Hi,
please post the output of debugging the above, print after and before in
these views and also check is something else is working using
request.session.
@csrf_exempt
def upload_local_dataset(request):
if request.method == 'POST':
dataset = pd.read_csv(request.FILES.get('datasetfilepath'),
header=None, index_col=None)
request.session['ts_datset'] = dataset.to_json(orient='values')
print(dataset.to_json(orient='values'))
request.session['ts_dataset_copy'] = dataset.to_json(orient=
'values')
print(request.session['ts_dataset_copy'])
return HttpResponse(dataset.to_json(orient='values'))
Post output of this plus the below one
def cv_classification(request, kfolds, dissimilarity_func, windows_length=0,
noisy_law="", mu=0,std=0):
noisy_law = noisy_law.lower()
print(request.session['ts_dataset_copy'])
df = pd.read_json(request.session['ts_dataset_copy'], orient=
'values')
predictions = cv_classify(df, kfolds, dissimilarity_func,
windows_length, noisy_law, mu, std)
return JsonResponse(predictions, safe=False)
On Tuesday, 25 February 2020 03:47:25 UTC+5:30, Guy NANA wrote:
>
> I have an angular frontend app which send file to django backend which
> data is setting in django session. After I send a httprequest to django
> backend to make ML tratements on that data and get the results. But I've a
> 500 sever error: keyerror 'ts_dataset_copy': KeyError: 'ts_dataset_copy'
> [24/Feb/2020 18:43:46] "GET /cv_classification/5/FOTS/283/None/0/0
> HTTP/1.1" 500 78264. Here are my django code:
>
> Firstly I upload timeseries dataset file from angular frontend (All thing
> is ok)
> @csrf_exempt
> def upload_local_dataset(request):
> if request.method == 'POST':
> dataset = pd.read_csv(request.FILES.get('datasetfilepath'),
> header=None, index_col=None)
> request.session['ts_datset'] = dataset.to_json(orient='values'
> )
> request.session['ts_dataset_copy'] = dataset.to_json(orient=
> 'values')
>
> return HttpResponse(dataset.to_json(orient='values'))
>
>
>
> # second httrequest that throws a server internal error
>
> def cv_classification(request, kfolds, dissimilarity_func,
> windows_length=0, noisy_law="", mu=0,
>
> std=0):
> noisy_law = noisy_law.lower()
> df = pd.read_json(request.session['ts_dataset_copy'], orient=
> 'values')
> predictions = cv_classify(df, kfolds, dissimilarity_func,
> windows_length, noisy_law, mu, std)
> return JsonResponse(predictions, safe=False)
>
>
>
> Thanks for your help!
>
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