I get this error when I run the code below:
'builtin_function_or_method' object is not iterable
I have searched stackoverflow, but cant find a answer to my question... Please help me!
def file2matrix(filename):
fr = open(filename)
arrayOLines = fr.readlines()
numberOfLines = len(arrayOLines)
returnMat = zeros((numberOfLines, 3))
classLabelVector = []
index = 0
for line in arrayOLines:
line = line.strip()
listFromLine = line.split('\t')
returnMat[index, :] = listFromLine[0:3]
classLabelVector.append(int(listFromLine[-1]))
index += 1
return returnMat, classLabelVector
and this is result...
>>> datingDataMat,datingLabels = kNN.file2matrix("datingTestSet.txt")
Traceback (most recent call last):
File "<input>", line 1, in <module>
File "C:\Users\Dennis Yang\PycharmProjects\mlaction\kNN.py", line 28, in file2matrix
for line in arrayOLines:
TypeError: 'builtin_function_or_method' object is not iterable
Related
Here is my model:
starts at line: 39
def make_input_fn(data_df, label_df, num_epochs=10, shuffle=True, batch_size=32):
def input_function():
ds = tf.data.Dataset.from_tensor_slices((dict(data_df), label_df))
if shuffle:
ds = ds.shuffle(1000)
ds = ds.batch(batch_size).repeat(num_epochs)
return ds()
return input_function()
train_input_fn = make_input_fn(dftrain, y_train)
ends at line: 49
Here is my error:
Traceback (most recent call last): File, line 49, in <module> train_input_fn = make_input_fn(dftrain, y_train) File, line 46, in make_input_fn return input_function() File, line 45, in input_function return ds() TypeError: 'RepeatDataset' object is not callable
The Variable ds is not callable, Try to change return ds() in the input_function() to return ds.
These types of error usually occur when you try to index an Integer or Float variable or you try to make a variable callable using ()
For Example
var=10
print(var())
var2=15
print(var2[0])
The above is the simplified example of what error you are getting.
I have a table object that I want to pass it to multiple threads. I use multiprocessing.Value function to create a semaphore for that object. However, it tells me that Float32Atom is not hashable. Not sure what to do in this case?
>>> import tables as tb
>>> f = tb.open_file('dot.h5', 'w')
>>> filters = tb.Filters(complevel=5, complib='blosc')
>>> n_ = 10000
>>> W_hat = f.create_carray(f.root, 'data', tb.Float32Atom(), shape=(n_, n_), filters=filters)
>>> W_hat = Value(tb.Float32Atom(), W_hat)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/lib/python3.8/multiprocessing/context.py", line 135, in Value
return Value(typecode_or_type, *args, lock=lock,
File "/home/lib/python3.8/multiprocessing/sharedctypes.py", line 74, in Value
obj = RawValue(typecode_or_type, *args)
File "/home/lib/python3.8/multiprocessing/sharedctypes.py", line 48, in RawValue
type_ = typecode_to_type.get(typecode_or_type, typecode_or_type)
TypeError: unhashable type: 'Float32Atom'
If it is correct that you have only threads (and no processes), you can just use multiprocessing.Semaphore. All threads run in the same context, so you can use it for all of them.
