ParaScheduler

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Storage functions

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AvailabilityCores

One entry for each availability core. Entries are None if the core is not currently occupied. Can be temporarily Some if scheduled but not occupied. The i'th parachain belongs to the i'th core, with the remaining cores all being parathread-multiplexers.

Bounded by the maximum of either of these two values: * The number of parachains and parathread multiplexers * The number of validators divided by configuration.max_validators_per_core.

Python

result = substrate.query(
    'ParaScheduler', 'AvailabilityCores', []
)

Return value

[
    {
        'Free': None,
        'Paras': {
            'assignment': {
                'Bulk': 'u32',
                'Pool': {'core_index': 'u32', 'para_id': 'u32'},
            },
            'availability_timeouts': 'u32',
            'ttl': 'u32',
        },
    },
]

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ClaimQueue

One entry for each availability core. The VecDeque represents the assignments to be scheduled on that core. None is used to signal to not schedule the next para of the core as there is one currently being scheduled. Not using None here would overwrite the CoreState in the runtime API. The value contained here will not be valid after the end of a block. Runtime APIs should be used to determine scheduled cores/ for the upcoming block.

Python

result = substrate.query(
    'ParaScheduler', 'ClaimQueue', []
)

Return value

'scale_info::795'

---

SessionStartBlock

The block number where the session start occurred. Used to track how many group rotations have occurred.

Note that in the context of parachains modules the session change is signaled during the block and enacted at the end of the block (at the finalization stage, to be exact). Thus for all intents and purposes the effect of the session change is observed at the block following the session change, block number of which we save in this storage value.

Python

result = substrate.query(
    'ParaScheduler', 'SessionStartBlock', []
)

Return value

'u32'

---

ValidatorGroups

All the validator groups. One for each core. Indices are into ActiveValidators - not the broader set of Polkadot validators, but instead just the subset used for parachains during this session.

Bound: The number of cores is the sum of the numbers of parachains and parathread multiplexers. Reasonably, 100-1000. The dominant factor is the number of validators: safe upper bound at 10k.

Python

result = substrate.query(
    'ParaScheduler', 'ValidatorGroups', []
)

Return value

[['u32']]

---