Merge branch 'develop' -> release 0.3

catalyst/algorithm.py

@@ -138,8 +138,9 @@ from catalyst.gens.sim_engine import MinuteSimulationClock
 from catalyst.sources.benchmark_source import BenchmarkSource
 from catalyst.catalyst_warnings import ZiplineDeprecationWarning
 
+from catalyst.constants import LOG_LEVEL
 
-log = logbook.Logger("ZiplineLog")
+log = logbook.Logger("CatalystLog", level=LOG_LEVEL)
 
 
 class TradingAlgorithm(object):

catalyst/assets/assets.py

@@ -76,7 +76,9 @@ from catalyst.utils.numpy_utils import as_column
 from catalyst.utils.preprocess import preprocess
 from catalyst.utils.sqlite_utils import group_into_chunks, coerce_string_to_eng
 
-log = Logger('assets.py')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('assets.py', level=LOG_LEVEL)
 
 # A set of fields that need to be converted to strings before building an
 # Asset to avoid unicode fields

catalyst/constants.py

@@ -0,0 +1,5 @@
+# -*- coding: utf-8 -*-
+
+import logbook
+
+LOG_LEVEL = logbook.INFO

catalyst/data/_equities.pyx

@@ -215,7 +215,7 @@ cpdef _read_bcolz_data(ctable_t table,
                 else:
                     continue
 
-        if column_name in ['open', 'high', 'low', 'close']:
+        if column_name in ['open', 'high', 'low', 'close', 'volume']:
             where_nan = (outbuf == 0)
             outbuf_as_float = outbuf.astype(float64) * .000000001
             outbuf_as_float[where_nan] = NAN

catalyst/data/bundles/base.py

@@ -30,8 +30,10 @@ from catalyst.utils.cli import (
 )
 from catalyst.utils.memoize import lazyval
 
+from catalyst.constants import LOG_LEVEL
+
 logbook.StderrHandler().push_application()
-log = logbook.Logger(__name__)
+log = logbook.Logger(__name__, level=LOG_LEVEL)
 
 DEFAULT_RETRIES = 5
 

catalyst/data/bundles/quandl.py

@@ -40,7 +40,9 @@ from catalyst.utils.cli import maybe_show_progress
 
 from . import core as bundles
 
-log = Logger(__name__)
+from catalyst.constants import LOG_LEVEL
+
+log = Logger(__name__, level=LOG_LEVEL)
 seconds_per_call = (pd.Timedelta('10 minutes') / 2000).total_seconds()
 
 class QuandlBundle(BaseEquityPricingBundle):

catalyst/data/data_portal.py

@@ -68,7 +68,9 @@ from catalyst.errors import (
     HistoryWindowStartsBeforeData,
 )
 
-log = Logger('DataPortal')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('DataPortal', level=LOG_LEVEL)
 
 BASE_FIELDS = frozenset([
     "open",

catalyst/data/loader.py

@@ -32,7 +32,9 @@ from ..utils.paths import (
     data_root,
 )
 
-logger = logbook.Logger('Loader')
+from catalyst.constants import LOG_LEVEL
+
+logger = logbook.Logger('Loader', level=LOG_LEVEL)
 
 # Mapping from index symbol to appropriate bond data
 INDEX_MAPPING = {

catalyst/data/minute_bars.py

@@ -44,7 +44,9 @@ from catalyst.utils.calendars import get_calendar
 from catalyst.utils.cli import maybe_show_progress
 from catalyst.utils.memoize import lazyval
 
-logger = logbook.Logger('MinuteBars')
+from catalyst.constants import LOG_LEVEL
+
+logger = logbook.Logger('MinuteBars', level=LOG_LEVEL)
 
 US_EQUITIES_MINUTES_PER_DAY = 390
 FUTURES_MINUTES_PER_DAY = 1440

catalyst/data/us_equity_pricing.py

@@ -83,7 +83,9 @@ from catalyst.utils.cli import (
 from ._equities import _compute_row_slices, _read_bcolz_data
 from ._adjustments import load_adjustments_from_sqlite
 
-logger = logbook.Logger('UsEquityPricing')
+from catalyst.constants import LOG_LEVEL
+
+logger = logbook.Logger('UsEquityPricing', level=LOG_LEVEL)
 
