\n")
html_file.write("
\n\n")
@@ -218,7 +218,7 @@
months=du.getMonths(funds,year)
for month in months:
html_file.write("\n")
- print >>html_file, "%.2f\n" % (mrets[i]*100)
+ print("%.2f\n" % (mrets[i]*100), file=html_file)
html_file.write("% | \n")
i+=1
html_file.write("\n")
@@ -241,7 +241,7 @@
if __name__ == '__main__':
input=open(sys.argv[1],"r")
- funds=cPickle.load(input)
+ funds=pickle.load(input)
if(len(sys.argv)>2):
input2=sys.argv[2]
--- ./Bin/sinewave_data_generator.py (original)
+++ ./Bin/sinewave_data_generator.py (refactored)
@@ -1,6 +1,6 @@
import datetime
import QSTK.qstkutil.qsdateutil
-import StringIO
+import io
import math
import random
@@ -17,12 +17,12 @@
amp = 20.0*random.random()
period = 10.0+(random.random()*100.0)
sin_gen = lambda x: (mean+(amp*math.sin(((math.pi*2)/period)*x)))
- print fname,"parameters"
- print "Mean:",mean
- print "Amplitude:",amp
- print "Period:", period
+ print(fname,"parameters")
+ print("Mean:",mean)
+ print("Amplitude:",amp)
+ print("Period:", period)
dllen = len(datelist)
- for t in xrange(dllen):
+ for t in range(dllen):
date = datelist[(dllen-1)-t]
val = sin_gen(t)
line = (date.date().isoformat(),)+((val,)*5)
@@ -30,6 +30,6 @@
#print write_to.getvalue()
write_to.close()
-for i in xrange(NUMFILES):
+for i in range(NUMFILES):
genfile("ML4T-%03d.csv"%i,START,END)
#genfile("foo.txt",datetime.datetime(2011,9,13),datetime.datetime(2012,9,13))
--- ./Examples/Validation.py (original)
+++ ./Examples/Validation.py (refactored)
@@ -14,80 +14,80 @@
# Printing what Python Version is installed : QSTK uses 2.7
import sys
import platform
-print "Python Details : "
-print sys.version
-print "Your Python Version is : ", platform.python_version()
-print "QSTK uses Python 2.7.X (2.7.3 recommended and supported)"
-print "Please make sure you're using the correct python version."
-print
+print("Python Details : ")
+print(sys.version)
+print("Your Python Version is : ", platform.python_version())
+print("QSTK uses Python 2.7.X (2.7.3 recommended and supported)")
+print("Please make sure you're using the correct python version.")
+print()
# Printing the directory you are in
import os
-print "Current Directory : ", os.path.abspath('.')
-print
+print("Current Directory : ", os.path.abspath('.'))
+print()
# Printing files in the current directory.
-print "Files in the current directory"
+print("Files in the current directory")
ls_files = os.listdir('.')
for s_file in ls_files:
- print s_file
-print
+ print(s_file)
+print()
# Testing the dependencies
# Testing numpy
try:
import numpy
- print "Numpy is installed and the version used is : ", numpy.__version__
- print "Please make sure you're using version >= 1.6.1"
+ print("Numpy is installed and the version used is : ", numpy.__version__)
+ print("Please make sure you're using version >= 1.6.1")
except ImportError:
sys.exit("Error : Numpy can not be imported or not installed.")
-print
+print()
# Testing matplotlib
try:
import matplotlib
- print "Matplotlib is installed and version is : ", matplotlib.__version__
- print "Please make sure you're using version >= 1.1.0"
+ print("Matplotlib is installed and version is : ", matplotlib.__version__)
+ print("Please make sure you're using version >= 1.1.0")
except ImportError:
sys.exit("Error : Matplotlib can not be imported or not installed.")
-print
+print()
# Testing Pandas
try:
import pandas
- print "Pandas is installed and the version used is : ", pandas.__version__
- print "Please make sure you're using version >= 0.7.3"
+ print("Pandas is installed and the version used is : ", pandas.__version__)
+ print("Please make sure you're using version >= 0.7.3")
except ImportError:
sys.exit("Error : Pandas can not be imported or not installed.")
-print
+print()
# Testing Scipy
try:
import scipy
- print "Scipy is installed and the version used is : ", scipy.__version__
- print "Please make sure you're using version >= 0.9.0"
+ print("Scipy is installed and the version used is : ", scipy.__version__)
+ print("Please make sure you're using version >= 0.9.0")
except ImportError:
sys.exit("Error : Scipy can not be imported or not installed.")
-print
+print()
# Testing Dateutil
try:
import dateutil
- print "Dateutil is installed and the version used is : ", dateutil.__version__
- print "Please make sure you're using version == 1.5"
+ print("Dateutil is installed and the version used is : ", dateutil.__version__)
+ print("Please make sure you're using version == 1.5")
except ImportError:
sys.exit("Error : Dateutil can not be imported or not installed.")
-print
+print()
# Testing Setuptools
try:
import setuptools
- print "Setuptools is installed and the version used is : ", setuptools.__version__
- print "Please make sure you're using version >= 0.6"
+ print("Setuptools is installed and the version used is : ", setuptools.__version__)
+ print("Please make sure you're using version >= 0.6")
except ImportError:
sys.exit("Error : Setuptools can not be imported or not installed.")
-print
+print()
# # Testing CVXOPT
# try:
@@ -100,40 +100,40 @@
# Testing datetime
try:
import datetime as dt
- print "datetime is installed and can be imported"
+ print("datetime is installed and can be imported")
except ImportError:
sys.exit("Error : datetime can not be imported or not installed.")
-print
+print()
# All dependencies are installed and working
-print "All dependencies are installed and working\n"
+print("All dependencies are installed and working\n")
# Testing import of QSTK
# Testing QSTK
try:
import QSTK
- print "QSTK is installed and can be imported"
+ print("QSTK is installed and can be imported")
except ImportError:
sys.exit("Error : QSTK can not be imported or not installed.")
-print
+print()
# Testing QSTK.qstkutil
try:
import QSTK.qstkutil.tsutil as tsu
import QSTK.qstkutil.qsdateutil as du
import QSTK.qstkutil.DataAccess as da
- print "QSTK.qstkutil is installed and can be imported"
+ print("QSTK.qstkutil is installed and can be imported")
except ImportError:
exit("Error : QSTK.qstkutil can not be imported.")
-print
+print()
# Testing QSTK.qstkstudy
try:
import QSTK.qstkstudy.EventProfiler
- print "QSTK.qstkstudy is installed and can be imported"
+ print("QSTK.qstkstudy is installed and can be imported")
except ImportError:
exit("Error : QSTK.qstkstudy can not be imported.")
-print
+print()
# Checking that the data installed is correct.
# Start and End date of the charts
@@ -149,29 +149,29 @@
c_dataobj = da.DataAccess('Yahoo', verbose=True)
# Reading adjusted_close prices
df_close = c_dataobj.get_data(ldt_timestamps, ls_symbols, "close")
-print df_close
-print
-print "\nCorrect Output using the Default Data should be : "
-print "Assignments use this data for grading"
-print " MSFT GOOG"
-print "2012-02-10 16:00:00 29.90 605.91"
-print "2012-02-13 16:00:00 29.98 612.20"RefactoringTool: Refactored ./Examples/Basic/numpy-tutorial.py
-print "2012-02-14 16:00:00 29.86 609.76"
-print "2012-02-15 16:00:00 29.66 605.56"
-print "2012-02-16 16:00:00 30.88 606.52"
-print "2012-02-17 16:00:00 30.84 604.64"
-print "2012-02-21 16:00:00 31.03 614.00"
-print "2012-02-22 16:00:00 30.86 607.94"
-print "2012-02-23 16:00:00 30.96 606.11"
-print
+print(df_close)
+print()
+print("\nCorrect Output using the Default Data should be : ")
+print("Assignments use this data for grading")
+print(" MSFT GOOG")
+print("2012-02-10 16:00:00 29.90 605.91")
+print("2012-02-13 16:00:00 29.98 612.20")
+print("2012-02-14 16:00:00 29.86 609.76")
+print("2012-02-15 16:00:00 29.66 605.56")
+print("2012-02-16 16:00:00 30.88 606.52")
+print("2012-02-17 16:00:00 30.84 604.64")
+print("2012-02-21 16:00:00 31.03 614.00")
+print("2012-02-22 16:00:00 30.86 607.94")
+print("2012-02-23 16:00:00 30.96 606.11")
+print()
dt_test = dt.datetime(2012, 2, 15, 16)
-print "Close price of MSFT on 2012/2/15 is : ", df_close['MSFT'].ix[dt_test]
+print("Close price of MSFT on 2012/2/15 is : ", df_close['MSFT'].ix[dt_test])
if df_close['MSFT'].ix[dt_test] == 29.66:
- print "Data looks correct as the close price in default data is 29.66"
+ print("Data looks correct as the close price in default data is 29.66")
else:
- print "Default data used in the assisgnments has close price as 29.66"
+ print("Default data used in the assisgnments has close price as 29.66")
sys.exit("Error : Data has changed so does not match data used in Assignments")
-print
+print()
-print "Everything works fine: You're all set."
+print("Everything works fine: You're all set.")
--- ./Examples/Basic/numpy-tutorial.py (original)
+++ ./Examples/Basic/numpy-tutorial.py (refactored)
@@ -35,33 +35,33 @@
#
#
## Lets get started!
-print "Importing numpy"
+print("Importing numpy")
import numpy as np
## This loads the numpy library and lets us refer to it by the shorthand "np",
## which is the convention used in the numpy documentation and in many
## online tutorials/examples
-print "Creating arrays"
+print("Creating arrays")
## Now lets make an array to play around with. You can make numpy arrays in
## a number of ways,
## Filled with zeros:
zeroArray = np.zeros( (2,3) ) # [[ 0. 0. 0.]
-print zeroArray # [ 0. 0. 0.]]
+print(zeroArray) # [ 0. 0. 0.]]
## Or ones:
oneArray = np.ones( (2,3) ) # [[ 1. 1. 1.]
-print oneArray # [ 1. 1. 1.]]
+print(oneArray) # [ 1. 1. 1.]]
## Or filled with junk:
emptyArray = np.empty( (2,3) )
-print emptyArray
+print(emptyArray)
## Note, emptyArray might look random, but it's just uninitialized which means
## you shouldn't count on it having any particular data in it, even random
## data! If you do want random data you can use random():
randomArray = np.random.random( (2,3) )
-print randomArray
+print(randomArray)
## If you're following along and trying these commands out, you should have
## noticed that making randomArray took a lot longer than emptyArray. That's
@@ -74,29 +74,29 @@
[4,5,6]]
myArray = np.array(foo) # [[1 2 3]
-print myArray # [4 5 6]]
-
-
-print "Reshaping arrays"
+print(myArray) # [4 5 6]]
+
+
+print("Reshaping arrays")
## Of course, if you're typing out a range for a larger matrix, it's easier to
## use arange(...):
rangeArray = np.arange(6,12).reshape( (2,3) ) # [[ 6 7 8]
-print rangeArray # [ 9 10 11]]
+print(rangeArray) # [ 9 10 11]]
## there's two things going on here. First, the arange(...) function returns a
## 1D array similar to what you'd get from using the built-in python function
## range(...) with the same arguments, except it returns a numpy array
## instead of a list.
-print np.arange(6,12) # [ 6 7 8 9 10 11 12]
+print(np.arange(6,12)) # [ 6 7 8 9 10 11 12]
## the reshape method takes the data in an existing array, and stuffs it into
## an array with the given shape and returns it.
-print rangeArray.reshape( (3,2) ) # [[ 6 7]
+print(rangeArray.reshape( (3,2) )) # [[ 6 7]
# [ 8 9]
# [10 11]]
#The original array doesn't change though.
