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import re
from pathlib import Path
import pytest
from morphsql.models import Dialect, MigrationObject, ObjectType
from morphsql.scanner.repository import scan_directory
from morphsql.translator.engine import translate_sql
from morphsql.risk.scorer import score_object, extract_business_rules
from morphsql.parser.sql_parser import count_sql_complexity, extract_tables
from morphsql.pipeline import MigrationPipeline
from morphsql.validation.reconciliation import generate_incremental_strategy
EXAMPLES = Path(__file__).parent.parent / "examples" / "vertica_legacy"
class TestScanner:
def test_scan_directory_finds_objects(self):
objects = scan_directory(EXAMPLES)
assert len(objects) >= 4
types = {o.object_type for o in objects}
assert ObjectType.STORED_PROCEDURE in types or ObjectType.SQL_SCRIPT in types
def test_objects_have_sql_content(self):
objects = scan_directory(EXAMPLES)
for obj in objects:
assert len(obj.source_sql) > 0
assert obj.name
class TestParser:
def test_extract_tables(self):
sql = "SELECT a FROM staging.customers JOIN analytics.orders ON a.id = b.id"
tables = extract_tables(sql, Dialect.VERTICA)
assert "STAGING.CUSTOMERS" in tables or "CUSTOMERS" in str(tables).upper()
def test_complexity_metrics(self):
sql = "WITH cte AS (SELECT 1) SELECT * FROM cte JOIN t ON 1=1"
metrics = count_sql_complexity(sql, Dialect.VERTICA)
assert metrics["ctes"] >= 1
assert metrics["joins"] >= 1
class TestTranslator:
def test_zeroifnull_maps_to_coalesce_with_default(self):
sql = "SELECT ZEROIFNULL(amount) FROM staging.transactions"
translated, confidence, _, _ = translate_sql(sql, Dialect.VERTICA, Dialect.SNOWFLAKE)
assert "COALESCE(amount," in translated.replace(" ", "") and ",0)" in translated.replace(" ", "")
assert confidence > 0
def test_procedure_parameter_binding(self):
sql = """CREATE OR REPLACE PROCEDURE p(load_date DATE) AS $$
BEGIN
DELETE FROM t WHERE d = load_date;
END; $$;"""
translated, _, _, _ = translate_sql(sql, Dialect.VERTICA, Dialect.SNOWFLAKE)
assert ":LOAD_DATE" in translated
assert "WHERE d = :LOAD_DATE" in translated
def test_date_arithmetic_uses_dateadd(self):
sql = "SELECT * FROM t WHERE order_date >= CURRENT_DATE - 365"
translated, _, _, _ = translate_sql(sql, Dialect.VERTICA, Dialect.SNOWFLAKE)
assert "DATEADD" in translated.upper()
def test_detects_dynamic_sql_review(self):
sql = "EXECUTE IMMEDIATE 'SELECT 1'"
_, _, _, review = translate_sql(sql, Dialect.VERTICA, Dialect.SNOWFLAKE)
assert any("dynamic" in r.lower() for r in review)
def test_vertica_to_bigquery_zeroifnull_and_dates(self):
sql = "SELECT ZEROIFNULL(amount) FROM t WHERE d >= CURRENT_DATE - 7"
translated, _, auto, _ = translate_sql(sql, Dialect.VERTICA, Dialect.BIGQUERY)
upper = translated.upper()
# BigQuery accepts IFNULL or COALESCE (sqlglot may normalize)
assert "IFNULL" in upper or "COALESCE" in upper
assert "DATE_SUB" in upper or "INTERVAL" in upper
assert auto
def test_oracle_nvl_to_snowflake(self):
sql = "SELECT NVL(amount, 0) AS amt FROM dual"
translated, _, auto, _ = translate_sql(sql, Dialect.ORACLE, Dialect.SNOWFLAKE)
assert "COALESCE" in translated.upper()
assert any("NVL" in a for a in auto)
