No it won&#39;t become redundant in Python 3.7 because `OrderedDict` is not just a `dict` that retains insertion order, it also offers an order dependent method, [`OrderedDict.move_to_end()`][1], and supports [`reversed()`][2] iteration*. 

Moreover, equality comparisons with `OrderedDict` are order sensitive and this is still not the case for `dict` in Python 3.7, for example:


    &gt;&gt;&gt; OrderedDict([(1,1), (2,2)]) == OrderedDict([(2,2), (1,1)]) 
    False
    &gt;&gt;&gt; dict([(1,1), (2,2)]) == dict([(2,2), (1,1)]) 
    True


Two relevant questions [here][3] and [here][4].

\* Support for `reversed()` iteration of regular Python `dict` is added for Python 3.8, see [issue33462][5]


  [1]: https://docs.python.org/3.7/library/collections.html#collections.OrderedDict.move_to_end
  [2]: https://docs.python.org/3.7/library/functions.html#reversed
  [3]: https://stackoverflow.com/questions/39980323/are-dictionaries-ordered-in-python-3-6
  [4]: https://stackoverflow.com/questions/49159238/why-does-the-kwargs-mapping-compare-equal-with-a-differently-ordered-ordereddi
  [5]: https://bugs.python.org/issue33462

How are the `min-content` and `max-content` values calculated in CSS? 

And what does intrinsic dimension mean?

How do min-content and max-content work?

I&#39;m using jest and enzyme with my create-react-app project. When I run `npm test`, I get an output that shows the names of the test files that passed but I&#39;d like the output to also include the names of the tests. 

Example: 

Button.test.js

    it (&#39;renders button&#39;, () =&gt; {
        const button = shallow(&lt;Button type=&quot;save&quot;/&gt;);
        expect(toJson(button)).toMatchSnapshot();
    });

Right now when I run npm test the output is just: 
&gt; PASS  src/Button.test.js&quot;

and the number of passed and failed tests (when the tests are successful). I would like the output to include &quot;renders button&quot; and any other test descriptions (like how the output looks when an rspec test is run). 

Is there an option to show all test descriptions when I run jest tests?

From the [Python 3.7 changelog][1]:
&gt; the insertion-order preservation nature of [dict][2] objects [has been declared][3] to be an official part of the Python language spec.

Would this mean that [`OrderedDict`][4] will become redundant? The only use I can think of it will be to maintain backwards compatibility with older versions of Python which don&#39;t preserve insertion-order for normal dictionaries.


  [1]: https://docs.python.org/3.7/whatsnew/3.7.html
  [2]: https://docs.python.org/3.7/library/stdtypes.html#typesmapping
  [3]: https://mail.python.org/pipermail/python-dev/2017-December/151283.html
  [4]: https://docs.python.org/3.7/library/collections.html#collections.OrderedDict

Will OrderedDict become redundant in Python 3.7?

<p>From the <a href="https://docs.python.org/3.7/whatsnew/3.7.html" target="_blank" rel="noopener noreferrer">Python 3.7 changelog</a>:
> the insertion-order preservation nature of <a href="https://docs.python.org/3.7/library/stdtypes.html#typesmapping" target="_blank" rel="noopener noreferrer">dict</a> objects <a href="https://mail.python.org/pipermail/python-dev/2017-December/151283.html" target="_blank" rel="noopener noreferrer">has been declared</a> to be an official part of the Python language spec.</p>
<p>Would this mean that <a href="https://docs.python.org/3.7/library/collections.html#collections.OrderedDict" target="_blank" rel="noopener noreferrer"><code>OrderedDict</code></a> will become redundant? The only use I can think of it will be to maintain backwards compatibility with older versions of Python which don't preserve insertion-order for normal dictionaries.</p>


I have the following string : 

    a = &quot;/home/user/Downloads/repo/test.txt&quot;

My goal is just to create a string which contains only `test`, hwo can I do this ?

actually a comes from 

    f = tkFileDialog.asksaveasfile(mode=&#39;w&#39;, defaultextension=&quot;.txt&quot;)

and a is equal to `a = f.name`

but I realized `f.name` does not give me just the name of the file.

How to get only the name of the path with python?

***What I am doing***  
I am training and using a convolutional neuron network (CNN) for image-classification using Keras with Tensorflow-gpu as backend.