-print rangeArray # [[ 6 7 8]
+print(rangeArray) # [[ 6 7 8]
# [ 9 10 11]
## When you use reshape(...) the total number of things in the array must stay
@@ -106,69 +106,69 @@
squareArray = np.arange(1,10).reshape( (3,3) ) #this is fine, 9 elements
-print "Accessing array elements"
+print("Accessing array elements")
## Accessing an array is also pretty straight forward. You access a specific
## spot in the table by referring to its row and column inside square braces
## after the array:
-print rangeArray[0,1] #7
+print(rangeArray[0,1]) #7
## Note that row and column numbers start from 0, not 1! Numpy also lets you
## refer to ranges inside an array:
-print rangeArray[0,0:2] #[6 7]
-print squareArray[0:2,0:2] #[[1 2] # the top left corner of squareArray
+print(rangeArray[0,0:2]) #[6 7]
+print(squareArray[0:2,0:2]) #[[1 2] # the top left corner of squareArray
# [4 5]]
## These ranges work just like slices and python lists. n:m:t specifies a range
## that starts at n, and stops before m, in steps of size t. If any of these
## are left off, they're assumed to be the start, the end+1, and 1 respectively
-print squareArray[:,0:3:2] #[[1 3] #skip the middle column
+print(squareArray[:,0:3:2]) #[[1 3] #skip the middle column
# [4 6]
# [7 9]]
## Also like python lists, you can assign values to specific positions, or
## ranges of values to slices
-squareArray[0,:] = np.array(range(1,4)) #set the first row to 1,2,3
+squareArray[0,:] = np.array(list(range(1,4))) #set the first row to 1,2,3
squareArray[1,1] = 0 # set the middle spot to zero
squareArray[2,:] = 1 # set the last row to ones
-print squareArray # [[1 2 3]
+print(squareArray) # [[1 2 3]
# [4 0 6]
# [1 1 1]]
## Something new to numpy arrays is indexing using an array of indices:
fibIndices = np.array( [1, 1, 2, 3] )
randomRow = np.random.random( (10,1) ) # an array of 10 random numbers
-print randomRow
-print randomRow[fibIndices] # the first, first, second and third element of
+print(randomRow)
+print(randomRow[fibIndices]) # the first, first, second and third element of
# randomRow
## You can also use an array of true/false values to index:
boolIndices = np.array( [[ True, False, True],
[False, True, False],
[ True, False, True]] )
-print squareArray[boolIndices] # a 1D array with the selected values
+print(squareArray[boolIndices]) # a 1D array with the selected values
# [1 3 0 1 1]
## It gets a little more complicated with 2D (and higher) arrays. You need
## two index arrays for a 2D array:
rows = np.array( [[0,0],[2,2]] ) #get the corners of our square array
cols = np.array( [[0,2],[0,2]] )
-print squareArray[rows,cols] #[[1 3]
+print(squareArray[rows,cols]) #[[1 3]
# [1 1]]
boolRows = np.array( [False, True, False] ) # just the middle row
boolCols = np.array( [True, False, True] ) # Not the middle column
-print squareArray[boolRows,boolCols] # [4 6]
-
-print "Operations on arrays"
+print(squareArray[boolRows,boolCols]) # [4 6]
+
+print("Operations on arrays")
## One useful trick is to create a boolean matrix based on some test and use
## that as an index in order to get the elements of a matrix that pass the
## test:
sqAverage = np.average(squareArray) # average(...) returns the average of all
# the elements in the given array
betterThanAverage = squareArray > sqAverage
-print betterThanAverage #[[False False True]RefactoringTool: Refactored ./Examples/Basic/pandas-tutorial.py
RefactoringTool: Refactored ./Examples/Basic/tutorial1.py
RefactoringTool: Refactored ./Examples/Basic/tutorial2.py
RefactoringTool: Refactored ./Examples/Basic/tutorial3.py
RefactoringTool: Refactored ./Examples/Basic/tutorial4.py
+print(betterThanAverage) #[[False False True]
# [ True False True]
# [False False False]]
-print squareArray[betterThanAverage] #[3 4 6]
+print(squareArray[betterThanAverage]) #[3 4 6]
## Indexing like this can also be used to assign values to elements of the
## array. This is particularly useful if you want to filter an array, say by
@@ -188,24 +188,24 @@
# truncate them down to integers.
clampedSqArray[ (squareArray-sqAverage) > sqStdDev ] = sqAverage+sqStdDev
clampedSqArray[ (squareArray-sqAverage) < -sqStdDev ] = sqAverage-sqStdDev
-print clampedSqArray # [[ 1. 2. 3. ]
+print(clampedSqArray) # [[ 1. 2. 3. ]
# [ 3.90272394 0.31949828 3.90272394]
# [ 1. 1. 1. ]]
## Multiplying and dividing arrays by numbers does what you'd expect. It
## multiples/divides element-wise
-print squareArray * 2 # [[ 2 4 6]
+print(squareArray * 2) # [[ 2 4 6]
# [ 8 0 12]
# [ 2 2 2]]
## Addition works similarly:
-print squareArray + np.ones( (3,3) ) #[[2 3 4]
+print(squareArray + np.ones( (3,3) )) #[[2 3 4]
# [5 1 7]
# [2 2 2]]
## Multiplying two arrays together (of the same size) is also element wise
-print squareArray * np.arange(1,10).reshape( (3,3) ) #[[ 1 4 9]
+print(squareArray * np.arange(1,10).reshape( (3,3) )) #[[ 1 4 9]
# [16 0 36]
# [ 7 8 9]]
@@ -213,7 +213,7 @@
## from linear algebra:
matA = np.array( [[1,2],[3,4]] )
matB = np.array( [[5,6],[7,8]] )
-print np.dot(matA,matB) #[[19 22]
+print(np.dot(matA,matB)) #[[19 22]
# [43 50]]
## And thats it! There's a lot more to the numpy library, and there are a few
--- ./Examples/Basic/pandas-tutorial.py (original)
+++ ./Examples/Basic/pandas-tutorial.py (refactored)
@@ -20,67 +20,67 @@
for i in range(1, 6):
ldt_timestamps.append(dt.datetime(2011, 1, i, 16))
-print "The index we created has the following dates : "
-print ldt_timestamps
-print
+print("The index we created has the following dates : ")
+print(ldt_timestamps)
+print()
## TimeSeries
ts_single_value = pd.TimeSeries(0.0, index=ldt_timestamps)
-print "A timeseries initialized to one single value : "
+print("A timeseries initialized to one single value : ")
na_vals = np.arange(len(ldt_timestamps))
-print "Dummy initialized array : "
-print na_vals
-print
+print("Dummy initialized array : ")
+print(na_vals)
+print()
ts_array = pd.TimeSeries(na_vals, index=ldt_timestamps)
-print "A timeseries initialized using a numpy array : "
-print ts_array
-print
+print("A timeseries initialized using a numpy array : ")
+print(ts_array)
+print()
-print "Reading the timeseries for a particular date"
-print "Date : ", ldt_timestamps[1]
-print "Value : ", ts_array[ldt_timestamps[1]]
-print
+print("Reading the timeseries for a particular date")
+print("Date : ", ldt_timestamps[1])
+print("Value : ", ts_array[ldt_timestamps[1]])
+print()
-print "Initializing a list of symbols : "
+print("Initializing a list of symbols : ")
ls_symbols = ['AAPL', 'GOOG', 'MSFT', 'IBM']
-print ls_symbols
-print
+print(ls_symbols)
+print()
-print "Initializing a dataframe with one value : "
+print("Initializing a dataframe with one value : ")
df_single = pd.DataFrame(index=ldt_timestamps, columns=ls_symbols)
df_single = df_single.fillna(0.0)
-print df_single
-print
+print(df_single)
+print()
-print "Initializing a dataframe with a numpy array : "
+print("Initializing a dataframe with a numpy array : ")
na_vals_2 = np.random.randn(len(ldt_timestamps), len(ls_symbols))
df_vals = pd.DataFrame(na_vals_2, index=ldt_timestamps, columns=ls_symbols)
-print df_vals
-print
+print(df_vals)
+print()
-print "Access the timeseries of a particular symbol : "
-print df_vals[ls_symbols[1]]
-print
+print("Access the timeseries of a particular symbol : ")
+print(df_vals[ls_symbols[1]])
+print()
-print "Access the timeseries of a particular date : "
-print df_vals.ix[ldt_timestamps[1]]
-print
+print("Access the timeseries of a particular date : ")
+print(df_vals.ix[ldt_timestamps[1]])
+print()
-print "Access the value for a specific symbol on a specific date: "
-print df_vals[ls_symbols[1]].ix[ldt_timestamps[1]]
-print
+print("Access the value for a specific symbol on a specific date: ")
+print(df_vals[ls_symbols[1]].ix[ldt_timestamps[1]])
+print()
-print "Reindexing the dataframe"
+print("Reindexing the dataframe")
ldt_new_dates = [dt.datetime(2011, 1, 3, 16),
dt.datetime(2011, 1, 5, 16),
dt.datetime(2011, 1, 7, 16)]
ls_new_symbols = ['AAPL', 'IBM', 'XOM']
df_new = df_vals.reindex(index=ldt_new_dates, columns=ls_new_symbols)
-print df_new
-print "Observe that reindex carried over whatever values it could find and set the rest to NAN"
-print
+print(df_new)
+print("Observe that reindex carried over whatever values it could find and set the rest to NAN")
+print()
-print "For pandas rolling statistics please refer : http://pandas.pydata.org/pandas-docs/dev/computation.html#moving-rolling-statistics-moments"
+print("For pandas rolling statistics please refer : http://pandas.pydata.org/pandas-docs/dev/computation.html#moving-rolling-statistics-moments")
--- ./Examples/Basic/tutorial1.py (original)
+++ ./Examples/Basic/tutorial1.py (refactored)
@@ -21,7 +21,7 @@
import matplotlib.pyplot as plt
import pandas as pd
-print "Pandas Version", pd.__version__
+print("Pandas Version", pd.__version__)
def main():
@@ -49,7 +49,7 @@
# Reading the data, now d_data is a dictionary with the keys above.
# Timestamps and symbols are the ones that were specified before.
ldf_data = c_dataobj.get_data(ldt_timestamps, ls_symbols, ls_keys)
- d_data = dict(zip(ls_keys, ldf_data))
+ d_data = dict(list(zip(ls_keys, ldf_data)))
# Filling the data for NAN
for s_key in ls_keys:
--- ./Examples/Basic/tutorial2.py (original)
+++ ./Examples/Basic/tutorial2.py (refactored)
@@ -33,11 +33,11 @@
ls_symbols = ['$SPX', 'XOM', 'GOOG', 'GLD']
# Printing the first 5 rows
- print "First 5 rows of Price Data:"
- print na_price[:5, :]
- print
- print "First 5 rows of Dates:"
- print na_dates[:5, :]
+ print("First 5 rows of Price Data:")
+ print(na_price[:5, :])
+ print()
+ print("First 5 rows of Dates:")
+ print(na_dates[:5, :])
# Creating the timestamps from dates read
ldt_timestamps = []
--- ./Examples/Basic/tutorial3.py (original)
+++ ./Examples/Basic/tutorial3.py (refactored)
@@ -28,11 +28,11 @@
# Reading the portfolio
na_portfolio = np.loadtxt('tutorial3portfolio.csv', dtype='S5,f4',
delimiter=',', comments="#", skiprows=1)
- print na_portfolio
+ print(na_portfolio)
# Sorting the portfolio by symbol name
na_portfolio = sorted(na_portfolio, key=lambda x: x[0])
- print na_portfolio
+ print(na_portfolio)
# Create two list for symbol names and allocation
ls_port_syms = []
@@ -48,7 +48,7 @@
ls_bad_syms = list(set(ls_port_syms) - set(ls_all_syms))
if len(ls_bad_syms) != 0:
- print "Portfolio contains bad symbols : ", ls_bad_syms
+ print("Portfolio contains bad symbols : ", ls_bad_syms)
for s_sym in ls_bad_syms:
i_index = ls_port_syms.index(s_sym)
@@ -70,7 +70,7 @@
# Reading the data, now d_data is a dictionary with the keys above.
# Timestamps and symbols are the ones that were specified before.
ldf_data = c_dataobj.get_data(ldt_timestamps, ls_port_syms, ls_keys)
- d_data = dict(zip(ls_keys, ldf_data))
+ d_data = dict(list(zip(ls_keys, ldf_data)))
# Copying close price into separate dataframe to find rets
df_rets = d_data['close'].copy()
--- ./Examples/Basic/tutorial4.py (original)
+++ ./Examples/Basic/tutorial4.py (refactored)RefactoringTool: Refactored ./Examples/Basic/tutorial5.py
RefactoringTool: No changes to ./Examples/Basic/tutorial8.py
RefactoringTool: Refactored ./Examples/DataAccess/setexample.py
RefactoringTool: Refactored ./Examples/EventProfiler/tutorial.py
RefactoringTool: Refactored ./Examples/FeatureSearch/code.py
RefactoringTool: No changes to ./Examples/FeatureSearch/functions.py
RefactoringTool: Refactored ./Examples/Features/featuretest.py
RefactoringTool: No changes to ./QSTK/__init__.py
RefactoringTool: Refactored ./QSTK/qstkfeat/__init__.py
RefactoringTool: No changes to ./QSTK/qstkfeat/classes.py
RefactoringTool: No changes to ./QSTK/qstkfeat/features.py
RefactoringTool: Refactored ./QSTK/qstkfeat/featutil.py
@@ -21,7 +21,7 @@
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
-import cPickle
+import pickle
def main():
@@ -72,7 +72,7 @@
# Create the outpul pickle file for the dataframe.
output = open('allocation.pkl', 'wb')
- cPickle.dump(df_alloc, output)
+ pickle.dump(df_alloc, output)
if __name__ == '__main__':
main()
--- ./Examples/Basic/tutorial5.py (original)
+++ ./Examples/Basic/tutorial5.py (refactored)
@@ -80,12 +80,12 @@
f_slippage=0.0005, f_minimumcommision=5.0, f_commision_share=0.0035,
i_target_leverage=1, f_rate_borrow=3.5, log="transaction.csv")
- print "Simulated Fund Time Series : "
- print ts_funds
- print "Transaction Costs : "
- print "Commissions : ", f_commission
- print "Slippage : ", f_slippage
- print "Borrowing Cost : ", f_borrow_cost
+ print("Simulated Fund Time Series : ")
+ print(ts_funds)
+ print("Transaction Costs : ")
+ print("Commissions : ", f_commission)
+ print("Slippage : ", f_slippage)
+ print("Borrowing Cost : ", f_borrow_cost)
if __name__ == '__main__':
main()
--- ./Examples/DataAccess/setexample.py (original)
+++ ./Examples/DataAccess/setexample.py (refactored)
@@ -30,11 +30,11 @@
# Getting a list of symbols from Lists
# Lists : S&P5002012, S&P5002008, Index
ls_symbols = c_dataobj.get_symbols_from_list('sp5002012')
- print "Symbols from the list : ", ls_symbols
+ print("Symbols from the list : ", ls_symbols)
# All symbols possible
ls_all_syms = c_dataobj.get_all_symbols()
- print "All symbols : ", ls_all_syms
+ print("All symbols : ", ls_all_syms)
ls_syms_toread = ['AAPL', 'GOOG']