 OHLC = frozenset(['open', 'high', 'low', 'close'])
 OHLCV = frozenset(['open', 'high', 'low', 'close', 'volume'])

catalyst/examples/buy_btc_simple.py

@@ -1,8 +1,8 @@
 from catalyst.api import order, record, symbol
 
 def initialize(context):
-   context.asset = symbol('btc_usd')
+    context.asset = symbol('btc_usd')
 
 def handle_data(context, data):
-   order(asset, 1)
-   record(btc=data.current(context.asset, 'price'))
+    order(context.asset, 1)
+    record(btc = data.current(context.asset, 'price'))

catalyst/exchange/asset_finder_exchange.py

@@ -1,6 +1,8 @@
 from logbook import Logger
 
-log = Logger('AssetFinderExchange')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('AssetFinderExchange', level=LOG_LEVEL)
 
 
 class AssetFinderExchange(object):
@@ -41,9 +43,9 @@ class AssetFinderExchange(object):
         """
         for sid in sids:
             if sid in self._asset_cache:
-                log.info('got asset from cache: {}'.format(sid))
+                log.debug('got asset from cache: {}'.format(sid))
             else:
-                log.info('fetching asset: {}'.format(sid))
+                log.debug('fetching asset: {}'.format(sid))
         return list()
 
     def lookup_symbol(self, symbol, exchange, as_of_date=None, fuzzy=False):

catalyst/exchange/bitfinex/bitfinex.py

@@ -33,7 +33,9 @@ requests.adapters.DEFAULT_RETRIES = 20
 
 BITFINEX_URL = 'https://api.bitfinex.com'
 
-log = Logger('Bitfinex')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('Bitfinex', level=LOG_LEVEL)
 warning_logger = Logger('AlgoWarning')
 
 

catalyst/exchange/bittrex/bittrex.py

@@ -16,7 +16,9 @@ from catalyst.finance.order import Order, ORDER_STATUS
 from catalyst.exchange.exchange_utils import get_exchange_symbols_filename, \
     download_exchange_symbols
 
-log = Logger('Bittrex')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('Bittrex', level=LOG_LEVEL)
 
 URL2 = 'https://bittrex.com/Api/v2.0'
 

catalyst/exchange/data_portal_exchange.py

@@ -29,7 +29,9 @@ from catalyst.exchange.exchange_errors import (
     PricingDataNotLoadedError, InvalidHistoryFrequencyError,
     BundleNotFoundError)
 
-log = Logger('DataPortalExchange')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('DataPortalExchange', level=LOG_LEVEL)
 
 
 class DataPortalExchangeBase(DataPortal):

catalyst/exchange/exchange.py

@@ -24,7 +24,9 @@ from catalyst.exchange.exchange_utils import get_exchange_symbols
 from catalyst.finance.order import ORDER_STATUS
 from catalyst.finance.transaction import Transaction
 
-log = Logger('Exchange')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('Exchange', level=LOG_LEVEL)
 
 
 class Exchange:

catalyst/exchange/exchange_algorithm.py

@@ -54,7 +54,9 @@ from catalyst.utils.input_validation import error_keywords, ensure_upper_case, \
 from catalyst.utils.preprocess import preprocess
 from catalyst.utils.math_utils import round_nearest
 
-log = logbook.Logger('exchange_algorithm')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('exchange_algorithm', level=LOG_LEVEL)
 
 
 class ExchangeAlgorithmExecutor(AlgorithmSimulator):

catalyst/exchange/exchange_blotter.py

@@ -6,7 +6,9 @@ from catalyst.finance.commission import CommissionModel
 from catalyst.finance.slippage import SlippageModel
 from catalyst.finance.transaction import Transaction
 
-log = Logger('exchange_blotter')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('exchange_blotter', level=LOG_LEVEL)
 
 # It seems like we need to accept greater slippage risk in cryptos
 # Orders won't often close at Equity levels.

catalyst/exchange/exchange_bundle.py

@@ -21,16 +21,15 @@ from catalyst.exchange.exchange_utils import get_exchange_folder
 from catalyst.utils.cli import maybe_show_progress
 from catalyst.utils.paths import ensure_directory
 
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('exchange_bundle', level=LOG_LEVEL)
+
+BUNDLE_NAME_TEMPLATE = '{root}/{frequency}_bundle'
 
 def _cachpath(symbol, type_):
     return '-'.join([symbol, type_])
 
