Nexus2 Pipeline Fix

Fixes JSON serialization of pandas Timestamps and ensures fresh fixture ingestion for accurate Nexus2 sports predictions.

Security Scan

The instructions describe a focused bugfix (JSON encoder + correct data loader usage) and only ask you to copy two patched files and restart the pipeline, but the skill does not supply the patches or their source so you should review and obtain the changes from a trusted location before applying them.

Purpose & Capability

The name/description (fix timestamp serialization and stale fixture ingestion) aligns with the actions described: modify publishing/publisher.py to add a NexusEncoder and change nexus.py to ingest into self.data_loader. No unrelated services, binaries, or credentials are requested.

Instruction Scope

Runtime instructions are narrowly scoped: copy two patched files into your Nexus2 installation and restart the prediction run. However, the skill does not include the patched files, diffs, or a URL/source for them—so the instructions assume you already have the patches or will obtain them elsewhere.

Install Mechanism

No install spec or code files are present; this is instruction-only, which minimizes disk writes and external downloads.

Credentials

No environment variables, credentials, or config paths are requested. The requested actions (file replacement + restart) are proportional to the stated fixes.

Persistence & Privilege

The skill does not request persistent/always-on privileges or attempt to modify other skills or system-wide agent settings.

Assessment

The advice looks coherent for a simple code fix, but proceed cautiously because the skill does not include the patched files or a verified source. Before applying: (1) obtain the actual patch/diff from a trusted repository or the author and review the changes line-by-line; (2) back up the original publishing/publisher.py and nexus.py; (3) run the changes in a staging environment and execute unit/integration tests; (4) verify the NexusEncoder handles pandas.Timestamp (including timezone-aware datetimes) and that nexus.py uses the correct data_loader instance in all code paths; (5) confirm the patch matches your Nexus2 codebase version to avoid breaking imports or API mismatches. If you can't obtain the patch from a trusted source, implement equivalent fixes yourself or request a full diff before applying.

Nexus2 Pipeline Fix — Sports Prediction Engine

What This Fixes

Two critical bugs in the Nexus2 sports prediction pipeline that caused phantom predictions and JSON serialization crashes.

Bug 1: Timestamp Serialization Crash

File: publishing/publisher.py
Problem: json.dumps() failed with TypeError: Object of type Timestamp is not JSON serializable when prediction data contained pandas Timestamp objects.
Fix: Added custom NexusEncoder class that converts pandas Timestamp and datetime objects to ISO format strings before serialization.

Bug 2: Stale Fixture Ingestion

File: nexus.py
Problem: Scraped fixtures were ingested into an isolated local NexusDataLoader() instance instead of self.data_loader. Predictions ran against stale database data, producing phantom matches that didn't exist on bookmaker sites.
Fix: Changed ingestion to use self.data_loader.ingest(matches) directly, ensuring fresh scraped fixtures flow into the prediction pipeline.

How to Apply

1. Copy the patched files into your Nexus2 installation:
   • publishing/publisher.py — adds NexusEncoder class
   • nexus.py — fixes fixture ingestion in predict() method
2. Restart the prediction pipeline: python nexus.py --predict
3. Verify output matches live bookmaker fixtures

Result

• Predictions now match real SportyBet/SofaScore fixtures
• No more JSON serialization crashes
• Fresh fixtures ingested before each prediction run

Author

TKDigital ( Imperial Court / OpenClaw )