One more problem that.....................
The C runtime Update(KB2999226) in Python 3.6.1 installation is taking very much time to complete , what can I do? Please help!!! -- https://mail.python.org/mailman/listinfo/python-list
Thread getting stuck\hang
Hi Team, I have python code that creates thread.Sometimes it works, sometimes it gets stuck once its finish its execution part. still not yet cannot find any difference between when it works or when it gets stuck. Please help. sniffer1 = threading.Thread(target=validate_traffic_stats_dy,args=(FT_item_dy,RT_item_dy,forward_path_list_dy,return_path_list_dy,nat_type_list_dy,pkt_dy_1,)) sniffer2 = threading.Thread(target=validate_traffic_stats_st,args=(FT_item_st,RT_item_st,forward_path_list_st,return_path_list_st,nat_type_list_st,pkt_st,)) sniffer1.start() sniffer2.start() sniffer3 = threading.Thread(target=delete_new_dynamic_nat_conf) sniffer3.start() sniffer1.join() sniffer2.join() sniffer3.join() Thanks, Iranna m -- https://mail.python.org/mailman/listinfo/python-list
Re: Thread getting stuck\hang
Hi Dennis,
all function arguments declare as global and pass it to the function.
All three thread is completed the execution part and after completion of
execution its stuck/hang the programme.
*def
validate_traffic_stats_st(FT_item,RT_item,forward_path_list,return_path_list,nat_type_list,pkt_st)*
:
global flag1
flag1 = 1
log.info('Starting Static NAT forward Traffic Test...')
returndict = itgen_explorer.startTrafficFlows(testbeddict,
log,'-traffic_items {0} -pktcount {1} -profile
{2}'.format(FT_item,pkt_st,itgenProfile))
time.sleep(5)
global_stats_list = []
temp = 0
forward_ip_list = []
return_ip_list = []
global count_st_Rx,count_st_in_Rx,count_st_out_Rx
count_st_Rx = 0
count_st_in_Rx = 0
count_st_out_Rx = 0
for data in returndict['txrxstats']['rx'].keys():
if "TI01" in data:
count_st_Rx += int(returndict['txrxstats']['rx'][data] )
count_st_in_Rx += int(returndict['txrxstats']['rx'][data] )
elif "TI22" in data:
count_st_Rx += int(returndict['txrxstats']['rx'][data] )
count_st_out_Rx += int(returndict['txrxstats']['rx'][data] )
global count_st_Tx,count_st_in_Tx,count_st_out_Tx
count_st_Tx = 0
count_st_in_Tx = 0
count_st_out_Tx = 0
for data in returndict['txrxstats']['tx'].keys():
if "TI01" in data:
count_st_Tx += int(returndict['txrxstats']['tx'][data] )
count_st_in_Tx += int(returndict['txrxstats']['tx'][data] )
elif "TI22" in data:
count_st_Tx += int(returndict['txrxstats']['tx'][data] )
count_st_out_Tx += int(returndict['txrxstats']['tx'][data] )
for forward_ip_list,return_ip_list,nat_type in zip
(forward_path_list,return_path_list,nat_type_list):
global_stats_list = []
for translation_ip,return_ip in zip
(forward_ip_list,return_ip_list):
output=listtostr(returndict['txrxstats']['rx'])
if re.search('{0}'.format(translation_ip),output,re.I):
pass
else:
global_stats_list.append(translation_ip)
if global_stats_list == []:
log.info('itgen traffic validation for {0} forward path -
verified'.format(nat_type))
forward_ip_list = []
return_ip_list = []
else:
log.error('{0} forward path itgen verification
failed'.format(nat_type))
flag1 = 0
return flag1
log.info("Trafiic validation for NAT return path starting")
returndict = itgen_explorer.startTrafficFlows(testbeddict,
log,'-traffic_items {0} -pktcount 1000 -profile
{1}'.format(RT_item,itgenProfile))
time.sleep(5)
local_stats_list = []
for forward_ip_list,return_ip_list,nat_type in zip
(forward_path_list,return_path_list,nat_type_list):
local_stats_list = []
for translation_ip,return_ip in zip
(forward_ip_list,return_ip_list):
output=listtostr(returndict['txrxstats']['rx'])
if re.search('{0}'.format(return_ip),output,re.I):
pass
else:
local_stats_list.append(return_ip)
if local_stats_list == []:
log.info('itgen traffic validation for {0} return path -
verified'.format(nat_type))
forward_ip_list = []
return_ip_list = []
else:
log.error('{0} return path itgen verification
failed'.format(nat_type))
flag1 = 0
return flag1
return
flag1,count_st_Rx,count_st_in_Rx,count_st_out_Rx,count_st_Tx,count_st_in_Tx,count_st_out_Tx
*def
validate_traffic_stats_dy(FT_item,RT_item,forward_path_list,return_path_list,nat_type_list,pkt_dy_1):*
global flag2
flag2 = 1
log.info('Starting Dynamic NAT forward Traffic Test...')