-
-BUNDLE_NAME_TEMPLATE = '{root}/{frequency}_bundle'
-log = Logger('exchange_bundle')
-log.level = INFO
-
-
 class ExchangeBundle:
     def __init__(self, exchange):
         self.exchange = exchange

catalyst/exchange/exchange_portfolio.py

@@ -3,7 +3,9 @@ from logbook import Logger
 
 from catalyst.protocol import Portfolio, Positions, Position
 
-log = Logger('ExchangePortfolio')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('ExchangePortfolio', level=LOG_LEVEL)
 
 
 class ExchangePortfolio(Portfolio):

catalyst/exchange/live_graph_clock.py

@@ -22,8 +22,9 @@ from logbook import Logger
 from catalyst.exchange.exchange_errors import \
     MismatchingBaseCurrenciesExchanges
 
+from catalyst.constants import LOG_LEVEL
 
-log = Logger('LiveGraphClock')
+log = Logger('LiveGraphClock', level=LOG_LEVEL)
 
 
 class LiveGraphClock(object):

catalyst/exchange/poloniex/poloniex.py

@@ -33,7 +33,9 @@ from catalyst.exchange.exchange_utils import get_exchange_symbols_filename, \
     download_exchange_symbols
 from catalyst.finance.transaction import Transaction
 
-log = Logger('Poloniex')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('Poloniex', level=LOG_LEVEL)
 
 
 class Poloniex(Exchange):

catalyst/finance/blotter.py

@@ -34,7 +34,9 @@ from catalyst.finance.commission import (
 from catalyst.finance.cancel_policy import NeverCancel
 from catalyst.utils.input_validation import expect_types
 
-log = Logger('Blotter')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('Blotter', level=LOG_LEVEL)
 warning_logger = Logger('AlgoWarning')
 
 

catalyst/finance/controls.py

@@ -24,7 +24,9 @@ from catalyst.errors import (
     TradingControlViolation,
 )
 
-log = logbook.Logger('TradingControl')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('TradingControl', level=LOG_LEVEL)
 
 
 class TradingControl(with_metaclass(abc.ABCMeta)):

catalyst/finance/performance/period.py

@@ -88,7 +88,10 @@ from six import itervalues, iteritems
 
 import catalyst.protocol as zp
 
-log = logbook.Logger('Performance')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Performance', level=LOG_LEVEL)
+
 TRADE_TYPE = zp.DATASOURCE_TYPE.TRADE
 
 

catalyst/finance/performance/position.py

@@ -40,7 +40,9 @@ import logbook
 from catalyst.assets import Future, Asset
 from catalyst.utils.input_validation import expect_types
 
-log = logbook.Logger('Performance')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Performance', level=LOG_LEVEL)
 
 
 class Position(object):

catalyst/finance/performance/position_tracker.py

@@ -32,7 +32,9 @@ from catalyst.assets import (
 )
 from . position import positiondict
 
-log = logbook.Logger('Performance')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Performance', level=LOG_LEVEL)
 
 
 PositionStats = namedtuple('PositionStats',

catalyst/finance/performance/tracker.py

@@ -70,7 +70,9 @@ import catalyst.finance.risk as risk
 
 from . position_tracker import PositionTracker
 
-log = logbook.Logger('Performance')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Performance', level=LOG_LEVEL)
 
 
 class PerformanceTracker(object):

catalyst/finance/risk/cumulative.py

@@ -38,7 +38,9 @@ from empyrical import (
     sortino_ratio,
 )
 
-log = logbook.Logger('Risk Cumulative')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Risk Cumulative', level=LOG_LEVEL)
 
 
 choose_treasury = functools.partial(choose_treasury, lambda *args: '10year',

catalyst/finance/risk/period.py

@@ -36,7 +36,9 @@ from empyrical import (
     sortino_ratio
 )
 
-log = logbook.Logger('Risk Period')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Risk Period', level=LOG_LEVEL)
 
 choose_treasury = functools.partial(risk.choose_treasury,
                                     risk.select_treasury_duration)

catalyst/finance/risk/report.py

@@ -63,7 +63,9 @@ from dateutil.relativedelta import relativedelta
 
 from . period import RiskMetricsPeriod
 
-log = logbook.Logger('Risk Report')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Risk Report', level=LOG_LEVEL)
 
 
 class RiskReport(object):

catalyst/finance/risk/risk.py

@@ -61,7 +61,9 @@ Risk Report
 import logbook
 import numpy as np
 
-log = logbook.Logger('Risk')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Risk', level=LOG_LEVEL)
 
 
 TREASURY_DURATIONS = [

catalyst/finance/trading.py

@@ -26,7 +26,9 @@ from catalyst.data.loader import load_market_data
 from catalyst.utils.calendars import get_calendar
 from catalyst.utils.memoize import remember_last
 
