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convtools is a Python library that simplifies data transformation by allowing you to define them in a declarative way. It then generates the necessary Python code in the background, saving you time and effort.
pip install convtools
from convtools import conversion as c
input_data = [
{"a": 5, "b": "foo"},
{"a": 10, "b": "foo"},
{"a": 10, "b": "bar"},
{"a": 10, "b": "bar"},
{"a": 20, "b": "bar"},
]
conv = (
c.group_by(c.item("b"))
.aggregate(
{
"b": c.item("b"),
"a_first": c.ReduceFuncs.First(c.item("a")),
"a_max": c.ReduceFuncs.Max(c.item("a")),
}
)
.pipe(
c.aggregate({
"b_values": c.ReduceFuncs.Array(c.item("b")),
"mode_a_first": c.ReduceFuncs.Mode(c.item("a_first")),
"median_a_max": c.ReduceFuncs.Median(c.item("a_max")),
})
)
.gen_converter()
)
assert conv(input_data) == {
'b_values': ['foo', 'bar'],
'mode_a_first': 10,
'median_a_max': 15.0
}
c.ReduceFuncs.First
* Sum
* SumOrNone
* Max
* MaxRow
* Min
* MinRow
* Count
* CountDistinct
* First
* Last
* Average
* Median
* Percentile
* Mode
* TopK
* Array
* ArrayDistinct
* ArraySorted
DICT REDUCERS ARE IN FACT AGGREGATIONS THEMSELVES, BECAUSE VALUES GET REDUCED.
* Dict
* DictArray
* DictSum
* DictSumOrNone
* DictMax
* DictMin
* DictCount
* DictCountDistinct
* DictFirst
* DictLast
AND LASTLY YOU CAN DEFINE YOUR OWN REDUCER BY PASSING ANY REDUCE FUNCTION
OF TWO ARGUMENTS TO ``c.reduce``.
black
is highly recommended for
pretty-printing generated code out of curiosity)The best way to support the development of convtools is to spread the word!
Also, if you already are a convtools user, we would love to hear about your use cases and challenges in the Discussions section.
To report a bug or suggest enhancements, please open an issue and/or submit a pull request.
Reporting a Security Vulnerability: see the security policy.
FAQs
dynamic, declarative data transformations with automatic code generation
We found that convtools 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.
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