def import_commodities(successfulPulls):
# imports commodities from around the world in USD
search_results = investpy.search_commodities(by='currency', value='USD')
list_of_commodity_names = search_results["name"]
firstIndex = datetime.datetime.strptime(_configKeys.STARTPULL, '%d/%m/%Y')
lastIndex = datetime.datetime.strptime(_configKeys.ENDPULL, '%d/%m/%Y')
for name in list_of_commodity_names[:2500]:
try:
# Have an if statement in place in case if we don't want to pull every etf because there are a lot of stocks
# Program takes a long time to run if we have to webscrape every etf each time we run
commodityData = []
commodityData = investpy.get_commodity_historical_data(
commodity=name,
country='united states',
from_date=_configKeys.STARTPULL,
to_date=_configKeys.ENDPULL)
newIndex = []
for index in commodityData.index:
newIndex.append(
datetime.datetime.strptime(
datetime.datetime.strftime((index + timedelta(days=1)),
'%Y-%m-%d'), '%Y-%m-%d'))
commodityData['Date'] = newIndex
commodityData.set_index('Date', inplace=True)
# If there's something that's been loaded into stockData, then the length is no longer 0
# if the differences is under 2~3 days, then it is ok to take this data since there is still enough data in the week to be usable
# this timedelta fixes the problem of trying to pull during a long weekend
name = str(name) + "Commodity"
if commodityData.empty == False and commodityData.index[
0] - firstIndex <= timedelta(
days=2
) and lastIndex - commodityData.index[-1] <= timedelta(
days=3):
successfulPulls["Symbol"].append(name)
successfulPulls["Type"].append("Commodity")
commodityData.to_csv(
os.path.join(Path(_configKeys.DATA_FOLDER), name + '.csv'))
except:
print("Something went wrong when importing: " + name)
def test_investpy_commodities():
"""
This function checks that commodity data retrieval functions listed in investpy work properly.
"""
params = [
{
'group': 'metals',
},
{
'group': None,
},
]
for param in params:
investpy.get_commodities(group=param['group'])
investpy.get_commodities_list(group=param['group'])
params = [
{
'group': None,
'columns': ['title', 'full_name', 'name'],
'as_json': True
},
{
'group': None,
'columns': ['title', 'full_name', 'name'],
'as_json': False
},
{
'group': 'metals',
'columns': ['title', 'full_name', 'name'],
'as_json': True
},
{
'group': 'metals',
'columns': ['title', 'full_name', 'name'],
'as_json': False
},
{
'group': 'metals',
'columns': None,
'as_json': False
},
]
for param in params:
investpy.get_commodities_dict(group=param['group'],
columns=param['columns'],
as_json=param['as_json'])
investpy.get_commodity_groups()
params = [
{
'country': None,
'as_json': True,
'order': 'ascending',
},
{
'country': 'united states',
'as_json': False,
'order': 'ascending',
},
{
'country': 'united states',
'as_json': True,
'order': 'descending',
},
{
'country': 'united states',
'as_json': False,
'order': 'descending',
},
]
for param in params:
investpy.get_commodity_recent_data(commodity='copper',
country=param['country'],
as_json=param['as_json'],
order=param['order'],
interval='Daily')
investpy.get_commodity_historical_data(commodity='copper',
from_date='01/01/1990',
to_date='01/01/2019',
country=param['country'],
as_json=param['as_json'],
order=param['order'],
interval='Daily')
params = [
{
'commodity': 'copper',
'country': None,
'as_json': False
},
{
'commodity': 'copper',
'country': 'united states',
'as_json': True
}
]
for param in params:
investpy.get_commodity_information(commodity=param['commodity'], country=param['country'], as_json=param['as_json'])
params = [
{
'group': 'metals',
'as_json': True,
'n_results': 100
},
{
'group': 'metals',
'as_json': False,
'n_results': 100
}
]
for param in params:
investpy.get_commodities_overview(group=param['group'], as_json=param['as_json'], n_results=param['n_results'])
investpy.search_commodities(by='name', value='gold')
