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gradlew: Permission Denied
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Try to set the execution flag on your gradlew file:
chmod +x gradlew
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Convert string to variable name in python [duplicate]
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x='buffalo'
exec("%s = %d" % (x,2))
After that you can check it by:
print buffalo
As an output you will see:
2
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%d,%c,%s,%x等转换符 释义 - C/C++ - 清泛网 - 专注C/C++及内核技术
%d,%c,%s,%x等转换符 释义转换说明符 %a(%A) 浮点数、十六进制数字和p-(P-)记数法(C99) %c 字符 %d 有符号十进制整数 %f 浮...转换说明符
%a(%A) 浮点数、十六进制数字和p-(P-)记数法(C99)
%c 字符
%d ...
关于 __VA_ARGS__ 宽字符版本的问题 - C/C++ - 清泛网 - 专注C/C++及内核技术
...日志函数，考虑到宽字符（Unicode版本）时：#define WIDEN2(x) L ## x#define WIDEN(x) WIDEN2(x)#define __...在写一个可变参数的记录日志函数，考虑到宽字符（Unicode版本）时：
#define WIDEN2(x) L ## x
#define WIDEN(x) WIDEN2(x)
#define __WFILE__ WIDEN(__FI...
正则表达式中 /i,/g,/m,/s,/e,/x 的含义 - 更多技术 - 清泛网 - 专注C/C++及内核技术
正则表达式中 /i,/g,/m,/s,/e,/x 的含义正则表达式中 i, g, m, s, e, x的区别和含义 i (忽略大小写) g (全文查找出现的所有匹配字符) m (多行查找) gi(全文查找、忽略大小写) ig...正则表达式中 /i,/g,/m,/x,/e,/x 的含义：
/i (忽略大小写)
/g (...
Undefined reference to symbol X509_free - C/C++ - 清泛网 - 专注C/C++及内核技术
Undefined reference to symbol X509_freeundefined-reference-to-symbol-x509-freeUndefined reference to symbol X509_free 编译错误的解决方法：链接库中增加 -lcrypto，而非 -lcrypt参考：https: stackoverflow com questions 33215936 undefined-reference-to-symbol-x509-freeUndefined refer...
Check if a class has a member function of a given signature
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I'm not sure if I understand you correctly, but you may exploit SFINAE to detect function presence at compile-time. Example from my code (tests if class has member function size_t used_memory() const).
template<typename T>
struct HasUsedMemoryMethod
{
template<typenam...
Why is Python 3.x's super() magic?
In Python 3.x, super() can be called without arguments:
1 Answer
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Update a dataframe in pandas while iterating row by row
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I'm not sure if we read it exactly the same. If you look in my pseudo code I do the modification on the dataframe, not on the value from the iterator. The iterator value is only used for the index of the value/object. What will fail is row['ifor']=some_...
How to normalize an array in NumPy?
...ormalize:
import numpy as np
from sklearn.preprocessing import normalize
x = np.random.rand(1000)*10
norm1 = x / np.linalg.norm(x)
norm2 = normalize(x[:,np.newaxis], axis=0).ravel()
print np.all(norm1 == norm2)
# True
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