see https://docs.python.org/3/library/threading.html#semaphore-objects
I have a function:
def create_variables(name, probabilities, labels):
print('function called')
model = Metrics(probabilities, labels)
prec_curve = model.precision_curve()
kappa_curve = model.kappa_curve()
tpr_curve = model.tpr_curve()
fpr_curve = model.fpr_curve()
pr_auc = auc(tpr_curve, prec_curve)
roc_auc = auc(fpr_curve, tpr_curve)
auk = auc(fpr_curve, kappa_curve)
return [name, prec_curve, kappa_curve, tpr_curve, fpr_curve, pr_auc, roc_auc, auk]
I have the following variables:
svm = pd.read_csv('SVM.csv')
svm_prob_1 = svm.probability[svm.fold_number == 1]
svm_prob_2 = svm.probability[svm.fold_number == 2]
svm_label_1 = svm.true_label[svm.fold_number == 1]
svm_label_2 = svm.true_label[svm.fold_number == 2]
I want to execute the following lines:
svm1 = create_variables('svm_fold1', svm_prob_1, svm_label_1)
svm2 = create_variables('svm_fold2', svm_prob_2, svm_label_2)
Python works as expected for svm1. However, when it starts processing svm2, I receive the following error:
svm2 = create_variables('svm_fold2', svm_prob_2, svm_label_2)
function called
Traceback (most recent call last):
File "<ipython-input-742-702cfac4d100>", line 1, in <module>
svm2 = create_variables('svm_fold2', svm_prob_2, svm_label_2)
File "<ipython-input-741-b8b5a84f0298>", line 6, in create_variables
prec_curve = model.precision_curve()
File "<ipython-input-734-dd9c309be961>", line 59, in precision_curve
self.tp, self.tn, self.fp, self.fn = self.confusion_matrix(self.preds)
File "<ipython-input-734-dd9c309be961>", line 72, in confusion_matrix
if pred == self.labels[i]:
File "C:\Users\20200016\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\series.py", line 1068, in __getitem__
result = self.index.get_value(self, key)
File "C:\Users\20200016\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 4730, in get_value
return self._engine.get_value(s, k, tz=getattr(series.dtype, "tz", None))
File "pandas\_libs\index.pyx", line 80, in pandas._libs.index.IndexEngine.get_value
File "pandas\_libs\index.pyx", line 88, in pandas._libs.index.IndexEngine.get_value
File "pandas\_libs\index.pyx", line 131, in pandas._libs.index.IndexEngine.get_loc
File "pandas\_libs\hashtable_class_helper.pxi", line 992, in pandas._libs.hashtable.Int64HashTable.get_item
File "pandas\_libs\hashtable_class_helper.pxi", line 998, in pandas._libs.hashtable.Int64HashTable.get_item
KeyError: 0
svm_prob_1 and svm_prob_2 are both of the same shape and contain non-zero values. svm_label_2 contains 0's and 1's and has the same length as svm_prob_2.
Furthermore, the error seems to be in svm_label_1. After changing this variable, the following line does work:
svm2 = create_variables('svm_fold2', svm_prob_2, svm_label_1
Based on the code below, there seems to be no difference between svm_label_1 and svm_label_2 though.
type(svm_label_1)
Out[806]: pandas.core.series.Series
type(svm_label_2)
Out[807]: pandas.core.series.Series
min(svm_label_1)
Out[808]: 0
min(svm_label_2)
Out[809]: 0
max(svm_label_1)
Out[810]: 1
max(svm_label_2)
Out[811]: 1
sum(svm_label_1)
Out[812]: 81
sum(svm_label_2)
Out[813]: 89
len(svm_label_1)
Out[814]: 856
len(svm_label_2)
Out[815]: 856
Does anyone know what's going wrong here?
I don't know why it works, but converting svm_label_2 into a list worked:
svm_label_2 = list(svm.true_label[svm.fold_number == 2])
Since, svm_label_1 and svm_label_2 are of the same type, I don't understand why the latter raised an error and the first one did not. Therefore, I still welcome any explanation to this phenomenon.
So I have a set of logs with random ip information and other things. Im making these logs into data frames and then trying to read the IP information afterwards and return if they are public or private its through running them with IPy. Im getting back an error and can't figure it out.
