Merge branch 'release/0.19'

.gitignore

@@ -3,12 +3,17 @@ MANIFEST
 doc/_build
 .idea
 .coverage
+.coverage.*
 .ipynb_checkpoints
 .ropeproject
+.tox
+.pytest_cache
 
-data
-dist
-build
-PyAlgoTrade.egg-info
+/venv
+/data
+/dist
+/build
+/PyAlgoTrade.egg-info
+/notebooks
 
-testcases/twitter_credentials.py
+/testcases/credentials.py

.travis.yml

@@ -1,27 +1,30 @@
+language: python
+python:
+  - "2.7"
+
 env:
   global:
+    # https://docs.travis-ci.com/user/environment-variables/#Defining-encrypted-variables-in-.travis.yml
+    # travis encrypt QUANDL_API_KEY=somevalue
     - secure: "YgngWTEKD6bUVgExTN8vWYCq7mrMKsVVqZaWIsepRziU++K1e9iBuQrSspQbyrdsKMqKMyMnsM3ru7M6+D0F+p/BC4gyWg6N+wn3RoqrWidyutejibsobDJnS3EsSfo4cJUFcoAOzzuXK+Du0yUZPNBxjJdF/NA1C8vDg0YAmzs="
     - secure: "GUuZEQSA9x96bIJiC/Ab/RxQ+Dv2eqwhRVaZYVlmuSDQXouDJdFAF9dEcUplwt3TCKg7CbOa3gr2c1rJ7bclk1ueUSXdwzlgEfEdcu7Xm+lf6LcfZESDtWUvPgRzvVqspp3hwx+SCpSl2TzXwgCRNOX8ybDC5ZvRZRQaagT6maA="
     - secure: "oAUaWICTHks6N/RNFZbF/NJE+1mB45DRZu1uvzKN5EhEp+Qys6LGHm1yZLI1sMAfwYrLro1oxNGpxD26hoMDjy2bDyBNZj59i2M7Eeo9juY3wR2sz0tKuvEdMdbuhMGyDgvXV6xlqO10hHeUUwbJOyxcQxmcp0c33B0Jse3m+pI="
     - secure: "OrR5+l3HzjKWQtVRUIHB1uLCFtRt1wNAQxJjoL6mufBMIigcpMnE2QzsoP9ywSgew8St4nFMGaL/xxR/RYTi59c6fVRh8zGg/JYMSYtr4UM8M2Gk0vSYmo3JO9OihOxn3JWbF4606vzEgqtjMT9qojo3Xx/d0Hp9br5s/wwe1oQ="
+    - secure: "beFEPV9JWgX4wFx3mBeBwE7hBAK2h9gW5qpNolgYrevDQxHDQdfcNN5Rcda2/VGQiEKM+X4dixNttogfNu4yS21c5/DPUhsKNwV/ClZgYsmkowGwkXsaF6J/cYcE9+WvziCfDV3z3wTKMmyPMJlbeFDB+zik2idzkG3txUVo27g="
 
 sudo: required
 
-language: python
-python:
-  - "2.7"
-
 services:
   - docker
 
 before_install:
-  - docker pull gbecedillas/pyalgotrade:0.18
+  - docker pull gbecedillas/pyalgotrade:0.20-py27
   - cp travis/Dockerfile .
-  - docker build -t testcases .
+  - docker build -t pyalgotrade_testcases .
   - sudo pip install coveralls
 
 script:
-  - docker run --name testcases --env TWITTER_CONSUMER_KEY=$TWITTER_CONSUMER_KEY --env TWITTER_CONSUMER_SECRET=$TWITTER_CONSUMER_SECRET --env TWITTER_ACCESS_TOKEN=$TWITTER_ACCESS_TOKEN --env TWITTER_ACCESS_TOKEN_SECRET=$TWITTER_ACCESS_TOKEN_SECRET testcases /bin/bash -c "cd /tmp/pyalgotrade; ./run_tests.sh"
+  - docker run --name testcases --env TWITTER_CONSUMER_KEY=$TWITTER_CONSUMER_KEY --env TWITTER_CONSUMER_SECRET=$TWITTER_CONSUMER_SECRET --env TWITTER_ACCESS_TOKEN=$TWITTER_ACCESS_TOKEN --env TWITTER_ACCESS_TOKEN_SECRET=$TWITTER_ACCESS_TOKEN_SECRET --env QUANDL_API_KEY=$QUANDL_API_KEY pyalgotrade_testcases /bin/bash -c "cd /tmp/pyalgotrade; ./run_tests.sh"
 
 after_success:
   - docker cp testcases:/tmp/pyalgotrade/.coverage .

