Cleaning your messy data.
Project description
Cleaning your messy data.
Getting started
Consider cleaning up some messy data. Here is a deep nested dictionary containing lots of unnecessary nesting and tuple.
some_messy_data = {
"body": {
"article": {
"articlesbody": {
"articlesmeta": {
"articles_meta_3": "Monty Python",
}
}
},
},
"published": {
"datetime": ("2014-11-05", "23:00:00"),
}
}
Values you want are 'Monty Python' and '2014-11-05', should be named 'title' and 'published_date'
Now let the hack begin with the dripper.
Defile declaration dictionary
Create dripper object by dripper.dripper_factory
Drip essential data
# Define
declaration = {
"title": ("body", "article", "articlesbody", "articlesmeta", "articles_meta_3"),
"published_date": ("published", "datetime", 0)
}
# Create
import dripper
d = dripper.dripper_factory(declaration)
# And drip
dripped = d(some_messy_data)
assert dripped == {
"title": "Monty Python",
"published_date": "2014-11-05",
}
Installation
Just use pip to install
pip install dripper
Requirements
dripper won’t require any kind of outer libraries. Supporting Python versions are:
Python 2.7
Python 3.3
Python 3.4
Python 3.5
Basics
Above example is not all features of dripper. It is created to handle various data to clean up.
As value
from dripper import dripper_factory
declaration = {
"title": ("meta", "meta1")
})
d = dripper_factory(declaration)
d({"meta": {"meta1": "Monty Python"}}) == {"title": "Monty Python"}
Also you can specify string or integer directly. It is as same as one-element tuple.
from dripper import dripper_factory
declaration = {
"title": "meta"
})
d = dripper_factory(declaration)
d({"meta": "Monty Python"}) == {"title": "Monty Python"}
As dict
dripper can define nested dictionary. Just pass nested dictionary to dripper_factory.
from dripper import dripper_factory
declaration = {
"article": {
"title": ["meta", "meta1"],
}
})
d = dripper_factory(declaration)
d({
"meta": {
"meta1": "Monty Python",
},
}) == {
"article": {
"title": "Monty Python",
}
}
You can apply '__source_root__' to set root path for dripping.
declaration = {
"article": {
"__source_root__": ("body", "meta"),
...
"title": "meta1",
"author": ("meta2", "meta22"),
}
})
d = dripper_factory(declaration)
d({
"body": {
"meta": {
"meta1": "Monty Python",
"meta2": {"meta22": "John Due"}
}
}
}) == {
"article": {
"title": "Monty Python",
"author": "John Due",
}
}
Technically, outermost dictionary of declaration is as same as inner dictionaries. So you can specify '__source_root__' the dictionary.
As list
dripper can define list of dictionaries. You need to apply '__type__': 'list'.
from dripper import dripper_factory
declaration = {
"articles": {
"__type__": "list",
"__source_root__": "articles",
...
"title": "meta1",
"author": ["meta2", "meta22"],
}
})
d = dripper_factory(declaration)
d({
"articles": [
{"meta1": "Monty Python", "meta2": {"meta22": "John Doe"}},
{"meta1": "Flying Circus", "meta2": {"meta22": "Jane Doe"}},
]
}) == {
"articles": [
{"title": "Monty Python", "author": "John Doe"},
{"title": "Flying Circus", "author": "Jane Doe"},
]
}
Advanced
Converting
Use dripper.ValueDripper to pass converter function.
import dripper
declaration = {
"title": dripper.ValueDripper(["title"], converter=lambda s: s.lower())
}
d = dripper.dripper_factory(declaration)
d({"title": "TITLE"}) == {"title": "title"}
Technically, each ends (list) will be replaced by instance of dripper.ValueDripper.
default value
Specify default keyword argument to change default value. None will be applied as default.
import dripper
declaration = {
"title": dripper.ValueDripper(["title"], default="default")
}
d = dripper.dripper_factory(declaration)
d({}) == {"title": "default"}
Technically, each ends (list) will be replaced by instance of dripper.ValueDripper.
Combining
By combining dripper.ValueDripper, result value of that key will be combined.
import dripper
declaration = {
"fullname": (dripper.ValueDripper(["firstname"]) +
dripper.ValueDripper(["lastname"]))
}
d = dripper.dripper_factory(declaration)
d({"firstname": "Hrioki", "lastname": "Kiyohara"}) == {"fullname": "HriokiKiyohara"}
CHANGES
1.2
Avoid deepcopy to improve speed
Thanks @afiram
1.1
None is default value of ValueDripper
Before this change ValueDripper without default keyword argument will raise DrippingError
In order to this behavior DictDripper will return empty dict when inner value dripper could not dig out values
Thanks for @bungoume to suggest this behavior
1.0
Officially supported Python 3.5
0.3.1
ValueDripper now accepts default argument.
0.3
Fixed to accept string or integer directly as source_root.
0.2
Improved error handling.
Added MixDripper.
0.1
Initial version
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.