short answer: YES

Ref:

http://docs.scipy.org/doc/numpy/reference/generated/numpy.invert.html

Notice:

&gt; Computes the bit-wise NOT of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ~.

and 

&gt; bitwise_not is an alias for invert:

    &gt;&gt; np.bitwise_not is np.invert
    &gt;&gt; True

I just read part of an optimization article and *segfaulted* on the following statement:

&gt; When using SQL replace statements using `OR` with a `UNION`:

&gt;     select username from users where company = ‘bbc’ or company = ‘itv’;

&gt; to:
 
&gt;     select username from users where company = ‘bbc’ union
    select username from users where company = ‘itv’;

From a quick `EXPLAIN`:

Using `OR`:

![enter image description here][1]

Using `UNION`:

![enter image description here][2]

Doesn&#39;t this mean `UNION` does in *double the work*?

While I appreciate `UNION` may be more performant for certain RDBMSes and certain table schemas, this is not *categorically true* as the author suggestions.

### Question
Am I wrong?


  [1]: http://i.stack.imgur.com/sxoLS.png
  [2]: http://i.stack.imgur.com/HAqu6.png

SQL Performance UNION vs OR

I have to insert about 2 million rows from a text file.

And with inserting I have to create some master tables. 

What is the best and fast way to insert such a large set of data into SQL Server?



Insert 2 million rows into SQL Server quickly

Can I use `~A` to invert a numpy array of booleans, instead of the rather awkward functions `np.logical_and()` and `np.invert()`? 

Indeed, `~` seems to work fine, but I can&#39;t find it in any nympy reference manual, and - more alarmingly - it certainly does _not_ work with scalars (e.g. `bool(~True)` returns `True` !), so I&#39;m a little bit worried ...

Inverting a numpy boolean array using ~

Can I use <code>~A</code> to invert a numpy array of booleans, instead of the rather awkward functions <code>np.logical_and()</code> and <code>np.invert()</code>?
Indeed, <code>~</code> seems to work fine, but I can't find it in any nympy reference manual, and - more alarmingly - it certainly does not work with scalars (e.g. <code>bool(~True)</code> returns <code>True</code> !), so I'm a little bit worried ...

I have a program that writes a list to a file. 
The list is a list of pipe delimited lines and the lines should be written to the file like this:

    123|GSV|Weather_Mean|hello|joe|43.45
    122|GEV|temp_Mean|hello|joe|23.45
    124|GSI|Weather_Mean|hello|Mike|47.45

BUT it wrote them line this ahhhh:

    123|GSV|Weather_Mean|hello|joe|43.45122|GEV|temp_Mean|hello|joe|23.45124|GSI|Weather_Mean|hello|Mike|47.45

This program wrote all the lines into like one line without any line breaks.. This hurts me a lot and I gotta figure-out how to reverse this but anyway, where is my program wrong here? I thought write lines should write lines down the file rather than just write everything to one line..

    fr = open(sys.argv[1], &#39;r&#39;) # source file
    fw = open(sys.argv[2]+&quot;/masked_&quot;+sys.argv[1], &#39;w&#39;) # Target Directory Location
    
    for line in fr:
        line = line.strip()
        if line == &quot;&quot;:
            continue
        columns = line.strip().split(&#39;|&#39;)
        if columns[0].find(&quot;@&quot;) &gt; 1:
            looking_for = columns[0] # this is what we need to search
        else:
            looking_for = &quot;Dummy@dummy.com&quot;
        if looking_for in d:
            # by default, iterating over a dictionary will return keys
                new_line = d[looking_for]+&#39;|&#39;+&#39;|&#39;.join(columns[1:])
                line_list.append(new_line)
        else:
            new_idx = str(len(d)+1)
            d[looking_for] = new_idx
            kv = open(sys.argv[3], &#39;a&#39;)
            kv.write(looking_for+&quot; &quot;+new_idx+&#39;\n&#39;)
            kv.close()
            new_line = d[looking_for]+&#39;|&#39;+&#39;|&#39;.join(columns[1:])
            line_list.append(new_line)
    fw.writelines(line_list)

Writelines writes lines without newline, Just fills the file

Say I have an array `a`:

    a = np.array([[1,2,3], [4,5,6]])
    
    array([[1, 2, 3],
           [4, 5, 6]])

I would like to convert it to a 1D array (i.e. a column vector):

    b = np.reshape(a, (1,np.product(a.shape)))

but this returns

    array([[1, 2, 3, 4, 5, 6]])

which is not the same as:

    array([1, 2, 3, 4, 5, 6])


I can take the first element of this array to manually convert it to a 1D array:
    
    b = np.reshape(a, (1,np.product(a.shape)))[0]

but this requires me to know how many dimensions the original array has (and concatenate [0]&#39;s when working with higher dimensions)

Is there a dimensions-independent way of getting a column/row vector from an arbitrary ndarray?




