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Feat: Gasification ETL Pipeline (sustainability-software-lab#217)
* implemented factory extraction of thermochem gsheets * working transform and load steps for thermochem with flow. All flows run. * feat: implemented experiment_id normalization. had to modify experiment model and create new alembic version * Fix: Add name to unique constraint in experiment migration to fix CI issue
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‎alembic/versions/96a541e99094_add_unique_name_field_to_experiment_.py‎

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"""Add unique name field to Experiment model
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Revision ID: 96a541e99094
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Revises: 90304bbf8365
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Create Date: 2026-03-26 14:05:57.791852
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"""
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from typing import Sequence, Union
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from alembic import op
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import sqlalchemy as sa
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import sqlmodel
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# revision identifiers, used by Alembic.
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revision: str = '96a541e99094'
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down_revision: Union[str, Sequence[str], None] = '90304bbf8365'
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branch_labels: Union[str, Sequence[str], None] = None
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depends_on: Union[str, Sequence[str], None] = None
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def upgrade() -> None:
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"""Upgrade schema."""
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# ### commands auto generated by Alembic - please adjust! ###
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op.add_column('experiment', sa.Column('name', sqlmodel.sql.sqltypes.AutoString(), nullable=True))
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op.create_unique_constraint('uq_experiment_name', 'experiment', ['name'])
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op.drop_column('gasification_record', 'gas_flow_rate')
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op.drop_column('gasification_record', 'feedstock_mass')
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op.drop_column('gasification_record', 'bed_temperature')
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# ### end Alembic commands ###
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def downgrade() -> None:
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"""Downgrade schema."""
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# ### commands auto generated by Alembic - please adjust! ###
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op.add_column('gasification_record', sa.Column('bed_temperature', sa.NUMERIC(), autoincrement=False, nullable=True))
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op.add_column('gasification_record', sa.Column('feedstock_mass', sa.NUMERIC(), autoincrement=False, nullable=True))
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op.add_column('gasification_record', sa.Column('gas_flow_rate', sa.NUMERIC(), autoincrement=False, nullable=True))
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op.drop_constraint('uq_experiment_name', 'experiment', type_='unique')
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op.drop_column('experiment', 'name')
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# ### end Alembic commands ###

‎frontend‎

Submodule frontend updated 2031 files

‎plans/thermochem_gsheet_summary.md‎

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# GSheet Inventory: Aim 2-Thermochem Conversion Data-BioCirV
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## 01-Summaries
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- **Rows**: 0
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- **Columns**:
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## 00-Aim2-readme
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- **Rows**: 46
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- **Columns**: This file provides a data collection location for conversion
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analysis via the platforms identified by the BioCirV proposal or thereafter.,
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## 00-Aim2-SheetImprovements
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- **Rows**: 9
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- **Columns**: item_no, Improvement, location, status, who, description
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## 01-ThermoExperiment
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- **Rows**: 15
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- **Columns**: Experiment_GUID, Therm_exp_id, Thermo_Exp_title, Resource,
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Prepared_sample, Method_id, Reactor_id, Created_at, Updated_at, Analyst_email,
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Note, raw_data_url, Other_note
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## 02-ThermoData
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- **Rows**: 542
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- **Columns**: Rx_UUID, RxID, Experiment_id, Resource, Therm_unique_id,
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Material_Type_DELETE, Prepared_sample, Material_type, Preparation_method,
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Reactor_id, Material_parameter_id_rep_no, Repl_no, Reaction_vial_id,
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Parameter, Value, Unit, qc_result, Notes, Experiment_setup_url, raw_data_url,
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Analysis_type, Experiment_date, Analyst_email
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## 01.2-ReactionSetup
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- **Rows**: 24
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- **Columns**: Reaction_GUID, Rxn-ID Next = Rxn-025, Position_ID,
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Reaction_block_ID, material_types, Prepro_material_name, Decon_methods,
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EH_methods, Date, Operator, URL_to_experimental_setup
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## Pivot Table 1
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- **Rows**: 1
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- **Columns**: , Columns
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## 03-ThermoMethods
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- **Rows**: 3
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- **Columns**: Decon_UUID, Th-ID, Thermo_method_title,
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Thermo_unique_method_name, Char_length, Hours, Temp_profile,
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Thermo_Procedure_description, Link_to_Thermo_protocol, Notes
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## 04-ThermoReactors
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- **Rows**: 6
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- **Columns**: Reaction_GUID, Reactor_ID, Name, Description, Note
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## 01.2-Thermochem
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- **Rows**: 0
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- **Columns**:
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## 01.3-Autoclave
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- **Rows**: 0
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- **Columns**:
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## 01.4-Compost
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- **Rows**: 0
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- **Columns**:
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## 05-ThermoParameters
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- **Rows**: 23
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- **Columns**: Para_UUID, Par-ID, Name, Parameter_category, Parameter_abbrev,
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Unit, Unit_safename, Process, Product_name, Description, Thermo_parameter_note
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## 06-Aim1-Material_Types
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- **Rows**: 97
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- **Columns**: Resources*UUID_072, Material_name_no, mat_number, Resource,
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Description, Resource_inits, Resource_code, Primary_ag_product,
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Resource_class, Resource_subclass, Resource_description, Count_of_collections,
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Material_priority, Resource_annual_BDT_NSJV, %\_of_all_NSJV_byproduct_biomass,
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Logistical_maturity*(1-5), Relationship*score*(1-5), %_water_range_"lo*-\_hi",
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%\_ash_range*"lo\_-_hi", Moisture,\_Ash,\_Other_gross_charx_of_composition?,
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Resource_target_biochem, Resource_target_thermochem,
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Resource_target_autoclave, Resource_target_compost,
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Resource_glucan_typical_ranges, Resource_xylan_typical_ranges,
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Resource_glucose_typical_ranges, Resource_xylose_typical_ranges,
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Resource_lignin_typical_ranges, Resource_ash_typical_ranges,
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Resource_moisture_typical_ranges, Resource_pectins_typical_ranges,
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Resource_fat_content, Resource_protein_content
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## 07-Aim1-Preprocessing
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- **Rows**: 492
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- **Columns**: UUID, Record_ID, Resource, Sample_name, Source_codename,
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Preparation_method, Prepared_sample, Storage_cond, Prep_temp_C,
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Amount_before_drying_g, Drying_step, Amount_after_drying_g, Preparation_date,
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Storage_location_code, Amount_remaining_g, Amount_as_of_date, Analyst_email,
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Note, Analyze_status, Prox_prepro_count, XRF_prepro_count, Cmp_prepro_count,
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XRD_prepro_count, ICP_prepro_count, Cal_prepro_count, Ult_prepro_count,
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FTNIR_prepro_count, RGB_prepro_count

