def post(request, pk):
data = request.POST
form = NewCompanyForm(data)
if form.is_valid():
current_company = form.save()
else:
return HttpResponseBadRequest(form.errors.as_json())
return HttpJson(ujson.dumps({"name": current_company.name}))
def put(request, pk):
try:
current_company = Company.objects.get(pk=pk)
current_company.name = request.data["name"]
current_company.save()
except Exception:
return HttpResponseBadRequest("Error: %s" % sys.exc_info()[1])
return HttpJson(ujson.dumps({"name": current_company.name}))
def get(request):
data = [{
"name": x[0],
"data": x[1],
"primary_columns": x[2],
"id": x[3]
}
for x in MapSettings.objects.values_list(
"name", "data", "primary_columns", "id")]
return HttpJson(ujson.dumps(data))
def put(self, request, pk):
data = request.PUT
try:
instance = MLData.objects.get(pk=pk)
except Exception:
return HttpResponseBadRequest(ujson.dumps(['Data set with `pk` %d not found' % pk]))
row_index = int(data["row_index"])
for x in instance.data:
if x["row_index"] == row_index:
x[data['col_name']] = data['value']
instance.save()
return HttpJson(ujson.dumps(["ok"]))
def save_form(self, form, data):
if form.is_valid():
data_mapping = form.save(commit=False)
data_mapping.data = ujson.loads(data["data"])
data_mapping.primary_columns = ujson.loads(data["primary_columns"])
data_mapping.save()
else:
return HttpResponseBadRequest(form.errors.as_json())
return HttpJson(
ujson.dumps({
"id": data_mapping.id,
"name": data_mapping.name,
"data": data_mapping.data,
"primary_columns": data_mapping.primary_columns
}))
def get(self, request, pk):
context = {}
try:
# todo: rewrite for one query
ml_data_q = MLData.objects.filter(id=pk).values("id", "name", "company_id", "company__name", "key_data",
"data")
ml_data = ml_data_q[0]
except Exception:
return HttpResponseBadRequest(ujson.dumps(['Data set with `pk` %d not found' % pk]))
context["id"] = ml_data["id"]
context["name"] = ml_data["name"]
context["company"] = {"id": ml_data["company_id"], "name": ml_data["company__name"]}
context["key_data"] = {"name": ml_data["key_data"]}
context["data"] = ml_data["data"]
return HttpJson(ujson.dumps(context))
def _create_update_data_set(file, req_data, pk=0):
if pk:
try:
instance = MLData.objects.get(pk=pk)
data_set = NewDataSetForm(req_data, instance=instance)
except Exception:
return HttpResponseBadRequest(ujson.dumps(['Data set with `pk` %d not found' % pk]))
else:
data_set = NewDataSetForm(req_data)
if not data_set.is_valid():
return HttpResponseBadRequest(data_set.errors.as_json())
ml_data = data_set.save(commit=False)
if file:
ml_data.data = csv_to_json(file)
ml_data.save()
return HttpJson(ujson.dumps({"data": ml_data.data, "id": ml_data.id}))
def post(self, request, pk):
try:
instance = MLData.objects.get(pk=pk)
except Exception:
return HttpResponseBadRequest(ujson.dumps(['Data set with `pk` %d not found' % pk]))
mapped_columns = ujson.loads(request.POST["mapped_columns"])
primary_mapping = ujson.loads(request.POST["primary_columns"])
origin_column = primary_mapping['origin_column']
new_set_column = primary_mapping['new_set_column']
file = request.FILES.get('file', '')
new_data_set = csv_to_json(file)
new_data_set_dict = {}
for x in new_data_set:
if new_set_column not in x:
return HttpResponseBadRequest(
ujson.dumps(['In new row %s column %s was not found' % (x, new_set_column)]))
new_data_set_dict[x[new_set_column]] = x
origin_data_set = instance.data
key_data = instance.key_data
for row in origin_data_set:
if origin_column not in row:
return HttpResponseBadRequest(ujson.dumps(['In row %s column %s was not found' % (row, origin_column)]))
pk = row[origin_column]
if pk in new_data_set_dict:
new_data_set_row = new_data_set_dict[pk]
for columns in mapped_columns:
if columns['origin_column'] == key_data:
continue
if columns['origin_column'] not in row:
return HttpResponseBadRequest(
ujson.dumps(['In row %s column %s was not found' % (row, columns['origin_column'])]))
if columns['new_set_column'] not in new_data_set_row:
return HttpResponseBadRequest(
ujson.dumps(['In new row %s column %s was not found' % (new_data_set_row,
columns['new_set_column'])]))
row[columns['origin_column']] = new_data_set_row[columns['new_set_column']]
instance.data = origin_data_set
instance.save()
return HttpJson(ujson.dumps(origin_data_set))
def get(request):
res = []
data_sets = list(MLData.objects.values_list("company_id", "name", "id"))
companies = Company.objects.values_list("name", "id").order_by("name")
tree = {x[1]: {"name": x[0], "children": []} for x in companies}
for data_set in data_sets:
company_id = data_set[0]
ds_name = data_set[1]
id_data_set = data_set[2]
tree[company_id]["children"].append({
"label": ds_name,
"data": id_data_set,
})
for tree_key, value in tree.items():
res.append({
"label": value["name"],
"data": tree_key,
"children": value["children"]
})
return HttpJson(ujson.dumps(res))
def get(request):
companies = Company.objects.all()
return HttpJson(ujson.dumps([{"name": x.name, "id": x.id} for x in companies]))
def delete(request, pk):
Company.objects.filter(pk=pk).delete()
return HttpJson(ujson.dumps(["ok"]))
def get(request, pk):
current_company = Company.objects.filter(pk=pk)
if not len(current_company):
return HttpResponseBadRequest("Company with id: %d not found" % pk)
return HttpJson(ujson.dumps({"name": current_company[0].name, "id": current_company[0].id}))
def delete(self, request, pk):
MapSettings.objects.filter(pk=pk).delete()
return HttpJson(ujson.dumps(["ok"]))