From ND to 1D arrays

I&#39;m using Python&#39;s logging module to log some debug strings to a file which works pretty well. Now in addition, I&#39;d like to use this module to also print the strings out to stdout. How do I do this? In order to log my strings to a file I use following code:

    import logging
    import logging.handlers
    logger = logging.getLogger(&quot;&quot;)
	logger.setLevel(logging.DEBUG)
	handler = logging.handlers.RotatingFileHandler(
		LOGFILE, maxBytes=(1048576*5), backupCount=7
	)
	formatter = logging.Formatter(&quot;%(asctime)s - %(name)s - %(levelname)s - %(message)s&quot;)
	handler.setFormatter(formatter)
	logger.addHandler(handler)
and then call a logger function like
    
    logger.debug(&quot;I am written to the file&quot;)

Thank you for some help here!

logger configuration to log to file and print to stdout

I&#39;m calling a command line program in python using the `os.system(command)` call.

How can I call this command passing a different folder for execution? There is a system call for this? Or I should save the current folder, and, after execution, change restore it.

Command line execution in different folder

I have a problem with the following code:


**callBash.py:**

    import subprocess
    print &quot;start&quot;
    subprocess.call(&quot;sleep.sh&quot;)
    print &quot;end&quot;

**sleep.sh:**

    sleep 10

I want the &quot;end&quot; to be printed after 10s. (I know that this is a dumb example, I could simply sleep within python, but this simple sleep.sh file was just as a test)

Running bash script from within python

So I have an unsorted numeric array `int[] anArray = { 1, 5, 2, 7 };` and I need to get both the value and the index of the largest value in the array which would be 7 and 3, how would I do this? 

C# find highest array value and index

This is also referred to as &quot;deep copying&quot;, which I&#39;ve found some articles on. Closest seems to be [this one][1] but it&#39;s for jQuery - I&#39;m trying to do this without a library.

I&#39;ve also seen, in two places, that it&#39;s possible to do something like:
    
    arr2 = JSON.decode(JSON.encode(arr1));

But that&#39;s apparently inefficient. It&#39;s also possible to loop and copy each value individually, and recurs through all the arrays. That seems tiring and inefficient as well. 

So what&#39;s the most efficient, non-library way to copy a JavaScript multi-dimensional array `[[a],[b],[c]]`? I am completely happy with a &quot;non-IE&quot; method if necessary.

Thanks!


  [1]: https://stackoverflow.com/questions/565430/deep-copying-an-array-using-jquery

Create copy of multi-dimensional array, not reference - JavaScript

What&#39;s the easiest and/or shortest way possible to get the names of enum elements as an array of `String`s?

What I mean by this is that if, for example, I had the following enum:

    public enum State {
    	NEW,
    	RUNNABLE,
    	BLOCKED,
    	WAITING,
    	TIMED_WAITING,
    	TERMINATED;
    	
    	public static String[] names() {
    		// ...
    	}
    }

the `names()` method would return the array `{ &quot;NEW&quot;, &quot;RUNNABLE&quot;, &quot;BLOCKED&quot;, &quot;WAITING&quot;, &quot;TIMED_WAITING&quot;, &quot;TERMINATED&quot; }`.

Getting all names in an enum as a String[]

I have some code I&#39;m trying to understand while learning C#.  I do not understand what I even need to search Google for to get here, but the code is as follows:

    float[,] heightAll = terData.GetHeights(0, 0, allWidth, allHeight);

Why does the array declaration have a comma in between the brackets?

What does it mean when there is a comma inside an array declaration? e.g. float[,]

Let&#39;s say I have an array of four objects:

    var jsObjects = [
       {a: 1, b: 2}, 
       {a: 3, b: 4}, 
       {a: 5, b: 6}, 
       {a: 7, b: 8}
    ];

Is there a way that I can get the third object (`{a: 5, b: 6}`) by the value of the property `b` for example without a `for...in` loop?