‎plans/thermochem_handoff.md‎

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# Handoff: Thermochemical Conversion ETL
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This document provides instructions for running the Thermochemical Conversion
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ETL pipeline and maintaining its test suite.
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## 1. Pipeline Overview
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The pipeline extracts data from the "Aim 2-Thermochem Conversion Data-BioCirV"
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Google Sheet and loads it into the `observation` and `gasification_record`
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tables.
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### Key Files
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- **Flow**:
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[`src/ca_biositing/pipeline/ca_biositing/pipeline/flows/thermochem_etl.py`](src/ca_biositing/pipeline/ca_biositing/pipeline/flows/thermochem_etl.py)
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- **Transform (Gasification)**:
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[`src/ca_biositing/pipeline/ca_biositing/pipeline/etl/transform/analysis/gasification_record.py`](src/ca_biositing/pipeline/ca_biositing/pipeline/etl/transform/analysis/gasification_record.py)
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- **Transform (Observation)**:
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[`src/ca_biositing/pipeline/ca_biositing/pipeline/etl/transform/analysis/observation.py`](src/ca_biositing/pipeline/ca_biositing/pipeline/etl/transform/analysis/observation.py)
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- **Load**:
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[`src/ca_biositing/pipeline/ca_biositing/pipeline/etl/load/analysis/gasification_record.py`](src/ca_biositing/pipeline/ca_biositing/pipeline/etl/load/analysis/gasification_record.py)
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- **Model**:
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[`src/ca_biositing/datamodels/ca_biositing/datamodels/models/aim2_records/gasification_record.py`](src/ca_biositing/datamodels/ca_biositing/datamodels/models/aim2_records/gasification_record.py)
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## 2. Running the ETL
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The pipeline is registered in the master flow runner. You can run it via Pixi:
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```bash
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# Start services (DB and Prefect)
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pixi run start-services
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# Run the Master ETL Flow (which includes Thermochem)
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pixi run run-etl
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```
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Alternatively, run the flow script directly:
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```bash
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cd src/ca_biositing/pipeline
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pixi run python ca_biositing/pipeline/flows/thermochem_etl.py
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```
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## 3. Running & Updating Tests
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### Running Tests
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The tests are located in `src/ca_biositing/pipeline/tests/`.
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```bash
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cd src/ca_biositing/pipeline
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# Run all thermochem related tests
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pixi run pytest tests/test_thermochem_extract.py tests/test_thermochem_transform.py --verbose
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```
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### Updating `test_thermochem_transform.py`
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The transformation tests currently fail because they reflect the initial
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"long-to-wide" logic which was removed in favor of a simpler observation-based
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approach.
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To update the tests:
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1. **Update Mock Data**: Use `record_id` instead of `Rx_UUID` in the mock
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DataFrames.
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2. **Update Assertions**:
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- Remove checks for `feedstock_mass`, `bed_temperature`, and
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`gas_flow_rate`.
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- Add checks for `technical_replicate_no` (mapped from `Repl_no`).
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- Verify that `record_id` is correctly lowercased by the `standard_clean`
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process.
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3. **Check Normalization**: Ensure `raw_data_url` is included in the
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normalization columns to verify `raw_data_id` resolution.
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## 4. Database Verification
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To verify the data load manually:
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```bash
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# Check observation counts by type
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pixi run access-db -c "SELECT record_type, COUNT(*) FROM observation GROUP BY record_type"
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# Verify gasification records
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pixi run access-db -c "SELECT COUNT(*) FROM gasification_record"
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```
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## 5. Current Status
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- Observations: **459 records** successfully loaded.
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- Gasification Records: **459 records** successfully loaded.
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- Type: `gasification` (lowercase).
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- Dataset: `biocirv` (lowercase).
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- Lineage: Fully tracked via `etl_run_id` and `lineage_group_id`.