@@ -58,7 +58,7 @@
# But a path can be provided using either an environment variable or
# as a prarameter.
df_close = c_dataobj.get_data(ldt_timestamps, ls_syms_toread, "close")
- print df_close
+ print(df_close)
if __name__ == '__main__':
--- ./Examples/EventProfiler/tutorial.py (original)
+++ ./Examples/EventProfiler/tutorial.py (refactored)
@@ -44,7 +44,7 @@
df_close = d_data['close']
ts_market = df_close['SPY']
- print "Finding Events"
+ print("Finding Events")
# Creating an empty dataframe
df_events = copy.deepcopy(df_close)
@@ -82,7 +82,7 @@
ls_keys = ['open', 'high', 'low', 'close', 'volume', 'actual_close']
ldf_data = dataobj.get_data(ldt_timestamps, ls_symbols, ls_keys)
- d_data = dict(zip(ls_keys, ldf_data))
+ d_data = dict(list(zip(ls_keys, ldf_data)))
for s_key in ls_keys:
d_data[s_key] = d_data[s_key].fillna(method='ffill')
@@ -90,7 +90,7 @@
d_data[s_key] = d_data[s_key].fillna(1.0)
df_events = find_events(ls_symbols, d_data)
- print "Creating Study"
+ print("Creating Study")
ep.eventprofiler(df_events, d_data, i_lookback=20, i_lookforward=20,
s_filename='MyEventStudy.pdf', b_market_neutral=True, b_errorbars=True,
s_market_sym='SPY')
--- ./Examples/FeatureSearch/code.py (original)
+++ ./Examples/FeatureSearch/code.py (refactored)
@@ -37,7 +37,7 @@
lsSym = list(set(lsSymTrain).union(set(lsSymTest)))
- dtStart = dt.datetime(2008,01,01)
+ dtStart = dt.datetime(2008,0o1,0o1)
dtEnd = dt.datetime(2010,12,31)
norObj = da.DataAccess('Norgate')
@@ -59,8 +59,8 @@
for temp in ldfDataTest:
temp.fillna(method="ffill").fillna(method="bfill")
- dDataTrain = dict(zip(lsKeys, ldfDataTrain))
- dDataTest = dict(zip(lsKeys, ldfDataTest))
+ dDataTrain = dict(list(zip(lsKeys, ldfDataTrain)))
+ dDataTest = dict(list(zip(lsKeys, ldfDataTest)))
''' Imported functions from qstkfeat.features, NOTE: last function is classification '''
lfcFeatures = [ featMA, featMA, featMA, featMA, featMA, featMA, \
@@ -98,9 +98,9 @@
ldfFeaturesTest = ftu.applyFeatures( dDataTest, lfcFeatures, ldArgs, '$SPX')
''' Pick Test and Training Points '''
- dtStartTrain = dt.datetime(2008,01,01)
+ dtStartTrain = dt.datetime(2008,0o1,0o1)
dtEndTrain = dt.datetime(2009,12,31)
- dtStartTest = dt.datetime(2010,01,01)
+ dtStartTest = dt.datetime(2010,0o1,0o1)
dtEndTest = dt.datetime(2010,12,31)
''' Stack all information into one Numpy array '''
@@ -113,7 +113,7 @@
ftu.normQuery( naFeatTest[:,:-1], ltWeights )
- lFeatures = range(0,len(lfcFeatures)-1)
+ lFeatures = list(range(0,len(lfcFeatures)-1))
classLabelIndex = len(lfcFeatures) - 1
funccall = sys.argv[1] + '(naFeatTrain,naFeatTest,lFeatures,classLabelIndex)'
--- ./Examples/Features/featuretest.py (original)
+++ ./Examples/Features/featuretest.py (refactored)
@@ -33,7 +33,7 @@
@summary: Takes testing and training data and computes average error over the test set
This is compared to a baseline guess which is just the average of the training set
'''
- llRange = range(5,51,5)
+ llRange = list(range(5,51,5))
lfRes = []
for lK in llRange:
@@ -70,7 +70,7 @@
#lsSym = ['XOM']
''' Get data for 2009-2010 '''
- dtStart = dt.datetime(2010,8,01)
+ dtStart = dt.datetime(2010,8,0o1)
dtEnd = dt.datetime(2010,12,31)
norObj = da.DataAccess('Yahoo')
@@ -78,7 +78,7 @@
lsKeys = ['open', 'high', 'low', 'close', 'volume']
ldfData = norObj.get_data( ldtTimestamps, lsSym, lsKeys )
- dData = dict(zip(lsKeys, ldfData))
+ dData = dict(list(zip(lsKeys, ldfData)))
''' Imported functions from qstkfeat.features, NOTE: last function is classification '''
lfcFeatures = [ featMA, featRSI, class_fut_ret ]
--- ./QSTK/qstkfeat/__init__.py (original)
+++ ./QSTK/qstkfeat/__init__.py (refactored)
@@ -1,3 +1,3 @@
-from classes import *
-from featutil import *
-from features import *
+from .classes import *
+from .featutil import *
+from .features import *
--- ./QSTK/qstkfeat/featutil.py (original)
+++ ./QSTK/qstkfeat/featutil.py (refactored)
@@ -60,7 +60,7 @@
#print dfCloseMark
#Make all data market relative, except for volume
- for sKey in dData.keys():
+ for sKey in list(dData.keys()):
# Don't calculate market relative volume, but still copy it over
if sKey == 'volume':
@@ -114,8 +114,8 @@
if 'MR' in ldArgs[i]:
if ldArgs[i]['MR'] == False:
- print 'Warning, setting MR to false will still be Market Relative',\
- 'simply do not include MR key in args'
+ print('Warning, setting MR to false will still be Market Relative',\
+ 'simply do not include MR key in args')
if sMarketRel == None:
raise AssertionError('Functions require market relative stock but sMarketRel=None')
@@ -244,7 +244,7 @@
'FEAT' == sDelNan and not math.isnan( np.sum(naStkData[i,:-1]) ):
llValidRows.append(i)
elif bShowRemoved:
- print 'Removed', sStock, naStkData[i,:]
+ print('Removed', sStock, naStkData[i,:])
naStkData = naStkData[llValidRows,:]
@@ -295,7 +295,7 @@
fRange = fFeatMax - fFeatMin
if fRange == 0:
- print 'Warning, bad query data range'
+ print('Warning, bad query data range')
fMult = 1.
fShigt = 0.
else:
@@ -430,7 +430,7 @@
lsKeys = ['open', 'high', 'low', 'close', 'volume', 'actual_close']
ldfData = norObj.get_data( ldtTimestamps, lsSym, lsKeys )
- dData = dict(zip(lsKeys, ldfData))
+ dData = dict(list(zip(lsKeys, ldfData)))
dfPrice = dData['close']
@@ -439,13 +439,13 @@
''' Generate a list of DataFrames, one for each feature, with the same index/column structure as price data '''
dtStart = dt.datetime.now()
ldfFeatures = applyFeatures( dData, [fcFeature], [dArgs], sMarketRel='$SPX' )
- print 'Runtime:', dt.datetime.now() - dtStart
+ print('Runtime:', dt.datetime.now() - dtStart)
''' Use last 3 months of index, to avoid lookback nans '''
dfPrint = ldfFeatures[0]['GOOG']RefactoringTool: Refactored ./QSTK/qstklearn/1knn.py
RefactoringTool: Refactored ./QSTK/qstklearn/fastknn.py
RefactoringTool: Refactored ./QSTK/qstklearn/gendata.py
RefactoringTool: Refactored ./QSTK/qstklearn/hmm.py
- print 'GOOG values:', dfPrint.values
- print 'GOOG Sum:', dfPrint.ix[dfPrint.notnull()].sum()
+ print('GOOG values:', dfPrint.values)
+ print('GOOG Sum:', dfPrint.ix[dfPrint.notnull()].sum())
for sSym in lsSym:
plt.subplot( 211 )
@@ -483,7 +483,7 @@
lsKeys = ['open', 'high', 'low', 'close', 'volume', 'actual_close']
ldtTimestamps = du.getNYSEdays( dtStart, dtEnd, dtTimeofday)
ldfData = daData.get_data( ldtTimestamps, lsSym, lsKeys)
- dData = dict(zip(lsKeys, ldfData))
+ dData = dict(list(zip(lsKeys, ldfData)))
'''loop through features'''
ltResults = []
@@ -497,7 +497,7 @@
'''print out result'''
for tResult in ltResults:
- print tResult[1], ':', tResult[0]
+ print(tResult[1], ':', tResult[0])
return ltResults
--- ./QSTK/qstklearn/1knn.py (original)
+++ ./QSTK/qstklearn/1knn.py (refactored)
@@ -91,7 +91,7 @@
plt.subplot(312)
- plt.plot( range( len(lfOneKnn) ), lfOneKnn )
+ plt.plot( list(range( len(lfOneKnn))), lfOneKnn )
plt.ylabel( '1-KNN Value' )
#plt.xlabel( 'Distribution Merge' )
@@ -100,7 +100,7 @@
plt.subplot(313)
- plt.plot( range( len(lf5Knn) ), lf5Knn )
+ plt.plot( list(range( len(lf5Knn))), lf5Knn )
plt.ylabel( '% Correct Classification' )
#plt.xlabel( 'Distribution Merge' )
@@ -201,8 +201,8 @@
naBoth[500:,0] = naBoth[500:,0] - .1
- print 'Runtime OneKnn:', cOneRuntime
- print 'Runtime 5-KNN:', cKnnRuntime
+ print('Runtime OneKnn:', cOneRuntime)
+ print('Runtime 5-KNN:', cKnnRuntime)
_plotResults( naTest1, naTest2, lfResults, lfKnnResults )
''' Tests performance of 1-KNN '''
--- ./QSTK/qstklearn/fastknn.py (original)
+++ ./QSTK/qstklearn/fastknn.py (refactored)
@@ -64,7 +64,7 @@
picks the first 'num_anchors' as new anchors.
"""
if selection_type == 'random':
- self.anchors = range(len(self.training_data))
+ self.anchors = list(range(len(self.training_data)))
random.shuffle(self.anchors)
self.anchors = self.anchors[0:self.num_anchors]
self.kdt = scipy.spatial.kdtree.KDTree(numpy.array(self.training_data)[self.anchors,:])
@@ -92,7 +92,7 @@
dist = self.distfun(data,self.training_data[a])
bisect.insort(self.data_by_anchors[a],(dist,new_idx))
elif len(data.shape)>1:
- for i in xrange(len(data)):
+ for i in range(len(data)):
thing = data[i]
new_idx = len(self.training_data)
self.training_data.append(thing)
@@ -138,7 +138,7 @@
neighbors = list()
maxd = None
maxd_idx = 0
- for i in xrange(0,len(anchor_list)):
+ for i in range(0,len(anchor_list)):
nextpnt_dist = self.distfun(point,self.training_data[anchor_list[i][1]])
self.num_checks += 1
nextthing = (nextpnt_dist,anchor_list[i][1])
@@ -177,10 +177,10 @@
else:
tmp = 0
class_count[clss] = tmp+1
- bleh = max(class_count.iteritems(),key=lambda item:item[1])
+ bleh = max(iter(class_count.items()),key=lambda item:item[1])
if dumdumcheck and bleh[1] == 1:
- print "aHAH!"
- print point
+ print("aHAH!")
