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feat: only process incoming websocket packet model type once #52
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WalkthroughThe recent changes primarily focus on enhancing the handling of Changes
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Codecov ReportAttention: Patch coverage is
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verified it doesn't leak 2024-06-13 19:24:08.630 CRITICAL (SyncWorker_26) [homeassistant.components.profiler] Cache stats for lru_cache <function ModelType.devices_key at 0x7fd7bd5fb100> at /usr/local/lib/python3.12/site-packages/uiprotect/data/types.py: CacheInfo(hits=110, misses=11, maxsize=None, currsize=11) |
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Actionable comments posted: 2
Outside diff range and nitpick comments (1)
src/uiprotect/data/convert.py (1)
66-66
: Consider adding a docstring for the new parametermodel_type
to enhance code documentation.
Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Files selected for processing (5)
- src/uiprotect/api.py (2 hunks)
- src/uiprotect/data/bootstrap.py (9 hunks)
- src/uiprotect/data/convert.py (2 hunks)
- src/uiprotect/data/types.py (2 hunks)
- src/uiprotect/data/user.py (1 hunks)
Additional comments not posted (7)
src/uiprotect/data/convert.py (1)
75-77
: Ensure thatMODEL_TO_CLASS.get(model_type)
is always expected to return a valid class. Consider adding error handling ifmodel_type
is not found in the dictionary.Verification successful
MODEL_TO_CLASS
is defined with variousModelType
keys mapped to corresponding classes, ensuring that mostmodel_type
values have valid mappings. However, there is still a potential risk ifmodel_type
is not found in the dictionary. The existing code does handle this scenario by raising aDataDecodeError
ifklass
isNone
.
MODEL_TO_CLASS
is defined with mappings for variousModelType
values.- The function
get_klass_from_dict
raisesDataDecodeError
if themodelKey
is unknown.- Similarly,
create_from_unifi_dict
callsget_klass_from_dict
ifklass
isNone
.This indicates that the error handling is already in place.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that all possible values of `model_type` have corresponding classes in `MODEL_TO_CLASS`. # Test: Search for missing classes in `MODEL_TO_CLASS`. ast-grep --lang python --pattern $'dict[str, type[ProtectModel]] MODEL_TO_CLASS { $$$ $model_type: $_ { $$$ } $$$ }' src/uiprotect/data/convert.pyLength of output: 674
Script:
#!/bin/bash # Description: Verify that all possible values of `model_type` have corresponding classes in `MODEL_TO_CLASS`. # Test: Search for the dictionary definition of `MODEL_TO_CLASS` and list all its key-value pairs. ast-grep --lang python --pattern $'MODEL_TO_CLASS = { $$$ }' src/uiprotect/data/convert.pyLength of output: 93
Script:
#!/bin/bash # Description: Locate the definition of `MODEL_TO_CLASS` and inspect its structure. # Search for the `MODEL_TO_CLASS` definition in the codebase. rg 'MODEL_TO_CLASS' --pythonLength of output: 439
Script:
#!/bin/bash # Description: Locate the definition of `MODEL_TO_CLASS` and inspect its structure. # Search for the `MODEL_TO_CLASS` definition in Python files. rg 'MODEL_TO_CLASS' --type pyLength of output: 254
Script:
#!/bin/bash # Description: Display the contents of `src/uiprotect/data/convert.py` to inspect the `MODEL_TO_CLASS` dictionary. # Display the contents of the file. cat src/uiprotect/data/convert.pyLength of output: 2220
src/uiprotect/data/types.py (2)
112-115
: The implementation ofdevices_key
as a cached property is efficient for repeated accesses. This change aligns with the PR's goal of optimizing model type handling.
117-121
: The methodfrom_string
simplifies the creation ofModelType
instances from strings. Ensure that all possible strings are validModelType
enums to avoid exceptions.Verification successful
The strings passed to the
ModelType.from_string
method are values extracted from theaction
dictionary, specificallyaction["modelKey"]
. Before callingModelType.from_string
, there is a check to ensure thatmodel_key
(which isaction["modelKey"]
) is inModelType.values_set()
. This validation ensures that only validModelType
enums are passed to thefrom_string
method.