def test_oracle_to_bigquery(self):
sql = "SELECT NVL(amount, 0) FROM orders"
translated, conf, _, _ = translate_sql(sql, Dialect.ORACLE, Dialect.BIGQUERY)
upper = translated.upper()
assert "IFNULL" in upper or "COALESCE" in upper
assert conf > 0
def test_redshift_getdate_to_snowflake(self):
sql = "SELECT GETDATE(), NVL(x, 0) FROM t"
translated, _, auto, _ = translate_sql(sql, Dialect.REDSHIFT, Dialect.SNOWFLAKE)
assert "CURRENT_TIMESTAMP" in translated.upper()
assert "COALESCE" in translated.upper()
assert auto
def test_redshift_listagg_to_bigquery(self):
sql = "SELECT LISTAGG(name, ',') FROM users"
translated, _, auto, _ = translate_sql(sql, Dialect.REDSHIFT, Dialect.BIGQUERY)
assert "STRING_AGG" in translated.upper()
assert auto
def test_bigquery_to_snowflake(self):
sql = "SELECT IFNULL(amount, 0), STRING_AGG(name, ',') FROM t"
translated, _, auto, _ = translate_sql(sql, Dialect.BIGQUERY, Dialect.SNOWFLAKE)
assert "COALESCE" in translated.upper()
assert "LISTAGG" in translated.upper()
assert auto
def test_snowflake_to_bigquery(self):
sql = "SELECT IFF(a IS NULL, 0, a), LISTAGG(name, ',') FROM t"
translated, _, auto, _ = translate_sql(sql, Dialect.SNOWFLAKE, Dialect.BIGQUERY)
assert re.search(r"\bIF\s*\(", translated, re.I)
assert "STRING_AGG" in translated.upper()
assert auto
def test_dbt_snowflake_target_matches_snowflake_sql(self):
sql = "SELECT ZEROIFNULL(x) FROM t"
snow, _, _, _ = translate_sql(sql, Dialect.VERTICA, Dialect.SNOWFLAKE)
dbt, _, _, _ = translate_sql(sql, Dialect.VERTICA, Dialect.DBT_SNOWFLAKE)
assert "COALESCE" in snow.upper() and "COALESCE" in dbt.upper()
def test_vertica_procedure_to_dbt_models(self):
from morphsql.dbt_generator.decomposer import decompose_to_dbt, format_dbt_project, is_dbt_target
assert is_dbt_target("dbt-snowflake")
sql = Path("examples/vertica_legacy/procedures/SP_BUILD_CUSTOMER_DAILY.sql").read_text()
translated, _, _, _ = translate_sql(sql, Dialect.VERTICA, Dialect.SNOWFLAKE)
obj = MigrationObject(
name="SP_BUILD_CUSTOMER_DAILY",
object_type=ObjectType.STORED_PROCEDURE,
source_sql=sql,
target_sql=translated,
)
files = decompose_to_dbt(obj, Dialect.VERTICA)
assert "dbt_project.yml" in files
assert any(p.startswith("models/staging/") and p.endswith(".sql") for p in files)
assert any(p.startswith("models/marts/") and p.endswith(".sql") for p in files)
mart = next(v for k, v in files.items() if k.startswith("models/marts/") and k.endswith(".sql"))
assert "source(" in "\n".join(files.values()) or "ref(" in mart
assert "END AS" in mart.upper() or "CUSTOMER_SEGMENT" in mart.upper()
assert "{{ var('load_date') }}" in "\n".join(files.values())
rendered = format_dbt_project(files)
assert "models/staging/" in rendered
assert "COALESCE" in rendered.upper()
def test_eval_suite_runs(self):
from morphsql.eval import ensure_pairs_file, run_eval
ensure_pairs_file()
results, summary = run_eval(limit=20, categories=["function", "date"])
assert summary["n_pairs"] >= 5
assert 0 <= summary["token_f1"] <= 1
assert len(results) == summary["n_pairs"]
def test_behavior_rag_retrieves(self):
from morphsql.intelligence.rag import get_rag
hits = get_rag().retrieve("empty string NULL oracle snowflake", top_k=3)