+ print(point)
rv = bleh[0]
elif method == 'mean':
return sum([self.data_classes[n[1]] for n in neighbors])/float(k)
@@ -195,7 +195,7 @@
#first line is the name of the attributes, strip it off
bar = bar[1:]
#trim, split, and cast the data. seperator is ';'
- return [map(float,thing.strip().split(';')) for thing in bar]
+ return [list(map(float,thing.strip().split(';'))) for thing in bar]
def testwine():
wqred = dataifywine('wine/winequality-red.csv') + dataifywine('wine/winequality-white.csv')
@@ -203,14 +203,14 @@
leftout = int(len(wqred)*leftoutperc)
testing = wqred[:leftout]
training = wqred[leftout:]
- print "Training:",len(training)
- print "Testing:",len(testing)
+ print("Training:",len(training))
+ print("Testing:",len(testing))
foo = FastKNN(10)
foo.addEvidence(numpy.array([thing[:-1] for thing in training]), [thing[-1] for thing in training])
knn.addEvidence(numpy.array(training))
total = 0
correct = 0
- for x in xrange(len(testing)):
+ for x in range(len(testing)):
thing = testing[x]
guess = foo.query(numpy.array(thing[:-1]),3)
#realknn = knn.query(numpy.array([thing[:-1],]),3,method='mean')
@@ -221,15 +221,15 @@
correct += 1
total += 1
if total % 50 == 0:
- print total,'/',len(testing)
- print correct,"/",total,":",float(correct)/float(total)
- print "Average checks per query:", float(foo.num_checks)/float(total)
+ print(total,'/',len(testing))
+ print(correct,"/",total,":",float(correct)/float(total))
+ print("Average checks per query:", float(foo.num_checks)/float(total))
def testspiral():
- for leftout in xrange(1,11):
- print "Fold",leftout
+ for leftout in range(1,11):
+ print("Fold",leftout)
foo = FastKNN(10)
- for x in xrange(1,11):
+ for x in range(1,11):
if x != leftout:
somedata = open("spiral/spiralfold%d.txt" % x)
pnts = list()
@@ -256,13 +256,13 @@
if guess == pbbbt:
correct += 1
total += 1
- print correct,"/",total,":",float(correct)/float(total)
- print "Average number of checks per query:",
- print float(foo.num_checks)/float(total)
+ print(correct,"/",total,":",float(correct)/float(total))
+ print("Average number of checks per query:", end=' ')
+ print(float(foo.num_checks)/float(total))
def getflatcsv(fname):
inf = open(fname)
- return numpy.array([map(float,s.strip().split(',')) for s in inf.readlines()])
+ return numpy.array([list(map(float,s.strip().split(','))) for s in inf.readlines()])
def testgendata():
anchors = 200
@@ -276,13 +276,13 @@
data = getflatcsv(fname)
foo.addEvidence(data[:,:-1],data[:,-1])
foo.num_checks = 0
- for x in xrange(querys):
+ for x in range(querys):
pnt = numpy.array(gendata.gensingle(d,bnds,clsses))
foo.query(pnt[:-1])
if x % 50 == 0:
- print float(foo.num_checks)/float(x+1),
- print x,"/",querys
- print "Average # queries:", float(foo.num_checks)/float(querys)
+ print(float(foo.num_checks)/float(x+1), end=' ')
+ print(x,"/",querys)
+ print("Average # queries:", float(foo.num_checks)/float(querys))
--- ./QSTK/qstklearn/gendata.py (original)
+++ ./QSTK/qstklearn/gendata.py (refactored)
@@ -1,16 +1,16 @@
import random
def gendata(N,d,bounds,clsses,fname):
outf = open(fname,'w')
- for i in xrange(N):
+ for i in range(N):
pnt = [None,]*(d+1)
- for x in xrange(d):
+ for x in range(d):
pnt[x] = random.uniform(bounds[x][0],bounds[x][1])
pnt[d] = random.choice(clsses)
outf.write(", ".join(map(str,pnt))+"\n")
outf.close()
def gensingle(d,bounds,clsses):
pnt = [None,]*(d+1)
- for x in xrange(d):
+ for x in range(d):
pnt[x] = random.uniform(bounds[x][0],bounds[x][1])
pnt[d] = random.choice(clsses)
return pnt
--- ./QSTK/qstklearn/hmm.py (original)
+++ ./QSTK/qstklearn/hmm.py (refactored)
@@ -26,11 +26,11 @@
first t symbols.
"""
alpha = numpy.zeros((len(observations),numstates),dtype=elem_size)
- for x in xrange(numstates):
+ for x in range(numstates):
alpha[0][x] = stateprior[x]*emission[x][observations[0]]
- for t in xrange(1,len(observations)):
- for j in xrange(numstates):
- for i in xrange(numstates):
+ for t in range(1,len(observations)):
+ for j in range(numstates):
+ for i in range(numstates):
alpha[t][j] += alpha[t-1][i]*transition[i][j]
alpha[t][j] *= emission[j][observations[t]]
return alpha
@@ -51,11 +51,11 @@
symbols from t+1 to the end (T).
"""
beta = numpy.zeros((len(observations),numstates),dtype=elem_size)
- for s in xrange(numstates):
+ for s in range(numstates):
beta[len(observations)-1][s] = 1.
- for t in xrange(len(observations)-2,-1,-1):
- for i in xrange(numstates):
- for j in xrange(numstates):
+ for t in range(len(observations)-2,-1,-1):
+ for i in range(numstates):
+ for j in range(numstates):
beta[t][i] += transition[i][j]*emission[j][observations[t+1]]*beta[t+1][j]
return beta
@@ -72,18 +72,18 @@
if beta is None:
beta = calcbeta(transition,emission,observations,numstates,elem_size)
xi = numpy.zeros((len(observations),numstates,numstates),dtype=elem_size)RefactoringTool: Refactored ./QSTK/qstklearn/kdtknn.py
RefactoringTool: Refactored ./QSTK/qstklearn/mldiagnostics.py
RefactoringTool: Refactored ./QSTK/qstklearn/parallelknn.py
RefactoringTool: Refactored ./QSTK/qstksim/__init__.py
RefactoringTool: Refactored ./QSTK/qstksim/tradesim.py
RefactoringTool: Refactored ./QSTK/qstksim/tests/test_tradesim.py
- for t in xrange(len(observations)-1):
+ for t in range(len(observations)-1):
denom = 0.0
- for i in xrange(numstates):
- for j in xrange(numstates):
+ for i in range(numstates):
+ for j in range(numstates):
thing = 1.0
thing *= alpha[t][i]
thing *= transition[i][j]
thing *= emission[j][observations[t+1]]
thing *= beta[t+1][j]
denom += thing
- for i in xrange(numstates):
- for j in xrange(numstates):
+ for i in range(numstates):
+ for j in range(numstates):
numer = 1.0
numer *= alpha[t][i]
numer *= transition[i][j]
@@ -100,8 +100,8 @@
in state 'i' at time 't' given the full observation sequence.
"""
gamma = numpy.zeros((seqlen,numstates),dtype=elem_size)
- for t in xrange(seqlen):
- for i in xrange(numstates):
+ for t in range(seqlen):
+ for i in range(numstates):
gamma[t][i] = sum(xi[t][i])
return gamma
@@ -114,20 +114,20 @@
gamma = calcgamma(xi,len(observations),numstates,elem_size)
newprior = gamma[0]
newtrans = numpy.zeros((numstates,numstates),dtype=elem_size)
- for i in xrange(numstates):
- for j in xrange(numstates):
+ for i in range(numstates):
+ for j in range(numstates):
numer = 0.0
denom = 0.0
- for t in xrange(len(observations)-1):
+ for t in range(len(observations)-1):
numer += xi[t][i][j]
denom += gamma[t][i]
newtrans[i][j] = numer/denom
newemiss = numpy.zeros( (numstates,numsym) ,dtype=elem_size)
- for j in xrange(numstates):
- for k in xrange(numsym):
+ for j in range(numstates):
+ for k in range(numsym):
numer = 0.0
denom = 0.0
- for t in xrange(len(observations)):
+ for t in range(len(observations)):
if observations[t] == k:
numer += gamma[t][j]
denom += gamma[t][j]
@@ -219,7 +219,7 @@
processed.
"""
if len(newData.shape) == 1:
- for i in xrange(iterations):
+ for i in range(iterations):
newp,newt,newe = baumwelchstep( self.prior, \
self.transition_matrix, \
self.emission_matrix, \
@@ -236,7 +236,7 @@
self.transition_matrix = newt
self.emission_matrix = newe
else:
- for i in xrange(iterations):
+ for i in range(iterations):
for sequence in newData:
newp,newt,newe = baumwelchstep( self.prior, \
self.transition_matrix, \
--- ./QSTK/qstklearn/kdtknn.py (original)
+++ ./QSTK/qstklearn/kdtknn.py (refactored)
@@ -96,15 +96,15 @@
na_dist, na_neighbors = self.kdt.query(points,k)
- n_clsses = map(lambda rslt: map(lambda p: p[-1], self.data[rslt]), na_neighbors)
+ n_clsses = [[p[-1] for p in self.data[rslt]] for rslt in na_neighbors]
#print n_clsses
if method=='mode':
- return map(lambda x: scipy.stats.stats.mode(x)[0],n_clsses)[0]
+ return [scipy.stats.stats.mode(x)[0] for x in n_clsses][0]
elif method=='mean':
- return numpy.array(map(lambda x: numpy.mean(x),n_clsses))
+ return numpy.array([numpy.mean(x) for x in n_clsses])
elif method=='median':
- return numpy.array(map(lambda x: numpy.median(x),n_clsses))
+ return numpy.array([numpy.median(x) for x in n_clsses])
elif method=='raw':
return numpy.array(n_clsses)
elif method=='all':
@@ -112,7 +112,7 @@
def getflatcsv(fname):
inf = open(fname)
- return numpy.array([map(float,s.strip().split(',')) for s in inf.readlines()])
+ return numpy.array([list(map(float,s.strip().split(','))) for s in inf.readlines()])
def testgendata():
fname = 'test2.dat'
@@ -126,12 +126,12 @@
kdt.addEvidence(data)
kdt.rebuildKDT()
stime = time.time()
- for x in xrange(querys):
+ for x in range(querys):
pnt = numpy.array(gendata.gensingle(d,bnds,clsses))
reslt = kdt.query(numpy.array([pnt[:-1]]))
- print pnt,"->",reslt
+ print(pnt,"->",reslt)
etime = time.time()
- print etime-stime,'/',querys,'=',(etime-stime)/float(querys),'avg wallclock time per query'
+ print(etime-stime,'/',querys,'=',(etime-stime)/float(querys),'avg wallclock time per query')
#foo.addEvidence(data[:,:-1],data[:,-1])
#foo.num_checks = 0
#for x in xrange(querys):
--- ./QSTK/qstklearn/mldiagnostics.py (original)
+++ ./QSTK/qstklearn/mldiagnostics.py (refactored)
@@ -50,7 +50,7 @@
savefig(filename,format='pdf')
def runDiagnostics(self,filename):
- for i,lambdaVal in zip(range(len(self.lambdaArray)),self.lambdaArray):
+ for i,lambdaVal in zip(list(range(len(self.lambdaArray))),self.lambdaArray):
learner = copy.copy(self.learner())# is deep copy required
# setLambda needs to be a supported function for all ML strategies.
learner.setLambda(lambdaVal)
--- ./QSTK/qstklearn/parallelknn.py (original)
+++ ./QSTK/qstklearn/parallelknn.py (refactored)
@@ -90,15 +90,15 @@
temp2= np.zeros (data.shape[0])
if (allQueries.shape[1] != (data.shape[1] -1) ):
- print "ERROR: Data and query points are not of the same dimension"
+ print("ERROR: Data and query points are not of the same dimension")
raise ValueError
#if ends
if (k < 1):
- print "ERROR: K should be >= 1"
+ print("ERROR: K should be >= 1")
raise ValueError
#if ends
if (k > data.shape[0]):
- print "ERROR: K is greater than the total number of data points."
+ print("ERROR: K is greater than the total number of data points.")