Get JavaScript object from array of objects by value of property

I have a numpy array of numbers, for example,  

    a = np.array([1, 3, 5, 6, 9, 10, 14, 15, 56])  

I would like to find all the indexes of the elements within a specific range. For instance, if the range is (6, 10), the answer should be (3, 4, 5). Is there a built-in function to do this?

Numpy: find index of the elements within range

I am trying to write a Pandas dataframe (or can use a numpy array) to a mysql database using MysqlDB . MysqlDB doesn&#39;t seem understand &#39;nan&#39; and my database throws out an error saying nan is not in the field list. I need to find a way to convert the &#39;nan&#39; into a NoneType.

Any ideas? 

Replacing Pandas or Numpy Nan with a None to use with MysqlDB

I have a very large 2D array which looks something like this:

    a=
    [[a1, b1, c1],
     [a2, b2, c2],
     ...,
     [an, bn, cn]]

Using numpy, is there an easy way to get a new 2D array with, e.g., 2 random rows from the initial array `a` (without replacement)?

e.g.

    b=
    [[a4,  b4,  c4],
     [a99, b99, c99]]



Numpy: Get random set of rows from 2D array

There seems to be no function that simply calculates the moving average on numpy/scipy, leading to [convoluted solutions](https://stackoverflow.com/questions/12816011/weighted-moving-average-with-numpy-convolve).

My question is two-fold:

 - What&#39;s the easiest way to (correctly) implement a moving average with numpy?
 - Since this seems non-trivial and error prone, is there a good reason not to have the [batteries included][1] in this case?


  [1]: https://www.python.org/dev/peps/pep-0206/#batteries-included-philosophy

How to calculate rolling / moving average using python + NumPy / SciPy?

I would like the element-wise logical OR operator. I know &quot;or&quot; itself is not what I am looking for.

I am aware that AND corresponds to `&amp;` and NOT, `~`. But what about OR? 

  [1]: https://stackoverflow.com/questions/21415661/logic-operator-for-boolean-indexing-in-pandas &quot;here&quot;
  [2]: https://stackoverflow.com/questions/15998188/how-can-i-obtain-the-element-wise-logical-not-of-a-pandas-series

Element-wise logical OR in Pandas

In pandas, I&#39;d like to create a computed column that&#39;s a boolean operation on two other columns. 

In pandas, it&#39;s easy to add together two numerical columns. I&#39;d like to do something similar with logical operator `AND`. Here&#39;s my first try:

    In [1]: d = pandas.DataFrame([{&#39;foo&#39;:True, &#39;bar&#39;:True}, {&#39;foo&#39;:True, &#39;bar&#39;:False}, {&#39;foo&#39;:False, &#39;bar&#39;:False}])
    
    In [2]: d
    Out[2]: 
         bar    foo
    0   True   True
    1  False   True
    2  False  False

    In [3]: d.bar and d.foo   ## can&#39;t
    ...
    ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

So I guess logical operators don&#39;t work quite the same way as numeric operators in pandas. I tried doing what the error message suggests and using `bool()`:


    In [258]: d.bar.bool() and d.foo.bool()  ## spoiler: this doesn&#39;t work either
    ...
    ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


I found a way that works by casting the boolean columns to `int`, adding them together and evaluating as a boolean.
    
    In [4]: (d.bar.apply(int) + d.foo.apply(int)) &gt; 0  ## Logical OR
    Out[4]: 
    0     True
    1     True
    2    False
    dtype: bool
    
    In [5]: (d.bar.apply(int) + d.foo.apply(int)) &gt; 1  ## Logical AND
    Out[5]: 
    0     True
    1    False
    2    False
    dtype: bool
    
This is convoluted. Is there a better way?