assert hits
assert hits[0].name
def test_hero_agent(self):
from demo.handlers import run_hero_agent
md, out, badge, share = run_hero_agent(
"SELECT ZEROIFNULL(a) FROM t WHERE d >= CURRENT_DATE - 7",
"vertica",
"snowflake",
)
assert "COALESCE" in out.upper()
assert "Confidence" in md or "%" in md or "VERTICA" in md.upper()
assert "%" in badge
assert "MorphSQL" in share or "morphsql" in share.lower() or "Open Space" in share
assert "dgvj-work/morphsql" in share or "GitHub" in share
def test_ai_risk_model_and_pipeline(self):
from morphsql.ai import pipeline, train_and_save
train_and_save()
risk = pipeline("sql-risk-classification")
out = risk("CREATE PROCEDURE p AS BEGIN EXECUTE IMMEDIATE 'x'; END;")
assert out["label"] in {"low", "medium", "high"}
assert 0 <= out["score"] <= 1
mig = pipeline("sql-migration")(
"SELECT ZEROIFNULL(a) FROM t", source="vertica", target="snowflake"
)
assert "COALESCE" in mig["converted_sql"].upper()
assert "predict_risk" in mig["tools_used"] or mig["risk"]
def test_ai_chat_agent(self):
from morphsql.ai.agent import chat_agent
history, msg, sql, badge = chat_agent(
"Convert this SQL and predict migration risk",
[],
"SELECT ZEROIFNULL(x) FROM t",
"vertica",
"snowflake",
)
assert len(history) >= 2
assert "COALESCE" in sql.upper()
assert msg == ""
def test_sql_to_pandas_from_each_source(self):
import pandas as pd
cases = [
(
Dialect.VERTICA,
"SELECT customer_id, ZEROIFNULL(order_amount) AS order_amount, "
"NVL(discount, 0) AS discount FROM staging.orders "
"WHERE order_date >= CURRENT_DATE - 30",
"staging.orders",
{
"customer_id": [1, 2],
"order_amount": [None, 10.0],
"discount": [None, 1.0],
"order_date": [pd.Timestamp.today(), pd.Timestamp.today()],
},
),
(
Dialect.ORACLE,
"SELECT NVL(amount, 0) AS amount, SYSDATE AS ts FROM dual",
None,
None,
),
(
Dialect.REDSHIFT,
"SELECT GETDATE() AS ts, name FROM users WHERE id > 1 LIMIT 5",
"users",
{"ts": [1, 2], "name": ["a", "b"], "id": [1, 3]},
),
(
Dialect.BIGQUERY,
"SELECT IFNULL(a, 0) AS a, b FROM t WHERE a IS NOT NULL",
"t",
{"a": [None, 2], "b": [9, 8]},
),
(
Dialect.SNOWFLAKE,
"SELECT COALESCE(x, 0) AS x FROM analytics.facts WHERE dt >= CURRENT_DATE",
"analytics.facts",
{"x": [None, 5], "dt": [pd.Timestamp.today(), pd.Timestamp.today()]},
),
]
for source, sql, table_key, frame in cases:
code, conf, auto, _review = translate_sql(sql, source, Dialect.PANDAS)
assert conf >= 50
assert "import pandas as pd" in code
assert "result" in code
assert any("pandas" in a.lower() or "→" in a for a in auto)
ns: dict = {"pd": pd, "np": __import__("numpy")}
if table_key and frame is not None:
ns["tables"] = {table_key: pd.DataFrame(frame)}
else:
ns["tables"] = {}
exec(code, ns, ns)
assert isinstance(ns["result"], pd.DataFrame)
def test_sql_to_pyspark_from_each_source(self):
cases = [
(
Dialect.VERTICA,
"SELECT customer_id, ZEROIFNULL(order_amount) AS order_amount "
"FROM staging.orders WHERE order_date >= CURRENT_DATE - 30",
),
(
Dialect.ORACLE,
"SELECT NVL(amount, 0) AS amount, SYSDATE AS ts FROM dual",
),
(
Dialect.REDSHIFT,
"SELECT GETDATE() AS ts, name FROM users WHERE id > 1 LIMIT 5",
),
(
Dialect.BIGQUERY,
"SELECT IFNULL(a, 0) AS a, b FROM t WHERE a IS NOT NULL",