returndict = itgen_explorer.startTrafficFlows(testbeddict,
log,'-traffic_items {0} -pktcount {1} -profile
{2}'.format(FT_item,pkt_dy_1,itgenProfile))
time.sleep(5)
global_stats_list = []
forward_ip_list = []
return_ip_list = []
global count_dy_Rx,count_dy_in_Rx,count_dy_out_Rx
count_dy_Rx = 0
count_dy_in_Rx = 0
count_dy_out_Rx = 0
for data in returndict['txrxstats']['rx'].keys():
if "TI05" in data:
count_dy_Rx += int(returndict['txrxstats']['rx'][data] )
count_dy_in_Rx += int(returndict['txrxstats']['rx'][data] )
elif "TI66" in data:
count_dy_Rx += int(returndict['txrxstats']['rx'][data] )
count_dy_out_Rx += int(returndict['txrxstats']['rx'][data] )
global count_dy_Tx,count_dy_in_Tx,count_dy_out_Tx
count_dy_Tx = 0
count_dy_in_Tx = 0
count_dy_out_Tx = 0
for data in returndict['txrxstats']['tx'].keys():
if "TI05" in data:
count_dy_Tx += int(returndict['txrxstats']['tx'][data] )
count_dy_in_Tx += int(returndict['txrxstats']['tx'][data] )
elif "TI66" in data:
count_dy_Tx += int(returndict['txrxstats']['tx
ValueError: Input contains NaN, infinity or a value too large for dtype('float32')
Source Code:
clean_train_reviews=[]
for review in train["review"]:
clean_train_reviews.append(review_to_wordlist(review,
remove_stopwords=True))
trainDataVecs=getAvgFeatureVecs(clean_train_reviews, model, num_features)
print "Creating average feature vecs for test reviews"
clean_test_reviews=[]
for review in test["review"]:
clean_test_reviews.append(review_to_wordlist(review,remove_stopwords=True))
testDataVecs=getAvgFeatureVecs(clean_test_reviews, model, num_features)
forest = RandomForestClassifier(n_estimators = 100)
forest = forest.fit(trainDataVecs, train["sentiment"])
result = forest.predict(testDataVecs)
output = pd.DataFrame(data={"id":test["id"], "sentiment":result})
output.to_csv("Word2Vec_AverageVectors.csv", index=False, quoting=3)
Error Message:
Traceback (most recent call last):
File "/test_IMDB_W2V_RF.py", line 224, in
result = forest.predict(testDataVecs)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
534, in predict
proba = self.predict_proba(X)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
573, in predict_proba
X = self._validate_X_predict(X)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
355, in _validate_X_predict
return self.estimators_[0]._validate_X_predict(X, check_input=True)
File "/.local/lib/python2.7/site-packages/sklearn/tree/tree.py", line 365, in
_validate_X_predict
X = check_array(X, dtype=DTYPE, accept_sparse="csr")
File "/.local/lib/python2.7/site-packages/sklearn/utils/validation.py", line
407, in check_array
_assert_all_finite(array)
File "/.local/lib/python2.7/site-packages/sklearn/utils/validation.py", line
58, in _assert_all_finite
" or a value too large for %r." % X.dtype)
ValueError: Input contains NaN, infinity or a value too large for
dtype('float32').
Process finished with exit code 1
Description :
Can any one help with the error message.