CHANGELOG

@@ -1,3 +1,17 @@
+Version 0.20 (20/Aug/2018)
+. [NEW] Added support for Python 3.7.
+. [NEW] Added setShares method for back-testing broker. Thanks winkidney for implementing this.
+. [NEW] Added an option to support skipping errors while parsing CSV files.
+. [NEW] Added batchSize parameter to optimizer component. Thanks micmicmichael for implementing this.
+. [NEW] Added savePlot to the plotter to save the plot to a file. Thanks Kimble Young for implementing this.
+. [FIX] Fixed a bug in the Event class when unsubscribing and re-subscribing while emitting. Thanks pjz for reporting this.
+. [FIX] Fixed a race condition in the local optimizer that was sometimes getting blocked waiting for workers.
+. [FIX] Fixed a bug while generating nonces for Bitstamp. Thanks pjz for reporting this.
+. [FIX] Fixed callback for BaseStrategy.resampleBarFeed to match onBars prototype.
+. [FIX] Fixed extra columns parsing in csvfeed.GenericRowParser. Thanks Jones Chung for reporting this.
+. [BREAKING CHANGE] Removed support for downloading bars from Yahoo Finance.
+. [BREAKING CHANGE] Removed support for downloading bars from Google Finance.
+
 Version 0.18 (17/Aug/2016)
 . [NEW] Returns analyzer now stores datetimes along with each sample. Thanks MatthiasKauer for implementing this.
 . [NEW] Quandl tool to build feed supports mapping column names.

LICENSE.txt → LICENSE

@@ -1,6 +1,6 @@
 PyAlgoTrade
 
-Copyright 2011 Gabriel Martin Becedillas Ruiz
+Copyright 2011-2018 Gabriel Martin Becedillas Ruiz
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.

README.md

@@ -14,7 +14,7 @@ and **live trading** is now possible using:
 
  * [Bitstamp](https://www.bitstamp.net/) for Bitcoins
 
-To get started with PyAlgoTrade take a look at the [tutorial](http://gbeced.github.io/pyalgotrade/docs/v0.18/html/tutorial.html) and the [full documentation](http://gbeced.github.io/pyalgotrade/docs/v0.18/html/index.html).
+To get started with PyAlgoTrade take a look at the [tutorial](http://gbeced.github.io/pyalgotrade/docs/v0.20/html/tutorial.html) and the [full documentation](http://gbeced.github.io/pyalgotrade/docs/v0.20/html/index.html).
 
 Main Features
 -------------
@@ -32,7 +32,7 @@ Main Features
 Installation
 ------------
 
-PyAlgoTrade is developed using Python 2.7 and depends on:
+PyAlgoTrade is developed and tested using Python 2.7/3.7 and depends on:
 
  * [NumPy and SciPy](http://numpy.scipy.org/).
  * [pytz](http://pytz.sourceforge.net/).

build_sdist.sh

@@ -2,4 +2,3 @@ export LC_ALL=en_US.UTF-8
 export LANG=en_US.UTF-8
 
 python setup.py sdist
-

cleanup.sh

@@ -4,7 +4,3 @@ find . -name *.pyc -delete
 find . -name .coverage -delete
 find . -name .noseids -delete
 find . -name htmlcov -exec rm -rf {} \;
-
-find . -name *.egg-info -exec rm -rf {} \;
-find . -name dist -exec rm -rf {} \;
-

coverage.cfg

@@ -1,4 +1,5 @@
 [report]
+show_missing = 1
 exclude_lines =
     pragma: no cover
     raise NotImplementedError()

doc/bitstamp_example.rst

@@ -15,7 +15,7 @@ The key things to highlight are:
     as the base class. This is not a backtest.
  2. Trade events get notified via the call to **onBars**. No need to manually subscribe.
  3. Order book update events are handled by manually subscribing to :class:`pyalgotrade.bitstamp.barfeed.LiveTradeFeed.getOrderBookUpdateEvent`.
-    This is needed to be up to date with latest bid and ask prices.
+    This is needed to stay up to date with latest bid and ask prices.
 