),
(
Dialect.SNOWFLAKE,
"SELECT COALESCE(x, 0) AS x FROM analytics.facts WHERE dt >= CURRENT_DATE",
),
]
for source, sql in cases:
code, conf, auto, _review = translate_sql(sql, source, Dialect.PYSPARK)
assert conf >= 50
assert "from pyspark.sql" in code
assert "result" in code
assert any("pyspark" in a.lower() or "→" in a for a in auto)
def test_hero_agent_pandas_primary(self):
from demo.handlers import run_hero_agent
md, out, badge, share = run_hero_agent(
"SELECT COALESCE(a, 0) AS a FROM t",
"snowflake",
"pandas",
)
assert "import pandas as pd" in out
assert "fillna" in out or "tables[" in out or "_coalesce" in out
assert "pandas" in share.lower() or "Python" in share
assert "%" in badge
assert "pandas" in md.lower() or "PANDAS" in md.upper() or "Python" in md
def test_hero_agent_pyspark(self):
from demo.handlers import run_hero_agent
md, out, badge, share = run_hero_agent(
"SELECT COALESCE(a, 0) AS a FROM t",
"snowflake",
"pyspark",
)
assert "from pyspark.sql" in out
assert "F.coalesce" in out or "tables[" in out or "result" in out
assert "pyspark" in share.lower() or "PySpark" in share or "Python" in share
assert "%" in badge
def test_sample_preview_and_convert_for_ui(self):
import pandas as pd
from demo.handlers import convert_for_ui, run_sample_preview
notes, output, status, share, preview, path, nb, api = convert_for_ui(
"SELECT customer_id, ZEROIFNULL(order_amount) AS order_amount "
"FROM staging.orders WHERE order_date >= CURRENT_DATE - 7",
"vertica",
"pandas",
)
assert "import pandas" in output
assert path.endswith(".py")
assert "notebook" in nb.lower() or "MorphSQL" in nb
assert "pipeline" in api
assert preview is None or isinstance(preview, pd.DataFrame)
df, note = run_sample_preview(output, "pandas", sql="SELECT a FROM staging.orders")
assert isinstance(df, pd.DataFrame)
assert "preview" in note.lower() or "Sample" in note
_, spark_out, _, _, spark_preview, spark_path, spark_nb, _ = convert_for_ui(
"SELECT COALESCE(a, 0) AS a FROM t",
"snowflake",
"pyspark",
)
assert "from pyspark.sql" in spark_out
assert spark_path.endswith(".py")
assert "pyspark" in spark_path or "morphsql_pyspark" in spark_path
assert isinstance(spark_preview, pd.DataFrame)
assert "Spark" in spark_nb or "pyspark" in spark_nb.lower()
for tgt in ("snowflake", "bigquery", "dbt-snowflake"):
_, out, _, _, prev, _, _, _ = convert_for_ui(
"SELECT COALESCE(a, 0) AS a FROM t WHERE a IS NOT NULL",
"snowflake",
tgt,
)
assert out.strip()
assert isinstance(prev, pd.DataFrame), f"preview missing for {tgt}"
df2, note2 = run_sample_preview(
out, tgt, sql="SELECT COALESCE(a, 0) AS a FROM t", source="snowflake"
)
assert isinstance(df2, pd.DataFrame)
assert "preview" in note2.lower() or "Sample" in note2
# Procedure → dbt must still produce a sample preview
proc = (
"CREATE OR REPLACE PROCEDURE p(load_date DATE) AS $$ BEGIN "
"CREATE LOCAL TEMP TABLE tmp ON COMMIT PRESERVE ROWS AS "
"SELECT customer_id, ZEROIFNULL(amount) AS amount FROM staging.orders "
"WHERE order_date = load_date; "
"INSERT INTO analytics.daily SELECT * FROM tmp; END; $$;"
)
_, _, _, _, proc_prev, _, _, _ = convert_for_ui(proc, "vertica", "dbt-snowflake")
assert isinstance(proc_prev, pd.DataFrame), "procedure dbt preview missing"
