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In-place type conversion of a NumPy array
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It seems to work perfectly in python3.3 with the latest numpy version.
– CHM
Oct 10 '13 at 21:41
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Using pickle.dump - TypeError: must be str, not bytes
I'm using python3.3 and I'm having a cryptic error when trying to pickle a simple dictionary.
2 Answers
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Getting the exception value in Python
...can add a exc_info=True to our logging function to not miss the error.
For python3, I think it's safe to use str(e).
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Pickle or json?
...k, but I had an existing game where it was saving the levels using pickle (python3). I wanted to try jsonpickle for the human readable aspect - however the level saves were sadly much slower. 1597ms for jsonpickle and 88ms or regular pickle on level save. For level load, 1604ms for jsonpickle and 38...
Python list directory, subdirectory, and files
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In Python3 use parenthesis for print function print(os.path.join(path, name))
– Ehsan
Aug 7 at 11:31
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Auto reloading python Flask app upon code changes
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or pyvenv in python3.5, flask run also works, since when you pip install flask, a flask executable file is also installed in the venv/bin/ folder.
– TonyTony
Jan 4 '17 at 14:00
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How to print a string in fixed width?
...t;5}' indicates the argument’s index passed to str.format().
Edit 2:
In python3 one could use also f-string:
sub_str='s'
for i in range(1,6):
s = sub_str*i
print(f'{s:>5}')
' s'
' ss'
' sss'
' ssss'
'sssss'
or:
for i in range(1,5):
s = sub_str*i
print(f'{s:&...
A Regex that will never be matched by anything
...r regarding timing, as I found the exact opposite measured with timeit and python3.
– nivk
Nov 4 '17 at 20:59
It's not...
如何编写一个独立的 PHP 扩展（译） - 更多技术 - 清泛网 - 专注C/C++及内核技术
...是说想要编写 PHP 扩展，你既需要已经安装了 PHP，也需要下载一份 PHP 源码。
定义一个新扩展
我们给示例扩展命名为 “foobar”。
新扩展包含两个资源文件：foo.c 和 bar.c（还有一些头文件，但这些不只重要）。
示例扩展不引...
Get list from pandas DataFrame column headers
...posted so far, so I'll just leave this here.
Extended Iterable Unpacking (python3.5+): [*df] and Friends
Unpacking generalizations (PEP 448) have been introduced with Python 3.5. So, the following operations are all possible.
df = pd.DataFrame('x', columns=['A', 'B', 'C'], index=range(5))
df
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