ENH: Adds futures trading and asset management logic to TradingAlgorithm and performance classes

zipline/utils/cli.py

@@ -31,14 +31,15 @@ except:
     PYGMENTS = False
 
 import zipline
+from zipline.errors import NoSourceError, PipelineDateError
 
 DEFAULTS = {
-    'start': '2012-01-01',
-    'end': '2012-12-31',
     'data_frequency': 'daily',
     'capital_base': '10e6',
     'source': 'yahoo',
-    'symbols': 'AAPL'
+    'symbols': 'AAPL',
+    'metadata_index': 'symbol',
+    'source_time_column': 'Date',
 }
 
 
@@ -99,9 +100,12 @@ def parse_args(argv, ipython_mode=False):
     parser.add_argument('--start', '-s')
     parser.add_argument('--end', '-e')
     parser.add_argument('--capital_base')
-    parser.add_argument('--source', choices=('yahoo',))
+    parser.add_argument('--source', '-d')
+    parser.add_argument('--source_time_column', '-t')
     parser.add_argument('--symbols')
     parser.add_argument('--output', '-o')
+    parser.add_argument('--metadata_path', '-m')
+    parser.add_argument('--metadata_index', '-x')
     if ipython_mode:
         parser.add_argument('--local_namespace', action='store_true')
 
@@ -153,14 +157,59 @@ def run_pipeline(print_algo=True, **kwargs):
            pygments syntax coloring if pygments is found.
 
     """
-    start = pd.Timestamp(kwargs['start'], tz='UTC')
-    end = pd.Timestamp(kwargs['end'], tz='UTC')
+    start = kwargs['start']
+    end = kwargs['end']
+    # Compare against None because strings/timestamps may have been given
+    if start is not None:
+        start = pd.Timestamp(start, tz='UTC')
+    if end is not None:
+        end = pd.Timestamp(end, tz='UTC')
+
+    # Fail out if only one bound is provided
+    if ((start is None) or (end is None)) and (start != end):
+        raise PipelineDateError(start=start, end=end)
+
+    # Check if start and end are provided, and if the sim_params need to read
+    # a start and end from the DataSource
+    if start is None:
+        overwrite_sim_params = True
+    else:
+        overwrite_sim_params = False
 
     symbols = kwargs['symbols'].split(',')
+    asset_identifier = kwargs['metadata_index']
 
-    if kwargs['source'] == 'yahoo':
+    # Pull asset metadata
+    asset_metadata = kwargs.get('asset_metadata', None)
+    asset_metadata_path = kwargs['metadata_path']
+    # Read in a CSV file, if applicable
+    if asset_metadata_path is not None:
+        if os.path.isfile(asset_metadata_path):
+            asset_metadata = pd.read_csv(asset_metadata_path,
+                                         index_col=asset_identifier)
+
+    source_arg = kwargs['source']
+    source_time_column = kwargs['source_time_column']
+
+    if source_arg is None:
+        raise NoSourceError()
+
+    elif source_arg == 'yahoo':
         source = zipline.data.load_bars_from_yahoo(
             stocks=symbols, start=start, end=end)
+
+    elif os.path.isfile(source_arg):
+        source = zipline.data.load_prices_from_csv(
+            filepath=source_arg,
+            identifier_col=source_time_column
+        )
+
+    elif os.path.isdir(source_arg):
+        source = zipline.data.load_prices_from_csv_folder(
+            folderpath=source_arg,
+            identifier_col=source_time_column
+        )
+
     else:
         raise NotImplementedError(
             'Source %s not implemented.' % kwargs['source'])
@@ -188,9 +237,13 @@ def run_pipeline(print_algo=True, **kwargs):
     algo = zipline.TradingAlgorithm(script=algo_text,
                                     namespace=kwargs.get('namespace', {}),
                                     capital_base=float(kwargs['capital_base']),
-                                    algo_filename=kwargs.get('algofile'))
+                                    algo_filename=kwargs.get('algofile'),
+                                    asset_metadata=asset_metadata,
+                                    identifiers=symbols,
+                                    start=start,
+                                    end=end)
 
-    perf = algo.run(source)
+    perf = algo.run(source, overwrite_sim_params=overwrite_sim_params)
 
     output_fname = kwargs.get('output', None)
     if output_fname is not None: