def test_ingest_minute(self):
data_frequency = 'minute'
exchange_name = 'poloniex'
exchange = get_exchange(exchange_name)
exchange_bundle = ExchangeBundle(exchange)
assets = [exchange.get_asset('eth_btc')]
start = pd.to_datetime('2016-03-01', utc=True)
end = pd.to_datetime('2017-11-1', utc=True)
log.info('ingesting exchange bundle {}'.format(exchange_name))
exchange_bundle.ingest(
data_frequency=data_frequency,
include_symbols=','.join([asset.symbol for asset in assets]),
# include_symbols=None,
exclude_symbols=None,
start=start,
end=end,
show_progress=True)
reader = exchange_bundle.get_reader(data_frequency)
for asset in assets:
arrays = reader.load_raw_arrays(sids=[asset.sid],
fields=['close'],
start_dt=start,
end_dt=end)
print('found {} rows for {} ingestion\n{}'.format(
len(arrays[0]), asset.symbol, arrays[0]))
pass
def test_merge_ctables(self):
exchange_name = 'bittrex'
# Switch between daily and minute for testing
# data_frequency = 'daily'
data_frequency = 'daily'
exchange = get_exchange(exchange_name)
assets = [
exchange.get_asset('eth_btc'),
exchange.get_asset('etc_btc'),
exchange.get_asset('wings_eth'),
]
start = pd.to_datetime('2017-9-1', utc=True)
end = pd.to_datetime('2017-9-30', utc=True)
exchange_bundle = ExchangeBundle(exchange)
writer = exchange_bundle.get_writer(start, end, data_frequency)
# In the interest of avoiding abstractions, this is writing a chunk
# to the ctable. It does not include the logic which creates chunks.
for asset in assets:
exchange_bundle.ingest_ctable(
asset=asset,
data_frequency=data_frequency,
# period='2017-9',
period='2017',
# Dont't forget to update if you change your dates
start_dt=start,
end_dt=end,
writer=writer,
empty_rows_behavior='strip'
)
# In daily mode, this returns an error. It appears that writing
# a second asset in the same date range removed the first asset.
# In minute mode, the data is there too. This signals that the minute
# writer / reader is more powerful. This explains why I did not
# encounter these problems as I have been focusing on minute data.
reader = exchange_bundle.get_reader(data_frequency)
for asset in assets:
# Since this pair was loaded last. It should be there in daily mode.
arrays = reader.load_raw_arrays(
sids=[asset.sid],
fields=['close'],
start_dt=start,
end_dt=end
)
print('found {} rows for {} ingestion\n{}'.format(
len(arrays[0]), asset.symbol, arrays[0])
)
pass
def test_ingest_daily(self):
exchange_name = 'bitfinex'
data_frequency = 'minute'
include_symbols = 'neo_btc'
# exchange_name = 'poloniex'
# data_frequency = 'daily'
# include_symbols = 'eth_btc'
# start = pd.to_datetime('2017-1-1', utc=True)
# end = pd.to_datetime('2017-10-16', utc=True)
# periods = get_periods_range(start, end, data_frequency)
start = None
end = None
exchange = get_exchange(exchange_name)
exchange_bundle = ExchangeBundle(exchange)
log.info('ingesting exchange bundle {}'.format(exchange_name))
exchange_bundle.ingest(
data_frequency=data_frequency,
include_symbols=include_symbols,
exclude_symbols=None,
start=start,
end=end,
show_progress=True
)
symbols = include_symbols.split(',')
assets = []
for pair_symbol in symbols:
assets.append(exchange.get_asset(pair_symbol))
reader = exchange_bundle.get_reader(data_frequency)
start_dt = reader.first_trading_day
end_dt = reader.last_available_dt
if data_frequency == 'daily':
end_dt = end_dt - pd.Timedelta(hours=23, minutes=59)
for asset in assets:
arrays = reader.load_raw_arrays(
sids=[asset.sid],
fields=['close'],
start_dt=start_dt,
end_dt=end_dt
)
print('found {} rows for {} ingestion\n{}'.format(
len(arrays[0]), asset.symbol, arrays[0])
)
pass
def _bundle_to_csv(self,
asset,
exchange_name,
data_frequency,
filename,
path=None,
start_dt=None,
end_dt=None):
bundle = ExchangeBundle(exchange_name)
reader = bundle.get_reader(data_frequency, path=path)
if start_dt is None:
start_dt = reader.first_trading_day
if end_dt is None:
end_dt = reader.last_available_dt
if data_frequency == 'daily':
end_dt = end_dt - pd.Timedelta(hours=23, minutes=59)
arrays = None
try:
arrays = reader.load_raw_arrays(
sids=[asset.sid],
fields=['open', 'high', 'low', 'close', 'volume'],
start_dt=start_dt,
end_dt=end_dt)
except Exception as e:
log.warn('skipping ctable for {} from {} to {}: {}'.format(
asset.symbol, start_dt, end_dt, e))
periods = bundle.get_calendar_periods_range(start_dt, end_dt,
data_frequency)
df = get_df_from_arrays(arrays, periods)
folder = os.path.join(tempfile.gettempdir(), 'catalyst', exchange_name,
asset.symbol)
ensure_directory(folder)
path = os.path.join(folder, filename + '.csv')
log.info('creating csv file: {}'.format(path))
print('HEAD\n{}'.format(df.head(100)))
print('TAIL\n{}'.format(df.tail(100)))
df.to_csv(path)
pass
def test_ingest_daily(self):
# exchange_name = 'bitfinex'
# data_frequency = 'daily'
# include_symbols = 'neo_btc,bch_btc,eth_btc'
exchange_name = 'bittrex'
data_frequency = 'daily'
include_symbols = 'wings_eth'
start = pd.to_datetime('2017-1-1', utc=True)
end = pd.to_datetime('2017-10-16', utc=True)
periods = get_periods_range(start, end, data_frequency)
exchange = get_exchange(exchange_name)
exchange_bundle = ExchangeBundle(exchange)
log.info('ingesting exchange bundle {}'.format(exchange_name))
exchange_bundle.ingest(
data_frequency=data_frequency,
include_symbols=include_symbols,
exclude_symbols=None,
start=start,
end=end,
show_progress=True
)
symbols = include_symbols.split(',')
assets = []
for pair_symbol in symbols:
assets.append(exchange.get_asset(pair_symbol))
reader = exchange_bundle.get_reader(data_frequency)
for asset in assets:
arrays = reader.load_raw_arrays(
sids=[asset.sid],
fields=['close'],
start_dt=start,
end_dt=end
)
print('found {} rows for {} ingestion\n{}'.format(
len(arrays[0]), asset.symbol, arrays[0])
)
pass