raise ValueError
#if ends
@@ -151,8 +151,8 @@
try:
data= np.vstack ((data, newData))
except Exception as ex:
- print "Type of exception: "+ str(type (ex))
- print "args: " + str(ex.args)
+ print("Type of exception: "+ str(type (ex)))
+ print("args: " + str(ex.args))
#except ends
#addEvidence ends
@@ -171,11 +171,11 @@
#answer = query(a, 5, 'mean')
for i in range (0, answer.shape[0]):
- print answer[i]
+ print(answer[i])
#end for
- print "The answer is: "
+ print("The answer is: ")
if __name__ == '__main__':
main (sys.argv)
--- ./QSTK/qstksim/__init__.py (original)
+++ ./QSTK/qstksim/__init__.py (refactored)
@@ -11,4 +11,4 @@
@summary: Init for simulator code
'''
-from tradesim import _calculate_leverage, tradesim, tradesim_comb
+from .tradesim import _calculate_leverage, tradesim, tradesim_comb
--- ./QSTK/qstksim/tradesim.py (original)
+++ ./QSTK/qstksim/tradesim.py (refactored)
@@ -161,12 +161,12 @@
"""
if alloc.index[-1] > df_historic.index[-1]:
- print "Historical Data not sufficient"
+ print("Historical Data not sufficient")
indices, = np.where(alloc.index <= df_historic.index[-1])
alloc = alloc.reindex(index = alloc.index[indices])
if alloc.index[0] < df_historic.index[0]:
- print "Historical Data not sufficient"
+ print("Historical Data not sufficient")
indices, = np.where(alloc.index >= df_historic.index[0])
alloc = alloc.reindex(index = alloc.index[indices])
@@ -176,7 +176,7 @@
#write column headings
if log!="false":
- print "writing transaction log to "+log
+ print("writing transaction log to "+log)
log_file.write("Symbol,Company Name,Txn Type,Txn Date/Time, Gross Leverage, Net Leverage,# Shares,Price,Txn Value,Portfolio # Shares,Portfolio Value,Commission,Slippage(10BPS),Comments\n")
#a dollar is always worth a dollar
@@ -474,4 +474,4 @@
f_commision_share, i_target_leverage, f_rate_borrow, log, b_exposure)
if __name__ == '__main__':
- print "Done"
+ print("Done")
--- ./QSTK/qstksim/tests/test_tradesim.py (original)
+++ ./QSTK/qstksim/tests/test_tradesim.py (refactored)
@@ -81,11 +81,11 @@
qstksim.tradesim( self.df_alloc, self.df_close, 10000, 1, True, 0.02,
5, 0.02 )
- print 'Commision Costs : ' + str(f_commision)
- print 'Slippage : ' + str(f_slippage)
- print 'Short Borrowing Cost : ' + str(f_borrow)
- print 'Leverage : '
- print ts_leverageRefactoringTool: Refactored ./QSTK/qstksim/tests/test_tradesim_SPY.py
RefactoringTool: Refactored ./QSTK/qstksim/tests/test_tradesim_SPY_Short.py
RefactoringTool: Refactored ./QSTK/qstkstrat/strategies.py
RefactoringTool: Refactored ./QSTK/qstkstudy/EventProfiler.py
RefactoringTool: Refactored ./QSTK/qstkstudy/Events.py
RefactoringTool: Refactored ./QSTK/qstkstudy/study.py
RefactoringTool: Refactored ./QSTK/qstktest/testDataAccess.py
+ print('Commision Costs : ' + str(f_commision))
+ print('Slippage : ' + str(f_slippage))
+ print('Short Borrowing Cost : ' + str(f_borrow))
+ print('Leverage : ')
+ print(ts_leverage)
np.testing.assert_approx_equal(df_funds[-1], \
10000 * self.i_open_result, significant = 3)
self.assertTrue(True)
--- ./QSTK/qstksim/tests/test_tradesim_SPY.py (original)
+++ ./QSTK/qstksim/tests/test_tradesim_SPY.py (refactored)
@@ -71,11 +71,11 @@
qstksim.tradesim( self.df_alloc, self.df_close, 10000, 1, True, 0.02,
5, 0.02)
- print 'Commision Costs : ' + str(f_commision)
- print 'Slippage : ' + str(f_slippage)
- print 'Short Borrowing Cost : ' + str(f_borrow)
- print 'Leverage : '
- print ts_leverage
+ print('Commision Costs : ' + str(f_commision))
+ print('Slippage : ' + str(f_slippage))
+ print('Short Borrowing Cost : ' + str(f_borrow))
+ print('Leverage : ')
+ print(ts_leverage)
np.testing.assert_approx_equal(df_funds[-1], \
10000 * self.i_open_result, significant = 3)
self.assertTrue(True)
--- ./QSTK/qstksim/tests/test_tradesim_SPY_Short.py (original)
+++ ./QSTK/qstksim/tests/test_tradesim_SPY_Short.py (refactored)
@@ -71,11 +71,11 @@
qstksim.tradesim( self.df_alloc, self.df_close, 10000, 1, True,
0.02, 5, 0.02)
- print 'Commision Costs : ' + str(f_commision)
- print 'Slippage : ' + str(f_slippage)
- print 'Short Borrowing Cost : ' + str(f_borrow)
- print 'Leverage : '
- print ts_leverage
+ print('Commision Costs : ' + str(f_commision))
+ print('Slippage : ' + str(f_slippage))
+ print('Short Borrowing Cost : ' + str(f_borrow))
+ print('Leverage : ')
+ print(ts_leverage)
np.testing.assert_approx_equal(df_funds[-1], \
10000 * self.i_open_result, significant = 3)
self.assertTrue(True)
--- ./QSTK/qstkstrat/strategies.py (original)
+++ ./QSTK/qstkstrat/strategies.py (refactored)
@@ -32,12 +32,12 @@
@param dFuncArgs: Dict of function args passed to the function
@return DataFrame corresponding to the portfolio allocations
"""
- if not dFuncArgs.has_key('dmPrice'):
- print 'Error: Strategy requires dmPrice information'
- return
-
- if not dFuncArgs.has_key('lfWeights'):
- print 'Error: Strategy requires weight information'
+ if 'dmPrice' not in dFuncArgs:
+ print('Error: Strategy requires dmPrice information')
+ return
+
+ if 'lfWeights' not in dFuncArgs:
+ print('Error: Strategy requires weight information')
return
dmPrice = dFuncArgs['dmPrice']
@@ -60,8 +60,8 @@
@param dFuncArgs: Dict of function args passed to the function
@return DataFrame corresponding to the portfolio allocations
"""
- if not dFuncArgs.has_key('dmPrice'):
- print 'Error: Strategy requires dmPrice information'
+ if 'dmPrice' not in dFuncArgs:
+ print('Error: Strategy requires dmPrice information')
return
dmPrice = dFuncArgs['dmPrice']
@@ -85,24 +85,24 @@
@param dFuncArgs: Dict of function args passed to the function
@return DataFrame corresponding to the portfolio allocations
"""
- if not dFuncArgs.has_key('dmPrice'):
- print 'Error:', stratMark.__name__, 'requires dmPrice information'
- return
-
- if not dFuncArgs.has_key('sPeriod'):
- print 'Error:', stratMark.__name__, 'requires rebalancing period'
- return
-
- if not dFuncArgs.has_key('lLookback'):
- print 'Error:', stratMark.__name__, 'requires lookback'
- return
-
- if not dFuncArgs.has_key('sMarkPoint'):
- print 'Error:', stratMark.__name__, 'requires markowitz point to choose'
+ if 'dmPrice' not in dFuncArgs:
+ print('Error:', stratMark.__name__, 'requires dmPrice information')
+ return
+
+ if 'sPeriod' not in dFuncArgs:
+ print('Error:', stratMark.__name__, 'requires rebalancing period')
+ return
+
+ if 'lLookback' not in dFuncArgs:
+ print('Error:', stratMark.__name__, 'requires lookback')
+ return
+
+ if 'sMarkPoint' not in dFuncArgs:
+ print('Error:', stratMark.__name__, 'requires markowitz point to choose')
return
''' Optional variables '''
- if not dFuncArgs.has_key('bAddAlpha'):
+ if 'bAddAlpha' not in dFuncArgs:
bAddAlpha = False
else:
bAddAlpha = dFuncArgs['bAddAlpha']
@@ -121,7 +121,7 @@
dtStart = dtDate - pand.DateOffset(days=lLookback)
if( dtStart < dmPrice.index[0] ):
- print 'Error, not enough data to rebalance'
+ print('Error, not enough data to rebalance')
continue
naRets = dmPrice.ix[ dtStart:dtDate ].values.copy()
@@ -184,7 +184,7 @@
lInd = 0
else:
- print 'Warning: invalid sMarkPoint'''
+ print('Warning: invalid sMarkPoint''')
return
--- ./QSTK/qstkstudy/EventProfiler.py (original)
+++ ./QSTK/qstkstudy/EventProfiler.py (refactored)
@@ -67,7 +67,7 @@
# Study Params
na_mean = np.mean(na_event_rets, axis=0)
na_std = np.std(na_event_rets, axis=0)
- li_time = range(-i_lookback, i_lookforward + 1)
+ li_time = list(range(-i_lookback, i_lookforward + 1))
# Plotting the chart
plt.clf()
--- ./QSTK/qstkstudy/Events.py (original)
+++ ./QSTK/qstkstudy/Events.py (refactored)
@@ -43,10 +43,10 @@
window = 10
if verbose:
- print __name__ + " reading data"
+ print(__name__ + " reading data")
close = d_data[closefield]
if verbose:
- print __name__ + " finding events"
+ print(__name__ + " finding events")
for symbol in symbols:
close[symbol][close[symbol]>= 1.0] = np.NAN
for i in range(1,len(close[symbol])):
--- ./QSTK/qstkstudy/study.py (original)
+++ ./QSTK/qstkstudy/study.py (refactored)
@@ -16,7 +16,7 @@
dataobj = da.DataAccess('Yahoo')
ls_keys = ['open', 'high', 'low', 'close', 'volume', 'actual_close']
ldf_data = dataobj.get_data(ldt_timestamps, ls_symbols, ls_keys)
- d_data = dict(zip(ls_keys, ldf_data))
+ d_data = dict(list(zip(ls_keys, ldf_data)))
eventMatrix = ev.find_events(ls_symbols,d_data,verbose=True)
ep.eventprofiler(eventMatrix, d_data,
--- ./QSTK/qstktest/testDataAccess.py (original)
+++ ./QSTK/qstktest/testDataAccess.py (refactored)
@@ -14,7 +14,7 @@
import QSTK.qstkutil.DataAccess as da
import tables as pt
import numpy as np
-from itertools import izip
+
import time
import dircache
@@ -22,7 +22,7 @@
listOfStocks=list()
#Path does not exist
- print "Reading in all stock names..."
+ print("Reading in all stock names...")
fileExtensionToRemove=".h5"
for path in listOfPaths:
@@ -30,9 +30,9 @@
stocksAtThisPath= dircache.listdir(str(path))
#Next, throw away everything that is not a .h5 And these are our stocks!
- stocksAtThisPath = filter (lambda x:(str(x).find(str(fileExtensionToRemove)) > -1), stocksAtThisPath)
+ stocksAtThisPath = [x for x in stocksAtThisPath if (str(x).find(str(fileExtensionToRemove)) > -1)]
#Now, we remove the .h5 to get the name of the stock
- stocksAtThisPath = map(lambda x:(x.partition(str(fileExtensionToRemove))[0]),stocksAtThisPath)
+ stocksAtThisPath = [(x.partition(str(fileExtensionToRemove))[0]) for x in stocksAtThisPath]
for stock in stocksAtThisPath:
listOfStocks.append(stock)
@@ -44,7 +44,7 @@
if __name__ == '__main__':
- print "Starting..."
+ print("Starting...")
dataItemsList=[]
dataItemsList.append('alphaValue')
@@ -100,7 +100,7 @@
alphaList= alpha.getStockDataList(stock, 'volume')RefactoringTool: Refactored ./QSTK/qstktest/testLearner.py
RefactoringTool: Refactored ./QSTK/qstktools/YahooDataPull.py
RefactoringTool: Refactored ./QSTK/qstktools/csv2fund.py
RefactoringTool: Refactored ./QSTK/qstktools/report.py
RefactoringTool: Refactored ./QSTK/qstkutil/DataAccess.py
ctr=0
for val in alphaList:
- print "stock: " + str(stock) + ", val: "+str(val) + ", ts: " + str(listOfTS[ctr])
+ print("stock: " + str(stock) + ", val: "+str(val) + ", ts: " + str(listOfTS[ctr]))
ctr+=1
- print "DONE!"
+ print("DONE!")