def test_sql_upload_convert_and_download(self):
import tempfile
import zipfile
from pathlib import Path
import pandas as pd
from demo.handlers import convert_upload_for_ui, load_sql_from_upload
with tempfile.TemporaryDirectory() as td:
td = Path(td)
sql_path = td / "orders.sql"
sql_path.write_text(
"SELECT COALESCE(order_amount, 0) AS order_amount FROM staging.orders",
encoding="utf-8",
)
loaded = load_sql_from_upload(str(sql_path))
assert "order_amount" in loaded
sql_in, notes, output, status, share, preview, path, nb, api = convert_upload_for_ui(
str(sql_path), "", "snowflake", "pandas"
)
assert "order_amount" in sql_in
assert "import pandas" in output
assert Path(path).exists() and path.endswith(".py")
assert "orders" in Path(path).name
assert isinstance(preview, pd.DataFrame)
spark_path = convert_upload_for_ui(str(sql_path), "", "snowflake", "pyspark")[6]
assert Path(spark_path).exists() and spark_path.endswith(".py")
assert "pyspark" in Path(spark_path).name
# Zip of two SQL files → zip download
zpath = td / "bundle.zip"
with zipfile.ZipFile(zpath, "w") as zf:
zf.write(sql_path, arcname="a.sql")
zf.writestr("b.sql", "SELECT IFNULL(x, 0) AS x FROM t")
batch = convert_upload_for_ui(str(zpath), "", "snowflake", "pandas")
assert batch[6].endswith(".zip")
assert Path(batch[6]).exists()
with zipfile.ZipFile(batch[6]) as zf:
names = zf.namelist()
assert any(n.endswith("_pandas.py") for n in names)
assert len(names) >= 2
def test_is_pandas_target(self):
from morphsql.translator.pandas_codegen import is_pandas_target
assert is_pandas_target("pandas")
assert is_pandas_target(Dialect.PANDAS)
assert not is_pandas_target("snowflake")
def test_is_pyspark_target(self):
from morphsql.translator.pyspark_codegen import is_pyspark_target
assert is_pyspark_target("pyspark")
assert is_pyspark_target(Dialect.PYSPARK)
assert is_pyspark_target("spark")
assert not is_pyspark_target("pandas")
assert not is_pyspark_target("snowflake")
def test_cte_query_to_dbt_models(self):
from morphsql.dbt_generator.decomposer import decompose_to_dbt
sql = Path("examples/vertica_legacy/queries/customer_lifetime_value.sql").read_text()
translated, _, _, _ = translate_sql(sql, Dialect.VERTICA, Dialect.SNOWFLAKE)
obj = MigrationObject(
name="customer_lifetime_value",
object_type=ObjectType.SQL_SCRIPT,
source_sql=sql,
target_sql=translated,
)
files = decompose_to_dbt(obj, Dialect.VERTICA)
assert any("marts/" in p for p in files)
assert any(p.endswith(".sql") and "stg_" in p or "int_" in p or "marts/" in p for p in files)
joined = "\n".join(files.values())
assert "COALESCE" in joined.upper()
assert "source(" in joined or "ref(" in joined
def test_procedure_to_bigquery(self):
sql = """CREATE OR REPLACE PROCEDURE p(load_date DATE) AS $$
BEGIN
DELETE FROM t WHERE d = load_date;
END; $$;"""
translated, _, auto, _ = translate_sql(sql, Dialect.VERTICA, Dialect.BIGQUERY)
assert "CREATE OR REPLACE PROCEDURE" in translated.upper()
assert "LANGUAGE SQL" not in translated.upper()
assert any("BigQuery" in a for a in auto)
def test_conversion_matrix_produces_output(self):
"""Every exposed source→target pair must return non-empty converted SQL."""
