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feat: login asset face verify acl #14610
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return face_code | ||
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class AuthMixin(CommonMixin, AuthPreCheckMixin, AuthACLMixin, AuthFaceMixin, MFAMixin, AuthPostCheckMixin, ): | ||
request = None | ||
partial_credential_error = None | ||
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In summary:
- The code contains several issues regarding naming conventions (e.g.
UserAuth
should beUserAuthentication
,authenticate_user
to avoid name conflicts with built-in function), incorrect use of type hints, unused imports (uuid
), and improper handling of asynchronous operations.
Suggestions for improvement include:
- Renaming functions/classes using Python's snake_case convention (i.e., change 'CustomCredentialsError' into 'custom_credentials_error').
- Use more descriptive variable names that reflect their purpose.
- Correctly handle asyncio dependencies where needed, like in async methods or when calling tasks on an external provider.
- Ensure the code adheres to PEP8 style guidelines.
Please review my edits for correctness
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def post(self, request, *args, **kwargs): | ||
token = self.new_face_context() | ||
return Response({'token': token}) | ||
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def get(self, request, *args, **kwargs): | ||
token = self.request.session.get('mfa_face_token') | ||
token = self.request.session.get(self.face_token_session_key) | ||
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cache_key = self.get_face_cache_key(token) | ||
context = cache.get(cache_key) |
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Since you did not provide any code snippet, I am unable to analyze it directly for differences or potential improvements. Please provide a specific piece of code that you want reviewed so that I can help you with your query.
def create(self, request, *args, **kwargs): | ||
try: | ||
response = super().create(request, *args, **kwargs) | ||
if self.need_face_verify: | ||
self.create_face_verify(response) | ||
except JMSException as e: | ||
data = {'code': e.detail.code, 'detail': e.detail} | ||
return Response(data, status=e.status_code) |
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This code snippet seems to be implementing the view for managing connection token objects in an app using Django REST framework. The main functions:
_validate
checks whether the given user has permissions and can access necessary information related to the asset.create_face_verify
handles face verification when creating a new connection token.
For comparison, I am unable to analyze differences between these functions directly as they do not appear to implement any specific logic that might require comparisons or suggestions.
As such, my suggestion would remain limited based on what you have shared regarding the purpose of this function implementation only. If there's more specific functionality or operations within each method, please provide them so I could give a more comprehensive analysis.
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return face_code | ||
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class AuthMixin(CommonMixin, AuthPreCheckMixin, AuthACLMixin, AuthFaceMixin, MFAMixin, AuthPostCheckMixin, ): | ||
request = None | ||
partial_credential_error = None | ||
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The provided code snippet seems to relate to a multi-factor authentication (MFA) implementation using Flask as framework. Please note that I can only offer general advice based on existing knowledge and do not have access to specific frameworks or libraries' API documentation.
For checking the code differences, it would be helpful to see actual versions of the code compared against each other so you could identify if there were any changes made, whether they fixed previously identified bugs/irregularities/problems, added new functionality, etc. To provide meaningful feedback or suggestions to optimize parts of this, please send me the complete set of files/codebase.
If the aim is primarily to find inaccuracies/errors in the current setup rather than propose improvement ideas, here are some recommendations:
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Avoid mutable objects: Ensure all variables used inside functions remain immutable through their lifetimes, which will avoid potential conflicts between function calls.
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Error Handling: Include clear error messages or exceptions around potentially risky operations like invalid tokens/retries/sessions/caches, especially if these lead users into unhandled states.
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Performance Profiling: Consider performance bottlenecks by profiling how data structures / methods operate under various load conditions with tools like Werkzeug profiler for Python web applications.
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Code Quality Checks: Implement linters like flake8/pylint to enforce certain coding best practices where appropriate.
To summarize, unless you can provide sample input outputs or expected behavior for testing purposes, I cannot offer specifics about any inconsistencies or problems within your code.
Feel free to share more information related to your project's specifics.
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def post(self, request, *args, **kwargs): | ||
token = self.new_face_context() | ||
return Response({'token': token}) | ||
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def get(self, request, *args, **kwargs): | ||
token = self.request.session.get('mfa_face_token') | ||
token = self.request.session.get(self.face_token_session_key) | ||
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cache_key = self.get_face_cache_key(token) | ||
context = cache.get(cache_key) |
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The main difference between perform_create
method in two versions is the usage of tmp_to_root_org()
inside _handle_success
. Also, there seems to be an error message "missing field 'face_code'" that needs to be handled differently.
In version one, this part:
context.update({
'is_finished': True,
'success': True,
'error': str(error),
})
Should read:
context.update({
'is_finished': True,
'success': True,
'error': '',
})
This would correct for what appears to be a missing string literal value being passed into _handle_success
, which results in the exception handling logic failing when attempting to set or update keys within the dictionary.
On another note, it may add utility to wrap the verification process with proper logging and response status codes. This could help catch unexpected errors before they reach the frontend user interface.
Additionally, make sure all calls to methods like _update_cache() have a clear intention on setting state back to expected behavior. It might also enhance readability by having consistent capitalization across variables names in different environments (__class_name_upper_case__, etc...
). The implementation itself looks good though!
def create(self, request, *args, **kwargs): | ||
try: | ||
response = super().create(request, *args, **kwargs) | ||
if self.need_face_verify: | ||
self.create_face_verify(response) | ||
except JMSException as e: | ||
data = {'code': e.detail.code, 'detail': e.detail} | ||
return Response(data, status=e.status_code) |
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This is an untested code file snippet that contains multiple classes, mixins, serializers, views, and functions related to Django projects, likely pertaining to authentication-related operations involving user profiles. The current content does not contain any inconsistencies since the dates given are 2021-09-01 which means the information presented reflects activities prior to those changes.
If you have specific points of interest about these files such as certain aspects being tested (e.g., performance optimizations), or would like to discuss how things could potentially deviate under hypothetical scenarios, feel free to ask! I'm here to provide concise English responses based on what's relevant and accurate according to the provided dates for reference. Always keep in mind this is pre-publication feedback so improvements and actual behavior after these dates may vary substantially compared to today's conditions without concrete knowledge beyond this period.
Quality Gate passedIssues Measures |
feat: login asset face verify acl