--- jupytext: text_representation: extension: .md format_name: myst format_version: 0.13 jupytext_version: 1.14.1 kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- How to convert to/from JSON =========================== Any JSON data can be converted to Awkward Arrays and any Awkward Arrays can be converted to JSON. Awkward type information, such as the distinction between fixed-size and variable-length lists, is lost in the transformation to JSON, however. ```{code-cell} ipython3 import awkward as ak import pathlib ``` From JSON to Awkward -------------------- The function for JSON → Awkward conversion is {func}`ak.from_json`. It can be given a JSON string: ```{code-cell} ipython3 ak.from_json("[[1.1, 2.2, 3.3], [], [4.4, 5.5]]") ``` or a file name: ```{code-cell} ipython3 !echo "[[1.1, 2.2, 3.3], [], [4.4, 5.5]]" > /tmp/awkward-example-1.json ``` ```{code-cell} ipython3 ak.from_json(pathlib.Path("/tmp/awkward-example-1.json")) ``` If the dataset contains a single JSON object, an {class}`ak.Record` is returned, rather than an {class}`ak.Array`. ```{code-cell} ipython3 ak.from_json('{"x": 1, "y": [1, 2], "z": "hello"}') ``` From Awkward to JSON -------------------- The function for Awkward → JSON conversion is {func}`ak.to_json`. With one argument, it returns a string. ```{code-cell} ipython3 ak.to_json(ak.Array([[1.1, 2.2, 3.3], [], [4.4, 5.5]])) ``` But if a `destination` is given, it is taken to be a filename for output. ```{code-cell} ipython3 ak.to_json(ak.Array([[1.1, 2.2, 3.3], [], [4.4, 5.5]]), "/tmp/awkward-example-2.json") ``` ```{code-cell} ipython3 !cat /tmp/awkward-example-2.json ``` Conversion of different types ----------------------------- All of the rules that apply for Python objects in {func}`ak.from_iter` and {func}`ak.to_list` apply to {func}`ak.from_json` and {func}`ak.to_json`, replacing builtin Python types for JSON types. (One exception: JSON has no equivalent of a Python tuple.) +++ Performance ----------- Since Awkward Array internally uses [RapidJSON](https://rapidjson.org/) to simultaneously parse and convert the JSON string, {func}`ak.from_json` and {func}`ak.to_json` should always be faster and use less memory than {func}`ak.from_iter` and {func}`ak.to_list`. Don't convert JSON strings into or out of Python objects for the sake of converting them as Python objects: use the JSON converters directly.