ENH: Add IPython cell magic.

When zipline is imported it checks whether
it runs in the IPython notebook. If it does,
it registers a %%zipline magic that takes the
same arguments as the CLI with the addition of
a -o for specifying the output variable to store
the performance frame in.

The algo code in the cell is, as of yet, executed
in its own environment rather than that of the
IPython NB which is probably what we want.

Also adds cli option to save the perf dataframe
to a pickle file.

Also adds an IPython notebook buyapple example.
This commit is contained in:
twiecki
2014-05-07 15:34:41 -04:00
parent 5b45c46502
commit f5086e4b0e
9 changed files with 1694 additions and 27 deletions
+53 -18
View File
@@ -16,17 +16,16 @@
import sys
import os
import argparse
import ConfigParser
from copy import copy
import datetime
from six import print_
from six.moves import configparser
import pandas as pd
try:
from pygments import highlight
from pygments.lexers import PythonLexer
from pygments.formatters import TerminalFormatter
from pygments.styles import STYLE_MAP
PYGMENTS = True
except:
PYGMENTS = False
@@ -42,7 +41,8 @@ DEFAULTS = {
'symbols': 'AAPL'
}
def parse_args(argv):
def parse_args(argv, ipython_mode=False):
# Parse any conf_file specification
# We make this parser with add_help=False so that
# it doesn't parse -h and print help.
@@ -51,7 +51,7 @@ def parse_args(argv):
formatter_class=argparse.RawDescriptionHelpFormatter,
# Turn off help, so we print all options in response to -h
add_help=False
)
)
conf_parser.add_argument("-c", "--conf_file",
help="Specify config file",
metavar="FILE")
@@ -60,7 +60,7 @@ def parse_args(argv):
defaults = copy(DEFAULTS)
if args.conf_file:
config = ConfigParser.SafeConfigParser()
config = configparser.SafeConfigParser()
config.read([args.conf_file])
defaults.update(dict(config.items("Defaults")))
@@ -82,10 +82,34 @@ def parse_args(argv):
parser.add_argument('--capital_base')
parser.add_argument('--source', choices=('yahoo',))
parser.add_argument('--symbols')
parser.add_argument('--output', '-o')
if ipython_mode:
parser.add_argument('--local_namespace', action='store_true')
args = parser.parse_args(remaining_argv)
return(vars(args))
def parse_cell_magic(line, cell):
"""Parse IPython magic"""
args_list = line.split(' ')
args = parse_args(args_list, ipython_mode=True)
local_namespace = args.pop('local_namespace', False)
# By default, execute inside IPython namespace
if not local_namespace:
args['namespace'] = get_ipython().user_ns # flake8: noqa
perf = run_algo(print_algo=False, algo_text=cell, **args)
# If we are running inside NB, do not output to file but create a
# variable instead
output_var_name = args.pop('output', None)
if output_var_name is not None:
get_ipython().user_ns[output_var_name] = perf # flake8: noqa
def run_algo(print_algo=True, **kwargs):
start = pd.Timestamp(kwargs['start'], tz='UTC')
end = pd.Timestamp(kwargs['end'], tz='UTC')
@@ -93,29 +117,40 @@ def run_algo(print_algo=True, **kwargs):
symbols = kwargs['symbols'].split(',')
if kwargs['source'] == 'yahoo':
source = zipline.data.load_bars_from_yahoo(stocks=symbols, start=start, end=end)
source = zipline.data.load_bars_from_yahoo(
stocks=symbols, start=start, end=end)
else:
raise NotImplementedError('Source %s not implemented.' % kwargs['source'])
raise NotImplementedError(
'Source %s not implemented.' % kwargs['source'])
algo_fname = kwargs['algofile']
with open(algo_fname, 'r') as fd:
algo_text = fd.read()
algo_text = kwargs.get('algo_text', None)
if algo_text is None:
# Expect algofile to be set
algo_fname = kwargs['algofile']
with open(algo_fname, 'r') as fd:
algo_text = fd.read()
analyze_fname = os.path.splitext(algo_fname)[0] + '_analyze.py'
if os.path.exists(analyze_fname):
with open(analyze_fname, 'r') as fd:
# Simply append
algo_text += fd.read()
analyze_fname = os.path.splitext(algo_fname)[0] + '_analyze.py'
if os.path.exists(analyze_fname):
with open(analyze_fname, 'r') as fd:
# Simply append
algo_text += fd.read()
if print_algo:
if PYGMENTS:
highlight(algo_text, PythonLexer(), TerminalFormatter(), outfile=sys.stdout)
highlight(algo_text, PythonLexer(), TerminalFormatter(),
outfile=sys.stdout)
else:
print algo_text
print_(algo_text)
algo = zipline.TradingAlgorithm(script=algo_text,
namespace=kwargs.get('namespace', {}),
capital_base=float(kwargs['capital_base']))
perf = algo.run(source)
output_fname = kwargs.get('output', None)
if output_fname is not None:
perf.to_pickle(output_fname)
return perf