--- ./QSTK/qstktest/testLearner.py (original)
+++ ./QSTK/qstktest/testLearner.py (refactored)
@@ -132,13 +132,13 @@
#
# Compare to ground truth
#
- print 'trainsize ' + str(trainsize)
+ print('trainsize ' + str(trainsize))
Ytruth = Y[-trainsize:]
- print 'Ytruth.shape ' + str(Ytruth.shape)
+ print('Ytruth.shape ' + str(Ytruth.shape))
Xtest = dataX[-trainsize:,:]
- print 'Xtest.shape ' + str(Xtest.shape)
+ print('Xtest.shape ' + str(Xtest.shape))
Ytest = learner.query(Xtest) # to check every point
- print 'Ytest.shape ' + str(Ytest.shape)
+ print('Ytest.shape ' + str(Ytest.shape))
plt.clf()
plt.scatter(Ytruth,Ytest,edgecolors='none')
@@ -148,7 +148,7 @@
plt.ylabel('Estimated')
savefig("scatterdata.png", format='png')
- print corrcoef(Ytruth,Ytest)
+ print(corrcoef(Ytruth,Ytest))
if __name__ == '__main__':
main()
--- ./QSTK/qstktools/YahooDataPull.py (original)
+++ ./QSTK/qstktools/YahooDataPull.py (refactored)
@@ -2,8 +2,8 @@
Pulling Yahoo CSV Data
'''
-import urllib2
-import urllib
+import urllib.request, urllib.error, urllib.parse
+import urllib.request, urllib.parse, urllib.error
import datetime
import os
import QSTK.qstkutil.DataAccess as da
@@ -35,9 +35,9 @@
# print "Getting {0}".format(symbol)
try:
- params = urllib.urlencode ({'a':0, 'b':1, 'c':2000, 'd':_now.month-1, 'e':_now.day, 'f':_now.year, 's': symbol})
+ params = urllib.parse.urlencode ({'a':0, 'b':1, 'c':2000, 'd':_now.month-1, 'e':_now.day, 'f':_now.year, 's': symbol})
url = "http://ichart.finance.yahoo.com/table.csv?%s" % params
- url_get = urllib2.urlopen(url)
+ url_get = urllib.request.urlopen(url)
header = url_get.readline()
symbol_data.append (url_get.readline())
@@ -58,16 +58,16 @@
f.close()
- except urllib2.HTTPError:
+ except urllib.error.HTTPError:
miss_ctr += 1
ls_missed_syms.append(symbol_name)
- print "Unable to fetch data for stock: {0} at {1}".format(symbol_name, url)
- except urllib2.URLError:
+ print("Unable to fetch data for stock: {0} at {1}".format(symbol_name, url))
+ except urllib.error.URLError:
miss_ctr += 1
ls_missed_syms.append(symbol_name)
- print "URL Error for stock: {0} at {1}".format(symbol_name, url)
+ print("URL Error for stock: {0} at {1}".format(symbol_name, url))
- print "All done. Got {0} stocks. Could not get {1}".format(len(ls_symbols) - miss_ctr, miss_ctr)
+ print("All done. Got {0} stocks. Could not get {1}".format(len(ls_symbols) - miss_ctr, miss_ctr))
return ls_missed_syms
--- ./QSTK/qstktools/csv2fund.py (original)
+++ ./QSTK/qstktools/csv2fund.py (refactored)
@@ -78,7 +78,7 @@
#first pass
reader=csv.reader(open(filename,'rU'), delimiter=',')
- reader.next()
+ next(reader)
prev=0
first=1
diffs=[]
@@ -256,7 +256,7 @@
@return commissions : value of slippage over the csv time
"""
reader=csv.reader(open(filename,'rU'), delimiter=',')
- reader.next()
+ next(reader)
symbols=[]
dates=[]
for row in reader:
@@ -265,9 +265,9 @@
symbols.append(row[0])
if not(dp.parse(row[3]) in dates):
dates.append(dp.parse(row[3]))
- print symbols
+ print(symbols)
reader=csv.reader(open(filename,'rU'), delimiter=',')
- reader.next()
+ next(reader)
if not("_CASH" in symbols):
symbols.append("_CASH")
vals=numpy.zeros([len(dates),len(symbols)])
@@ -309,7 +309,7 @@
column_index = sorted(share_table.columns)
share_table = share_table.reindex(index=time_index, columns=column_index)
i_start_cash = share_table["_CASH"].ix[0]
- print i_start_cash
+ print(i_start_cash)
return [share_table, commissions, i_start_cash]
# def ofx2fund(filename, start_val):
@@ -408,14 +408,14 @@
if __name__ == "__main__":
filename = "Strat.csv"
plot_name = "Strategy"
- print "load csv"
+ print("load csv")
[share_table, commissions, i_start_cash] = csv2fund(filename)
- print share_table
+ print(share_table)
[fund_ts, ts_leverage] = share_table2fund(share_table)
- print "print report"
- print fund_ts
+ print("print report")
+ print(fund_ts)
report.print_stats(fund_ts, ["SPY"], plot_name, directory="./" + plot_name, commissions=commissions, i_start_cash=i_start_cash)
- print "analyze transactions"
+ print("analyze transactions")
#Generate new plot based off transactions alone
analyze_transactions(filename, plot_name, share_table, True)
- print "done"
+ print("done")
--- ./QSTK/qstktools/report.py (original)
+++ ./QSTK/qstktools/report.py (refactored)
@@ -26,7 +26,7 @@
from matplotlib import pyplot
from matplotlib import gridspec
import matplotlib.dates as mdates
-import cPickle
+import pickle
import datetime as dt
import pandas
import numpy as np
@@ -433,7 +433,7 @@
splot_dir = path.join(directory, splot)
ostream = open(sfile, "wb")
ostream.write("")
- print "writing to ", sfile
+ print("writing to ", sfile)
if type(original)==type("str"):
if type(leverage)!=type(False):
@@ -706,7 +706,7 @@
splot = "plot-%s.png" % name
splot_dir = path.join(directory, splot)
ostream = open(sfile, "wb")
- print "writing to ", sfile
+ print("writing to ", sfile)
if type(original)==type("str"):
if type(leverage)!=type(False):
@@ -842,8 +842,8 @@
lf_vals.append(get_annual_return(benchmark_close[bench_sym], years))
ls_labels.append(bench_sym)
- print lf_vals
- print ls_labels
+ print(lf_vals)
+ print(ls_labels)
ls_year_labels=[]
for i in range(0,len(years)):
ls_year_labels.append(str(years[i]))
@@ -915,7 +915,7 @@
def print_bar_chart(llf_vals, ls_fund_labels, ls_year_labels, s_filename):
llf_vals=((1,2,3),(3,2,1),(2,2,2))
amin=min(min(llf_vals))
- print amin
+ print(amin)
min_lim=0
if amin<0:
min_lim = amin
@@ -1167,7 +1167,7 @@
if(ROBUST == 1):
ANINPUT = open(sys.argv[2],"r")
- FUNDS = cPickle.load(ANINPUT)
+ FUNDS = pickle.load(ANINPUT)
generate_robust_report(FUNDS, FILENAME)
else:
FILES = sys.argv
@@ -1175,7 +1175,7 @@
FUNDS = []
for AFILE in FILES:
ANINPUT = open(AFILE,"r")
- FUND = cPickle.load(ANINPUT)
+ FUND = pickle.load(ANINPUT)
FUNDS.append(FUND)
generate_report(FUNDS, FILES, FILENAME)
--- ./QSTK/qstkutil/DataAccess.py (original)
+++ ./QSTK/qstkutil/DataAccess.py (refactored)
@@ -93,11 +93,11 @@
self.scratchdir = os.path.join(tempfile.gettempdir(), 'QSScratch')
if verbose:
- print "Scratch Directory: ", self.scratchdir
- print "Data Directory: ", self.rootdir
+ print("Scratch Directory: ", self.scratchdir)
+ print("Data Directory: ", self.rootdir)
if not os.path.isdir(self.rootdir):
- print "Data path provided is invalid"
+ print("Data path provided is invalid")
raise
if not os.path.exists(self.scratchdir):
@@ -245,7 +245,7 @@
if bIncDelist:
lsDelPaths = self.getPathOfFile( symbol, True )
if file_path == None and len(lsDelPaths) > 0:
- print 'Found delisted paths:', lsDelPaths
+ print('Found delisted paths:', lsDelPaths)
''' If we don't have a file path continue... unless we have delisted paths '''
if (type (file_path) != type ("random string")):
@@ -256,7 +256,7 @@
_file = open(file_path, "rb")
except IOError:
# If unable to read then continue. The value for this stock will be nan
- print _file
+ print(_file)
continue;
assert( not _file == None or bIncDelist == True )
@@ -264,8 +264,8 @@
if _file != None:
if (self.source==DataSource.CUSTOM) or (self.source==DataSource.YAHOO)or (self.source==DataSource.MLT):
creader = csv.reader(_file)
- row=creader.next()
- row=creader.next()
+ row=next(creader)
+ row=next(creader)
#row.pop(0)
for i, item in enumerate(row):
if i==0:
@@ -315,7 +315,7 @@
#now remove all the columns except the timestamps and one data column
if verbose:
- print self.getPathOfFile(symbol)
+ print(self.getPathOfFile(symbol))
''' Fix 1 row case by reshaping '''
if( naData.ndim == 1 ):
@@ -337,7 +337,7 @@
num_rows= temp_np.shape[0]
- symbol_ts_list = range(num_rows) # preallocate
+ symbol_ts_list = list(range(num_rows)) # preallocate
for i in range (0, num_rows):
timebase = temp_np[i][0]
@@ -460,7 +460,7 @@
# final complete filename
cachefilename = self.scratchdir + '/' + hashstr + '.pkl'
if verbose:
- print "cachefilename is: " + cachefilename
+ print("cachefilename is: " + cachefilename)
# now eather read the pkl file, or do a hardread
readfile = False # indicate that we have not yet read the file
@@ -476,7 +476,7 @@
if os.path.exists(cachefilename):
if ((dt.datetime.now() - dt.datetime.fromtimestamp(os.path.getmtime(cachefilename))) < cachestall):
if verbose:
- print "cache hit"
+ print("cache hit")
try:
cachefile = open(cachefilename, "rb")
start = time.time() # start timer
@@ -486,36 +486,36 @@
cachefile.close()
except IOError:
if verbose:
- print "error reading cache: " + cachefilename
- print "recovering..."
+ print("error reading cache: " + cachefilename)
+ print("recovering...")
except EOFError:
if verbose:
- print "error reading cache: " + cachefilename
- print "recovering..."
+ print("error reading cache: " + cachefilename)
+ print("recovering...")
if (readfile!=True):
if verbose:
- print "cache miss"
- print "beginning hardread"
+ print("cache miss")
+ print("beginning hardread")
start = time.time() # start timer
if verbose:
- print "data_item(s): " + str(data_item)
- print "symbols to read: " + str(symbol_list)
+ print("data_item(s): " + str(data_item))
+ print("symbols to read: " + str(symbol_list))
retval = self.get_data_hardread(ts_list,
symbol_list, data_item, verbose, bIncDelist)
elapsed = time.time() - start # end timer
if verbose:
- print "end hardread"
- print "saving to cache"
+ print("end hardread")
+ print("saving to cache")
try:
cachefile = open(cachefilename,"wb")
pkl.dump(retval, cachefile, -1)
- os.chmod(cachefilename,0666)
+ os.chmod(cachefilename,0o666)
except IOError:
- print "error writing cache: " + cachefilename
+ print("error writing cache: " + cachefilename)
if verbose:
- print "end saving to cache"
+ print("end saving to cache")
if verbose:
- print "reading took " + str(elapsed) + " seconds"
+ print("reading took " + str(elapsed) + " seconds")
if type(retval) == type([]):
for i, df_single in enumerate(retval):
@@ -555,7 +555,7 @@
lsPaths.sort()
return lsPaths
- print "Did not find path to " + str(symbol_name) + ". Looks like this file is missing"
+ print("Did not find path to " + str(symbol_name) + ". Looks like this file is missing")
def getPathOfCSVFile(self, symbol_name):
@@ -565,7 +565,7 @@
return (str(str(path1)+str(symbol_name)+".csv"))
#if ends
#for ends
- print "Did not find path to " + str (symbol_name)+". Looks like this file is missing"
+ print("Did not find path to " + str (symbol_name)+". Looks like this file is missing")
def get_all_symbols (self):
'''
@@ -584,9 +584,9 @@
#print str(path)
stocksAtThisPath = dircache.listdir(str(path))
#Next, throw away everything that is not a .pkl And these are our stocks!
- stocksAtThisPath = filter (lambda x:(str(x).find(str(self.fileExtensionToRemove)) > -1), stocksAtThisPath)
+ stocksAtThisPath = [x for x in stocksAtThisPath if (str(x).find(str(self.fileExtensionToRemove)) > -1)]
#Now, we remove the .pkl to get the name of the stock
- stocksAtThisPath = map(lambda x:(x.partition(str(self.fileExtensionToRemove))[0]),stocksAtThisPath)
+ stocksAtThisPath = [(x.partition(str(self.fileExtensionToRemove))[0]) for x in stocksAtThisPath]
listOfStocks.extend(stocksAtThisPath)
#for stock in stocksAtThisPath:
@@ -645,11 +645,11 @@
#Next, throw away everything that is not a .pkl And these are our stocks!
try:
- stocksAtThisPath = filter (lambda x:(str(x).find(str(self.fileExtensionToRemove)) > -1), stocksAtThisPath)
+ stocksAtThisPath = [x for x in stocksAtThisPath if (str(x).find(str(self.fileExtensionToRemove)) > -1)]
#Now, we remove the .pkl to get the name of the stock
- stocksAtThisPath = map(lambda x:(x.partition(str(self.fileExtensionToRemove))[0]),stocksAtThisPath)
+ stocksAtThisPath = [(x.partition(str(self.fileExtensionToRemove))[0]) for x in stocksAtThisPath]
except:
- print "error: no path to " + subdir
+ print("error: no path to " + subdir)
stocksAtThisPath = list()
return stocksAtThisPath
@@ -671,7 +671,7 @@
'''
if (self.source != DataSource.COMPUSTAT):
- print 'Function only valid for Compustat objects!'
+ print('Function only valid for Compustat objects!')
return []
return DataItem.COMPUSTAT
@@ -725,7 +725,7 @@
else:
retstr = "DataAccess internal error\n"
- print retstr
+ print(retstr)
return retstr
#get_sublists
@@ -737,18 +737,18 @@
# Check if GOOG is a valid symbol.
val = c_dataobj.check_symbol('GOOG')
- print "Is GOOG a valid symbol? :" , val
+ print("Is GOOG a valid symbol? :" , val)
# Check if QWERTY is a valid symbol.
val = c_dataobj.check_symbol('QWERTY')
- print "Is QWERTY a valid symbol? :" , val
+ print("Is QWERTY a valid symbol? :" , val)
