77 lines
1.7 KiB
Python
77 lines
1.7 KiB
Python
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#!/usr/bin/env python
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from agate import utils
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@classmethod
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def from_object(cls, obj, row_names=None, column_types=None):
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"""
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Create a new table from a Python object.
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The object should be a list containing a dictionary for each "row".
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Nested objects or lists will also be parsed. For example, this object:
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.. code-block:: python
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{
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'one': {
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'a': 1,
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'b': 2,
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'c': 3
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},
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'two': [4, 5, 6],
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'three': 'd'
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}
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Would generate these columns and values:
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.. code-block:: python
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{
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'one/a': 1,
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'one/b': 2,
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'one/c': 3,
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'two.0': 4,
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'two.1': 5,
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'two.2': 6,
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'three': 'd'
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}
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Column names and types will be inferred from the data.
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Not all rows are required to have the same keys. Missing elements will
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be filled in with null values.
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:param obj:
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Filepath or file-like object from which to read JSON data.
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:param row_names:
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See :meth:`.Table.__init__`.
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:param column_types:
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See :meth:`.Table.__init__`.
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"""
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from agate.table import Table
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column_names = []
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row_objects = []
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for sub in obj:
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parsed = utils.parse_object(sub)
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for key in parsed.keys():
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if key not in column_names:
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column_names.append(key)
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row_objects.append(parsed)
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rows = []
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for sub in row_objects:
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r = []
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for name in column_names:
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r.append(sub.get(name, None))
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rows.append(r)
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return Table(rows, column_names, row_names=row_names, column_types=column_types)
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