from trading_ig.utils import remove
from trading_ig.config import config
"""
Environment variables must be set using
export IG_SERVICE_USERNAME=""
export IG_SERVICE_PASSWORD=""
export IG_SERVICE_API_KEY=""
export IG_SERVICE_ACC_TYPE="DEMO" # LIVE / DEMO
export IG_SERVICE_ACC_NUMBER=""
"""
CACHE_NAME = "cache"
remove(CACHE_NAME)
@pytest.mark.skip(reason="old nose test, ignoring")
def test_ig_service():
delay_for_ig = 30
def wait(delay):
print(
"Wait %s s to avoid 'error.public-api.exceeded-account-allowance'"
% delay)
time.sleep(delay)
session_cached = requests_cache.CachedSession(
cache_name=CACHE_NAME,
def test_ig_service():
delay_for_ig = 5
def wait(delay):
print(
"Wait %s s to avoid 'error.public-api.exceeded-account-allowance'"
% delay)
time.sleep(delay)
# session_cached = requests_cache.CachedSession(
# cache_name=CACHE_NAME, backend="sqlite", expire_after=timedelta(hours=1)
# )
session_not_cached = requests.Session()
# for i, session in enumerate([session_cached, session_cached, session_not_cached]):
for i, session in enumerate([session_not_cached]):
# pp = pprint.PrettyPrinter(indent=4)
assert isinstance(trading_ig.__version__, six.string_types)
ig_service = IGService(config.username, config.password,
config.api_key, config.acc_type, session)
ig_service.create_session()
print("%d - fetch_accounts" % i)
response = ig_service.fetch_accounts()
print(response)
# assert(response['balance'][0]['available']>0)
assert response["balance"][0] > 0
print("")
print("fetch_account_activity_by_period")
response = ig_service.fetch_account_activity_by_period(10000)
print(response)
assert isinstance(response, pd.DataFrame)
print("")
print("fetch_transaction_history_by_type_and_period")
response = ig_service.fetch_transaction_history_by_type_and_period(
10000, "ALL")
print(response)
assert isinstance(response, pd.DataFrame)
wait(delay_for_ig)
print("")
print("fetch_open_positions")
response = ig_service.fetch_open_positions()
print(response)
assert isinstance(response, pd.DataFrame)
print("")
print("fetch_working_orders")
response = ig_service.fetch_working_orders()
print(response)
assert isinstance(response, pd.DataFrame)
print("")
print("fetch_top_level_navigation_nodes")
response = ig_service.fetch_top_level_navigation_nodes()
print(response) # dict with nodes and markets
assert isinstance(response, dict)
market_id = response["nodes"]["id"].iloc[0]
print("")
print("fetch_client_sentiment_by_instrument")
response = ig_service.fetch_client_sentiment_by_instrument(market_id)
print(response)
assert isinstance(response, dict)
print("")
# print("fetch_related_client_sentiment_by_instrument")
# response = ig_service.fetch_related_client_sentiment_by_instrument(market_id)
# print(response)
# assert isinstance(response, pd.DataFrame)
print("")
print("fetch_sub_nodes_by_node")
node = market_id
response = ig_service.fetch_sub_nodes_by_node(node)
print(response)
assert isinstance(response["markets"], pd.DataFrame)
assert isinstance(response["nodes"], pd.DataFrame)
print("")
wait(delay_for_ig)
print("fetch_all_watchlists")
response = ig_service.fetch_all_watchlists()
print(response)
assert isinstance(response, pd.DataFrame)
watchlist_id = response["id"].iloc[0] # u'Popular Markets'
print("")
print("fetch_watchlist_markets")
response = ig_service.fetch_watchlist_markets(watchlist_id)
print(response)
assert isinstance(response, pd.DataFrame)
# epic = 'CS.D.EURUSD.MINI.IP'
# epic = u'IX.D.CAC.IDF.IP'
epic = response["epic"].iloc[0]
print("")
print("fetch_market_by_epic")
response = ig_service.fetch_market_by_epic(epic)
print(response)
# pp.pprint(response)
assert isinstance(response, dict)
print("")
print("search_markets")
search_term = "EURUSD"
# search_term = 'SPY'
response = ig_service.search_markets(search_term)
print(response)
assert isinstance(response, pd.DataFrame)
print("")
wait(delay_for_ig)
print("fetch_historical_prices_by_epic_and_num_points")
# epic = 'CS.D.EURUSD.MINI.IP'
# epic = 'IX.D.ASX.IFM.IP' # US 500 (SPY)
# epic = 'IX.D.ASX.IFM.IP' # US (SPY) - mini
# MINUTE, MINUTE_2, MINUTE_3, MINUTE_5, MINUTE_10, MINUTE_15,
# MINUTE_30, HOUR, HOUR_2, HOUR_3, HOUR_4, DAY, WEEK, MONTH
# resolution = 'HOUR'
# http://pandas.pydata.org/pandas-docs/stable/timeseries.html#dateoffset-objects
resolution = "H"
num_points = 10
response = ig_service.fetch_historical_prices_by_epic_and_num_points(
epic, resolution, num_points)
print(response)
# print(response['prices']['price'])
# print(response['prices']['price']['ask'])
# print(response['prices']['volume'])
assert isinstance(response["allowance"], dict)
# assert(isinstance(response['prices']['volume'], pd.Series))
# assert(isinstance(response['prices']['price'], pd.Panel))
assert isinstance(response["prices"], pd.DataFrame)
print("")
wait(delay_for_ig)
print("fetch_historical_prices_by_epic_and_date_range")
end_date = datetime.utcnow().replace(hour=0,
minute=0,
second=0,
microsecond=0)
start_date = end_date - timedelta(days=3)
response = ig_service.fetch_historical_prices_by_epic_and_date_range(
epic, resolution, start_date, end_date)
print(response)
assert isinstance(response["allowance"], dict)
# assert(isinstance(response['prices']['volume'], pd.Series))
# assert(isinstance(response['prices']['price'], pd.Panel))
assert isinstance(response["prices"], pd.DataFrame)
print("")
wait(delay_for_ig)
remove(CACHE_NAME)