My coding looks like this
df2 = pd.read_csv( 'p0f.txt',sep='|',header=0, engine='python')
df2.columns = ['time','client_ip','server_ip','d','connection','mtu','g','raw_ip']
df2['client_ip'] = df2['client_ip'].map(lambda x: str(x)[4:])
df2['server_ip'] = df2['server_ip'].map(lambda x: str(x)[4:])
df2['mtu'] = df2['mtu'].map(lambda x: x.lstrip('raw_mtu=langEnglishnonefreqdistHz').rstrip('=Hz'))
df2['time'] = df2['time'].map(lambda x: x.lstrip('').rstrip('mod=mtu,cli=mod=syn+ackmod=uptimemod=httpreqmod= httpmod=host chang'))
df2_client_ip = df2[['client_ip']]
df_client_ip_check = df.applymap(lambda x: IP(x).iptype())
when I print I get this error
Traceback (most recent call last):
File "/Users/mykelxknight/CodeProjects/chiron/BroHttpParse.py", line 44, in <module>
df_client_ip_check = df.applymap(lambda x: IP(x).iptype())
File "/usr/local/lib/python3.6/site-packages/pandas/core/frame.py", line 4453, in applymap
return self.apply(infer)
File "/usr/local/lib/python3.6/site-packages/pandas/core/frame.py", line 4262, in apply
ignore_failures=ignore_failures)
File "/usr/local/lib/python3.6/site-packages/pandas/core/frame.py", line 4358, in _apply_standard
results[i] = func(v)
File "/usr/local/lib/python3.6/site-packages/pandas/core/frame.py", line 4451, in infer
return lib.map_infer(x.asobject, func)
File "pandas/_libs/src/inference.pyx", line 1574, in pandas._libs.lib.map_infer (pandas/_libs/lib.c:66645)
File "/Users/mykelxknight/CodeProjects/chiron/BroHttpParse.py", line 44, in <lambda>
df_client_ip_check = df.applymap(lambda x: IP(x).iptype())
File "/usr/local/lib/python3.6/site-packages/IPy.py", line 246, in __init__
(self.ip, parsedVersion) = parseAddress(ip)
File "/usr/local/lib/python3.6/site-packages/IPy.py", line 1417, in parseAddress
raise ValueError("%r: single byte must be 0 <= byte < 256" % (ipstr))
ValueError: ("'1433937432.495592': single byte must be 0 <= byte < 256", 'occurred at index #fields')
I am trying to debug this function:
def check_domains(url):
global num_websites,domain_queue,domains,doc_queue,stanford_tagger
the_domain = re.match(r'^(:?https?:\/\/[^.]*\.)?([^/#?&]+).*$',url)
if the_domain is not None:
if the_domain.groups(0)[1] not in domains.keys():
domains[the_domain.groups(0)[1]] = website(doc_queue,the_domain.groups(0)[1])
domains[the_domain.groups(0)[1]].add_initial_url(url)
domain_queue.append(domains[the_domain.groups(0)[1]])
num_websites = num_websites + 1
else:
domains[the_domain.groups(0)[1]].add_url(url)
error:
File "web_crawler.py", line 178, in getdoc
check_domains(check)
File "web_crawler.py", line 133, in check_domains
the_domain = re.match(r'^(:?https?:\/\/[^.]*\.)?([^/#?&]+).*$',url)
File "/usr/local/lib/python2.7/re.py", line 137, in match
return _compile(pattern, flags).match(string)
TypeError: expected string or buffer
I try and be a good boy and test in interactive mode:
>>> def check_domains(url):
... the_domain = re.match(r'^(:?https?:\/\/[^.]*\.)?([^/#?&]+).*$',url) #right here
... if the_domain is not None:
... print the_domain.groups(0)[1]
... else:
... print "NOOOO!!!!!"
...
>>>
>>> check_domains("http://www.hulu.com/watch/6704")
hulu.com
>>> check_domains("https://docs.python.org/2/library/datetime.html")
python.org
so this does what I want it to do and I didn't change that line. But why???
The value of url can still be None and that's what gives this error:
>>> re.match(r'^(:?https?:\/\/[^.]*\.)?([^/#?&]+).*$', None)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/re.py", line 137, in match
return _compile(pattern, flags).match(string)
TypeError: expected string or buffer
So you should check whether the object that you're passing for url is indeed a string. It may even be a number or something else but it's not a string which is what the matching function expects.