-log = logbook.Logger('Trading')
+from catalyst.constants import LOG_LEVEL
+
+log = logbook.Logger('Trading', level=LOG_LEVEL)
 
 
 DEFAULT_CAPITAL_BASE = 1e5

catalyst/gens/tradesimulation.py

@@ -27,7 +27,9 @@ from catalyst.gens.sim_engine import (
     BEFORE_TRADING_START_BAR
 )
 
-log = Logger('Trade Simulation')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('Trade Simulation', level=LOG_LEVEL)
 
 
 class AlgorithmSimulator(object):

catalyst/sources/requests_csv.py

@@ -23,7 +23,9 @@ from catalyst.protocol import (
 )
 from catalyst.assets import Equity
 
-logger = Logger('Requests Source Logger')
+from catalyst.constants import LOG_LEVEL
+
+logger = Logger('Requests Source Logger', level=LOG_LEVEL)
 
 
 def roll_dts_to_midnight(dts, trading_day):

catalyst/utils/run_algo.py

@@ -43,7 +43,9 @@ from catalyst.exchange.exchange_utils import get_exchange_auth, \
     get_algo_object
 from logbook import Logger
 
-log = Logger('run_algo')
+from catalyst.constants import LOG_LEVEL
+
+log = Logger('run_algo', level=LOG_LEVEL)
 
 
 class _RunAlgoError(click.ClickException, ValueError):