--
https://mail.python.org/mailman/listinfo/python-list
Re: ValueError: Input contains NaN, infinity or a value too large for dtype('float32')
On 27/04/17 18:39, Siva Kumar S wrote:
Source Code:
clean_train_reviews=[]
for review in train["review"]:
clean_train_reviews.append(review_to_wordlist(review,
remove_stopwords=True))
trainDataVecs=getAvgFeatureVecs(clean_train_reviews, model, num_features)
print "Creating average feature vecs for test reviews"
clean_test_reviews=[]
for review in test["review"]:
clean_test_reviews.append(review_to_wordlist(review,remove_stopwords=True))
testDataVecs=getAvgFeatureVecs(clean_test_reviews, model, num_features)
forest = RandomForestClassifier(n_estimators = 100)
forest = forest.fit(trainDataVecs, train["sentiment"])
result = forest.predict(testDataVecs)
output = pd.DataFrame(data={"id":test["id"], "sentiment":result})
output.to_csv("Word2Vec_AverageVectors.csv", index=False, quoting=3)
Error Message:
Traceback (most recent call last):
File "/test_IMDB_W2V_RF.py", line 224, in
result = forest.predict(testDataVecs)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
534, in predict
proba = self.predict_proba(X)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
573, in predict_proba
X = self._validate_X_predict(X)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
355, in _validate_X_predict
return self.estimators_[0]._validate_X_predict(X, check_input=True)
File "/.local/lib/python2.7/site-packages/sklearn/tree/tree.py", line 365, in
_validate_X_predict
X = check_array(X, dtype=DTYPE, accept_sparse="csr")
File "/.local/lib/python2.7/site-packages/sklearn/utils/validation.py", line
407, in check_array
_assert_all_finite(array)
File "/.local/lib/python2.7/site-packages/sklearn/utils/validation.py", line
58, in _assert_all_finite
" or a value too large for %r." % X.dtype)
ValueError: Input contains NaN, infinity or a value too large for
dtype('float32').
Process finished with exit code 1
Description :
Can any one help with the error message.
It means exactly what it says. One of the values in your testDataVecs
(I assume) is not a number, infinite or too big for a 32-bit IEEE float
to represent. You may be using the sklearn package incorrectly; you'll
have to read the (apparently quite prolific) documentation yourself,
I've never used it.
--
Rhodri James *-* Kynesim Ltd
--
https://mail.python.org/mailman/listinfo/python-list
Re: ValueError: Input contains NaN, infinity or a value too large for dtype('float32')
On 4/27/2017 1:39 PM, Siva Kumar S wrote:
Source Code:
clean_train_reviews=[]
for review in train["review"]:
clean_train_reviews.append(review_to_wordlist(review,
remove_stopwords=True))
trainDataVecs=getAvgFeatureVecs(clean_train_reviews, model, num_features)
print "Creating average feature vecs for test reviews"
clean_test_reviews=[]
for review in test["review"]:
clean_test_reviews.append(review_to_wordlist(review,remove_stopwords=True))
testDataVecs=getAvgFeatureVecs(clean_test_reviews, model, num_features)
forest = RandomForestClassifier(n_estimators = 100)
forest = forest.fit(trainDataVecs, train["sentiment"])
result = forest.predict(testDataVecs)
output = pd.DataFrame(data={"id":test["id"], "sentiment":result})
output.to_csv("Word2Vec_AverageVectors.csv", index=False, quoting=3)
Error Message:
Traceback (most recent call last):
File "/test_IMDB_W2V_RF.py", line 224, in
result = forest.predict(testDataVecs)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
534, in predict
proba = self.predict_proba(X)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
573, in predict_proba
X = self._validate_X_predict(X)
File "/.local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line
355, in _validate_X_predict
return self.estimators_[0]._validate_X_predict(X, check_input=True)
File "/.local/lib/python2.7/site-packages/sklearn/tree/tree.py", line 365,
in _validate_X_predict
X = check_array(X, dtype=DTYPE, accept_sparse="csr")
File "/.local/lib/python2.7/site-packages/sklearn/utils/validation.py", line
407, in check_array
_assert_all_finite(array)
File "/.local/lib/python2.7/site-packages/sklearn/utils/validation.py", line
58, in _assert_all_finite
" or a value too large for %r." % X.dtype)
ValueError: Input contains NaN, infinity or a value too large for
dtype('float32').
