Post Numpy Array With Json To Flask App With Requests
Solution 1:
To convert a numpy array arr
to json, it can be serialized while preserving dimension with json.dumps(arr.tolist())
. Then on the api side, it can be parsed with np.array(json.loads(arr))
.
However, when using the requests json
parameter, the dumping and loading is handled for you. So arr.tolist()
is all that is required on the client, and np.array(arr)
on the api. Full example code below.
Client:
params = {'param0': 'param0', 'param1': 'param1'}
arr = np.random.rand(10, 10)
data = {'params': params, 'arr': arr.tolist()}
response = requests.post(url, json=data)
API:
@app.route('/test', methods=['POST'])
def test():
data = request.json
params = data['params']
arr = np.array(data['arr'])
print(params, arr.shape)
return"Success"
Output:
{'param0': 'param0', 'param1': 'param1'} (10, 10)
Note: When either the files
or data
parameter is being used in requests.post
, the json
parameter is disabled.
Solution 2:
The accepted answer gets the job done for small arrays but has huge low performance for large arrays (At least 150% of overhead).
I would recommend using tostring() instead of tolist().
So client would become:
params = {'param0': 'param0', 'param1': 'param1'}
arr = np.random.rand(10, 10)
data = {'params': params, 'arr': arr.tostring()}
response = requests.post(url, json=data)
And API:
@app.route('/test', methods=['POST'])
def test():
data = request.json
params = data['params']
arr = np.fromstring(data['arr'],dtype=float).reshape(10,10)
print(params, arr.shape)
return"Success"
You should note that the shape and dtype of the array must be known beforehand or informed in the request body.
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