# Check if EBAY is part of SP5002012 list.
val = c_dataobj.check_symbol('EBAY', s_list='sp5002012')
- print "Is EBAY a valid symbol in SP5002012 list? :", val
+ print("Is EBAY a valid symbol in SP5002012 list? :", val)
# Check if GLD is part of SP5002012 after checking if GLD is a valid symbol.RefactoringTool: No changes to ./QSTK/qstkutil/fundutil.py
RefactoringTool: Refactored ./QSTK/qstkutil/qsdateutil.py
RefactoringTool: Refactored ./QSTK/qstkutil/tsutil.py
RefactoringTool: No changes to ./QSTK/qstkutil/utils.py
RefactoringTool: No changes to ./QSTK/qstkutil/tests/test_utils.py
RefactoringTool: Files that were modified:
RefactoringTool: ./ez_setup.py
RefactoringTool: ./setup.py
RefactoringTool: ./Bin/DataGenerate_SineWave.py
RefactoringTool: ./Bin/Data_CSV.py
RefactoringTool: ./Bin/converter.py
RefactoringTool: ./Bin/csvformatter.py
RefactoringTool: ./Bin/gen_nyse_dates.py
RefactoringTool: ./Bin/investors_report.py
RefactoringTool: ./Bin/sinewave_data_generator.py
RefactoringTool: ./Examples/Validation.py
RefactoringTool: ./Examples/Basic/numpy-tutorial.py
RefactoringTool: ./Examples/Basic/pandas-tutorial.py
RefactoringTool: ./Examples/Basic/tutorial1.py
RefactoringTool: ./Examples/Basic/tutorial2.py
RefactoringTool: ./Examples/Basic/tutorial3.py
RefactoringTool: ./Examples/Basic/tutorial4.py
RefactoringTool: ./Examples/Basic/tutorial5.py
RefactoringTool: ./Examples/Basic/tutorial8.py
RefactoringTool: ./Examples/DataAccess/setexample.py
RefactoringTool: ./Examples/EventProfiler/tutorial.py
RefactoringTool: ./Examples/FeatureSearch/code.py
RefactoringTool: ./Examples/FeatureSearch/functions.py
RefactoringTool: ./Examples/Features/featuretest.py
RefactoringTool: ./QSTK/__init__.py
RefactoringTool: ./QSTK/qstkfeat/__init__.py
RefactoringTool: ./QSTK/qstkfeat/classes.py
RefactoringTool: ./QSTK/qstkfeat/features.py
RefactoringTool: ./QSTK/qstkfeat/featutil.py
RefactoringTool: ./QSTK/qstklearn/1knn.py
RefactoringTool: ./QSTK/qstklearn/fastknn.py
RefactoringTool: ./QSTK/qstklearn/gendata.py
RefactoringTool: ./QSTK/qstklearn/hmm.py
RefactoringTool: ./QSTK/qstklearn/kdtknn.py
RefactoringTool: ./QSTK/qstklearn/mldiagnostics.py
RefactoringTool: ./QSTK/qstklearn/parallelknn.py
RefactoringTool: ./QSTK/qstksim/__init__.py
RefactoringTool: ./QSTK/qstksim/tradesim.py
RefactoringTool: ./QSTK/qstksim/tests/test_tradesim.py
RefactoringTool: ./QSTK/qstksim/tests/test_tradesim_SPY.py
RefactoringTool: ./QSTK/qstksim/tests/test_tradesim_SPY_Short.py
RefactoringTool: ./QSTK/qstkstrat/strategies.py
RefactoringTool: ./QSTK/qstkstudy/EventProfiler.py
RefactoringTool: ./QSTK/qstkstudy/Events.py
RefactoringTool: ./QSTK/qstkstudy/study.py
RefactoringTool: ./QSTK/qstktest/testDataAccess.py
RefactoringTool: ./QSTK/qstktest/testLearner.py
RefactoringTool: ./QSTK/qstktools/YahooDataPull.py
RefactoringTool: ./QSTK/qstktools/csv2fund.py
RefactoringTool: ./QSTK/qstktools/report.py
RefactoringTool: ./QSTK/qstkutil/DataAccess.py
RefactoringTool: ./QSTK/qstkutil/fundutil.py
RefactoringTool: ./QSTK/qstkutil/qsdateutil.py
RefactoringTool: ./QSTK/qstkutil/tsutil.py
RefactoringTool: ./QSTK/qstkutil/utils.py
RefactoringTool: ./QSTK/qstkutil/tests/test_utils.py
RefactoringTool: Warnings/messages while refactoring:
RefactoringTool: ### In file ./QSTK/qstklearn/fastknn.py ###
RefactoringTool: Line 12: absolute and local imports together
RefactoringTool: ### In file ./QSTK/qstklearn/kdtknn.py ###
RefactoringTool: Line 12: absolute and local imports together
val = c_dataobj.check_symbol('GLD')
- print "Is GLD a valid symbol? : ", val
+ print("Is GLD a valid symbol? : ", val)
val = c_dataobj.check_symbol('GLD', 'sp5002012')
- print "Is GLD a valid symbol in sp5002012 list? :", val
+ print("Is GLD a valid symbol in sp5002012 list? :", val)
--- ./QSTK/qstkutil/qsdateutil.py (original)
+++ ./QSTK/qstkutil/qsdateutil.py (refactored)
@@ -27,7 +27,7 @@
# filename = os.environ['QS'] + "/qstkutil/NYSE_dates.txt"
filename = os.path.join(os.path.dirname(__file__), 'NYSE_dates.txt')
except KeyError:
- print "Please be sure you have NYSE_dates.txt in the qstkutil directory"
+ print("Please be sure you have NYSE_dates.txt in the qstkutil directory")
datestxt = np.loadtxt(filename, dtype=str)
dates = []
@@ -172,8 +172,8 @@
# filename = os.environ['QS'] + "/qstkutil/NYSE_dates.txt"
filename = os.path.join(os.path.dirname(__file__), 'NYSE_dates.txt')
except KeyError:
- print "Please be sure to set the value for QS in config.sh or\n"
- print "in local.sh and then \'source local.sh\'.\n"
+ print("Please be sure to set the value for QS in config.sh or\n")
+ print("in local.sh and then \'source local.sh\'.\n")
datestxt = np.loadtxt(filename,dtype=str)
dates=[]
@@ -198,8 +198,8 @@
# filename = os.environ['QS'] + "/qstkutil/NYSE_dates.txt"
filename = os.path.join(os.path.dirname(__file__), 'NYSE_dates.txt')
except KeyError:
- print "Please be sure to set the value for QS in config.sh or\n"
- print "in local.sh and then \'source local.sh\'.\n"
+ print("Please be sure to set the value for QS in config.sh or\n")
+ print("in local.sh and then \'source local.sh\'.\n")
datestxt = np.loadtxt(filename,dtype=str)
@@ -263,7 +263,7 @@
dr_range = pd.DateRange(dt_start, dt_end,
timeRule=s_period[1:])
dr_range = np.asarray(dr_range)
- li_even = np.array(range(len(dr_range)))
+ li_even = np.array(list(range(len(dr_range))))
dr_range = dr_range[li_even[li_even % 2 == 0]]
else:
dr_range = pd.DateRange(dt_start, dt_end,
--- ./QSTK/qstkutil/tsutil.py (original)
+++ ./QSTK/qstkutil/tsutil.py (refactored)
@@ -324,8 +324,8 @@
pass
import nagint as nag
except ImportError:
- print 'Could not import NAG library'
- print 'make sure nagint.so is in your python path'
+ print('Could not import NAG library')
+ print('make sure nagint.so is in your python path')
return ([], 0, 0)
# Get number of stocks """
@@ -367,7 +367,7 @@
naReturn = nag.optPort( naConstraints, naLower, naUpper, \
naCov, naInitial, lNagDebug )
except RuntimeError:
- print 'NAG Runtime error with target: %.02lf'%(f_target)
+ print('NAG Runtime error with target: %.02lf'%(f_target))
return ( naInitial, sqrt( naCov[0][0] ) )
#return semi-junk to not mess up the rest of the plot
@@ -402,7 +402,7 @@
from cvxopt.solvers import qp, options
except ImportError:
- print 'Could not import CVX library'
+ print('Could not import CVX library')
raise
''' Get number of stocks '''
@@ -481,7 +481,7 @@
(fMin, fMax) = getRetRange(False, naLower, naUpper, naExpected, "long")
#print (fTarget, fMin, fMax)
if fTargetfMax:
- print "Target not possible", fTarget, fMin, fMax
+ print("Target not possible", fTarget, fMin, fMax)
b_error = True
naLower = naLower*(-1)
@@ -519,7 +519,7 @@
b_error = True
if b_error == True:
- print "Optimization not Possible"
+ print("Optimization not Possible")
na_port = naLower*-1
if sum(na_port) < 1:
if sum(naUpper) == 1:
@@ -765,7 +765,7 @@
for sStock in dmPrice.columns:
fValid = 0.0
- print sStock
+ print(sStock)
# loop through all dates """
for dtDate in dmPrice.index:
# Count null (nan/inf/etc) values """
@@ -830,7 +830,7 @@
lsRetStocks = []
# Loop until we have enough randomly selected stocks """
- llRemainingIndexes = range(0,len(lsStocks))
+ llRemainingIndexes = list(range(0,len(lsStocks)))
lsValid = None
while( len(lsRetStocks) != lNum ):
@@ -838,7 +838,7 @@
for i in range( lNum - len(lsRetStocks) ):
lRemaining = len(llRemainingIndexes)
if( lRemaining == 0 ):
- print 'Error in getRandPort: ran out of stocks'
+ print('Error in getRandPort: ran out of stocks')
return lsRetStocks
# Pick a stock and remove it from the list of remaining stocks """
+ RPM_EC=0
++ jobs -p
+ exit 0
Executing(%build): /bin/sh -e /home/iurt/rpmbuild/tmp/rpm-tmp.i7VfMO
+ umask 022
+ cd /home/iurt/rpmbuild/BUILD
+ cd QSTK-0.2.8
+ '[' 1 -eq 1 ']'
+ '[' 1 -eq 1 ']'
+ CFLAGS='-O2 -g -pipe -Wformat -Werror=format-security -Wp,-D_FORTIFY_SOURCE=2 -fstack-protector --param=ssp-buffer-size=4 -fasynchronous-unwind-tables'
+ LDFLAGS=' -Wl,--as-needed -Wl,--no-undefined -Wl,-z,relro -Wl,-O1 -Wl,--build-id -Wl,--enable-new-dtags'
+ /usr/bin/python3 setup.py build '--executable=/usr/bin/python3 -s'
running build
running build_py
creating build
creating build/lib
creating build/lib/Bin
copying Bin/sinewave_data_generator.py -> build/lib/Bin
copying Bin/converter.py -> build/lib/Bin
copying Bin/Data_CSV.py -> build/lib/Bin
copying Bin/gen_nyse_dates.py -> build/lib/Bin
copying Bin/__init__.py -> build/lib/Bin
copying Bin/DataGenerate_SineWave.py -> build/lib/Bin
copying Bin/csvformatter.py -> build/lib/Bin
copying Bin/investors_report.py -> build/lib/Bin
creating build/lib/QSTK
copying QSTK/__init__.py -> build/lib/QSTK
creating build/lib/QSTK/qstksim
copying QSTK/qstksim/tradesim.py -> build/lib/QSTK/qstksim
copying QSTK/qstksim/__init__.py -> build/lib/QSTK/qstksim
creating build/lib/QSTK/qstktest
copying QSTK/qstktest/testDataAccess.py -> build/lib/QSTK/qstktest
copying QSTK/qstktest/__init__.py -> build/lib/QSTK/qstktest
copying QSTK/qstktest/testLearner.py -> build/lib/QSTK/qstktest
creating build/lib/QSTK/qstktools
copying QSTK/qstktools/report.py -> build/lib/QSTK/qstktools
copying QSTK/qstktools/csv2fund.py -> build/lib/QSTK/qstktools
copying QSTK/qstktools/YahooDataPull.py -> build/lib/QSTK/qstktools
copying QSTK/qstktools/__init__.py -> build/lib/QSTK/qstktools
creating build/lib/QSTK/qstkfeat
copying QSTK/qstkfeat/classes.py -> build/lib/QSTK/qstkfeat
copying QSTK/qstkfeat/features.py -> build/lib/QSTK/qstkfeat
copying QSTK/qstkfeat/__init__.py -> build/lib/QSTK/qstkfeat
copying QSTK/qstkfeat/featutil.py -> build/lib/QSTK/qstkfeat
creating build/lib/QSTK/qstkutil
copying QSTK/qstkutil/DataAccess.py -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/fundutil.py -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/utils.py -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/__init__.py -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/qsdateutil.py -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/tsutil.py -> build/lib/QSTK/qstkutil
creating build/lib/QSTK/qstklearn
copying QSTK/qstklearn/gendata.py -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/hmm.py -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/parallelknn.py -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/kdtknn.py -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/__init__.py -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/mldiagnostics.py -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/fastknn.py -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/1knn.py -> build/lib/QSTK/qstklearn
creating build/lib/QSTK/qstkstrat
copying QSTK/qstkstrat/__init__.py -> build/lib/QSTK/qstkstrat
copying QSTK/qstkstrat/strategies.py -> build/lib/QSTK/qstkstrat
creating build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/EventProfiler.py -> build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/study.py -> build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/Events.py -> build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/__init__.py -> build/lib/QSTK/qstkstudy
creating build/lib/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim_SPY_Short.py -> build/lib/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim_SPY.py -> build/lib/QSTK/qstksim/tests
copying QSTK/qstksim/tests/__init__.py -> build/lib/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim.py -> build/lib/QSTK/qstksim/tests
creating build/lib/QSTK/qstkutil/tests
copying QSTK/qstkutil/tests/__init__.py -> build/lib/QSTK/qstkutil/tests
copying QSTK/qstkutil/tests/test_utils.py -> build/lib/QSTK/qstkutil/tests
running egg_info
creating QSTK.egg-info
writing QSTK.egg-info/PKG-INFO
writing dependency_links to QSTK.egg-info/dependency_links.txt
writing namespace_packages to QSTK.egg-info/namespace_packages.txt
writing requirements to QSTK.egg-info/requires.txt
writing top-level names to QSTK.egg-info/top_level.txt
writing manifest file 'QSTK.egg-info/SOURCES.txt'
reading manifest file 'QSTK.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*' under directory 'bin'
warning: manifest_maker: MANIFEST.in, line 8: 'recursive-include' expects ...
warning: manifest_maker: MANIFEST.in, line 9: 'recursive-include' expects ...
