🧶 pydlib

The python dictionary library to get into complex nested python dictionary structures (e.g. json) in a safe and clean way. We take inspiration from Greek myth of Minotaur, where Ariadne with the help of a thread escaped the labyrinth with his beloved Theseus.

Why use pydlib

Sometimes you have to navigate deep json dicts from remote sources, like elastic logs: you can make a series of .get() and check for None every time; or you can do obj["path"]["to"]["nested"]["field"] and wrap everything in a try/except...

Or you can use pydlib and write:

pydlib.get(obj, "path.to.nested.field")

to get the value of field, or None if anything is not a dict along the given path.

Installation

To install pydlib, simply use pip:

$ pip install pydlib

or install from the repository:

$ git clone https://github.com/aitechnologies-it/dlib.git
$ cd dlib
$ python setup.py install

Basic usage

get()

You can get the value from a nested field, just by indicating the path to the nested sub-structure as follows:

>>> import pydlib as dl

>>> dictionary = {
>>>   'path': {
>>>       'to': {
>>>          'nested': {
>>>             'field': 42
>>>           }
>>>        }
>>>    }
>>> }
>>> dl.get(dictionary, path='path.to.nested.field', default=0)
42

Instead, if the field we are looking for doesn't exists, or, if it exists but has a None value, then:

>>> ...
>>> dl.get(dictionary, path='path.to.nested.nonexisting.field', default=0)
0

has()

You can also test for a field simply calling:

>>> import pydlib as dl

>>> dictionary = { ... }
>>> dl.has(dictionary, path='path.to.nested.field')
True

update()

Furthermore, the pydlib comes with built-in functions to also update and delete fields. For example, to update:

>>> import pydlib as dl

>>> dictionary = { ... }
>>> dl.update(dictionary, path='path.to.nested.field', value=1)
{
   'path': {
       'to': {
          'nested': {
             'field': 1
           }
        }
    }
}

delete()

Instead, to delete:

>>> import pydlib as dl

>>> dictionary = { ... }
>>> dl.delete(dictionary, path='path.to.nested.field')
{
   'path': {
       'to': {
          'nested': {}
        }
    }
}

Type-safety

pydlib is type safe, in fact you don't have to manually check the type of inputs, pydlib does it for you:

>>> import pydlib as dl

>>> res = dl.get("not a dictionary", path="nowhere", default=None)
>>> res is None
True

Advanced features

Custom separator

It may happen that a dictionary has a string key with . in it. In this case you should use a different separator:

>>> import pydlib as dl

>>> d = {"a": {"b.c": 42}}

# Separator conflict
>>> dl.get(d, "a.b.c")
None

# This works!
>>> dl.get(d, "a/b.c", sep="/")
42

Search inside lists

has() and get() (but not update and delete!) can handle lists. This means that, if a list is encountered, the search for the rest of the path continues for each element of the list. A few examples are needed:

• b is a list, get() will return a list with all dictionaries containing the rest of the path c.d:

  >>> d = {"a":
              {"b": [
                  {"c":   {"d":   1}}, # <-- this
                  {"bad": {"d":   2}},
                  {"c":   {"d":   3}}, # <-- this
                  {"c":   {"bad": 4}}
              ]
          }
      }
  
  >>> dl.get(d, "a.b.c.d")
  [1, 3]

• this works also for nested lists. In this case a nested list of matching depth is returned:

  >>> d = {"a":
              {"b": [
                  {"c":
                      {"d": [
                          {"e":   1},
                          {"e":   2},
                          {"bad": 3},
                      ]}
                  },
                  {"bad":
                      {"d": [
                          {"e":   4},
                      ]}
                  },
                  {"c":
                      {"d": [
                          {"e": 5},
                      ]}
                  },
              ]
          }
      }
  
  >>> dl.get(d, "a.b.c.d.e")
  [[1, 2], [5]]

• In this case the elements of list b are of different types, (1) and (3) are dictionaries, (2) is a list:

  >>> d = {"a":
              {"b": [
                  {"c": {"d": 1}},     # (1)
                  [ {"c": {"d": 3}} ], # (2)
                  {"c": {"d": 4}},     # (3)
              ]
          }
      }
  
  >>> dl.get(d, "a.b.c.d")
  [1, [3], 4]

• Handling of lists can be disabled by setting search_lists=False. Here's different behaviours for search_lists:

  >>> d = {"a":
              {"b": [
                  {"c":   {"d":   1}},
                  {"bad": {"d":   2}},
                  {"c":   {"d":   3}},
                  {"c":   {"bad": 4}}
              ]
          }
      }
  
  >>> dl.get(d, "a.b.c.d", search_lists=True)
  [1, 3]
  >>> dl.get(d, "a.b.c.d", search_lists=False)
  None
  
  # But if instead we want to get `a.b`, no lists are traversed and both return the value of `b`
  >>> dl.get(d, "a.b", search_lists=True)
  [{'c': {'d': 1}}, [{'c': {'d': 3}}], {'c': {'d': 4}}]
  >>> dl.get(d, "a.b", search_lists=False)
  [{'c': {'d': 1}}, [{'c': {'d': 3}}], {'c': {'d': 4}}]