Process finished with exit code 1
Description :
Can any one help with the error message.
What part of the error message do you need help with?
--
Terry Jan Reedy
--
https://mail.python.org/mailman/listinfo/python-list
Re: Array column separations for beginners
Thanks a lot, it helped me. I have new question..maybe very easy but I am trying to search on web and I have no clue. I have array(table) with 3 rows - x, y, y. I would like to plot graph with double y axis from that table. Should I use twinxs? or does exist easier way? Thanks! -- https://mail.python.org/mailman/listinfo/python-list
Re: Array column separations for beginners
On Thursday, April 27, 2017 at 8:10:33 PM UTC+1, katari...@gmail.com wrote: > Thanks a lot, it helped me. > > I have new question..maybe very easy but I am trying to search on web and I > have no clue. > I have array(table) with 3 rows - x, y, y. I would like to plot graph with > double y axis from that table. Should I use twinxs? or does exist easier way? > Thanks! http://matplotlib.org/examples/api/two_scales.html Kindest regards. Mark Lawrence. -- https://mail.python.org/mailman/listinfo/python-list
Unable to subclass ctypes.c_uint64: was: Re: Battle of the garbage collectors, or ARGGHHHHHH!!!!
On Wed, Apr 26, 2017 at 10:38 PM, Cem Karan wrote: > > On Apr 24, 2017, at 8:54 PM, Jon Ribbens > wrote: > > > On 2017-04-24, CFK wrote: > >> Long version: I'm trying to write bindings for python via ctypes to > control > >> a library written in C that uses the bdwgc garbage collector ( > >> http://www.hboehm.info/gc/). The bindings mostly work, except for when > >> either bdwgc or python's garbage collector decide to get into an > argument > >> over what is garbage and what isn't, in which case I get a segfault > because > >> one or the other collector has already reaped the memory. > > > > Make your Python C objects contain a pointer to a > > GC_MALLOC_UNCOLLECTABLE block that contains a pointer to the > > bwdgc object it's an interface to? And GC_FREE it in tp_dealloc? > > Then bwdgc won't free any C memory that Python is referencing. > > OK, I realized today that there was a miscommunication somewhere. My > python code is all pure python, and the library is pure C, and it is not > designed to be called by python (it's intended to be language neutral, so > if someone wants to call it from a different language, they can). That > means that tp_dealloc (which is part of the python C API) is probably not > going to work. > > I got interrupted (again) so I didn't have a chance to try the next trick > and register the ctypes objects as roots from which to scan in bdwgc, but > I'm hoping that roots aren't removed. If that works, I'll post it to the > list. > > Thanks, > Cem Karan I'm still working on fixing the battle of the garbage collectors, but as a part of that work I've realized that it would be handy for me to subclass various ctypes like so: """ from ctypes import * class foo(c_uint64): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) #Additional setup work here, including marking this type as something bdwgc should alone def __del__(self): #Allow anything not owned by python to be reclaimed by bdwgc super().__del__() """ Where the additional work would shift the type from being in the root set to out of it, and (I hope) stopping the battle of the garbage collectors. The issue is that while the above code works in python 3.4 and earlier, I get the following from python 3.6.1: """ Traceback (most recent call last): File "", line 1, in TypeError: __class__ set to defining 'foo' as """ Is this the way of the future, or is this a bug that should be reported appropriately? Relevant info: """ $ python Python 3.6.1 (default, Apr 24 2017, 08:00:07) [GCC 4.2.1 Compatible Apple LLVM 8.1.0 (clang-802.0.42)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> exit() $ uname -a Darwin Mac-Pro.local 16.5.0 Darwin Kernel Version 16.5.0: Fri Mar 3 16:52:33 PST 2017; root:xnu-3789.51.2~3/RELEASE_X86_64 x86_64 $ sw_vers ProductName:Mac OS X ProductVersion:10.12.4 BuildVersion:16E195 """ Thanks, Cem Karan -- https://mail.python.org/mailman/listinfo/python-list
Re: Unable to subclass ctypes.c_uint64: was: Re: Battle of the garbage collectors, or ARGGHHHHHH!!!!
