Skip to main content

Firestore/Python - get() function to access a document fails in GCP Cloud Function

I'm trying to access a document in Firestore like this:

from google.cloud import firestore

def check_stuff(document_id, update_time):
    firestore_client = firestore.Client()
    doc_ref = firestore_client.collection(u'TestCollection').document(document_id)
    print(f"Ref OK")
    document = doc_ref.get()
    print(f"Doc OK")

    if document.exists:
        return True
    else:
        return False

It prints the first print ("Ref OK") but not the following one. Instead I get this error, which I don't really understand. I seems to comes from the get() function itself:

Exception on / [POST] Traceback (most recent call last): File "/layers/google.python.pip/pip/lib/python3.7/site-packages/flask/app.py", line 2073, in wsgi_app response = self.full_dispatch_request() File "/layers/google.python.pip/pip/lib/python3.7/site-packages/flask/app.py", line 1518, in full_dispatch_request rv = self.handle_user_exception(e) File "/layers/google.python.pip/pip/lib/python3.7/site-packages/flask/app.py", line 1516, in full_dispatch_request rv = self.dispatch_request() File "/layers/google.python.pip/pip/lib/python3.7/site-packages/flask/app.py", line 1502, in dispatch_request return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args) File "/layers/google.python.pip/pip/lib/python3.7/site-packages/functions_framework/init.py", line 171, in view_func function(data, context) File "/workspace/main.py", line 110, in main check = check_stuff(document_id, update_time) File "/workspace/main.py", line 87, in check_stuff document = document_ref.get() File "/layers/google.python.pip/pip/lib/python3.7/site-packages/google/cloud/firestore_v1/document.py", line 370, in get data = _helpers.decode_dict(document_pb.fields, self._client) File "/layers/google.python.pip/pip/lib/python3.7/site-packages/google/cloud/firestore_v1/_helpers.py", line 318, in decode_dict return {key: decode_value(value, client) for key, value in value_fields.items()} File "/layers/google.python.pip/pip/lib/python3.7/site-packages/google/cloud/firestore_v1/_helpers.py", line 318, in return {key: decode_value(value, client) for key, value in value_fields.items()} File "/layers/google.python.pip/pip/lib/python3.7/site-packages/google/cloud/firestore_v1/_helpers.py", line 276, in decode_value value_type = value._pb.WhichOneof("value_type") AttributeError: _pb

I checked that the collection truly exists, as well as the document in it. No problem here.

My code is located on a Google Cloud Function, called by Firestore Trigger (write trigger on the same document). The code works locally on my machine but not on GCP. It doesn't fail every time. It seems to fail only with certain document_id (even if they exist).

Python is 3.7 and google-cloud-firestore==2.0.1



source https://stackoverflow.com/questions/73079130/firestore-python-get-function-to-access-a-document-fails-in-gcp-cloud-functi

Comments

Popular posts from this blog

How to split a rinex file if I need 24 hours data

Trying to divide rinex file using the command gfzrnx but getting this error. While doing that getting this error msg 'gfzrnx' is not recognized as an internal or external command Trying to split rinex file using the command gfzrnx. also install'gfzrnx'. my doubt is I need to run this program in 'gfzrnx' or in 'cmdprompt'. I am expecting a rinex file with 24 hrs or 1 day data.I Have 48 hrs data in RINEX format. Please help me to solve this issue. source https://stackoverflow.com/questions/75385367/how-to-split-a-rinex-file-if-i-need-24-hours-data

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings