Javascript Enum Tostring

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A Java enumeration is a data type that stores a list of constants. You can create an ENUM object using the enum keyword. Enum constants appear in the form of a separate list by commas in a set of braces.

An enum, which is the abbreviation for enumeration, is a data type that has a fixed set of possible values.

Enumerations are useful if you are working with a value that should only contain a specific value contained in a list of values. For example, an ENUM would be used if you want to store a list of the sizes of coffee sold in a store.

This tutorial will cover the basics of enumeration in Java. We will refer to some examples of an ENUM class in a Java program to help you get started.

Java Enum Syntax

A Java ENUM represents a list of constants. A variable assigned by an enumeration can have only one value that appears in the enumeration. Enumerations help developers store data that they know will not change.

Suppose you decide that a Java variables store employee compensation degrees can only have one of five values. Or, decide that a variable that store employee contracts can only store part-time, full-time, or zero hours. In these cases, you need to use an ENUM to store the data.

enumerations are declared using "ENUM" kind. The syntax of "ENUM " word - key:

Let’s analyze this syntax:

  • ENUM indicates our program that we want to declare an enumeration .
  • name is the name of our ENUM.
  • VALUE1, VALUE2, VALUE3 are the set of constant values ‚Äã‚Äãthat our stores enum. These values ‚Äã‚Äãare usually written in upper case.

Why use Enum in Java?

Using ENUM allows you to express an algorithm in a way that is more readable both for you and for the computer.

Writing an ENUM tells the computer that a variable cannot have a specific number of values. It also tells you, the programmer, that this is the case, which will make your code easier to understand. If you see a variable that uses an ENUM, you know that the variable can only have one of a limited number of values ‚Äã‚Äã

In addition, the enumerations allow you to use constants more efficiently. in fact, ENUM was introduced to replace the int constants in Java, which spanned multiple lines and were difficult to read. Here is an example of an old int constant in Java:

Our code takes five lines to declare these constants. But by using an ENUM, we can reduce our code to three lines. In the following example, we declare a list of enum constants:

Our code takes five lines to declare these constants. But by using an ENUM, we can reduce our code to three lines. In the following example, we declare a list of enum constants:

 AirplaneClasses class {Economy, FIRST_CLASS} 

This code is simpler and easier to read.

Declaring Java Enum

We are creating an application that waiters can use to send coffee to baristas in a coffee shop.

When a barista enters a value for the size of the drink, we want there to be only three possible options. These options are: small, regular, and LARGE. We could use an ENUM to limit the possible sizes of a drink to these options:

In this example, we have declared an ENUM called Sizes which has three possible values. Now that we have declared an ENUM, we can refer to its values ‚Äã‚Äãin our code.

Java Enum Example

We write a program that prints the size of the coffee a customer has ordered from the console. This value will be read by the bartender preparing the customer’s drink

We could use the following code to print the size of the coffee a customer ordered on the console:

Our code returns:.

This cafe must be small

First, we declare an ENUM called Sizes. Power have three values: SMALL, REGULAR or LARGE. Next, we declared a class called PrintSize. This class accepts the customer’s drink size and prints the glass size to the console.

In our main program, we declare an object called order173, ‚" which uses the PrintSize class. We went through our code Java parameter Sizes.SMALL. This tells our program to assign the value SMALL to the coffeeSize variable in the PrintSize class.

Next, we use order173.placeOrder () to run the code in the switch case statement in the PrintSize class. This evaluates the variable value "coffeeSize" against three cases. A message is printed on the console based on the size of the coffee a customer has ordered.

We indicated that the customer ordered a small coffee. Our code impressions "This coffee should be weak." » on the console.

If you are looking to learn more about Java switch case statements, you can read them in our tutorial on the switch statement Java < / a>.

Java Enum Methods

The Java Enum class has a number of predefined methods used to extract and manipulate values using the ENUM class. We have broken five of the most commonly used enum methods below

compareTo ()

compareTo () compares constants in a lexicographic ENUM and returns the difference between their ordinal values. Here is an example of compareTo () used with an ENUM value from our previous example:

Our code returns the difference between the SMALL and GRAND tags according to their value In this case , our code returns:

-2

toString ()

toString () converts the name of an ENUM to a string Here is an example of toString () used to convert the ENUM LARGE value to a string:.

Our code returns:

"LARGE"

name ()

the name () method returns the name used to define a constant in an enum class. Here is an example of the name of the method () used to return the defined name of the regular coffee size:

Our code returns:

"regular"

Values ‚Äã‚Äã()

The values of the process yields (a) Java array that stores all the constants in an enum. Here’s an example of the values ‚Äã‚Äã() method in action:

Sizes [] = sizeList Sizes.value s ();

valueOf ()

valueOf () accepts a string and returns the constant ENUM, which has the same name. So if we wanted to retrieve the constant enum with the name REGULAR, we could do it using this code:

Our code returns:

REGULAR

Conclusion

A ENUM, short for enumeration, is a Java data type that has a fixed set of values.

Enumerations are useful if you are working with variables that should only be able to store one in a selected range of values.

After practicing what you have read in this tutorial, you will be an expert at using enumerations in Java. To learn more about coding in Java, see our complete guide How to code Java .

Javascript Enum Tostring exp: Questions

exp

How do I merge two dictionaries in a single expression (taking union of dictionaries)?

5 answers

Carl Meyer By Carl Meyer

I have two Python dictionaries, and I want to write a single expression that returns these two dictionaries, merged (i.e. taking the union). The update() method would be what I need, if it returned its result instead of modifying a dictionary in-place.

>>> x = {"a": 1, "b": 2}
>>> y = {"b": 10, "c": 11}
>>> z = x.update(y)
>>> print(z)
None
>>> x
{"a": 1, "b": 10, "c": 11}

How can I get that final merged dictionary in z, not x?

(To be extra-clear, the last-one-wins conflict-handling of dict.update() is what I"m looking for as well.)

5839

Answer #1

How can I merge two Python dictionaries in a single expression?

For dictionaries x and y, z becomes a shallowly-merged dictionary with values from y replacing those from x.

  • In Python 3.9.0 or greater (released 17 October 2020): PEP-584, discussed here, was implemented and provides the simplest method:

    z = x | y          # NOTE: 3.9+ ONLY
    
  • In Python 3.5 or greater:

    z = {**x, **y}
    
  • In Python 2, (or 3.4 or lower) write a function:

    def merge_two_dicts(x, y):
        z = x.copy()   # start with keys and values of x
        z.update(y)    # modifies z with keys and values of y
        return z
    

    and now:

    z = merge_two_dicts(x, y)
    

Explanation

Say you have two dictionaries and you want to merge them into a new dictionary without altering the original dictionaries:

x = {"a": 1, "b": 2}
y = {"b": 3, "c": 4}

The desired result is to get a new dictionary (z) with the values merged, and the second dictionary"s values overwriting those from the first.

>>> z
{"a": 1, "b": 3, "c": 4}

A new syntax for this, proposed in PEP 448 and available as of Python 3.5, is

z = {**x, **y}

And it is indeed a single expression.

Note that we can merge in with literal notation as well:

z = {**x, "foo": 1, "bar": 2, **y}

and now:

>>> z
{"a": 1, "b": 3, "foo": 1, "bar": 2, "c": 4}

It is now showing as implemented in the release schedule for 3.5, PEP 478, and it has now made its way into the What"s New in Python 3.5 document.

However, since many organizations are still on Python 2, you may wish to do this in a backward-compatible way. The classically Pythonic way, available in Python 2 and Python 3.0-3.4, is to do this as a two-step process:

z = x.copy()
z.update(y) # which returns None since it mutates z

In both approaches, y will come second and its values will replace x"s values, thus b will point to 3 in our final result.