samples = {
Dialect.VERTICA: "SELECT ZEROIFNULL(a) AS x FROM staging.t WHERE d >= CURRENT_DATE - 1",
Dialect.ORACLE: "SELECT NVL(a, 0) AS x FROM orders WHERE created_at >= SYSDATE",
Dialect.REDSHIFT: "SELECT GETDATE() AS ts, NVL(a, 0) AS x FROM t",
Dialect.BIGQUERY: "SELECT IFNULL(a, 0) AS x, STRING_AGG(b, ',') FROM t GROUP BY a",
Dialect.SNOWFLAKE: "SELECT COALESCE(a, 0) AS x, LISTAGG(b, ',') FROM t GROUP BY a",
}
targets = [
Dialect.PANDAS,
Dialect.PYSPARK,
Dialect.SNOWFLAKE,
Dialect.DBT_SNOWFLAKE,
Dialect.BIGQUERY,
]
for source, sql in samples.items():
for target in targets:
translated, conf, auto, review = translate_sql(sql, source, target)
assert translated.strip(), f"{source.value}→{target.value} returned empty SQL"
assert conf >= 0
if target == Dialect.PANDAS:
assert "import pandas as pd" in translated
continue
if target == Dialect.PYSPARK:
assert "from pyspark.sql" in translated
continue
# Same-family routes may only apply light transforms; others must change or note work
if source != target and not (
source == Dialect.SNOWFLAKE and target == Dialect.DBT_SNOWFLAKE
):
assert auto or translated != sql or review, (
f"{source.value}→{target.value} produced no conversion signal"
)
class TestRiskScorer:
def test_score_simple_query(self):
obj = MigrationObject(name="TEST", object_type=ObjectType.SQL_SCRIPT, source_sql="SELECT 1")
scored = score_object(obj, Dialect.VERTICA, Dialect.SNOWFLAKE)
assert scored.complexity_score >= 0
assert scored.risk_level is not None
def test_extract_business_rules(self):
sql = """SELECT CASE WHEN x > 5 THEN 'HIGH' WHEN x > 2 THEN 'MED' ELSE 'LOW' END FROM t"""
rules = extract_business_rules(sql)
assert len(rules) >= 1
class TestPipeline:
def test_full_analyze(self):
pipeline = MigrationPipeline(source=Dialect.VERTICA, target=Dialect.SNOWFLAKE)
report = pipeline.analyze(EXAMPLES)
assert report.dashboard.total_objects >= 4
assert len(report.objects) >= 4
def test_convert_pipeline(self):
pipeline = MigrationPipeline(source=Dialect.VERTICA, target=Dialect.SNOWFLAKE)
report = pipeline.analyze(EXAMPLES)
report = pipeline.convert(report)
converted = sum(1 for o in report.objects if o.target_sql)
assert converted >= 1
def test_validate_pipeline(self):
pipeline = MigrationPipeline(source=Dialect.VERTICA, target=Dialect.SNOWFLAKE)
report = pipeline.analyze(EXAMPLES)
report = pipeline.convert(report)
report = pipeline.validate(report)
assert len(report.validation_results) > 0
class TestIntelligence:
def test_runbook_generation(self):
from morphsql.pipeline import MigrationPipeline
from morphsql.intelligence.runbook import generate_runbook, generate_executive_summary
pipeline = MigrationPipeline(source=Dialect.VERTICA, target=Dialect.SNOWFLAKE)
report = pipeline.analyze(EXAMPLES)
runbook = generate_runbook(report)
assert "Migration Runbook" in runbook
assert "Phase 1" in runbook
summary = generate_executive_summary(report)
assert "objects" in summary.lower()
def test_rationalization(self):
from morphsql.pipeline import MigrationPipeline
from morphsql.intelligence.rationalization import generate_rationalization
report = MigrationPipeline(source=Dialect.VERTICA, target=Dialect.SNOWFLAKE).analyze(EXAMPLES)
rat = generate_rationalization(report)
assert "Workload rationalization" in rat
def test_copilot_context(self):
from morphsql.assistant.copilot import MigrationCopilot
from morphsql.pipeline import MigrationPipeline
report = MigrationPipeline(source=Dialect.VERTICA, target=Dialect.SNOWFLAKE).analyze(EXAMPLES)
ctx = MigrationCopilot().build_context(report)
assert "Objects discovered" in ctx
def test_copilot_fallback(self):
from morphsql.assistant.copilot import MigrationCopilot
reply = MigrationCopilot()._fallback(
"explain cutover plan", None, "", "vertica", "snowflake"
)
assert "cutover" in reply.lower() or "phase" in reply.lower()
def test_copilot_priority_with_report(self):
from morphsql.assistant.copilot import MigrationCopilot
from morphsql.pipeline import MigrationPipeline
report = MigrationPipeline(source=Dialect.VERTICA, target=Dialect.SNOWFLAKE).analyze(
EXAMPLES
)
reply = MigrationCopilot().respond(
"What should we migrate first?",
[],
report,
"",
"vertica",
"snowflake",
)
assert "Start with" in reply or "Recommended" in reply or "first" in reply.lower()
class TestIncrementalStrategy:
def test_delete_insert_pattern(self):
sql = "DELETE FROM t WHERE d = 1; INSERT INTO t SELECT * FROM s"
result = generate_incremental_strategy(sql)
assert result["legacy_pattern"] == "Delete and reload"
assert result["dbt_materialized"] == "incremental"
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