when notebooks open, we have added a signature to the notebook, stored in metadata. The notebook server verifies this signature when a notebook is opened. If the signature stored in the notebook metadata does command-line with: $ jupyter trust mynotebook.ipynb [other notebooks.ipynb] This just generates a new signature stored in each notebook. You can generate a new notebook signing key with: $ jupyter trust --reset serializer. Session.session [CUnicode] Default: '' The UUID identifying this session. Session.signature_scheme [Unicode] Default: 'hmac-sha256' The digest scheme used to construct the message

3 Exceptions 11 3.4 Signing With Timestamps 12 3.5 URL Safe Serialization 13 3.6 JSON Web Signature (JWS) 14 3.7 Encoding Utilities 15 3.8 License 15 3.9 Changes 16 Python Module Index 21 attach a signature to a specific string: from itsdangerous import Signer s = Signer("secret-key") s.sign("my string") b'my string.wh6tMHxLgJqB6oY1uT73iMlyrOA' The signature is appended you won't be able to tell if it was Unicode or a bytestring. If the value is changed, the signature will no longer match, and unsigned will raise a BadSignature exception: s.unsigned(b"different

you may want to pass the signature of a task invocation to another process or as an argument to another function, for this Celery uses something called signatures. A signature wraps the arguments and execution across the wire. You can create a signature for the add task using the arguments (2, 2), and a countdown of 10 seconds like this: ```python >>> add.signature((2, 2), countdown=10) tasks.add(2 . Signature instances also supports the calling API: meaning they have the delay and apply_async methods. But there's a difference in that the signature may already have an argument signature specified

you may want to pass the signature of a task invocation to another process or as an argument to another function, for this Celery uses something called signatures. A signature wraps the arguments and execution across the wire. You can create a signature for the add task using the arguments (2, 2), and a countdown of 10 seconds like this: ```python >>> add.signature((2, 2), countdown=10) tasks.add(2 . Signature instances also supports the calling API: meaning they have the delay and apply_async methods. But there's a difference in that the signature may already have an argument signature specified

you may want to pass the signature of a task invocation to another process or as an argument to another function, for which Celery uses something called signatures. A signature wraps the arguments and across the wire. You can create a signature for the add task using the arguments (2, 2), and a countdown of 10 seconds like this: ```python >>> add.signature((2, 2), countdown=10) tasks.add(2 again... Signature instances also support the calling API, meaning they have delay and apply_async methods. But there's a difference in that the signature may already have an argument signature specified

you may want to pass the signature of a task invocation to another process or as an argument to another function, for which Celery uses something called signatures. A signature wraps the arguments and across the wire. You can create a signature for the add task using the arguments (2, 2), and a countdown of 10 seconds like this: ```python >>> add.signature((2, 2), countdown=10) tasks.add(2 again... Signature instances also support the calling API, meaning they have delay and apply_async methods. But there's a difference in that the signature may already have an argument signature specified

you may want to pass the signature of a task invocation to another process or as an argument to another function, for which Celery uses something called signatures. A signature wraps the arguments and across the wire. You can create a signature for the add task using the arguments (2, 2), and a countdown of 10 seconds like this: ```python >>> add.signature((2, 2), countdown=10) tasks.add(2 again... Signature instances also support the calling API, meaning they have delay and apply_async methods. But there's a difference in that the signature may already have an argument signature specified

you may want to pass the signature of a task invocation to another process or as an argument to another function, for which Celery uses something called signatures. A signature wraps the arguments and across the wire. You can create a signature for the add task using the arguments (2, 2), and a countdown of 10 seconds like this: ```python >>> add.signature((2, 2), countdown=10) tasks.add(2 again... Signature instances also support the calling API, meaning they have delay and apply_async methods. But there's a difference in that the signature may already have an argument signature specified

you may want to pass the signature of a task invocation to another process or as an argument to another function, for which Celery uses something called signatures. A signature wraps the arguments and across the wire. You can create a signature for the add task using the arguments (2, 2), and a countdown of 10 seconds like this: ```python >>> add.signature((2, 2), countdown=10) tasks.add(2 again... Signature instances also support the calling API, meaning they have delay and apply_async methods. But there's a difference in that the signature may already have an argument signature specified

you may want to pass the signature of a task invocation to another process or as an argument to another function, for this Celery uses something called signatures. A signature wraps the arguments and execution across the wire. You can create a signature for the add task using the arguments $ (2, 2) $ , and a countdown of 10 seconds like this: >>> add.signature((2, 2), countdown=10) tasks.add(2, 2) again... Signature instances also support the calling API: meaning they have the delay and apply_async methods. But there’s a difference in that the signature may already have an argument signature specified