Not yet on Python 3.5, but want a single expression

If you are not yet on Python 3.5 or need to write backward-compatible code, and you want this in a single expression, the most performant while the correct approach is to put it in a function:

def merge_two_dicts(x, y):
    """Given two dictionaries, merge them into a new dict as a shallow copy."""
    z = x.copy()
    z.update(y)
    return z

and then you have a single expression:

z = merge_two_dicts(x, y)

You can also make a function to merge an arbitrary number of dictionaries, from zero to a very large number:

def merge_dicts(*dict_args):
    """
    Given any number of dictionaries, shallow copy and merge into a new dict,
    precedence goes to key-value pairs in latter dictionaries.
    """
    result = {}
    for dictionary in dict_args:
        result.update(dictionary)
    return result

This function will work in Python 2 and 3 for all dictionaries. e.g. given dictionaries a to g:

z = merge_dicts(a, b, c, d, e, f, g) 

and key-value pairs in g will take precedence over dictionaries a to f, and so on.

Critiques of Other Answers

Don"t use what you see in the formerly accepted answer:

z = dict(x.items() + y.items())

In Python 2, you create two lists in memory for each dict, create a third list in memory with length equal to the length of the first two put together, and then discard all three lists to create the dict. In Python 3, this will fail because you"re adding two dict_items objects together, not two lists -

>>> c = dict(a.items() + b.items())
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unsupported operand type(s) for +: "dict_items" and "dict_items"

and you would have to explicitly create them as lists, e.g. z = dict(list(x.items()) + list(y.items())). This is a waste of resources and computation power.

Similarly, taking the union of items() in Python 3 (viewitems() in Python 2.7) will also fail when values are unhashable objects (like lists, for example). Even if your values are hashable, since sets are semantically unordered, the behavior is undefined in regards to precedence. So don"t do this:

>>> c = dict(a.items() | b.items())

This example demonstrates what happens when values are unhashable:

>>> x = {"a": []}
>>> y = {"b": []}
>>> dict(x.items() | y.items())
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unhashable type: "list"

Here"s an example where y should have precedence, but instead the value from x is retained due to the arbitrary order of sets:

>>> x = {"a": 2}
>>> y = {"a": 1}
>>> dict(x.items() | y.items())
{"a": 2}

Another hack you should not use:

z = dict(x, **y)

This uses the dict constructor and is very fast and memory-efficient (even slightly more so than our two-step process) but unless you know precisely what is happening here (that is, the second dict is being passed as keyword arguments to the dict constructor), it"s difficult to read, it"s not the intended usage, and so it is not Pythonic.

Here"s an example of the usage being remediated in django.

Dictionaries are intended to take hashable keys (e.g. frozensets or tuples), but this method fails in Python 3 when keys are not strings.

>>> c = dict(a, **b)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: keyword arguments must be strings

From the mailing list, Guido van Rossum, the creator of the language, wrote:

I am fine with declaring dict({}, **{1:3}) illegal, since after all it is abuse of the ** mechanism.

and

Apparently dict(x, **y) is going around as "cool hack" for "call x.update(y) and return x". Personally, I find it more despicable than cool.

It is my understanding (as well as the understanding of the creator of the language) that the intended usage for dict(**y) is for creating dictionaries for readability purposes, e.g.:

dict(a=1, b=10, c=11)

instead of

{"a": 1, "b": 10, "c": 11}

Response to comments

Despite what Guido says, dict(x, **y) is in line with the dict specification, which btw. works for both Python 2 and 3. The fact that this only works for string keys is a direct consequence of how keyword parameters work and not a short-coming of dict. Nor is using the ** operator in this place an abuse of the mechanism, in fact, ** was designed precisely to pass dictionaries as keywords.

Again, it doesn"t work for 3 when keys are not strings. The implicit calling contract is that namespaces take ordinary dictionaries, while users must only pass keyword arguments that are strings. All other callables enforced it. dict broke this consistency in Python 2:

>>> foo(**{("a", "b"): None})
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: foo() keywords must be strings
>>> dict(**{("a", "b"): None})
{("a", "b"): None}

This inconsistency was bad given other implementations of Python (PyPy, Jython, IronPython). Thus it was fixed in Python 3, as this usage could be a breaking change.