***What I am using***   
- PyCharm Community 2018.1.2  
- both Python 2.7 and 3.5 (but not both at a time)   
- Ubuntu 16.04   
- Keras 2.2.0   
- Tensorflow-GPU 1.8.0 as backend


***What I want to know***   
In many codes I see people using

    from keras import backend as K 

    # Do some code, e.g. train and save model

    K.clear_session()
or deleting the model after using it:

    del model

The keras documentation says regarding `clear_session`: &quot;Destroys the current TF graph and creates a new one. Useful to avoid clutter from old models / layers.&quot; - https://keras.io/backend/
  
What is the point of doing that and should I do it as well? When loading or creating a new model my model gets overwritten anyway, so why bother?

What do I need K.clear_session() and del model for (Keras with Tensorflow-gpu)?

I have a data frame that stores store name and daily sales count. I am trying to insert this to Salesforce using the Python script below. 

However, I get the following error:

    TypeError: Object of type &#39;int64&#39; is not JSON serializable

Below, there is the view of the data frame.

    Storename,Count
    Store A,10
    Store B,12
    Store C,5

I use the following code to insert it to Salesforce.

    update_list = []
    for i in range(len(store)):
        update_data = {
            &#39;name&#39;: store[&#39;entity_name&#39;].iloc[i],
            &#39;count__c&#39;: store[&#39;count&#39;].iloc[i] 
        }
        update_list.append(update_data)
    
    sf_data_cursor = sf_datapull.salesforce_login()
    sf_data_cursor.bulk.Account.update(update_list)

I get the error when the last line above gets executed.

How do I fix this?

Python - TypeError: Object of type &#39;int64&#39; is not JSON serializable

mypy is really handy and catches a lot of bugs, but when I write &quot;scientific&quot; applications, I often end up doing:

    def my_func(number: Union[float, int]):
        # Do something

```number``` is either a float or int, depending on the user&#39;s input. Is there an official way to do that?

mypy, type hint: Union[float, int] -&gt; is there a Number type?

How does [`torch.nn.Parameter()`](https://pytorch.org/docs/stable/generated/torch.nn.parameter.Parameter.html#torch.nn.parameter.Parameter) work?

Understanding torch.nn.Parameter

Today, in an interview, the CTO asked me what looks like an easy question, 

What does this statement return ? :

    None is None is None

I thought Python executed the first operation `None is None` and would return `True`. After that, it would compare `True is None` which would return `False`. But, to my surprise, the right answer is `True`. I am trying to find answer to this question, but after a couple of days searching I didn&#39;t find anything. Can someone explain why this happens?

Why does `None is None is None` return True?

I want to write a function that randomly picks elements from a training set, based on the **bin probabilities** provided. I **divide the set indices to 11 bins**, then create **custom probabilities** for them.

    bin_probs = [0.5, 0.3, 0.15, 0.04, 0.0025, 0.0025, 0.001, 0.001, 0.001, 0.001, 0.001]
    
    X_train = list(range(2000000))
    
    train_probs = bin_probs * int(len(X_train) / len(bin_probs)) # extend probabilities across bin elements
    train_probs.extend([0.001]*(len(X_train) - len(train_probs))) # a small fix to match number of elements
    train_probs = train_probs/np.sum(train_probs) # normalize
    indices = np.random.choice(range(len(X_train)), replace=False, size=50000, p=train_probs)
    out_images = X_train[indices.astype(int)] # this is where I get the error

I get the following error:

    TypeError: only integer scalar arrays can be converted to a scalar index with 1D numpy indices array

I find this weird, since I already checked the array of indices that I have created. It is **1-D**, it is **integer**, and it is **scalar**.

What am I missing?

Note : I tried to pass `indices` with `astype(int)`. Same error.

TypeError: only integer scalar arrays can be converted to a scalar index with 1D numpy indices array

    import pandas as pd
    df = pd.read_csv(&#39;https://query.data.world/s/Hfu_PsEuD1Z_yJHmGaxWTxvkz7W_b0&#39;)
    percent= 100*(len(df.loc[:,df.isnull().sum(axis=0)&gt;=1 ].index) / len(df.index))
    print(round(percent,2))

input is https://query.data.world/s/Hfu_PsEuD1Z_yJHmGaxWTxvkz7W_b0

and the output should be

    Ord_id                 0.00
    Prod_id                0.00
    Ship_id                0.00
    Cust_id                0.00
    Sales                  0.24
    Discount               0.65
    Order_Quantity         0.65
    Profit                 0.65
    Shipping_Cost          0.65
    Product_Base_Margin    1.30
    dtype: float64

Find out the percentage of missing values in each column in the given dataset

I have Python 3.7.0 and I installed PyQt5 with this command:

    pip install PyQt5

I have returned this error:

        main.py&quot;, line 4, in &lt;module&gt;
        from PyQt5.QtWebEngineWidgets import *
    ModuleNotFoundError: No module named &#39;PyQt5.QtWebEngineWidgets&#39;

In Eclipse I have this configuration:

[![enter image description here][1]][1]


What may be wrong?

Thanks

  [1]: https://i.stack.imgur.com/J7p4J.png

Python 3.7.0 No module named &#39;PyQt5.QtWebEngineWidgets&#39;

Do dataclasses have a way to add additional initialization aside from what is provided with its built in initializer, without overriding it? Specifically, I want to check some values of a list of integers that is one of the fields in the data class upon initialization.

Python 3 dataclass initialization

In Dart language how to get MAP keys by values? 

I have a Map like;

    {
      &quot;01&quot;: &quot;USD&quot;,
      &quot;17&quot;: &quot;GBP&quot;,
      &quot;33&quot;: &quot;EUR&quot;
    }

And I need to use values to get keys. How do I do that?

How to get Map keys by values in Dart?

I have a dataframe ```df``` as follows:

    | name  | coverage |
    |-------|----------|
    | Jason | 25.1     |
I want to convert it to a dictionary.
I used the following command in ```pandas``` :

    dict=df.to_dict()
The output of ```dict``` gave me the following:

    {&#39;coverage&#39;: {0: 25.1}, &#39;name&#39;: {0: &#39;Jason&#39;}} 
I do not want the ```0``` in my output. I believe this is captured because of the column index in my dataframe ```df```.
What can I do to eliminate ```0``` in my output
( I do not want index to be captured.) expected output :

    {&#39;coverage&#39;: 25.1, &#39;name&#39;: &#39;Jason&#39;} 



How to convert dataframe to dictionary in pandas WITHOUT index

Consider following example.

    enum DialogType {
        Options,
        Help
    }
    
    class Dialog { 
        test() : string {
            return &quot;&quot;;