warning: no files found matching '*' under directory 'QSData'
warning: no files found matching 'QSTK/QSData/Yahoo/*.csv''
writing manifest file 'QSTK.egg-info/SOURCES.txt'
copying QSTK/__init__.pyc -> build/lib/QSTK
creating build/lib/QSTK/QSData
creating build/lib/QSTK/QSData/Yahoo
creating build/lib/QSTK/QSData/Yahoo/Lists
copying QSTK/QSData/Yahoo/Lists/index.txt -> build/lib/QSTK/QSData/Yahoo/Lists
copying QSTK/QSData/Yahoo/Lists/sp5002008.txt -> build/lib/QSTK/QSData/Yahoo/Lists
copying QSTK/QSData/Yahoo/Lists/sp5002012.txt -> build/lib/QSTK/QSData/Yahoo/Lists
copying QSTK/qstksim/__init__.py.bak -> build/lib/QSTK/qstksim
copying QSTK/qstksim/tradesim.py.bak -> build/lib/QSTK/qstksim
copying QSTK/qstktest/data-classification-prob.csv -> build/lib/QSTK/qstktest
copying QSTK/qstktest/data-ripple-prob.csv -> build/lib/QSTK/qstktest
copying QSTK/qstktest/testDataAccess.py.bak -> build/lib/QSTK/qstktest
copying QSTK/qstktest/testLearner.py.bak -> build/lib/QSTK/qstktest
copying QSTK/qstktools/YahooDataPull.py.bak -> build/lib/QSTK/qstktools
copying QSTK/qstktools/csv2fund.py.bak -> build/lib/QSTK/qstktools
copying QSTK/qstktools/report.py.bak -> build/lib/QSTK/qstktools
copying QSTK/qstkfeat/__init__.py.bak -> build/lib/QSTK/qstkfeat
copying QSTK/qstkfeat/featutil.py.bak -> build/lib/QSTK/qstkfeat
copying QSTK/qstkutil/DataAccess.py.bak -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/NYSE_dates.txt -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/graph.png -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/qsdateutil.py.bak -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/report.html -> build/lib/QSTK/qstkutil
copying QSTK/qstkutil/tsutil.py.bak -> build/lib/QSTK/qstkutil
copying QSTK/qstklearn/1knn.py.bak -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/fastknn.py.bak -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/gendata.py.bak -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/hmm.py.bak -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/kdtknn.py.bak -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/mldiagnostics.py.bak -> build/lib/QSTK/qstklearn
copying QSTK/qstklearn/parallelknn.py.bak -> build/lib/QSTK/qstklearn
copying QSTK/qstkstrat/strategies.py.bak -> build/lib/QSTK/qstkstrat
copying QSTK/qstkstudy/EventProfiler.py.bak -> build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/Events.py.bak -> build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/sp500.txt -> build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/study.py.bak -> build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/symbol-set1.txt -> build/lib/QSTK/qstkstudy
copying QSTK/qstkstudy/symbol-set2.txt -> build/lib/QSTK/qstkstudy
copying QSTK/qstksim/tests/test_tradesim.py.bak -> build/lib/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim_SPY.py.bak -> build/lib/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim_SPY_Short.py.bak -> build/lib/QSTK/qstksim/tests
+ RPM_EC=0
++ jobs -p
+ exit 0
Executing(%install): /bin/sh -e /home/iurt/rpmbuild/tmp/rpm-tmp.QCTKbR
+ umask 022
+ cd /home/iurt/rpmbuild/BUILD
+ '[' 1 -eq 1 ']'
+ '[' /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64 '!=' / ']'
+ rm -rf /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64
++ dirname /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64
+ mkdir -p /home/iurt/rpmbuild/BUILDROOT
+ mkdir /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64
+ cd QSTK-0.2.8
+ '[' 1 -eq 1 ']'
+ /usr/bin/python3 setup.py install --skip-build --root /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64
running install
running install_lib
copying Bin/sinewave_data_generator.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin
copying Bin/converter.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin
copying Bin/Data_CSV.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin
copying Bin/gen_nyse_dates.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin
copying Bin/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin
copying Bin/DataGenerate_SineWave.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin
copying Bin/csvformatter.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin
copying Bin/investors_report.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin
Skipping installation of /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/__init__.py (namespace package)
Skipping installation of /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/__init__.pyc (namespace package)
copying QSTK/qstksim/tradesim.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim
copying QSTK/qstksim/tradesim.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim
copying QSTK/qstksim/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim
copying QSTK/qstksim/__init__.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim
copying QSTK/qstksim/tests/test_tradesim_SPY_Short.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim_SPY.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim_SPY.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim_SPY_Short.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests
copying QSTK/qstksim/tests/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests
copying QSTK/qstksim/tests/test_tradesim.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests
copying QSTK/qstktest/testDataAccess.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest
copying QSTK/qstktest/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest
copying QSTK/qstktest/data-ripple-prob.csv -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest
copying QSTK/qstktest/testLearner.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest
copying QSTK/qstktest/testLearner.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest
copying QSTK/qstktest/data-classification-prob.csv -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest
copying QSTK/qstktest/testDataAccess.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest
copying QSTK/qstktools/report.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools
copying QSTK/qstktools/csv2fund.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools
copying QSTK/qstktools/YahooDataPull.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools
copying QSTK/qstktools/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools
copying QSTK/qstktools/csv2fund.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools
copying QSTK/qstktools/report.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools
copying QSTK/qstktools/YahooDataPull.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools
copying QSTK/qstkfeat/classes.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat
copying QSTK/qstkfeat/features.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat
copying QSTK/qstkfeat/featutil.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat
copying QSTK/qstkfeat/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat
copying QSTK/qstkfeat/__init__.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat
copying QSTK/qstkfeat/featutil.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat
copying QSTK/qstkutil/DataAccess.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/NYSE_dates.txt -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/fundutil.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/DataAccess.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/utils.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/report.html -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/tsutil.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/qsdateutil.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/tsutil.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/qsdateutil.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/graph.png -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil
copying QSTK/qstkutil/tests/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/tests
copying QSTK/qstkutil/tests/test_utils.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/tests
copying QSTK/qstklearn/gendata.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/kdtknn.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/hmm.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/hmm.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/parallelknn.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/parallelknn.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/fastknn.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/kdtknn.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/gendata.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/mldiagnostics.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/fastknn.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/mldiagnostics.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/1knn.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/qstklearn/1knn.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn
copying QSTK/QSData/Yahoo/Lists/sp5002012.txt -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/QSData/Yahoo/Lists
copying QSTK/QSData/Yahoo/Lists/sp5002008.txt -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/QSData/Yahoo/Lists
copying QSTK/QSData/Yahoo/Lists/index.txt -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/QSData/Yahoo/Lists
copying QSTK/qstkstrat/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstrat
copying QSTK/qstkstrat/strategies.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstrat
copying QSTK/qstkstrat/strategies.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstrat
copying QSTK/qstkstudy/study.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/EventProfiler.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/symbol-set2.txt -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/sp500.txt -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/study.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/Events.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/symbol-set1.txt -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/__init__.py -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/EventProfiler.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
copying QSTK/qstkstudy/Events.py.bak -> /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin/sinewave_data_generator.py to sinewave_data_generator.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin/converter.py to converter.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin/Data_CSV.py to Data_CSV.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin/gen_nyse_dates.py to gen_nyse_dates.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin/DataGenerate_SineWave.py to DataGenerate_SineWave.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin/csvformatter.py to csvformatter.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/Bin/investors_report.py to investors_report.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tradesim.py to tradesim.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests/test_tradesim_SPY_Short.py to test_tradesim_SPY_Short.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests/test_tradesim_SPY.py to test_tradesim_SPY.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstksim/tests/test_tradesim.py to test_tradesim.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest/testDataAccess.py to testDataAccess.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktest/testLearner.py to testLearner.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools/report.py to report.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools/csv2fund.py to csv2fund.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools/YahooDataPull.py to YahooDataPull.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstktools/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat/classes.py to classes.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat/features.py to features.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkfeat/featutil.py to featutil.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/DataAccess.py to DataAccess.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/fundutil.py to fundutil.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/utils.py to utils.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/qsdateutil.py to qsdateutil.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/tsutil.py to tsutil.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/tests/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkutil/tests/test_utils.py to test_utils.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn/gendata.py to gendata.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn/hmm.py to hmm.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn/parallelknn.py to parallelknn.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn/kdtknn.py to kdtknn.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn/mldiagnostics.py to mldiagnostics.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn/fastknn.py to fastknn.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstklearn/1knn.py to 1knn.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstrat/__init__.py to __init__.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstrat/strategies.py to strategies.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy/EventProfiler.py to EventProfiler.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy/study.py to study.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy/Events.py to Events.cpython-38.pyc
byte-compiling /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK/qstkstudy/__init__.py to __init__.cpython-38.pyc
running install_egg_info
running egg_info
writing QSTK.egg-info/PKG-INFO
writing dependency_links to QSTK.egg-info/dependency_links.txt
writing namespace_packages to QSTK.egg-info/namespace_packages.txt
writing requirements to QSTK.egg-info/requires.txt
writing top-level names to QSTK.egg-info/top_level.txt
reading manifest file 'QSTK.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*' under directory 'bin'
warning: manifest_maker: MANIFEST.in, line 8: 'recursive-include' expects ...
warning: manifest_maker: MANIFEST.in, line 9: 'recursive-include' expects ...
warning: no files found matching '*' under directory 'QSData'
warning: no files found matching 'QSTK/QSData/Yahoo/*.csv''
writing manifest file 'QSTK.egg-info/SOURCES.txt'
Copying QSTK.egg-info to /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK-0.2.8-py3.8.egg-info
Installing /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8/site-packages/QSTK-0.2.8-py3.8-nspkg.pth
running install_scripts
+ mv /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64//usr/lib/python3.8/site-packages/Bin /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64//usr/lib/python3.8/site-packages/QSTK
+ /usr/lib/rpm/find-debuginfo.sh -j96 --strict-build-id -m -i --build-id-seed 0.2.8-11.mga8 --unique-debug-suffix -0.2.8-11.mga8.x86_64 --unique-debug-src-base python-qstk-0.2.8-11.mga8.x86_64 --run-dwz --dwz-low-mem-die-limit 10000000 --dwz-max-die-limit 110000000 -S debugsourcefiles.list /home/iurt/rpmbuild/BUILD/QSTK-0.2.8
+ /usr/lib/rpm/check-buildroot
+ '[' -n '' ']'
+ /usr/share/spec-helper/clean_files
+ '[' -n '' ']'
+ /usr/share/spec-helper/compress_files .xz
+ '[' -n '' ']'
+ /usr/share/spec-helper/relink_symlinks
+ '[' -n '' ']'
+ /usr/share/spec-helper/clean_perl
+ '[' -n '' ']'
+ /usr/share/spec-helper/lib_symlinks
+ '[' -n '' ']'
+ /usr/share/spec-helper/gprintify
+ '[' -n '' ']'
+ /usr/share/spec-helper/fix_mo
+ '[' -n '' ']'
+ /usr/share/spec-helper/fix_pamd
+ '[' -n '' ']'
+ /usr/share/spec-helper/remove_info_dir
+ '[' -n '' ']'
+ /usr/share/spec-helper/fix_eol
+ '[' -n '' ']'
+ /usr/share/spec-helper/check_desktop_files
+ '[' -n '' ']'
+ /usr/share/spec-helper/check_elf_files
+ /usr/lib/rpm/brp-python-bytecompile /usr/bin/python3 1 1
Bytecompiling .py files below /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/lib/python3.8 using /usr/bin/python3.8
+ /usr/lib/rpm/brp-python-hardlink
+ /usr/lib/rpm/redhat/brp-mangle-shebangs
Processing files: python3-qstk-0.2.8-11.mga8.noarch
Executing(%doc): /bin/sh -e /home/iurt/rpmbuild/tmp/rpm-tmp.Dk1vmN
+ umask 022
+ cd /home/iurt/rpmbuild/BUILD
+ cd QSTK-0.2.8
+ DOCDIR=/home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/share/doc/python3-qstk
+ export LC_ALL=C
+ LC_ALL=C
+ export DOCDIR
+ /usr/bin/mkdir -p /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/share/doc/python3-qstk
+ cp -pr docs/README.md /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/share/doc/python3-qstk
+ cp -pr README.md /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/share/doc/python3-qstk
+ cp -pr LICENSE.txt /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64/usr/share/doc/python3-qstk
+ RPM_EC=0
++ jobs -p
+ exit 0
warning: File listed twice: /usr/share/doc/python3-qstk/README.md
Provides: python-qstk = 0.2.8-11.mga8 python3-qstk = 0.2.8-11.mga8 python3.8-qstk = 0.2.8-11.mga8 python3.8dist(qstk) = 0.2.8 python3dist(qstk) = 0.2.8
Requires(rpmlib): rpmlib(CompressedFileNames) <= 3.0.4-1 rpmlib(FileDigests) <= 4.6.0-1 rpmlib(PartialHardlinkSets) <= 4.0.4-1 rpmlib(PayloadFilesHavePrefix) <= 4.0-1
Requires: python(abi) = 3.8 python3.8dist(matplotlib) >= 1.1 python3.8dist(numpy) >= 1.6.1 python3.8dist(pandas) >= 0.7.3 python3.8dist(python-dateutil) >= 1.5 python3.8dist(scikit-learn) >= 0.11 python3.8dist(scipy) >= 0.9
Checking for unpackaged file(s): /usr/lib/rpm/check-files /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64
Wrote: /home/iurt/rpmbuild/RPMS/noarch/python3-qstk-0.2.8-11.mga8.noarch.rpm
Executing(%clean): /bin/sh -e /home/iurt/rpmbuild/tmp/rpm-tmp.DoCaIQ
+ umask 022
+ cd /home/iurt/rpmbuild/BUILD
+ cd QSTK-0.2.8
+ /usr/bin/rm -rf /home/iurt/rpmbuild/BUILDROOT/python-qstk-0.2.8-11.mga8.x86_64
+ RPM_EC=0
++ jobs -p
+ exit 0
Executing(--clean): /bin/sh -e /home/iurt/rpmbuild/tmp/rpm-tmp.X3v0JR
+ umask 022
+ cd /home/iurt/rpmbuild/BUILD
+ rm -rf QSTK-0.2.8
+ RPM_EC=0
++ jobs -p
+ exit 0
D: [iurt_root_command] Success!