 .. literalinclude:: ../samples/tutorial_bitstamp_1.py
 
@@ -134,5 +134,5 @@ In order to live trade this strategy you should use :class:`pyalgotrade.bitstamp
 :class:`pyalgotrade.bitstamp.broker.PaperTradingBroker`.
 
 **Note that if you try to live trade this strategy you will probably loose money.**
-Before jumping to live trading, be sure to write your own strategy, backtest and paper trade it thoroughly
+Before jumping into live trading, be sure to write your own strategy, backtest and paper trade it thoroughly
 before risking real money.

doc/compinvpart1.rst

@@ -2,12 +2,12 @@ Computational Investing Part I
 ==============================
 
 As I was taking the `Computational Investing Part I <https://class.coursera.org/compinvesting1-2012-001/class>`_ course in 2012
-I had to work on a set of assignments and for some of them I used PyAlgoTrade.
+I had to work on a set of assignments and for one of them I used PyAlgoTrade.
 
 Homework 1
 ----------
 
-For this assignment I had to pick 4 stocks, invest a total of $100000 during 2011, and calculate:
+For this assignment I had to pick 4 stocks, invest a total of $1000000 during 2011, and calculate:
 
  * Final portfolio value
  * Anual return
@@ -17,10 +17,10 @@ For this assignment I had to pick 4 stocks, invest a total of $100000 during 201
 
 Download the data with the following commands: ::
 
-    python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('aeti', 2011, 'aeti-2011-yahoofinance.csv')"
-    python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('egan', 2011, 'egan-2011-yahoofinance.csv')"
-    python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('glng', 2011, 'glng-2011-yahoofinance.csv')"
-    python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('simo', 2011, 'simo-2011-yahoofinance.csv')"
+    python -m "pyalgotrade.tools.quandl" --source-code="WIKI" --table-code="IBM" --from-year=2011 --to-year=2011 --storage=. --force-download --frequency=daily
+    python -m "pyalgotrade.tools.quandl" --source-code="WIKI" --table-code="AES" --from-year=2011 --to-year=2011 --storage=. --force-download --frequency=daily
+    python -m "pyalgotrade.tools.quandl" --source-code="WIKI" --table-code="AIG" --from-year=2011 --to-year=2011 --storage=. --force-download --frequency=daily
+    python -m "pyalgotrade.tools.quandl" --source-code="WIKI" --table-code="ORCL" --from-year=2011 --to-year=2011 --storage=. --force-download --frequency=daily
 
 Although the deliverable was an Excel spreadsheet, I validated the results using this piece of code:
 
@@ -29,53 +29,3 @@ Although the deliverable was an Excel spreadsheet, I validated the results using
 The results were:
 