On Thu, Apr 27, 2017 at 8:55 PM, CFK wrote: > > I'm still working on fixing the battle of the garbage collectors, but as a > part of that work I've realized that it would be handy for me to subclass > various ctypes like so: > > """ > from ctypes import * > class foo(c_uint64): > def __init__(self, *args, **kwargs): > super().__init__(*args, **kwargs) > #Additional setup work here, including marking this type as > something bdwgc should alone > def __del__(self): > #Allow anything not owned by python to be reclaimed by bdwgc > super().__del__() See http://bugs.python.org/issue29270. You can still use c_uint64.__init__(self, value) explicitly. However, super().__del__() shouldn't work anyway. ctypes uses tp_traverse and tp_clear, not tp_finalize (or tp_del), so there is no c_uint64.__del__ method. Its tp_clear is PyCData_clear, which frees the object's internal b_ptr if b_needsfree (i.e. the _b_needsfree_ attribute) is true, i.e. the object owns the referenced memory, and the object is currently using an allocated buffer as opposed to the default internal buffer. Many ctypes instances do not own the memory referenced by b_ptr. This includes dereferenced pointers and struct/array aggregate elements (assuming it's not a base simple type that gets converted to a Python native type) as well instances created with the from_buffer and from_address constructors. -- https://mail.python.org/mailman/listinfo/python-list
Re: Bigotry (you win, I give up)
On Wednesday, April 19, 2017 at 9:44:15 AM UTC-7, Rurpy wrote: > On 04/18/2017 04:34 PM, Chris Angelico wrote: > > On Wed, Apr 19, 2017 at 8:28 AM, Ben Finney > > wrote: > >> Chris Angelico writes: > >> <> Interesting thread... but volatile. I find imaginary numbers to be quite useful for understanding real problems... but I do not try to make them real. They are simply useful ways of looking at the real world. I do the same thing when I think of gods and monsters... useful, but not real. Therefore, I have no problems with any religions or beliefs or unqualified theories that serve to help one deal with real world issues... until the believer or adherent becomes an instigator of issues and accuser of errors. -- https://mail.python.org/mailman/listinfo/python-list
Re: Bigotry (you win, I give up)
On Friday, April 28, 2017 at 9:36:02 AM UTC+5:30, Mike Reveile wrote: > On Wednesday, April 19, 2017 at 9:44:15 AM UTC-7, Rurpy wrote: > > On 04/18/2017 04:34 PM, Chris Angelico wrote: > > > On Wed, Apr 19, 2017 at 8:28 AM, Ben Finney wrote: > > >> Chris Angelico writes: > > >> > <> > > Interesting thread... but volatile. > I find imaginary numbers to be quite useful for understanding real > problems... but I do not try to make them real. They are simply useful ways > of looking at the real world. > I do the same thing when I think of gods and monsters... useful, but not real. > > Therefore, I have no problems with any religions or beliefs or unqualified > theories that serve to help one deal with real world issues... until the > believer or adherent becomes an instigator of issues and accuser of errors. Thanks for that I find this https://www.facebook.com/photo.php?fbid=10154620461548763&set=a.51095183762.64373.542743762 funny (and somewhat insightful) Some will find it racist, 'religionist'(?) I guess? -- https://mail.python.org/mailman/listinfo/python-list
Re: Bigotry (you win, I give up)
On Friday, April 28, 2017 at 9:36:02 AM UTC+5:30, Mike Reveile wrote: > On Wednesday, April 19, 2017 at 9:44:15 AM UTC-7, Rurpy wrote: > > On 04/18/2017 04:34 PM, Chris Angelico wrote: > > > On Wed, Apr 19, 2017 at 8:28 AM, Ben Finney wrote: > > >> Chris Angelico writes: > > >> > <> > > Interesting thread... but volatile. > I find imaginary numbers to be quite useful for understanding real > problems... but I do not try to make them real. They are simply useful ways > of looking at the real world. > I do the same thing when I think of gods and monsters... useful, but not real. Lets call real in the math sense realₘ — ie real-number, imaginary-umber etc Lets call real in the ordinary sense realₒ —ie having existence History suggests