Python dict exclude key

Code example for excluding dictionary keys when printing values using Python

The given code demonstrates the use of a dictionary to iterate through its keys and values. If the keys are always present, the first solution can be used. Alternatively, if you want to eliminate the columns from the dataframe after parsing all the json data, the second solution can be used. For the first solution, keys with a leading underscore are not hidden but are treated as strings in JSON. The default hook does not prevent the key from being added to the output, but it can help you avoid errors. Recursively filtering can keep the code clean, and an additional argument can be added to skip keys that have a character at the start.

Excluding items from dictionary in for loop and using if and else with dictionary

The dic_name.items() function can be useful in this situation. For example, if we have a dictionary named dic_name with key-value pairs , we can use the items() function to iterate over the dictionary and print out each key-value pair using a for loop as follows: for key, val in dic_name.items(): print(key, val)

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Ignore specific JSON keys when extracting data in Python

Assuming the keys are consistently present, they can be utilized.

del d[0]['identities'][0]['likes'] del d[0]['identities'][0]['favorites'] 

Alternatively, if you wish to eliminate columns from the dataframe subsequent to reading all the JSON data, you may utilize the following approach.

df.drop(df.filter(regex='identities.0.favorites|identities.0.likes').columns, axis=1, inplace=True) 

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How to make json.dumps in Python ignore a non-serializable field

Keys that begin with the _ underscore do not qualify as being ‘hidden’; rather, they are simply additional string values in the JSON. The Container Construct class is essentially an ordered dictionary, with the _io key holding no particular significance within the class.

• Install a hook with default that solely provides an alternate value.
• Before serialising, eliminate the key-value pairs that are known to be ineffective.

Upon examining the Construct project pages, it is unclear if there is a third output available. However, it would be beneficial if Construct could produce a JSON-compatible dictionary, or at least output JSON, by implementing adapters.

The hook that is set by default doesn’t have the ability to stop the addition of the _io key to the result. However, it can help you avoid encountering the error.

json.dumps(packet, default=lambda o: '') 

Recursion can be utilized for filtering repeatedly, and to maintain the cleanliness of such code, the decorator @functools.singledispatch() can be employed.

from functools import singledispatch _cant_serialize = object() @singledispatch def json_serializable(object, skip_underscore=False): """Filter a Python object to only include serializable object types In dictionaries, keys are converted to strings; if skip_underscore is true then keys starting with an underscore ("_") are skipped. """ # default handler, called for anything without a specific # type registration. return _cant_serialize @json_serializable.register(dict) def _handle_dict(d, skip_underscore=False): converted = ((str(k), json_serializable(v, skip_underscore)) for k, v in d.items()) if skip_underscore: converted = ((k, v) for k, v in converted if k[:1] != '_') return @json_serializable.register(list) @json_serializable.register(tuple) def _handle_sequence(seq, skip_underscore=False): converted = (json_serializable(v, skip_underscore) for v in seq) return [v for v in converted if v is not _cant_serialize] @json_serializable.register(int) @json_serializable.register(float) @json_serializable.register(str) @json_serializable.register(bool) # redudant, supported as int subclass @json_serializable.register(type(None)) def _handle_default_scalar_types(value, skip_underscore=False): return value 

In addition to the above implementation, I have included an extra argument, skip_underscore , which allows for the explicit skipping of keys that begin with the character _ . By doing this, any additional ‘hidden’ attributes used by the Construct library can be skipped.

As a subclass of dict , Container can handle instances like packet without the need for additional code.

As previously noted, implementing the logic to disregard a non-serializable field can be a complex task.

If excluding the field is not necessary, you have the option to create a default value in its place.

def safe_serialize(obj): default = lambda o: f">>" return json.dumps(obj, default=default) obj = # bytes is non-serializable by default print(safe_serialize(obj)) 

That will produce this result:

Printing the type name can come in handy if you plan on developing your own serializers in the future.

The functionality of skipkeys may not be obvious: it directs json.JSONEncoder to ignore keys that are not of a basic type, rather than the values associated with those keys. For example, if you had a dict , json.JSONEncoder would skip the object() key if skipkeys was set to True . Without this setting, an error ( TypeError ) would be raised.

