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File: //var/opt/nydus/ops/primordial/__pycache__/context.cpython-39.pyc
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    Context instances can be used to hold state and values during the execution life cycle of a
    python application without needing to change the existing API of various interacting classes.
    State/values can be updated in one part of the application and be visible in another part
    of the application without requiring to pass this state thru the various methods of the call stack.
    Context also supports maintenance of global and thread specific state which can be very useful
    in a multi-threaded applications like Flask/Falcon based web applications or the NES Journal reader.
    State stored at the global level is visible in every concurrently executed thread, while thread
    specific state is isolated to the corresponding thread of execution. This can useful again in a
    multi-threaded application like a web-app where each incoming request is processed by a separate
    thread and things like request headers, authentication user context is thread specific and isolated
    to the thread handling a particular request.

    Example usage:

    -- In the main thread of an application's start up code we might want to inject some global state
    like so.

    # In some start-up file called app.py

    from primordial.context import Context
    MY_APP_CTX = Context()
    # Instantiate some shared object
    jwt_fetcher = JWTFetcher(some_config)
    MY_APP_CTX.set_global('jwt_fetcher', jwt_fetcher)

    # In a thread that's handling a particular HTTP request
    # handle_req.py
    from app import MY_APP_CTX
    MY_APP_CTX.user = User()
    MY_APP_CTX.token = copy_token_from_header()

    # In a third file somewhere down the line of request processing
    # some_file_called_by_controller.py
    from app import MY_APP_CTX
    def some_func():
        # All of these are magically available.
        # some_func's function signature didn't require to be changed
        MY_APP_CTX.jwt_fetcher.get()
        MY_APP_CTX.user.name == 'jDoe'
        MY_APP_CTX.token.is_valid()
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cs�|r|nt}|r|ni}|r |ni}|��D]\}}t|||�q,|��D]\}}|�||�qJz2|VW|D]}t||�qn|D]}|�|�q�n*|D]}t||�q�|D]}|�|�q�0dS)a^
    Python context-manager for managing the life-cycle of state stored in a context.
    This context manager allows for state to be both stored in a context and
    also cleans up this state when the context-manager is exited.

    Usage:

    # In some python module file1.py
    from primordial import Context
    ctx = Context()

    # In some python module file2.py
    from threading import Thread
    from primordial import make_context
    from file1 import ctx
    from file3 import fn3

    def fn2():
        global_vals = {'v1': 'abc', v2: 'def'}
        # Set some global values
        with make_context(global_vals=global_value, ctx):
            # Kick of fn3 in a new thread
            t1 = Thread(target=fn3, args=[])
            t1.start()
            t1.join()

    fn2()

    # In some python module file3.py
    from primordial import make_context
    from file1 import ctx
    from file4 import fn4

    def fn3():
        # v2 will shadow the value that was set globally
        local_vals = {'v3': 'ghi', v2: 'jkl'}
        # Set some thread specific values
        # Once this function returns, ctx.v3 and ctx.v2 are not available for access
        with make_context(local_vals=local_value, ctx):
            fn4()

        # We can still access the globally set state here even after the above context manager
        # has exited.
        ctx.v1
        ctx.v2  # The globally set v2

    # In some python module file3.py
    from file1 import ctx

    def fn4():
        # All of the accesses are valid
        ctx.v1
        ctx.v2  # This accesses the local thread specific v2
        ctx.v3
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