def handle(self, cmd: UpdateRankings) -> RankingsUpdated:
"""Update project rankings"""
if not cmd.language:
raise ValueError("Language must not be empty")
if cmd.start_date and cmd.start_date > cmd.end_date:
raise ValueError("Invalid dates")
rankings = self._query_database_num_ratings(cmd)
# Use pandas to perform the ranking
df = pd.DataFrame(rankings)
df["language"] = cmd.language
df["period"] = cmd.period
df["start_date"] = cmd.start_date
df["end_date"] = cmd.end_date
df["rank"] = df[df.columns[1]].rank(0, "min", ascending=False).astype(np.int)
# Delete existing rankings prior to insert
query = (
Ranking.query.filter(Ranking.language == cmd.language)
.filter(Ranking.end_date == cmd.end_date)
.filter(Ranking.period == cmd.period)
)
query.delete()
data = iter(df.to_records(False))
batch = from_sqlalchemy_table(Ranking.__table__, data, list(df.columns))
batch.execute(db.engine.raw_connection)
yield RankingsUpdated(cmd.period, cmd.start_date, cmd.end_date, cmd.language)
def handle(self, cmd: ExecuteMahoutRecommender):
model = MODELS.get(cmd.model)
source = abspath(join(RATINGS_PATH, model.source))
destination = abspath(join(EXPORT_PATH, model.destination))
log.info('Running Mahout')
run = ["mvn", "exec:java", "-DbatchSize=100",
"-DmodelID={}".format(model.id),
"-Dsrc=" + source,
"-Dout=" + destination]
subprocess.call(run, cwd="../growser-mahout/")
Recommendation.query.filter(
Recommendation.model_id == model.id).delete()
columns = ['model_id', 'repo_id', 'recommended_repo_id', 'score']
batch = from_sqlalchemy_table(
Recommendation.__table__, from_csv(destination), columns)
for rows in batch.batch_execute(db.engine.raw_connection):
log.info("Batch complete: {}".format(rows))
return RecommendationsUpdated(model.id, batch)
def test_errors_invalid_type(self):
with self.assertRaises(TypeError):
from_sqlalchemy_table(None, get_fake_rows(5), columns)
def test_sqlalchemy_table(self):
bulk = from_sqlalchemy_table(TestTable, get_fake_rows(5), columns)
assert columns == [c.name for c in bulk.columns]
