def testUniqueIndex(self):
with recorder.open_store(mode='a') as store:
for key in store.keys():
df = store[key]
self.assertEqual(len(df.index.unique()),
len(df.index),
msg=key)
def testAppend(self):
path = 'data/test.hdf'
# First open and close
fst_df = pd.DataFrame(data={'a': [0, 1], 'b': [2, 3]})
with recorder.open_store(path) as hdf_store:
hdf_store['fst'] = fst_df
# Engine connect to MySQL
sa_url = 'sqlalchemy.url'
mysql_url, dbname = db_conf[sa_url].rsplit(sep='/', maxsplit=1)
mysql_engine = sa.engine_from_config({sa_url: mysql_url})
create_fmt = 'CREATE DATABASE IF NOT EXISTS {dbname}'
mysql_engine.execute(create_fmt.format(dbname=dbname))
# Engine connecting to MySQL database
engine = sa.engine_from_config(db_conf)
metadata = sa.MetaData()
mkt_conf = config.read_markets()
create_all(metadata, mkt_conf)
metadata.create_all(engine)
insert_config_data(engine)
# Query market table. Does metadata drop and create the table?
db_mkt_df = pd.read_sql_table(config.MARKETS, engine, index_col=config.ID)
db_bundle_df = pd.read_sql_table(config.BUNDLES, engine, index_col=config.ID)
db_asset_df = pd.read_sql_table(config.ASSETS, engine, index_col=config.ID)
# TODO: Populate data
markets = [contract.Market(mkt_nm) for mkt_nm in mkt_conf.keys()]
with recorder.open_store('data/hist_iem.hdf') as hdf_store:
for market in markets:
mkt_hist_key = recorder.history_key(market)
mkt_hist_df = hdf_store[mkt_hist_key]
def plot_cumsum(bundle_history_srs):
cumsum_df = cumsum_frame(bundle_history_srs)
# First trade index
fst_trade_idx = (cumsum_df.sum(axis=1) > 0).idxmax()
nonzero_cum_units_df = cumsum_df.loc[fst_trade_idx:]
plt.figure(get_new_fignum())
plt.plot(nonzero_cum_units_df)
plt.show()
if __name__ == '__main__':
mkt_name = 'FedPolicyB'
mkt = contract.Market(mkt_name)
with recorder.open_store(mode='r') as hdf_store:
px_hist_df = hdf_store[recorder.history_key(market=mkt)]
mkts_json = config.read_markets()
mkt_conf = mkts_json[mkt_name]
# Clean dataframe
df = px_hist_df.copy().reset_index()
# Expiry
df[EXPIRY] = df[iem.CONTRACT].apply(expiry)
# Expiry date
expiry_date_json = mkt_conf[config.BUNDLE]
kwargs = {'expiry_date_json': expiry_date_json}
df[config.EXPIRY_DATE] = df[EXPIRY].apply(expiry_date_series, **kwargs)
# Days to expiration
df[DAYS_TO_EXPIRY_DATE] = df[config.EXPIRY_DATE] - df[iem.DATE]