        }
    }
    
    class Greeter {
    
        openDialogs: { [key in DialogType]: Dialog | undefined } = {
            0: undefined,
            1: undefined
        };
    
        getDialog(t: DialogType) {
            return this.openDialogs[t];
        }
    }
    
    const greeter = new Greeter();
    const d = greeter.getDialog(DialogType.Help);
    if (d) document.write(d.test());

[Also in playground][1]

There are 3 issues/questions with it:

1. Why I cannot omit properties in my initializer literal, even though I declare properties as &#39;| undefined&#39;
2. Why I cannot use &#39;DialogType.Options&#39; as type key, and have to use hardcoded number instead?
3. Why do I have to use &#39;key in DialogType&#39; instead of &#39;key: DialogType&#39;? (Or can I? )


  [1]: https://www.typescriptlang.org/play/#src=enum%20DialogType%20%7B%0D%0A%20%20%20%20Options%2C%0D%0A%20%20%20%20Help%0D%0A%7D%0D%0A%0D%0Aclass%20Dialog%20%7B%20%0D%0A%20%20%20%20test()%20%3A%20string%20%7B%0D%0A%20%20%20%20%20%20%20%20return%20%22%22%3B%0D%0A%20%20%20%20%7D%0D%0A%7D%0D%0A%0D%0Aclass%20Greeter%20%7B%0D%0A%0D%0A%20%20%20%20openDialogs%3A%20%7B%20%5Bkey%20in%20DialogType%5D%3A%20Dialog%20%7C%20undefined%20%7D%20%3D%20%7B%0D%0A%20%20%20%20%20%20%20%200%3A%20undefined%2C%0D%0A%20%20%20%20%20%20%20%201%3A%20undefined%0D%0A%20%20%20%20%7D%3B%0D%0A%0D%0A%20%20%20%20getDialog(t%3A%20DialogType)%20%7B%0D%0A%20%20%20%20%20%20%20%20return%20this.openDialogs%5Bt%5D%3B%0D%0A%20%20%20%20%7D%0D%0A%7D%0D%0A%0D%0Aconst%20greeter%20%3D%20new%20Greeter()%3B%0D%0Aconst%20d%20%3D%20greeter.getDialog(DialogType.Help)%3B%0D%0Aif%20(d)%20document.write(d.test())%3B

How to use enum as index key type in typescript?

This seems trivial, but I cannot find a built-in or simple way to determine if two dictionaries are equal.

What I want is:

    a = {&#39;foo&#39;: 1, &#39;bar&#39;: 2}
    b = {&#39;foo&#39;: 1, &#39;bar&#39;: 2}
    c = {&#39;bar&#39;: 2, &#39;foo&#39;: 1}
    d = {&#39;foo&#39;: 2, &#39;bar&#39;: 1}
    e = {&#39;foo&#39;: 1, &#39;bar&#39;: 2, &#39;baz&#39;:3}
    f = {&#39;foo&#39;: 1}

    equal(a, b)   # True 
    equal(a, c)   # True  - order does not matter
    equal(a, d)   # False - values do not match
    equal(a, e)   # False - e has additional elements
    equal(a, f)   # False - a has additional elements

I could make a short looping script, but I cannot imagine that mine is such a unique use case.

Python3 Determine if two dictionaries are equal

This might be a very simple question but I am having trouble finding an answer.
I have a object/map that I would not like to iterate but access a specific key/value at an index.

For example:

    var _results = {
      &#39;Key_1&#39; : &#39;Value_1&#39;,
      &#39;Key_2&#39; : &#39;Value_2&#39;, 
    };

How would I access the index[1]&#39;s key_2 and value_2?

I&#39;ve tried `_results[index]`, `_results[index].value`, `_results[index].key` and `_results[index].toString()` but all returning null.

Flutter/Dart: How to access a single entry in a map/object

I&#39;ve been reading up on Python 3.7&#39;s dataclass as an alternative to namedtuples (what I typically use when having to group data in a structure). I was wondering if dataclass is compatible with the property decorator to define getter and setter functions for the data elements of the dataclass. If so, is this described somewhere? Or are there examples available? 

Dataclasses and property decorator

I&#39;m currently trying my hands on the new dataclass constructions introduced in Python 3.7. I am currently stuck on trying to do some inheritance of a parent class. It looks like the order of the arguments are botched by my current approach such that the bool parameter in the child class is passed before the other parameters. This is causing a type error.

    from dataclasses import dataclass
    
    @dataclass
    class Parent:
        name: str
        age: int
        ugly: bool = False
    
        def print_name(self):
            print(self.name)
    
        def print_age(self):
            print(self.age)
    
        def print_id(self):
            print(f&#39;The Name is {self.name} and {self.name} is {self.age} year old&#39;)
    
    @dataclass
    class Child(Parent):
        school: str
        ugly: bool = True
    

    jack = Parent(&#39;jack snr&#39;, 32, ugly=True)
    jack_son = Child(&#39;jack jnr&#39;, 12, school = &#39;havard&#39;, ugly=True)
    
    jack.print_id()
    jack_son.print_id()


When I run this code I get this `TypeError`:

    TypeError: non-default argument &#39;school&#39; follows default argument

How do I fix this?

Class inheritance in Python 3.7 dataclasses

Long story short
----------------

[PEP-557][1] introduced data classes into Python standard library, that basically can fill the same role as `collections.namedtuple` and `typing.NamedTuple`. And now I&#39;m wondering how to separate the use cases in which namedtuple is still a better solution.