Instead of overloading JSONEncoder.iterencode() and its underlying functions to perform look-ahead filtering, which would require rewriting the json module and slowing it down as you won’t be able to take advantage of the compiled parts, a better approach would be to pre-process your data through iterative filtering. In doing so, you can skip keys/types that are not required for your final JSON output, and the json module should be able to process it without any additional instructions. Here’s an example:

import collections class SkipFilter(object): def __init__(self, types=None, keys=None, allow_empty=False): self.types = tuple(types or []) self.keys = set(keys or []) self.allow_empty = allow_empty # if True include empty filtered structures def filter(self, data): if isinstance(data, collections.Mapping): result = <> # dict-like, use dict as a base for k, v in data.items(): if k in self.keys or isinstance(v, self.types): # skip key/type continue try: result[k] = self.filter(v) except ValueError: pass if result or self.allow_empty: return result elif isinstance(data, collections.Sequence): result = [] # a sequence, use list as a base for v in data: if isinstance(v, self.types): # skip type continue try: result.append(self.filter(v)) except ValueError: pass if result or self.allow_empty: return result else: # we don't know how to traverse this structure. return data # return it as-is, hope for the best. raise ValueError 

import io preprocessor = SkipFilter([io.BytesIO], ["_io"]) # double-whammy skip of io.BytesIO 

If the _io key contains any unwanted information, skipping by type alone should be enough to ensure it does not appear in the final result. Alternatively, you can filter the data before passing it to JSONEncoder .

import json json_data = json.dumps(preprocessor.filter(packet)) # no _io keys or io.BytesIO data. 

While this method is sufficient for most general use cases, it may not be suitable for structures that contain unique or atypical data, or data that is presented in JSON with varying formats depending on its type. In these cases, applying this approach could potentially result in errors as it converts all mappings to dict and all sequences to list .

Python | Get dictionary keys as a list, Output: dict_keys([1, 2, 3]) Method 2: Get dictionary keys as a list using dict.keys() Python list() function takes any iterable as a parameter and returns a list. In Python iterable is the object you can iterate over.

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Python Remove Key from Dictionary – How to Delete Keys from a Dict

Shittu Olumide

Dictionaries are a useful data type in Python for storing data in a key-value format. And there are times when you might need to remove a particular key-value pair from a dictionary.

You’ll learn some dictionary basics, as well as how to delete keys, in this tutorial.

How to Write a Dict in Python

Dictionaries are denoted by curly braces <> and the key-value pairs are separated by colons : . For example, the following code initializes a dictionary with three key-value pairs:

You can also initialize dictionaries using the built-in dict() function. For example:

my_dict = dict(apple=2, banana=3, orange=5) 

Now I’ll teach you how to securely remove keys from a Python dictionary. When I say «securely,» I mean that if the key doesn’t actually exist in the dictionary, the code won’t throw an error.

We’ll discover how to accomplish this using the del keyword, the pop() method, and the popitem() method. Finally, you’ll see how to use Python to remove multiple keys from a dictionary.

How to Remove a Key from a Dict Using the del Keyword

The most popular method for removing a key:value pair from a dictionary is to use the del keyword. You can also use it to eliminate a whole dictionary or specific words.

Simply use the syntax shown below to access the value you need to delete:

Let’s have a look at an example:

Members = del Members["Doe"] print(Members) 

How to Remove a Key from a Dict Using the pop() Method

Another technique to remove a key-value pair from a dictionary is to use the pop() method. The syntax is shown below:

dictionary.pop(key, default_value) 

My_Dict = data = My_Dict.pop(1) print(data) print(My_Dict) 

How to Remove a Key from a Dict Using the popitem() Function

The built-in popitem() function eliminates the the last key:value pair from a dictionary. The element that needs to be removed cannot be specified and the function doesn’t accept any inputs.

The syntax looks like this:

Let’s consider and example for a better understanding.

# initialize a dictionary My_dict = # using popitem() Deleted_key = My_dict.popitem() print(Deleted_key) 

As you can see, the function removed the last key:value pair – 5: «Black» – from the dictionary.

How to Remove Multiple Keys from a Dict

You can easily delete multiple keys from a dictionary using Python. The .pop() method, used in a loop over a list of keys, is the safest approach for doing this.

Let’s examine how we can supply a list of unique keys to remove, including some that aren’t present:

My_dict = #define the keys to remove keys = ['Sam', 'John', 'Doe'] for key in keys: My_dict.pop(key, None) print(My_dict) 

One thing to note is that in the pop() method inside the loop, we pass in None and the default value, just to make sure no KeyError is printed if a key doesn’t exist.

How to Remove All Keys from a Dict Using the clear() Method

You can use the clear() method to remove all key-value pairs from a dictionary. The syntax is as follows:

Colors = Colors.clear() print(Colors) 

Conclusion

For removing a key-value pair or several key-value pairs from a dictionary, we discussed a variety of Python methods in this article.

You can do so using the del keyword, which is the most common method of removing a key-value pair from a dictionary. The pop() method is useful when we need to remove a key-value pair and also get the value of the key-value pair. Using the popitem() function, we can remove the final key-value pair in a dictionary.

Also, if you need to remove all key:value pairs in a dictionary, you can use the clear() method.

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