that realₘ was a defiant attempt by mathematicians to cock a snook at other mathematicians who contended that the set ℝ was un-realₒ Interestingly these arguments led to the establishment of the field of computer science: http://blog.languager.org/2015/03/cs-history-0.html Personal Note: As a 11-year old reading George Gamov 1-2-3-∞, I had a great deal of trouble understanding imaginary numbers. Later when studying it in math-class I managed to get along with them by playing by the symbol-manipulation rules Much later I understood why I did not understand: The word 'imaginary' was cueing me — subconsciously of course — This is not real... This is not true... This is not... What the &*^%#% is this?? And still later... learnt from Dijkstra the term 'lousy-language' and its consequences -- https://mail.python.org/mailman/listinfo/python-list
Re: Bigotry (you win, I give up)
On Thursday, April 27, 2017 at 9:19:43 PM UTC-7, Rustom Mody wrote: > On Friday, April 28, 2017 at 9:36:02 AM UTC+5:30, Mike Reveile wrote: > > On Wednesday, April 19, 2017 at 9:44:15 AM UTC-7, Rurpy wrote: > > > On 04/18/2017 04:34 PM, Chris Angelico wrote: > > > > On Wed, Apr 19, 2017 at 8:28 AM, Ben Finney wrote: > > > >> Chris Angelico writes: > > > >> > > <> > > > > Interesting thread... but volatile. > > I find imaginary numbers to be quite useful for understanding real > > problems... but I do not try to make them real. They are simply useful ways > > of looking at the real world. > > I do the same thing when I think of gods and monsters... useful, but not > > real. > > > > Therefore, I have no problems with any religions or beliefs or unqualified > > theories that serve to help one deal with real world issues... until the > > believer or adherent becomes an instigator of issues and accuser of errors. > > Thanks for that > > I find this > https://www.facebook.com/photo.php?fbid=10154620461548763&set=a.51095183762.64373.542743762 > funny (and somewhat insightful) > > Some will find it racist, 'religionist'(?) I guess? That is funny :) -- https://mail.python.org/mailman/listinfo/python-list
Re: Bigotry (you win, I give up)
On Thursday, April 27, 2017 at 9:36:26 PM UTC-7, Rustom Mody wrote: > On Friday, April 28, 2017 at 9:36:02 AM UTC+5:30, Mike Reveile wrote: > > On Wednesday, April 19, 2017 at 9:44:15 AM UTC-7, Rurpy wrote: > > > On 04/18/2017 04:34 PM, Chris Angelico wrote: > > > > On Wed, Apr 19, 2017 at 8:28 AM, Ben Finney wrote: > > > >> Chris Angelico writes: > > > >> > > <> > > > > Interesting thread... but volatile. > > I find imaginary numbers to be quite useful for understanding real > > problems... but I do not try to make them real. They are simply useful ways > > of looking at the real world. > > I do the same thing when I think of gods and monsters... useful, but not > > real. > > > Lets call real in the math sense realₘ — ie real-number, imaginary-umber etc > Lets call real in the ordinary sense realₒ —ie having existence > > History suggests that realₘ was a defiant attempt by mathematicians > to cock a snook at other mathematicians who contended that the set ℝ was > un-realₒ > > Interestingly these arguments led to the establishment of the field of > computer > science: http://blog.languager.org/2015/03/cs-history-0.html > > Personal Note: As a 11-year old reading George Gamov 1-2-3-∞, I had a great > deal of trouble understanding imaginary numbers. > Later when studying it in math-class I managed to get along with them by > playing by the symbol-manipulation rules > Much later I understood why I did not understand: The word 'imaginary' was > cueing > me — subconsciously of course — > This is not real... > This is not true... > This is not... > What the &*^%#% is this?? > > And still later... learnt from Dijkstra the term 'lousy-language' and its > consequences I can measure a Pineapple... by weight, volume, color, taste, smell, ripeness... but none of these numbers are the pineapple. They only help me relate to the pineapple. In this way Math itself (and the entire realm of computer science) is unreal. -- https://mail.python.org/mailman/listinfo/python-list