docs/source/beginner-tutorial.rst

@@ -52,7 +52,7 @@ My first algorithm
 ~~~~~~~~~~~~~~~~~~
 
 Lets take a look at a very simple algorithm from the ``examples``
-directory, ``buy_btc.py``:
+directory: `buy_btc_simple.py <https://github.com/enigmampc/catalyst/blob/master/catalyst/examples/buy_btc_simple.py>`_:
 
 .. code-block:: python
 
@@ -225,16 +225,16 @@ Thus, to execute our algorithm from above and save the results to
 
 .. code-block:: python
 
-    catalyst run -f buy_btc_simple.py -x bitfinex --start 2016-1-1 --end 2016-9-29 -o buy_simple_btc_out.pickle
+    catalyst run -f buy_btc_simple.py -x bitfinex --start 2016-1-1 --end 2017-9-30 -o buy_btc_simple_out.pickle
 
 
-.. 
-.. parsed-literal
+.. parsed-literal:: 
 
-..    AAPL
-..    [2015-11-04 22:45:32.820166] INFO: Performance: Simulated 3521 trading days out of 3521.
-..    [2015-11-04 22:45:32.820314] INFO: Performance: first open: 2000-01-03 14:31:00+00:00
-..    [2015-11-04 22:45:32.820401] INFO: Performance: last close: 2013-12-31 21:00:00+00:00
+    INFO: run_algo: running algo in backtest mode
+    INFO: exchange_algorithm: initialized trading algorithm in backtest mode
+    INFO: Performance: Simulated 639 trading days out of 639.
+    INFO: Performance: first open: 2016-01-01 00:00:00+00:00
+    INFO: Performance: last close: 2017-09-30 23:59:00+00:00
 
 
 ``run`` first calls the ``initialize()`` function, and then
@@ -255,7 +255,7 @@ slippage model that ``catalyst`` uses).
 
 Let's take a quick look at the performance ``DataFrame``. For this, we
 use ``pandas`` from inside the IPython Notebook and print the first ten
-rows. Note that ``catalyst`` makes heavy usage of 
+rows. and print the first ten rows. Note that ``catalyst`` makes heavy usage of 
 `pandas <http://pandas.pydata.org/>`_, especially for data input and 
 outputting so it's worth spending some time to learn it.
 
@@ -265,17 +265,196 @@ outputting so it's worth spending some time to learn it.
     perf = pd.read_pickle('buy_btc_simple_out.pickle') # read in perf DataFrame
     perf.head()
 
+.. raw:: html
+
+    <div style="max-height:1000px;max-width:1500px;overflow:auto;">
+      <table border="1" class="dataframe">
+        <thead>
+          <tr style="text-align: right;">
+            <th></th>
+            <th>algo_volatility</th>
+            <th>algorithm_period_return</th>
+            <th>alpha</th>
+            <th>benchmark_period_return</th>
+            <th>benchmark_volatility</th>
+            <th>beta</th>
+            <th>btc</th>
+            <th>capital_used</th>
+            <th>ending_cash</th>
+            <th>ending_exposure</th>
+            <th>...</th>
+            <th>short_exposure</th>
+            <th>short_value</th>
+            <th>shorts_count</th>
+            <th>sortino</th>
+            <th>starting_cash</th>
+            <th>starting_exposure</th>
+            <th>starting_value</th>
+            <th>trading_days</th>
+            <th>transactions</th>
+            <th>treasury_period_return</th>
+          </tr>
+        </thead>
+        <tbody>
+          <tr>
+            <th>2016-01-01 23:59:00+00:00</th>
+            <td>NaN</td>
+            <td>0.000000e+00</td>
+            <td>NaN</td>
+            <td>-0.010937</td>
+            <td>NaN</td>
+            <td>NaN</td>
+            <td>433.979999</td>
+            <td>0.000000</td>
+            <td>1.000000e+07</td>
+            <td>0.00</td>
+            <td>...</td>
+            <td>0</td>
+            <td>0</td>
+            <td>0</td>
+            <td>NaN</td>
+            <td>1.000000e+07</td>
+            <td>0.00</td>
+            <td>0.00</td>
+            <td>1</td>
+            <td>[]</td>
+            <td>0.0227</td>
+          </tr>
+          <tr>
+            <th>2016-01-02 23:59:00+00:00</th>
+            <td>0.000011</td>
+            <td>-9.536708e-07</td>
+            <td>-0.000170</td>
+            <td>-0.006480</td>
+            <td>0.173338</td>
+            <td>-0.000062</td>
+            <td>432.700000</td>
+            <td>-442.236708</td>
+            <td>9.999558e+06</td>
+            <td>432.70</td>
+            <td>...</td>
+            <td>0</td>
+            <td>0</td>
+            <td>0</td>
+            <td>-11.224972</td>
+            <td>1.000000e+07</td>
+            <td>0.00</td>
+            <td>0.00</td>
+            <td>2</td>
+            <td>[{u'order_id': u'7869f7828fa140328eb40477bb7de...</td>
+            <td>0.0227</td>
+          </tr>
+          <tr>
+            <th>2016-01-03 23:59:00+00:00</th>
+            <td>0.000011</td>
+            <td>-2.328842e-06</td>
+            <td>-0.000176</td>
+            <td>-0.026512</td>
+            <td>0.197857</td>
+            <td>0.000009</td>
+            <td>428.390000</td>
+            <td>-437.831716</td>
+            <td>9.999120e+06</td>
+            <td>856.78</td>
+            <td>...</td>
+            <td>0</td>
+            <td>0</td>
+            <td>0</td>
+            <td>-12.754262</td>
+            <td>9.999558e+06</td>
+            <td>432.70</td>
+            <td>432.70</td>
+            <td>3</td>
+            <td>[{u'order_id': u'be62ff77760c4599abaac43be9cc9...</td>
+            <td>0.0227</td>
+          </tr>
+          <tr>
+            <th>2016-01-04 23:59:00+00:00</th>
+            <td>0.000011</td>
+            <td>-2.380954e-06</td>
+            <td>-0.000139</td>
+            <td>-0.008640</td>
+            <td>0.269790</td>
+            <td>0.000020</td>
+            <td>432.900000</td>
