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docs/src/compute/make.md

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@@ -6,19 +6,19 @@ careful record of data provenance and ensure reproducibility. Data should never
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entered using the `insert` method directly.
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[^1]: For information on differentiating these data tiers, see the Table Tier section on
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[Automation](../tabletiers#automation-imported-and-computed).
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[Automation](../design/tables/tiers#automation-imported-and-computed).
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The `make` method receives one argument: the *key*, which represents the upstream table
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entries that need populating. The `key` is a `dict` in Python.
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A `make` function should do three things:
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1. [Fetch](../../query-lang/common-commands#fetch) data from tables upstream in the
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1. [Fetch](../query/common-commands#fetch) data from tables upstream in the
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pipeline using the key for restriction.
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2. Compute and add any missing attributes to the fields already in the key.
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3. [Inserts](../../query-lang/common-commands#insert) the entire entity into the
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3. [Inserts](../query/common-commands#insert) the entire entity into the
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triggering table.
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## Populate
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the class method called to run the `make` method on all relevant keys[^2].
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[^2]: For information on reprocessing keys that resulted in an error, see information
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on the [Jobs table](../../ref-integrity/distributed-computing).
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on the [Jobs table](./distributed).
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``` python
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Segmentation.populate()

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