SampleRerun and SampleRerunValues models, sampleRedrawFlag states, ReportFormat meta fields, Redis cache structure, and activity log constants.

Data Model

SampleRerun (DocumentDB)

File: report/models/sample_rerun.py Collection: SampleRerun

Tracks the transactional state of each rerun — which parameters were requested, which have been fulfilled, and whether the rerun is still active.

class SampleRerun(BaseModel, DocumentDBModelBase):
    document_db_table_name = "SampleRerun"

    REQUESTED_RERUN_STATE = 3
    COMPLETED_RERUN_STATE = 4
    INSTRUMENT_TRIGGERED_RERUN_NUMBER = -1
    AUTO_RERUN_DEFAULT_RERUN_NUMBER = "1"
    CUSTOM_RANGE_PARAMETER = "custom"

Fields

Field	Type	Description
`lab_id`	`PositiveIntegerField`	Lab the rerun belongs to
`type`	`CharField`	`"Manual"` or `"Auto"`
`rerun_number`	`PositiveSmallIntegerField`	Iteration number (`1`, `2`, … or `-1` for instrument-triggered)
`lab_report_id`	`PositiveBigIntegerField`	FK to the `LabReportRelation` this rerun targets
`is_active`	`BooleanField`	`True` while the rerun is in progress; `False` once fulfilled or cancelled
`requested_parameters`	`JSONField`	Array of parameter indices requested for re-run (e.g., `[1, 3, 5]`)
`fulfilled_parameters`	`JSONField`	Array of parameter indices that have received rerun values
`parameter_name`	`CharField`	Display name of the parameter
`created_by`	`PositiveIntegerField`	User who initiated the rerun (`-1` for auto/internal)
`created_at`	`PositiveBigIntegerField`	Unix timestamp
`updated_by`	`PositiveIntegerField`	User who last updated
`updated_at`	`PositiveBigIntegerField`	Unix timestamp

Key methods

Method	Purpose
`get_valid_requested_parameters()`	Filters incoming device data to only include parameters that were actually requested
`add_received_parameters_to_fulfilled_parameters()`	Merges received indices into `fulfilled_parameters`
`is_rerun_fulfilled()`	Returns `True` when all `requested_parameters` are in `fulfilled_parameters`
`fulfill_rerun()`	Marks `is_active = False` in DocumentDB
`auto_rerun_condition_met()`	Evaluates a value against the configured auto-rerun range
`get_auto_rerun_qualified_indices()`	Returns indices that qualify for auto rerun from a batch of device values
`auto_rerun_record_exists()`	Guard: prevents duplicate auto reruns for the same report
`get_reports_rerun_details()`	Bulk fetch of active rerun details for a list of report IDs

SampleRerunValues (DocumentDB)

File: report/models/sample_rerun_values.py Collection: SampleRerunValues

Stores the actual parameter values received during a rerun — one record per parameter per rerun iteration.

Fields

Field	Type	Description
`lab_id`	`IntegerField`	Lab identifier
`profile_test_id`	`IntegerField`	Profile test identifier
`sample_id`	`CharField`	Sample barcode / manual ID
`value`	`TextField`	The rerun result value
`order`	`IntegerField`	Parameter order in the report
`index`	`IntegerField`	Parameter index in the report format
`highlight`	`IntegerField`	Highlight flag (0 or 1)
`automated_value`	`IntegerField`	Whether value was automated
`lab_report_id`	`IntegerField`	FK to the report
`device_id`	`CharField`	Source device identifier
`device_name`	`CharField`	Source device display name
`rerun_type`	`CharField`	`"manual_rerun"` or `"instrument_triggered"`
`rerun_number`	`IntegerField`	Rerun iteration number
`parameter_name`	`CharField`	Display name of the parameter
`created_at`	`DateTimeField`	Auto-set on creation

Key methods

Method	Purpose
`serialize_records()`	Converts DocumentDB records (with ObjectId) to JSON-safe format
`delete_values_and_transactions_for_report()`	Deletes all `SampleRerunValues` and `SampleRerun` records for a report, clears Redis cache
`close_rerun()`	Full cleanup — resets `sampleRedrawFlag = 0`, syncs ES, deletes DocDB records and cache