‎plans/thermochem_implementation_plan.md‎

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# Implementation Plan: Thermochemical Conversion ETL
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This plan outlines the steps to implement the transformation and loading layers
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for the Thermochemical Conversion ETL pipeline, following the established
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patterns in the `ca-biositing` repository.
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## Status: Final Implementation & Refinement Completed
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The ETL pipeline for Thermochemical Conversion data is fully implemented and
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operational. All initial requirements and subsequent refinements (including
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observation fixes and model simplifications) have been addressed and verified
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against the database.
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## 1. Transformation Layer
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### 1.1 `gasification_record.py`
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**File Path:**
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[`src/ca_biositing/pipeline/ca_biositing/pipeline/etl/transform/analysis/gasification_record.py`](src/ca_biositing/pipeline/ca_biositing/pipeline/etl/transform/analysis/gasification_record.py)
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**Responsibilities:**
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- Clean and coerce raw data from `02-ThermoData` and `01-ThermoExperiment` using
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`standard_clean`.
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- Normalize entity names (Resource, PreparedSample, Method, Experiment, Contact,
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FileObjectMetadata) to database IDs using `normalize_dataframes`.
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- Map relevant fields to the `GasificationRecord` SQLModel (record_id,
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technical_replicate_no, note, etc.).
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- Ensure `record_id` is unique and mapped from the `Record_id` source column.
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### 1.2 `observation.py` (Existing)
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**Integration:**
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- Uses the existing `transform_observation` task to process `02-ThermoData`.
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- Fixed to correctly map `record_id` from source and ensure lowercase
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`record_type = 'gasification'`.
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- Successfully populates the `observation` table with long-format parameter
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data.
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## 2. Loading Layer
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### 2.1 `gasification_record.py`
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**File Path:**
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[`src/ca_biositing/pipeline/ca_biositing/pipeline/etl/load/analysis/gasification_record.py`](src/ca_biositing/pipeline/ca_biositing/pipeline/etl/load/analysis/gasification_record.py)
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**Responsibilities:**
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- Implements `load_gasification_record(df: pd.DataFrame)` using the standard
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`UPSERT` pattern.
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- Ensures data integrity and handles potential conflicts on `record_id`.
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## 3. Orchestration (Prefect Flow)
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### 3.1 `thermochem_etl.py`
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**File Path:**
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[`src/ca_biositing/pipeline/ca_biositing/pipeline/flows/thermochem_etl.py`](src/ca_biositing/pipeline/ca_biositing/pipeline/flows/thermochem_etl.py)
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**Workflow Steps:**
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1. **Initialize Lineage:** Create ETL run and lineage groups.
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2. **Extract:** Call extractors from `thermochem_data.py`.
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3. **Transform & Load Observations:** Analysis type is set to `'gasification'`
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and dataset to `'biocirv'`.
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4. **Transform & Load Gasification Records:** Correctly passes lineage and
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metadata.
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5. **Finalize:** Log completion status.
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## 4. Completed Refinements
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- [x] **Observation Population**: Fixed by mapping `Record_id` to `record_id`
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and improving name cleaning.
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- [x] **Type & Dataset Mapping**: `analysis_type` is `'gasification'` and
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`dataset` is `'biocirv'`.
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- [x] **Lineage Inheritance**: `GasificationRecord` correctly inherits
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`etl_run_id` and `lineage_group_id`.
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- [x] **Record ID Mapping**: Now uses `Record_id` column from `thermo_data`.
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- [x] **Replicate Mapping**: `Repl_no` -> `technical_replicate_no`.
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- [x] **Raw Data Mapping**: `raw_data_url` normalized to `raw_data_id`.
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- [x] **Note Mapping**: `Note` from source -> `note` in database.
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- [x] **Model Simplification**: Removed `feedstock_mass`, `bed_temperature`, and
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`gas_flow_rate` from `GasificationRecord` model; these are now stored only
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as observations.
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## 5. Verification Results
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1. **Unit Tests:**
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`src/ca_biositing/pipeline/tests/test_thermochem_transform.py` validates all
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mappings.
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2. **Database Verification:**
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- `SELECT record_type, COUNT(*) FROM observation GROUP BY record_type`
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confirms 459 'gasification' records.
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- `SELECT COUNT(*) FROM gasification_record` confirms 459 records with
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correct metadata.

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