Flatten/unflatten dicts
Project description
Dotli
yet another library for flattening structures
Installation
pip install dotli
Usage
flatten
from dotli import Dotli
data = {
'a': {
'c': 'val1',
'd': 'val2',
},
'b': {
'c': 2,
'd': {'key3': 'val3', 'key4': 'val4'},
}
}
d = Dotli() # create an obj with a default configuration
flat = d.flatten(data) # flatten
orig = d.unflatten(flat) # unflatten
assert data == orig
print(flat)
{
'a.c': 'val1',
'a.d': 'val2',
'b.c': 2,
'b.d.key3': 'val3',
'b.d.key4': 'val4',
}
The separator can be configured
data = {
'a': {'c': 'd'},
'b': {'e': 'f'}
}
d = Dotli(separator='-')
print(d.flatten(data))
{
'a-c': 'd',
'b-e': 'f',
}
It is also possible to flatten lists and a mixture of lists and dicts
data = {
'a': {
'c': [1, 2, 3],
'd': ['e1', 'e2', 'e3'],
},
'b': 'h'
}
d = Dotli()
print(d.flatten(data))
{
'a.c.0': 1,
'a.c.1': 2,
'a.c.2': 3,
'a.d.0': 'e1',
'a.d.1': 'e2',
'a.d.2': 'e3',
'b': 'h',
}
List indices can be wrapped in square brackets to allow numerical strings in dicts as keys
data = {
'a': {
'1': [1, 2, 3],
'2': ['e1', 'e2', 'e3'],
},
'b': 'h'
}
d = Dotli(list_brackets=True)
flat = d.flatten(data)
orig = d.unflatten(flat)
assert data == orig
print(flat)
{
'a.1.[0]': 1,
'a.1.[1]': 2,
'a.1.[2]': 3,
'a.2.[0]': 'e1',
'a.2.[1]': 'e2',
'a.2.[2]': 'e3',
'b': 'h',
}
There will be a nice error message the dict can not be flattened including the path to the invalid element.
from dotli.errors import SeparatorInKeyError
data = {
'a': {
'b.b': 1,
},
'b': 'h'
}
try:
Dotli().flatten(data)
except SeparatorInKeyError as e:
print(e)
Separator "." is in key "b.b"! @ root.a
unflatten
When elements are missing in a list Dotli will throw an error
from dotli.errors import IncompleteListError
data = {
'a.0': 0,
'a.2': 2,
}
try:
d = Dotli()
d.unflatten(data)
except IncompleteListError as e:
print(e)
No entry for index "1" in list! @ a
However it is possible to specify a fill value which will automatically be inserted into the list for missing entries
data = {
'a.0': 0,
'a.2': 2,
}
d = Dotli(fill_value_list=None)
print(d.unflatten(data))
{
'a': [0, None, 2],
}
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