Confirmation report keys

When confirming rerun values, only these fields are copied back to ReportValue:

CONFIRMATION_REPORT_KEYS = [
    "profileTestId", "value", "order", "index",
    "highlight", "automatedValue", "reportForId_id",
]

sampleRedrawFlag (MySQL)

File: report/models/lab_report_relation.py

An integer field on every LabReportRelation row:

sampleRedrawFlag = models.IntegerField(default=0)

Value	Constant	State
`0`	—	No rerun active
`1`	—	Legacy partial redraw
`2`	—	Legacy full redraw
`3`	`SampleRerun.REQUESTED_RERUN_STATE`	Rerun requested, awaiting values
`4`	`SampleRerun.COMPLETED_RERUN_STATE`	Rerun values received, awaiting confirmation

Where sampleRedrawFlag is filtered

The flag is used extensively in queries to exclude rerun-in-progress reports from normal workflows:

Query Context	Filter
Waiting list (normal)	`sampleRedrawFlag = 0`
Waiting list (with reruns)	`sampleRedrawFlag ∈ [0, 3]` (Bool should query)
Completed tests	`sampleRedrawFlag ∈ [0, 1, 2, 4]`
Device results validation	`sampleRedrawFlag = 0` for new records; `∈ [0, 3, 4]` for tox
ES mappers (org, staff, doctor)	`sampleRedrawFlag = 0` or `must_not sampleRedrawFlag = 2`
Accession sample query	`sampleRedrawFlag = 0`

ReportFormat meta — rerun configuration

File: report/models/report_format.py

Rerun configuration is stored in the meta JSON field of each ReportFormat row:

{
  "auto_rerun": 1,
  "manual_rerun": 1,
  "parameter_result_value": "ABNORMAL",
  "customLowerMale": "10",
  "customUpperMale": "50",
  "customLowerFemale": "8",
  "customUpperFemale": "45"
}

Key properties

Property	Returns
`auto_rerun_allowed`	`True` if `meta.auto_rerun == 1`
`auto_rerun_parameter_condition`	The condition string: `"normal"`, `"abnormal"`, `"critical"`, `"custom"`
`get_auto_rerun_custom_ranges(patient_sex)`	`(lower, upper)` tuple from custom meta fields

Range evaluation

SampleRerun.auto_rerun_condition_met() delegates to ReportFormat.value_meets_parameter_condition() which compares the value against:

Normal/Abnormal: Standard reference ranges (or ValueRanges if ageRangeFlag = 1)
Critical: Critical reference ranges
Custom: Custom bounds from meta fields

Redis cache structure

Key pattern: sample_rerun_{lab_id} (Redis hash)

Hash field	Value	Description
`{lab_report_id}`	`{rerun_number}`	Maps each report to its current active rerun number

TTL: 86,400 seconds (1 day)

Cache operations

Method	Operation
`set_rerun_cache()`	`HSET` a single lab_report_id → rerun_number
`get_rerun_cache()`	`HGET` for a single lab_report_id
`get_rerun_cache_bulk()`	`HMGET` for multiple lab_report_ids
`delete_rerun_cache()`	`HDEL` for a single lab_report_id
`fill_rerun_cache()`	Backfill from DocumentDB on cache miss

Activity log constants

File: core/utils/activity_log/__init__.py

RERUN_VALUES_RECEIVED = 979
RERUN_VALUES_CONFIRMED = 980
RERUN_REQUESTED = 981
RERUN_FAILED = 984
RERUN_CANCELLED = 985

Log text format

Event	Activity text pattern
Request	`"Manual Sample Rerun requested for Sample ID: '{id}' on parameters: (...) of Test: '{name}'."`
Values received	`"Sample Rerun values received for parameters: {name} ({value}) of Test: '{name}' with Sample ID: '{id}'."`
Confirmed	`"Sample Rerun values confirmed for parameters: {name} (Value: {value}) of Test: '{name}' with Sample ID: '{id}'."`
Failed	`"Sample rerun request failed for Test: '{name}' with Sample ID: '{id}'."`
Cancelled	`"Sample rerun cancelled successfully for Test: '{name}' with Sample ID: '{id}'."`

Data Model

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