Question: I often see comments on other Stack Overflow questions about how the use of `except: pass` is discouraged. Why is this bad? Sometimes I just don't care what the errors are and I want to just continue with the code.

```
try:
    something
except:
    pass

```

Why is using an `except: pass` block bad? What makes it bad? Is it the fact that I `pass` on an error or that I `except` any error?

Answer: 
```
>>> import this

```

> 
> The Zen of Python, by Tim Peters
> 
> 
> Beautiful is better than ugly.  
> 
>  Explicit is better than implicit.  
> 
>  Simple is better than complex.  
> 
>  Complex is better than complicated.  
> 
>  Flat is better than nested.  
> 
>  Sparse is better than dense.  
> 
>  Readability counts.  
> 
>  Special cases aren't special enough to break the rules.  
> 
>  Although practicality beats purity.  
> 
> **Errors should never pass silently.**  
> 
>  Unless explicitly silenced.  
> 
>  In the face of ambiguity, refuse the temptation to guess.  
> 
>  There should be one-- and preferably only one --obvious way to do it.  
> 
>  Although that way may not be obvious at first unless you're Dutch.  
> 
>  Now is better than never.  
> 
>  Although never is often better than *right* now.  
> 
>  If the implementation is hard to explain, it's a bad idea.  
> 
>  If the implementation is easy to explain, it may be a good idea.  
> 
>  Namespaces are one honking great idea -- let's do more of those!
> 
> 
> 

So, here is my opinion. Whenever you find an error, you should do something to handle it, i.e. write it in logfile or something else. At least, it informs you that there used to be a error.
I personally prefer this solution:

```
except ValueError as error:
                print(error.args)
                pass

```

`error.args` gives me a one-liner that is not too distracting but really helps with code review, especially if there are different reasons for the errors such as

```
(ValueError('year 0 is out of range'),)
(ValueError('month must be in 1..12'),)
(ValueError('day is out of range for month'),)

```

when working with time periods in `pandas`.