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Add new snippet: Half quoted triple strings

Closes https://github.com/satwikkansal/wtfpython/issues/40
This commit is contained in:
Satwik Kansal 2017-10-11 22:44:47 +05:30
parent ea29aa034d
commit 41e9b72fea

20
README.md vendored
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@ -1774,6 +1774,26 @@ a, b = a[b] = {}, 5
print(dis.dis(f)) print(dis.dis(f))
``` ```
* Half triple-quoted strings (suggested by @asottile in [this](https://github.com/satwikkansal/wtfpython/issues/40) issue).
```py
>>> print('wtfpython''')
wtfpython
>>> print("wtfpython""")
wtfpython
>>> # The following statements raise `SyntaxError`
>>> # print('''wtfpython')
>>> # print("""wtfpython")
```
**💡 Explanation:**
+ Python support implicit [string literal concatenation](https://docs.python.org/2/reference/lexical_analysis.html#string-literal-concatenation), Example,
```
>>> print("wtf" "python")
wtfpython
>>> print("wtf" "") # or "wtf"""
wtf
```
+ `'''` and `"""` are also string delimiters in Python which causes a SyntaxError because the Python interpreter was expecting a terminating triple quote as delimiter while scanning the currently encountered triple quoted string literal.
* Multiple Python threads won't run your *Python code* concurrently (yes you heard it right!). It may seem intuitive to spawn several threads and let them execute your Python code concurrently, but, because of the [Global Interpreter Lock](https://wiki.python.org/moin/GlobalInterpreterLock) in Python, all you're doing is making your threads execute on the same core turn by turn. Python threads are good for IO-bound tasks, but to achieve actual parallelization in Python for CPU-bound tasks, you might want to use the Python [multiprocessing](https://docs.python.org/2/library/multiprocessing.html) module. * Multiple Python threads won't run your *Python code* concurrently (yes you heard it right!). It may seem intuitive to spawn several threads and let them execute your Python code concurrently, but, because of the [Global Interpreter Lock](https://wiki.python.org/moin/GlobalInterpreterLock) in Python, all you're doing is making your threads execute on the same core turn by turn. Python threads are good for IO-bound tasks, but to achieve actual parallelization in Python for CPU-bound tasks, you might want to use the Python [multiprocessing](https://docs.python.org/2/library/multiprocessing.html) module.
* List slicing with out of the bounds indices throws no errors * List slicing with out of the bounds indices throws no errors