AҐi)TdZddlZddlZddlmZmZGddZdZdZd Z d Z y) z Dirty Application Base Class Provides the DirtyApp base class that all dirty applications must inherit from, and utilities for loading dirty apps from import paths. N) DirtyAppErrorDirtyAppNotFoundErrorc&eZdZdZdZdZdZdZy)DirtyAppaf Base class for dirty applications. Dirty applications are loaded once when the dirty worker starts and persist in memory for the lifetime of the worker. They are designed for stateful resources like ML models, connection pools, etc. Lifecycle --------- 1. ``__init__()``: Called when the app is instantiated (once per worker) 2. ``init()``: Called after instantiation to initialize resources 3. ``__call__()``: Called for each request from HTTP workers 4. ``close()``: Called when the worker shuts down State Persistence ----------------- Instance variables persist across requests. This is the key feature that enables loading heavy resources once and reusing them:: class MLApp(DirtyApp): def init(self): self.model = load_model() # Loaded once, reused forever def predict(self, data): return self.model.predict(data) # Same model for all requests Thread Safety ------------- With ``dirty_threads=1`` (default): Only one request runs at a time, so no thread safety concerns. With ``dirty_threads > 1``: Multiple requests may run concurrently in the same worker. Your app MUST be thread-safe. Options: - Use locks: ``threading.Lock()`` for shared state - Use thread-local: ``threading.local()`` for per-thread state - Use read-only state: Load models once in init(), never mutate Example:: import threading class ThreadSafeMLApp(DirtyApp): def __init__(self): self.models = {} self._lock = threading.Lock() def init(self): self.models['default'] = load_model('base-model') def load_model(self, name): with self._lock: if name not in self.models: self.models[name] = load_model(name) return {"loaded": True, "name": name} Worker Allocation ----------------- By default, all dirty workers load all apps. For apps that consume significant memory (like large ML models), you can limit how many workers load the app by setting the ``workers`` class attribute:: class HeavyModelApp(DirtyApp): workers = 2 # Only 2 workers will load this app def init(self): self.model = load_10gb_model() Subclasses should implement: - init(): Called once at worker startup to initialize resources - __call__(action, *args, **kwargs): Handle requests from HTTP workers - close(): Called at worker shutdown to cleanup resources Ncy)az Initialize the application. Called once when the dirty worker starts, after the app instance is created. Use this for expensive initialization like loading ML models, establishing database connections, etc. This method is called in the child process after fork, so it's safe to initialize non-fork-safe resources here. Nselfs K/var/www/descvideos/venv/lib/python3.12/site-packages/gunicorn/dirty/app.pyinitz DirtyApp.initbcnt||d}||jdrtd|||i|S)a Handle a request from an HTTP worker. Args: action: The action/method name to execute *args: Positional arguments for the action **kwargs: Keyword arguments for the action Returns: The result of the action (must be JSON-serializable) Raises: ValueError: If the action is unknown Any exception: Will be caught and returned as DirtyAppError N_zUnknown action: )getattr startswith ValueError)r actionargskwargsmethods r __call__zDirtyApp.__call__nsG vt, >V..s3/x89 9t&v&&rcy)z Cleanup resources. Called when the dirty worker is shutting down. Use this to release resources like database connections, unload models, etc. Nr r s r closezDirtyApp.closerr)__name__ __module__ __qualname____doc__workersr rrr rr rrsHZG  '* rrc\d|vrtd|d||jd}t|dk(r|dfSt|dk(r5|\}}}|d|} t|}|d krtd|d ||||fStd|d|#t$rtd|d |d |wxYw) a Parse a dirty app specification. Supports two formats: - ``"module:Class"`` - standard format, all workers load the app - ``"module:Class:N"`` - worker-limited format, only N workers load the app Args: spec: The app specification string Returns: tuple: (import_path, worker_count) - import_path: The "module:Class" part for importing - worker_count: Integer limit or None for all workers Raises: DirtyAppError: If the spec format is invalid or worker_count is < 1 Examples:: >>> parse_dirty_app_spec("myapp:App") ("myapp:App", None) >>> parse_dirty_app_spec("myapp:App:2") ("myapp:App", 2) >>> parse_dirty_app_spec("myapp.sub:App:1") ("myapp.sub:App", 1) :Invalid import path format: z?. Expected 'module.path:ClassName' or 'module.path:ClassName:N'app_pathNzInvalid worker count in spec: z. Expected integer, got ''rz!. Worker count must be >= 1, got )rsplitlenintr)specparts module_path class_name count_str import_path worker_counts r parse_dirty_app_specr3s'< $*4&1L M  JJsOE 5zQd| 5zQ-2* Z$ Qzl3  y>L ! 0722>A  \**  &tf-H I # 07**3A7  s  B B+cnd|vrtd|d||jdd\}} |tjvrtj|}nt j |} t||}t|tst|d| |}gd }|D]5}t||rtt||r%t|d |||S#t $r}t||d}~wwxYw#t$r t|dwxYw#t$r}td|d |||d}~wwxYw) aO Load a dirty app class from an import path. Args: import_path: String in format 'module.path:ClassName' Returns: An instance of the dirty app class Raises: DirtyAppNotFoundError: If the module or class cannot be found DirtyAppError: If the class is not a valid DirtyApp subclass r"r#". Expected 'module.path:ClassName'r$rN is not a classzFailed to instantiate z: )r rrz is missing required method: )rrsplitsysmodules importlib import_module ImportErrorrrAttributeError isinstancetype Exceptionhasattrcallable) r1r.r/modulee app_classapprequired_methods method_names r load_dirty_apprIs +*;-8/ 0   *00a8K8 #++ %[[-F,,[9F ;FJ/ i &m? +   k5' sK(k9R0S-<[MJ$  JE 8#K0a78 ;#K0d:; $[MA3 7   s;;C( C9D C6% C11C69D D4D//D4c4i}|D]}t|||<|S)z Load multiple dirty apps from a list of import paths. Args: import_paths: List of import path strings Returns: dict: Mapping of import path to app instance Raises: DirtyAppError: If any app fails to load )rI) import_pathsappsr1s r load_dirty_appsrMs, D#8 *;7[8 Krcd|vrtd|d||jdd\}} |tjvrtj|}nt j |} t||}t|tst|d|t|ddS#t $r}t||d}~wwxYw#t$r t|dwxYw) a Get the workers class attribute from a dirty app without instantiating it. This is used by the arbiter to determine how many workers should load an app based on the class attribute, without needing to actually load the app. Args: import_path: String in format 'module.path:ClassName' Returns: The workers class attribute value (int or None) Raises: DirtyAppNotFoundError: If the module or class cannot be found DirtyAppError: If the import path format is invalid r"r#r5r$rNr6r ) rr7r8r9r:r;r<rrr=r>r?)r1r.r/rCrDrEs r get_app_workers_attributerO,s$ +*;-8/ 0   *00a8K8 #++ %[[-F,,[9F ;FJ/ i &m? +   9i ..# 8#K0a78 ;#K0d:;s#;B!( B>! B;* B66B;>C) rr:r8errorsrrrr3rIrMrOr rr rQs9  8w w tHV?D&2/r