I submit to you that it is malicious incompetence to intentionally write code that only works in one version of a language or that only works given certain arbitrary constraints.

More comments:

dict(x.items() + y.items()) is still the most readable solution for Python 2. Readability counts.

My response: merge_two_dicts(x, y) actually seems much clearer to me, if we"re actually concerned about readability. And it is not forward compatible, as Python 2 is increasingly deprecated.

{**x, **y} does not seem to handle nested dictionaries. the contents of nested keys are simply overwritten, not merged [...] I ended up being burnt by these answers that do not merge recursively and I was surprised no one mentioned it. In my interpretation of the word "merging" these answers describe "updating one dict with another", and not merging.

Yes. I must refer you back to the question, which is asking for a shallow merge of two dictionaries, with the first"s values being overwritten by the second"s - in a single expression.

Assuming two dictionaries of dictionaries, one might recursively merge them in a single function, but you should be careful not to modify the dictionaries from either source, and the surest way to avoid that is to make a copy when assigning values. As keys must be hashable and are usually therefore immutable, it is pointless to copy them:

from copy import deepcopy

def dict_of_dicts_merge(x, y):
    z = {}
    overlapping_keys = x.keys() & y.keys()
    for key in overlapping_keys:
        z[key] = dict_of_dicts_merge(x[key], y[key])
    for key in x.keys() - overlapping_keys:
        z[key] = deepcopy(x[key])
    for key in y.keys() - overlapping_keys:
        z[key] = deepcopy(y[key])
    return z

Usage:

>>> x = {"a":{1:{}}, "b": {2:{}}}
>>> y = {"b":{10:{}}, "c": {11:{}}}
>>> dict_of_dicts_merge(x, y)
{"b": {2: {}, 10: {}}, "a": {1: {}}, "c": {11: {}}}

Coming up with contingencies for other value types is far beyond the scope of this question, so I will point you at my answer to the canonical question on a "Dictionaries of dictionaries merge".

Less Performant But Correct Ad-hocs

These approaches are less performant, but they will provide correct behavior. They will be much less performant than copy and update or the new unpacking because they iterate through each key-value pair at a higher level of abstraction, but they do respect the order of precedence (latter dictionaries have precedence)

You can also chain the dictionaries manually inside a dict comprehension:

{k: v for d in dicts for k, v in d.items()} # iteritems in Python 2.7

or in Python 2.6 (and perhaps as early as 2.4 when generator expressions were introduced):

dict((k, v) for d in dicts for k, v in d.items()) # iteritems in Python 2

itertools.chain will chain the iterators over the key-value pairs in the correct order:

from itertools import chain
z = dict(chain(x.items(), y.items())) # iteritems in Python 2

Performance Analysis

I"m only going to do the performance analysis of the usages known to behave correctly. (Self-contained so you can copy and paste yourself.)

from timeit import repeat
from itertools import chain

x = dict.fromkeys("abcdefg")
y = dict.fromkeys("efghijk")

def merge_two_dicts(x, y):
    z = x.copy()
    z.update(y)
    return z

min(repeat(lambda: {**x, **y}))
min(repeat(lambda: merge_two_dicts(x, y)))
min(repeat(lambda: {k: v for d in (x, y) for k, v in d.items()}))
min(repeat(lambda: dict(chain(x.items(), y.items()))))
min(repeat(lambda: dict(item for d in (x, y) for item in d.items())))

In Python 3.8.1, NixOS:

>>> min(repeat(lambda: {**x, **y}))
1.0804965235292912
>>> min(repeat(lambda: merge_two_dicts(x, y)))
1.636518670246005
>>> min(repeat(lambda: {k: v for d in (x, y) for k, v in d.items()}))
3.1779992282390594
>>> min(repeat(lambda: dict(chain(x.items(), y.items()))))
2.740647904574871
>>> min(repeat(lambda: dict(item for d in (x, y) for item in d.items())))
4.266070580109954
$ uname -a
Linux nixos 4.19.113 #1-NixOS SMP Wed Mar 25 07:06:15 UTC 2020 x86_64 GNU/Linux