+            <td>-442.441116</td>
+            <td>9.998677e+06</td>
+            <td>1298.70</td>
+            <td>...</td>
+            <td>0</td>
+            <td>0</td>
+            <td>0</td>
+            <td>-11.287205</td>
+            <td>9.999120e+06</td>
+            <td>856.78</td>
+            <td>856.78</td>
+            <td>4</td>
+            <td>[{u'order_id': u'd6dca79513214346a646079213526...</td>
+            <td>0.0224</td>
+          </tr>
+          <tr>
+            <th>2016-01-05 23:59:00+00:00</th>
+            <td>0.000011</td>
+            <td>-3.650729e-06</td>
+            <td>-0.000158</td>
+            <td>-0.021426</td>
+            <td>0.245989</td>
+            <td>0.000024</td>
+            <td>431.840000</td>
+            <td>-441.357754</td>
+            <td>9.998236e+06</td>
+            <td>1727.36</td>
+            <td>...</td>
+            <td>0</td>
+            <td>0</td>
+            <td>0</td>
+            <td>-12.333847</td>
+            <td>9.998677e+06</td>
+            <td>1298.70</td>
+            <td>1298.70</td>
+            <td>5</td>
+            <td>[{u'order_id': u'505275d6646a41f3856b22b16678d...</td>
+            <td>0.0225</td>
+          </tr>
+        </tbody>
+      </table>
+    </div>
+
+|
 There is a row for each trading day, starting on the first day of our 
 simulation Jan 1st, 2016. In the columns you can find various
-information about the state of your algorithm. The very first column
+information about the state of your algorithm. The column
 ``btc`` was placed there by the ``record()`` function mentioned earlier
 and allows us to plot the price of bitcoin. For example, we could easily
 examine now how our portfolio value changed over time compared to the
 bitcoin price.
 
-Our algorithm performance as assessed by the
-``portfolio_value`` closely matches that of the bitcoin price. This
-is not surprising as our algorithm only bought bitcoin every chance it got.
+.. code-block:: python
+
+    %pylab inline
+    figsize(12, 12)
+    import matplotlib.pyplot as plt
+
+    ax1 = plt.subplot(211)
+    perf.portfolio_value.plot(ax=ax1)
+    ax1.set_ylabel('portfolio value')
+    ax2 = plt.subplot(212, sharex=ax1)
+    perf.btc.plot(ax=ax2)
+    ax2.set_ylabel('bitcoin price')
+
+.. parsed-literal::
+
+    Populating the interactive namespace from numpy and matplotlib
+
+.. parsed-literal::
+
+    <matplotlib.text.Text at 0x10eaeadd0>
+
+.. image:: https://s3.amazonaws.com/enigmaco-docs/github.io/buy_btc_simple_graph.png
+
+Our algorithm performance as assessed by the ``portfolio_value`` closely 
+matches that of the bitcoin price. This is not surprising as our algorithm 
+only bought bitcoin every chance it got.
 
 
 Access to previous prices using ``history``
@@ -305,13 +484,14 @@ a function we use in the ``handle_data()`` section:
 
 .. code-block:: python
 
-    from catalyst.api import order, record, symbol
+    %%catalyst --start 2016-1-1 --end 2017-9-30 -x bitfinex -o dma.pickle
+    from catalyst.api import order, record, symbol, order_target
 
     def initialize(context):
        context.i = 0
        context.asset = symbol('btc_usd')
 
-   def handle_data(context, data):
+    def handle_data(context, data):
        # Skip first 300 days to get full windows
        context.i += 1
        if context.i < 300:
@@ -336,6 +516,46 @@ a function we use in the ``handle_data()`` section:
               short_mavg=short_mavg,
               long_mavg=long_mavg)
 
+    def analyze(context, perf):
+       import matplotlib.pyplot as plt
+       fig = plt.figure()
+       ax1 = fig.add_subplot(211)
+       perf.portfolio_value.plot(ax=ax1)
+       ax1.set_ylabel('portfolio value in $')
+
+       ax2 = fig.add_subplot(212)
+       perf['btc'].plot(ax=ax2)
+       perf[['short_mavg', 'long_mavg']].plot(ax=ax2)
+
+       perf_trans = perf.ix[[t != [] for t in perf.transactions]]
+       buys = perf_trans.ix[[t[0]['amount'] > 0 for t in perf_trans.transactions]]
+       sells = perf_trans.ix[
+           [t[0]['amount'] < 0 for t in perf_trans.transactions]]
+       ax2.plot(buys.index, perf.short_mavg.ix[buys.index],
+                '^', markersize=10, color='m')
+       ax2.plot(sells.index, perf.short_mavg.ix[sells.index],
+                'v', markersize=10, color='k')
+       ax2.set_ylabel('price in $')
+       plt.legend(loc=0)
+       plt.show()
+
+Here we are explicitly defining an ``analyze()`` function that gets
+automatically called once the backtest is done.
+
+Although it might not be directly apparent, the power of ``history()``
+(pun intended) can not be under-estimated as most algorithms make use of
+prior market developments in one form or another. You could easily
+devise a strategy that trains a classifier with
+`scikit-learn <http://scikit-learn.org/stable/>`__ which tries to
+predict future market movements based on past prices (note, that most of
+the ``scikit-learn`` functions require ``numpy.ndarray``\ s rather than
+``pandas.DataFrame``\ s, so you can simply pass the underlying
+``ndarray`` of a ``DataFrame`` via ``.values``).
+
+We also used the ``order_target()`` function above. This and other
+functions like it can make order management and portfolio rebalancing
+much easier.
+
 
 Conclusions
 ~~~~~~~~~~~

etc/requirements.txt

@@ -1,7 +1,7 @@
 # Incompatible with earlier PIP versions
 pip>=7.1.0
 # bcolz fails to install if this is not in the build_requires.
-setuptools>18.0
+setuptools>36.0
 
 # Logging
 Logbook==0.12.5