select(collection, ['date'],
[date]) == None:
server.db_insert(
collection, ['date', 'br_plateau_area'],
[date, utils.string_to_float(colunm[2])])
else:
if idx > 1:
collection = 'historical_data_weekly'
keys = [
'date', 'dolar', 'open_dolar', 'max_dolar', 'min_dolar',
'var_dolar'
]
values = [
utils.string_to_date(colunm[0]),
utils.string_to_float(colunm[1]),
utils.string_to_float(colunm[2]),
utils.string_to_float(colunm[3]),
utils.string_to_float(colunm[4]),
utils.string_to_float(colunm[5])
]
colunm[0] = utils.string_to_date(colunm[0]) - timedelta(days=1)
if server.db_select(collection, [keys[0]], [values[0]]) == None:
server.db_insert(collection, keys, values)
else:
for i, *_ in enumerate(colunm):
if i >= 1:
server.db_update(collection, {keys[0]: values[0]},
{keys[i]: values[i]})
with open('../files/dolar_brl_historio.csv', 'r') as arquivo_csv:
reader = csv.reader(arquivo_csv, delimiter=',')
for idx, colunm in enumerate(reader):
if idx > 1:
collection = 'historical_data_daily'
keys = [
'date', 'dolar', 'open_dolar', 'max_dolar', 'min_dolar',
'var_dolar'
"$lt": dt.datetime(2019, 1, 1)
}
}, {
"corn_br": {
"$ne": 0
}
}]
}
writer.writerow([
"date", "corn_usd", "br_production", "br_plateau_area", "br_productivity",
"dolar", "corn_br_-1", "corn_br"
])
corn_one_day_before = 0
for item in server.db_select('historical_data_daily', _query=query):
date = item.get('date')
corn_br = item.get('corn_br')
corn_usd = item.get('corn_usd')
br_production = item.get('br_production')
br_plateau_area = item.get('br_plateau_area')
br_productivity = item.get('br_productivity')
dolar = item.get('dolar')
if corn_br and corn_usd and br_production and br_plateau_area and br_productivity and dolar:
date_corn_one_day_before = date - timedelta(days=1)
for i in server.db_select('historical_data_daily',
_query={"date": date_corn_one_day_before}):
if i.get('corn_br'):
writer = csv.writer(open("../files/dataset_2.csv", 'w'))
writer.writerow(['date', 'corn_br', 'corn_usd', 'dolar', 'corn_br-1', 'corn_br-2', 'corn_br-3', 'max_corn_br-1', 'min_corn_br-1', 'open_corn_br-1', 'var_corn_br-1', 'vol_corn_br-1'])
year = 2011
month = 1
corn_br_days_before = [{}, {}, {}]
print(corn_br_days_before )
while year <= 2019 and month <= 12:
for *week, _, _ in calendar.monthcalendar(year, month):
for day in week:
if day != 0:
results = server.db_select('historical_data_daily', ['date'], [dt.datetime(year, month, day)])
if results.get('corn_br'):
copy_results = results.copy()
corn_br_days_before.append(copy_results)
corn_3_before = corn_br_days_before.pop(0)
corn_2_before = corn_br_days_before[-3]
corn_1_before = corn_br_days_before[-2]
max_corn_br_1_before = get_last_not_null_value('max_corn_br', corn_1_before, corn_2_before, corn_3_before)
min_corn_br_1_before = get_last_not_null_value('min_corn_br', corn_1_before, corn_2_before, corn_3_before)
open_corn_br_1_before = get_last_not_null_value('open_corn_br', corn_1_before, corn_2_before, corn_3_before)
var_corn_br_1_before = get_last_not_null_value('var_corn_br', corn_1_before, corn_2_before, corn_3_before)
print('\n\nImportando dados Semanais do Preço do Milho\n\n')
with open('../files/milho_br_semanal.csv', 'r') as arquivo_csv:
reader = csv.reader(arquivo_csv, delimiter = ',')
for idx, colunm in enumerate(reader):
if idx > 1:
date = colunm[0].replace(',','')
date = date.split(' ')
date = utils.format_number(date[1], 2) + '.' + utils.format_number(str(utils.mounth_numeric.get(date[0])), 2) + '.' + date[2]
collection = 'historical_data_weekly'
keys = ['date', 'corn_br', 'open_corn_br', 'max_corn_br', 'min_corn_br', 'vol_corn_br', 'var_corn_br']
values = [utils.string_to_date(date), utils.string_to_float(colunm[1]), utils.string_to_float(colunm[2]), utils.string_to_float(colunm[3]), utils.string_to_float(colunm[4]), utils.string_to_float(colunm[5]), utils.string_to_float(colunm[6])]
if server.db_select(collection, [keys[0]], [utils.string_to_date(date)]) == None:
server.db_insert(collection, keys, values)
else:
for i, *_ in enumerate(colunm):
if i >= 1:
server.db_update(collection, {keys[0]: values[0]}, {keys[i]: values[i]})
print('\n\nImportando dados Diarios do Preço do Milho\n\n')
with open('../files/milho_br.csv', 'r') as arquivo_csv:
reader = csv.reader(arquivo_csv, delimiter = ',')
for idx, colunm in enumerate(reader):
if idx > 1:
collection = 'historical_data_daily'
keys = ['date', 'corn_br', 'open_corn_br', 'max_corn_br', 'min_corn_br', 'vol_corn_br', 'var_corn_br']
values = [colunm[0], utils.string_to_float(colunm[1]), utils.string_to_float(colunm[2]), utils.string_to_float(colunm[3]), utils.string_to_float(colunm[4]), utils.string_to_float(colunm[5]), utils.string_to_float(colunm[6])]