Resources on Dictionaries

5839

Answer #2

In your case, what you can do is:

z = dict(list(x.items()) + list(y.items()))

This will, as you want it, put the final dict in z, and make the value for key b be properly overridden by the second (y) dict"s value:

>>> x = {"a":1, "b": 2}
>>> y = {"b":10, "c": 11}
>>> z = dict(list(x.items()) + list(y.items()))
>>> z
{"a": 1, "c": 11, "b": 10}

If you use Python 2, you can even remove the list() calls. To create z:

>>> z = dict(x.items() + y.items())
>>> z
{"a": 1, "c": 11, "b": 10}

If you use Python version 3.9.0a4 or greater, then you can directly use:

x = {"a":1, "b": 2}
y = {"b":10, "c": 11}
z = x | y
print(z)
{"a": 1, "c": 11, "b": 10}

5839

Answer #3

An alternative:

z = x.copy()
z.update(y)

Javascript Enum Tostring iat: Questions

iat

InsecurePlatformWarning: A true SSLContext object is not available. This prevents urllib3 from configuring SSL appropriately

3 answers

Tried to perform REST GET through python requests with the following code and I got error.

Code snip:

import requests
header = {"Authorization": "Bearer..."}
url = az_base_url + az_subscription_id + "/resourcegroups/Default-Networking/resources?" + az_api_version
r = requests.get(url, headers=header)

Error:

/usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/util/ssl_.py:79: 
          InsecurePlatformWarning: A true SSLContext object is not available. 
          This prevents urllib3 from configuring SSL appropriately and may cause certain SSL connections to fail. 
          For more information, see https://urllib3.readthedocs.org/en/latest/security.html#insecureplatformwarning.
  InsecurePlatformWarning

My python version is 2.7.3. I tried to install urllib3 and requests[security] as some other thread suggests, I still got the same error.

Wonder if anyone can provide some tips?

334

Answer #1

The docs give a fair indicator of what"s required., however requests allow us to skip a few steps:

You only need to install the security package extras (thanks @admdrew for pointing it out)

$ pip install requests[security]

or, install them directly:

$ pip install pyopenssl ndg-httpsclient pyasn1

Requests will then automatically inject pyopenssl into urllib3


If you"re on ubuntu, you may run into trouble installing pyopenssl, you"ll need these dependencies:

$ apt-get install libffi-dev libssl-dev

iat

Dynamic instantiation from string name of a class in dynamically imported module?

3 answers

In python, I have to instantiate certain class, knowing its name in a string, but this class "lives" in a dynamically imported module. An example follows:

loader-class script:

import sys
class loader:
  def __init__(self, module_name, class_name): # both args are strings
    try:
      __import__(module_name)
      modul = sys.modules[module_name]
      instance = modul.class_name() # obviously this doesn"t works, here is my main problem!
    except ImportError:
       # manage import error

some-dynamically-loaded-module script:

class myName:
  # etc...

I use this arrangement to make any dynamically-loaded-module to be used by the loader-class following certain predefined behaviours in the dyn-loaded-modules...

222

Answer #1

You can use getattr

getattr(module, class_name)

to access the class. More complete code:

module = __import__(module_name)
class_ = getattr(module, class_name)
instance = class_()

As mentioned below, we may use importlib

import importlib
module = importlib.import_module(module_name)
class_ = getattr(module, class_name)
instance = class_()

iat

How to get all of the immediate subdirectories in Python

3 answers

I"m trying to write a simple Python script that will copy a index.tpl to index.html in all of the subdirectories (with a few exceptions).

I"m getting bogged down by trying to get the list of subdirectories.

184

Answer #1

import os
def get_immediate_subdirectories(a_dir):
    return [name for name in os.listdir(a_dir)
            if os.path.isdir(os.path.join(a_dir, name))]

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