nested_lookup #############
Make working with JSON, YAML, and XML document responses fun again!
The nested_lookup package provides many Python functions for working with deeply nested documents.
A document in this case is a a mixture of Python dictionary and list objects typically derived from YAML or JSON.
nested_lookup:
Perform a key lookup on a deeply nested document.
Returns a list of matching values.
nested_update:
Given a document, find all occurences of the given key and update the value.
By default, returns a copy of the document.
To mutate the original specify the in_place=True argument.
nested_delete:
Given a document, find all occurrences of the given key and delete it.
By default, returns a copy of the document.
To mutate the original specify the in_place=True argument.
nested_alter:
Given a document, find all occurrences of the given key and alter it with a callback function.
By default, returns a copy of the document.
To mutate the original specify the in_place=True argument.
get_all_keys:
Fetch all keys from a deeply nested dictionary.
Returns a list of keys.
get_occurrence_of_key/get_occurrence_of_value: Returns the number of occurrences of a key/value from a nested dictionary.
For examples on how to invoke these functions, please check out the tutorial sections.
.. contents::
install from pypi using pip::
pip install nested-lookup
or install from source using::
git clone ssh://git@git.unturf.com:2222/python/nested-lookup.git cd nested-lookup pip install .
This tutorial uses the Python Interactive shell, please follow along : )
Before we start, let's define an example document to work on.
.. code-block:: python
document = [ { 'taco' : 42 } , { 'salsa' : [ { 'burrito' : { 'taco' : 69 } } ] } ]
First, we lookup a key from all layers of a document using nested_lookup:
.. code-block:: python
from nested_lookup import nested_lookup print(nested_lookup('taco', document)) [42, 69]
As you can see the function returned a list of two integers, these integers are the values from the matched key lookups.
Next, we update a key and value from all layers of a document using nested_update:
.. code-block:: python
from nested_lookup import nested_update nested_update(document, key='burrito', value='test') [{'taco': 42}, {'salsa': [{'burrito': 'test'}]}]
Here you see that the key burrito had it's value changed to the string 'test', like we asked.
Finally, we try out a delete operation using nested_delete:
.. code-block:: python
from nested_lookup import nested_delete nested_delete(document, 'taco') [{}, {'salsa': [{'burrito': {}}]}]
Perfect, the returned document looks just like we expected!
You may control the function's behavior by passing some optional arguments.
wild (defaults to False):
if wild is True, treat the given key as a case insensitive
substring when performing lookups.
with_keys (defaults to False):
if with_keys is True, return a dictionary of all matched keys
and a list of values.
For example, given the following document:
.. code-block:: python
from nested_lookup import nested_lookup
my_document = { "name" : "Rocko Ballestrini", "email_address" : "test1@example.com", "other" : { "secondary_email" : "test2@example.com", "EMAIL_RECOVERY" : "test3@example.com", "email_address" : "test4@example.com", }, }
Next, we could act wild and find all the email addresses like this:
.. code-block:: python
results = nested_lookup( key = "mail", document = my_document, wild = True )
print(results)
.. code-block:: python
["test1@example.com", "test4@example.com", "test2@example.com", "test3@example.com"]
Additionally, if you also needed the matched key names, you could do this:
.. code-block:: python
results = nested_lookup( key = "mail", document = my_document, wild = True, with_keys = True, )
print(results)
.. code-block:: python
{ "email_address": ["test1@example.com", "test4@example.com"], "secondary_email": ["test2@example.com"], "EMAIL_RECOVERY": ["test3@example.com"] }
We do not mutate input, if we do you found a defect. Please open an issue.
Let's delete and update our deeply nested key / values and see the results:
.. code-block:: python
from nested_lookup import nested_update, nested_delete
result = nested_delete(my_document, 'EMAIL_RECOVERY') print(result)
result = nested_update(my_document, key='other', value='Test') print(result)
Now let's say we wanted to get a list of every nested key in a document, we could run this:
.. code-block:: python
from nested_lookup import get_all_keys
keys = get_all_keys(my_document) print(keys)
.. code-block:: python
['name', 'email_address', 'other', 'secondary_email', 'EMAIL_RECOVERY', 'email_address']
Also, to get the number of times a key or value occurs in the document, try:
.. code-block:: python
from nested_lookup import ( get_occurrence_of_key, get_occurrence_of_value, )
key_occurrence_count = get_occurrence_of_key(my_document, key='email_address') print(no_of_key_occurrence)
value_occurrence_count = get_occurrence_of_value(my_document, value='test2@example.com') print(no_of_value_occurrence)
To get the number of occurrence and their respective values
.. code-block:: python
from nested_lookup import get_occurrences_and_values
my_documents = [ { "processor_name": "4", "processor_speed": "2.7 GHz", "core_details": { "total_numberof_cores": "4", "l2_cache(per_core)": "256 KB", } } ]
result = get_occurrences_and_values(my_documents, value='4')
print(result)
{ "4": { "occurrences": 2, "values": [ { "processor_name": "4", "processor_speed": "2.7 GHz", "core_details": { "total_numberof_cores": "4", "l2_cache(per_core)": "256 KB" } }, { "total_numberof_cores": "4", "l2_cache(per_core)": "256 KB" } ] } }
Nested Alter: write a callback function which processes a scalar value. Be aware about the possible types which can be passed to the callback functions. In this example we can be sure that only int will be passed, in production you should check the type because it could be anything.
Before we start, let's define an example document to work on.
.. code-block:: python
document = [ { 'taco' : 42 } , { 'salsa' : [ { 'burrito' : { 'taco' : 69 } } ] } ]
.. code-block:: python
def callback(data): return data + 10 # add 10 to every taco prize
The alter-version only works for scalar input (one dict), if you need to adress a list of dicts, you have to manually iterate over those and pass them to nested_update one by one
.. code-block:: python
out =[] for elem in document: altered_document = nested_alter(elem,"taco", callback) out.append(altered_document)
print(out) [ { 'taco' : 52 } , { 'salsa' : [ { 'burrito' : { 'taco' : 79 } } ] } ]
from nested_lookup import get_all_keys
get_all_keys(document) ['taco', 'salsa', 'burrito', 'taco']
from nested_lookup import get_occurrence_of_key, get_occurrence_of_value
get_occurrence_of_key(document, key='taco') 2
get_occurrence_of_value(document, value='42') 1
:license:
:authors:
:web:
FAQs
Python functions for working with deeply nested documents (lists and dicts)
We found that nested-lookup demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
Security News
Attackers used a malicious npm package typosquatting a popular ESLint plugin to steal sensitive data, execute commands, and exploit developer systems.
Security News
The Ultralytics' PyPI Package was compromised four times in one weekend through GitHub Actions cache poisoning and failure to rotate previously compromised API tokens.
Security News
Research
Socket researchers found a malicious Maven package impersonating the legitimate ‘XZ for Java’ library, introducing a backdoor for remote code execution.