 .. literalinclude:: ../samples/compinv-1.output
-
-Homework 3 and 4
-----------------
-
-For these assignments I had to build a market simulation tool that loads orders from a file, executes those,
-and prints the results for each day.
-
-The orders file for homework 3 look like this: ::
-
-    2011,1,10,AAPL,Buy,1500,
-    2011,1,13,AAPL,Sell,1500,
-    2011,1,13,IBM,Buy,4000,
-    2011,1,26,GOOG,Buy,1000,
-    2011,2,2,XOM,Sell,4000,
-    2011,2,10,XOM,Buy,4000,
-    2011,3,3,GOOG,Sell,1000,
-    2011,3,3,IBM,Sell,2200,
-    2011,6,3,IBM,Sell,3300,
-    2011,5,3,IBM,Buy,1500,
-    2011,6,10,AAPL,Buy,1200,
-    2011,8,1,GOOG,Buy,55,
-    2011,8,1,GOOG,Sell,55,
-    2011,12,20,AAPL,Sell,1200,
-
-This is the market simulation tool that I built:
-
-.. literalinclude:: ../samples/compinv-3.py
-
-The output for homework 3 looks like this: ::
-
-    First date 2011-01-10 00:00:00
-    Last date 2011-12-20 00:00:00
-    Symbols ['AAPL', 'IBM', 'GOOG', 'XOM']
-    2011-01-10 00:00:00: Portfolio value: $1000000.00
-    2011-01-11 00:00:00: Portfolio value: $998785.00
-    2011-01-12 00:00:00: Portfolio value: $1002940.00
-    2011-01-13 00:00:00: Portfolio value: $1004815.00
-    .
-    .
-    .
-    2011-12-15 00:00:00: Portfolio value: $1113532.00
-    2011-12-16 00:00:00: Portfolio value: $1116016.00
-    2011-12-19 00:00:00: Portfolio value: $1117444.00
-    2011-12-20 00:00:00: Portfolio value: $1133860.00
-    Final portfolio value: $1133860.00
-    Anual return: 13.39 %
-    Average daily return: 0.05 %
-    Std. dev. daily return: 0.0072
-    Sharpe ratio: 1.21
-

doc/conf.py

@@ -51,9 +51,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '0.18'
+version = '0.20'
 # The full version, including alpha/beta/rc tags.
-release = '0.18'
+release = '0.20'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

doc/eventprofiler.rst

@@ -1,7 +1,7 @@
 Event profiler
 ==============
 
-Inspired in QSTK (http://wiki.quantsoftware.org/index.php?title=QSTK_Tutorial_9), the **eventprofiler** module is a tool to analyze,
+Inspired in `QSTK <http://wiki.quantsoftware.org/index.php?title=QSTK_Tutorial_9>`_, the **eventprofiler** module is a tool to analyze,
 statistically, how events affect future equity prices.
 The event profiler scans over historical data for a specified event and then calculates the impact of that event on the equity prices in the past
 and the future over a certain lookback period.

doc/intro.rst

@@ -8,7 +8,7 @@ PyAlgoTrade is an event driven algorithmic trading Python library with support f
 
 It should also make it easy to optimize a strategy using multiple computers.
 
-PyAlgoTrade is developed using Python 2.7 and depends on:
+PyAlgoTrade is developed and tested using Python 2.7/3.7 and depends on:
  * NumPy and SciPy (http://numpy.scipy.org/).
  * pytz (http://pytz.sourceforge.net/).
  * matplotlib (http://matplotlib.sourceforge.net/) for plotting support.

doc/optimizer.rst

@@ -17,6 +17,6 @@ optimizer -- Parallel optimizers
     :show-inheritance:
 
 .. note::
-    * The server component will split strategy executions in chunks which are distributed among the different workers. **pyalgotrade.optimizer.server.Server.defaultBatchSize** controls the chunk size.
+    * The server component will split strategy executions in chunks which are distributed among the different workers. You can optionally set the chunk size by passing in **batchSize** to the constructor of **pyalgotrade.optimizer.xmlrpcserver.Server**.
     * The :meth:`pyalgotrade.strategy.BaseStrategy.getResult` method is used to select the best strategy execution. You can override that method to rank executions using a different criteria.
 

doc/sample_market_timing.rst

@@ -13,7 +13,7 @@ returns in the last month.
 
 This is what the output should look like:
 
-.. literalinclude:: ../samples/market_timing.output
+.. literalinclude:: ../samples/market_timing.output.27
 
 This is what the plot should look like:
 

doc/sample_vwap_momentum.rst

@@ -1,8 +1,7 @@
 VWAP Momentum Trade
 ===================
 
-This example is based on:
- * https://www.quantopian.com/posts/momentum-trade
+This example is based on `Momentum Trade <https://www.quantopian.com/posts/momentum-trade>`_
 
 .. literalinclude:: ../samples/vwap_momentum.py
 

doc/tools.rst

@@ -1,13 +1,6 @@
 Tools
 =====
 
-Yahoo! Finance
---------------
-
-.. automodule:: pyalgotrade.tools.yahoofinance
-    :members:
-    :show-inheritance:
-
 Quandl
 ------