Data classes advantages over NamedTuple
----------------------------------------

Of course, all the credit goes to `dataclass` if we need:

 - mutable objects
 - inheritance support
 - `property` decorators, manageable attributes
 - generated method definitions out of the box or customizable method definitions

Data classes advantages are briefly explained in the same PEP: [Why not just use namedtuple][2].

Q: In which cases namedtuple is still a better choice?
---------------------------------------------------

But how about an opposite question for namedtuples: why not just use dataclass?
I guess probably namedtuple is better from the performance standpoint but found no confirmation on that yet.

Example
-------

Let&#39;s consider the following situation:

We are going to store pages dimensions in a small container with statically defined fields, type hinting and named access. No further hashing, comparing and so on are needed.

**NamedTuple approach:**

    from typing import NamedTuple
    
    PageDimensions = NamedTuple(&quot;PageDimensions&quot;, [(&#39;width&#39;, int), (&#39;height&#39;, int)])

**DataClass approach:**

    from dataclasses import dataclass
    
    @dataclass
    class PageDimensions:
        width: int
        height: int

Which solution is preferable and why?

P.S. the question isn&#39;t a duplicate of [that one][3] in any way, because here I&#39;m asking about **the cases** in which namedtuple is better, not about **the difference** (I&#39;ve checked docs and sources before asking)


  [1]: https://www.python.org/dev/peps/pep-0557/
  [2]: https://www.python.org/dev/peps/pep-0557/#why-not-just-use-namedtuple
  [3]: https://stackoverflow.com/questions/47955263

Data Classes vs typing.NamedTuple primary use cases

I am trying to run this code:

    import web
    
    urls = (
    	&#39;/&#39;, &#39;index&#39;
    )
    
    if __name__ == &quot;__main__&quot;:
        app = web.application(urls, globals())
        app.run()
But it gives me this error everytime

    C:\Users\aidke\Desktop&gt;python app.py
    Traceback (most recent call last):
      File &quot;C:\Users\aidke\AppData\Local\Programs\Python\Python37-32\lib\site-packages\web\utils.py&quot;, line 526, in take
        yield next(seq)
    StopIteration
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File &quot;app.py&quot;, line 14, in &lt;module&gt;
        app = web.application(urls, globals())
      File &quot;C:\Users\aidke\AppData\Local\Programs\Python\Python37-32\lib\site-packages\web\application.py&quot;, line 62, in __init__
        self.init_mapping(mapping)
      File &quot;C:\Users\aidke\AppData\Local\Programs\Python\Python37-32\lib\site-packages\web\application.py&quot;, line 130, in init_mapping
        self.mapping = list(utils.group(mapping, 2))
      File &quot;C:\Users\aidke\AppData\Local\Programs\Python\Python37-32\lib\site-packages\web\utils.py&quot;, line 531, in group
        x = list(take(seq, size))
    RuntimeError: generator raised StopIteration

I tried someone else&#39;s code and the exact same thing happened.  Additionally I tried reinstalling web.py(experimental) but it still didn&#39;t work.

&quot;RuntimeError: generator raised StopIteration&quot; every time I try to run app

I&#39;m trying to install tensorflow onto a Mac with Python3.7. However, I&#39;m getting the error:

    $ pip3 -v install tensorflow
    ...    
        Skipping link https://files.pythonhosted.org/packages/56/7a/c6bca0fe52a94ca508731d8b139e7dbd5a36cddc64c19f422f97e5a853e8/tensorflow-1.10.0rc1-cp36-cp36m-win_amd64.whl#sha256=3ab24374888d6a13d55ce2e3cf4ba0c9cd6f824723313db5322512087525cb78 (from https://pypi.org/simple/tensorflow/); it is not compatible with this Python
      Could not find a version that satisfies the requirement tensorflow (from versions: )
    Cleaning up...
    Removed build tracker &#39;/private/var/folders/4n/9342s4wd3jv0qzwjz8rxrygr0000gp/T/pip-req-tracker-3p60r2lo&#39;

    No matching distribution found for tensorflow

From what I can gather this is happening because tensorflow doesn&#39;t yet support Python3.7. As a workaround I want to install Python3.6 alongside 3.7 and then install tensorflow to that version. However, I&#39;m new to Mac and not sure of the correct way to do this without potentially messing with the preexisting Python version. 

I&#39;ve tried using brew, but it looks like Python3 is as specific as it gets. What is the correct way to do what I&#39;m after?

Content Type	Original Author	Original Content on Stackoverflow
Question	James Hiew	View Question on Stackoverflow
Solution 1 - Python	Chris_Rands	View Answer on Stackoverflow

Will OrderedDict become redundant in Python 3.7?

Python Problem Overview

Python Solutions

Solution 1 - Python

Is there an option to show all test descriptions when I run jest tests?

How do min-content and max-content work?

Attributions