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Merge branch 'py3k'
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kwgoodman committed Mar 18, 2013
2 parents 93aa17f + 63665b7 commit 057d989
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4 changes: 2 additions & 2 deletions README.rst
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Expand Up @@ -122,9 +122,9 @@ After you have installed ``la``, run the suite of unit tests::
>>> import la >>> import la
>>> la.test() >>> la.test()
<snip> <snip>
Ran 3020 tests in 9.225s Ran 3012 tests in 9.225s
OK OK
<nose.result.TextTestResult run=3020 errors=0 failures=0> <nose.result.TextTestResult run=3012 errors=0 failures=0>
The ``la`` package contains C extensions that speed up common alignment The ``la`` package contains C extensions that speed up common alignment
operations such as adding two unaligned larrys. If the C extensions don't operations such as adding two unaligned larrys. If the C extensions don't
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4 changes: 2 additions & 2 deletions la/__init__.py
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@@ -1,5 +1,5 @@
"la init" "la init"

from __future__ import print_function
# Classes # Classes
from la.deflarry import larry from la.deflarry import larry


Expand All @@ -22,7 +22,7 @@
test = Tester().test test = Tester().test
del Tester del Tester
except (ImportError, ValueError): except (ImportError, ValueError):
print "No la unit testing available." print("No la unit testing available.")


try: try:
# Namespace cleaning # Namespace cleaning
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6 changes: 3 additions & 3 deletions la/data/yahoo.py
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@@ -1,4 +1,4 @@

from __future__ import print_function
import datetime import datetime
import numpy as np import numpy as np
import la import la
Expand Down Expand Up @@ -110,10 +110,10 @@ def quotes(tickers, date1=None, date2=None, adjust=True, verbose=False):
lar = None lar = None
items = ['open', 'close', 'high', 'low', 'volume', 'adjclose'] items = ['open', 'close', 'high', 'low', 'volume', 'adjclose']
if verbose: if verbose:
print "Load data" print("Load data")
for ticker in tickers: for ticker in tickers:
if verbose: if verbose:
print "\t" + ticker print("\t" + ticker)
data, dates = quotes_historical_yahoo(ticker, date1, date2) data, dates = quotes_historical_yahoo(ticker, date1, date2)
data = np.array(data).T data = np.array(data).T
qlar = la.larry(data, [items, dates]) qlar = la.larry(data, [items, dates])
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