Logical operation on two columns of a dataframe

Given this input:

    [
      {
        &quot;Id&quot;: &quot;cb94e7a42732b598ad18a8f27454a886c1aa8bbba6167646d8f064cd86191e2b&quot;,
        &quot;Names&quot;: [
          &quot;condescending_jones&quot;,
          &quot;loving_hoover&quot;
        ]
      },
      {
        &quot;Id&quot;: &quot;186db739b7509eb0114a09e14bcd16bf637019860d23c4fc20e98cbe068b55aa&quot;,
        &quot;Names&quot;: [
          &quot;foo_data&quot;
        ]
      },
      {
        &quot;Id&quot;: &quot;a4b7e6f5752d8dcb906a5901f7ab82e403b9dff4eaaeebea767a04bac4aada19&quot;,
        &quot;Names&quot;: [
          &quot;jovial_wozniak&quot;
        ]
      },
      {
        &quot;Id&quot;: &quot;76b71c496556912012c20dc3cbd37a54a1f05bffad3d5e92466900a003fbb623&quot;,
        &quot;Names&quot;: [
          &quot;bar_data&quot;
        ]
      }
    ]

I&#39;m trying to construct a filter with [jq](http://stedolan.github.io/jq/) that returns all objects with `Id`s that **do not** contain &quot;data&quot; in the inner `Names` array, with the output being newline-separated.  For the above data, the output I&#39;d like is:

    cb94e7a42732b598ad18a8f27454a886c1aa8bbba6167646d8f064cd86191e2b
    a4b7e6f5752d8dcb906a5901f7ab82e403b9dff4eaaeebea767a04bac4aada19

I think I&#39;m somewhat close with this:

    (. - select(.Names[] contains(&quot;data&quot;))) | .[] .Id

but the `select` filter is not correct and it doesn&#39;t compile (get `error: syntax error, unexpected IDENT`).

How to filter an array of objects based on values in an inner array with jq?

Is there a short negation of `%in%` in R like `!%in%` or `%!in%`?


----------

Of course I can negate `c(&quot;A&quot;, &quot;B&quot;) %in% c(&quot;B&quot;, &quot;C&quot;)` by `!(c(&quot;A&quot;, &quot;B&quot;) %in% c(&quot;B&quot;, &quot;C&quot;))` (cf. [this question][1]) but I would prefere a more straight forward approach and save a pair of brackets (alike presumably most people would prefer `c(&quot;A&quot;, &quot;B&quot;) != c(&quot;B&quot;, &quot;C&quot;)` over `!(c(&quot;A&quot;, &quot;B&quot;) == c(&quot;B&quot;, &quot;C&quot;))`).


  [1]: https://stackoverflow.com/questions/5831794/opposite-of-in

Negation of %in% in R

In C/C++, why should one use `abs()` or `fabs()` to find the absolute value of a variable without using the following code?

    int absoluteValue = value &lt; 0 ? -value : value;

Does it have something to do with fewer instructions at lower level?

Why use abs() or fabs() instead of conditional negation?

So this is more of a theoretical question. C++ and languages (in)directly based on it (Java, C#, PHP) have [shortcut operators][1] for assigning the result of most binary operators to the first operand, such as

    a += 3;   // for a = a + 3
    a *= 3;   // for a = a * 3;
    a &lt;&lt;= 3;  // for a = a &lt;&lt; 3;

but when I want to toggle a boolean expression I always find myself writing something like

    a = !a;

which gets annoying when `a` is a long expression like.

    this.dataSource.trackedObject.currentValue.booleanFlag =
        !this.dataSource.trackedObject.currentValue.booleanFlag;

(yeah, Demeter&#39;s Law, I know). 

So I was wondering, *is there any language with a unary boolean toggle operator* that would allow me to abbreviate `a = !a` without repeating the expression for `a`, for example

    !=a;  
    // or
    a!!;

Let&#39;s assume that our language has a proper boolean type (like `bool` in C++) and that `a` is of that type (so no C-style `int a = TRUE`).

If you can find a documented source, I&#39;d also be interested to learn whether e.g. the C++ designers have considered adding an operator like that when `bool` became a built-in type and if so, why they decided against it.

---

(Note: I know that some people are of the opinion that assignment should not use 
`=` and that `++` and `+=` are not useful operators but design flaws; let&#39;s just assume I&#39;m happy with them and focus on why they would not extend to bools).


  [1]: https://en.cppreference.com/w/cpp/language/operator_assignment

Content Type	Original Author	Original Content on Stackoverflow
Question	Rolf Bartstra	View Question on Stackoverflow
Solution 1 - Python	squid	View Answer on Stackoverflow

Inverting a numpy boolean array using ~

Python Problem Overview

Python Solutions

Solution 1 - Python

Insert 2 million rows into SQL Server quickly

SQL Performance UNION vs OR

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