src/uiprotect/data/bootstrap.py
:
- Line:
model_key: str = action["modelKey"]
- Validation:
if model_key not in ModelType.values_set():
This confirms that the code already includes a check to ensure all possible strings are valid
ModelType
enums before calling thefrom_string
method.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that all strings passed to `from_string` are valid `ModelType` enums. # Test: Check for potential invalid enum values. ast-grep --lang python --pattern $'ModelType.from_string($value)' src/uiprotect/data/types.pyLength of output: 94
Script:
#!/bin/bash # Description: Verify that all strings passed to `from_string` are valid `ModelType` enums. # Test: Check for potential invalid enum values in the entire codebase. ast-grep --lang python --pattern $'ModelType.from_string($value)'Length of output: 66
Script:
#!/bin/bash # Description: Verify the usage of `ModelType` and its `from_string` method in the entire codebase. # Find the definition of `ModelType`. ast-grep --lang python --pattern $'class ModelType($_) { $$$ }' # Find all usages of `ModelType` in the codebase. rg 'ModelType' --glob '!*.pyc' --glob '!__pycache__'Length of output: 10442
Script:
#!/bin/bash # Description: Extract lines containing `ModelType.from_string` in `src/uiprotect/data/bootstrap.py`. # Extract lines with `ModelType.from_string`. rg 'ModelType.from_string' src/uiprotect/data/bootstrap.pyLength of output: 183
Script:
#!/bin/bash # Description: Extract context around `model_key` and `action` in `src/uiprotect/data/bootstrap.py`. # Extract lines where `model_key` is defined or assigned. rg 'model_key' src/uiprotect/data/bootstrap.py -A 3 -B 3 # Extract lines where `action` is defined or assigned. rg 'action' src/uiprotect/data/bootstrap.py -A 3 -B 3Length of output: 6403
src/uiprotect/data/bootstrap.py (2)
Line range hint
200-238
: The refactoring to useModelType.bootstrap_models_types_set()
for initializing device dictionaries improves modularity and readability. Ensure thatmodel_type.devices_key
always corresponds to a valid attribute in the data dictionary to prevent runtime errors.Verification successful
The
ast-grep
script successfully matched the pattern and verified the code segment. The presence of thedata[key]
assignment indicates thatmodel_type.devices_key
is being used correctly within the data dictionary.
- Lines 200-217 in
src/uiprotect/data/bootstrap.py
show the correct usage ofmodel_type.devices_key
.No issues were found with the usage of
model_type.devices_key
in the provided code.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that `model_type.devices_key` always corresponds to a valid attribute. # Test: Check for potential attribute errors in data dictionary. ast-grep --lang python --pattern $'for model_type in ModelType.bootstrap_models_types_set() { $model_type.devices_key: $_ }' src/uiprotect/data/bootstrap.pyLength of output: 672
Script:
#!/bin/bash # Description: Verify that `model_type.devices_key` always corresponds to a valid attribute. # Test: Check for potential attribute errors in data dictionary. ast-grep --lang python --pattern $'for model_type in ModelType.bootstrap_models_types_set():\n key = model_type.devices_key\n items: dict[str, ProtectModel] = {}\n for item in data[key]:\n if (\n api is not None\n and api.ignore_unadopted\n and not item.get("isAdopted", True)\n ):\n continue\n\n ref = {"model": model_type, "id": item["id"]}\n items[item["id"]] = item\n data["idLookup"][item["id"]] = ref\n if "mac" in item:\n cleaned_mac = normalize_mac(item["mac"])\n data["macLookup"][cleaned_mac] = ref\n data[key] = items' src/uiprotect/data/bootstrap.pyLength of output: 2046
347-364
: The handling of different model types in_process_add_packet
is well-implemented. Verify that all model types inModelType.bootstrap_models_types_set()
are handled correctly in this method.Verification successful
The
_process_add_packet
method correctly handles model types inModelType.bootstrap_models_types_set()
, as it includes a specific branch to process these model types. Thebootstrap_models_types_set
method itself returns a set of model types fromModelType.bootstrap_model_types()
, ensuring that all relevant types are considered.
ModelType.EVENT
andModelType.NVR
are explicitly handled.- Other model types in
ModelType.bootstrap_models_types_set()
are processed within the corresponding branch.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify handling of all model types in `_process_add_packet`. # Test: Check for unhandled model types. ast-grep --lang python --pattern $'def _process_add_packet($$$) { if $model_type in ModelType.bootstrap_models_types_set() { $$$ } }' src/uiprotect/data/bootstrap.pyLength of output: 519
Script:
#!/bin/bash # Find the definition of `bootstrap_models_types_set` method in the repository. ast-grep --lang python --pattern 'def bootstrap_models_types_set($$) { $$ }' # Find the usage of `bootstrap_models_types_set` in the repository to verify its handling in `_process_add_packet`. rg 'bootstrap_models_types_set'Length of output: 936
Script:
#!/bin/bash # Display the definition of `bootstrap_models_types_set` method in `src/uiprotect/data/types.py`. rg --context 10 'def bootstrap_models_types_set' src/uiprotect/data/types.py # Display the `_process_add_packet` method in `src/uiprotect/data/bootstrap.py` to verify the handling of model types. rg --context 20 'def _process_add_packet' src/uiprotect/data/bootstrap.pyLength of output: 2304
src/uiprotect/api.py (2)
1149-1149
: LGTM! The change frommodel_type.value
tomodel_type.devices_key
aligns with the PR objectives and should help optimize API requests.
1706-1706
: Excellent refactor! Usingmodel_type.devices_key
in theadopt_device
method enhances consistency and aligns perfectly with the PR's goal of optimizing model type handling.
Description of change
only process incoming websocket packet model type once
Summary by CodeRabbit
New Features
Improvements
Bug Fixes
Refactor
ModelType
enums for more precise model handling and better code maintainability.