average, and low based on their revenue. Order by classification and facility name. Postgres ONLY (as written). SELECT name, CASE class WHEN 1 THEN 'high' WHEN 2 THEN 'average' ELSE 'low' END FROM ( .group_by(Facility.name)) klass_case = Case(subq.c.klass, [(1, 'high'), (2, 'average')], 'low') query = (Select(columns=[subq.c.name, klass_case]) .from_(subq) .order_by(subq.c with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. Method Meaning .regexp(exp) Regular expression match. .bin_and(value)

it will usually be more performant than doing n queries in your application code, which involves latency communicating with the database and may not take advantage of indices or other optimizations employed performance hit. It all depends on the data you are querying, the database you are using, and the latency involved in executing queries and retrieving results. As always when making optimizations, profile with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. .regexp(exp) Regular expression match (case-sensitive). .iregexp(exp)

average, and low based on their revenue. Order by classification and facility name. Postgres ONLY (as written). SELECT name, CASE class WHEN 1 THEN 'high' WHEN 2 THEN 'average' ELSE 'low' END FROM ( .group_by(Facility.name)) klass_case = Case(subq.c.klass, [(1, 'high'), (2, 'average')], 'low') query = (Select(columns=[subq.c.name, klass_case]) .from_(subq) .order_by(subq.c with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. .regexp(exp) Regular expression match (case-sensitive). .iregexp(exp)

average, and low based on their revenue. Order by classification and facility name. Postgres ONLY (as written). SELECT name, CASE class WHEN 1 THEN 'high' WHEN 2 THEN 'average' ELSE 'low' END FROM ( .group_by(Facility.name)) klass_case = Case(subq.c.klass, [(1, 'high'), (2, 'average')], 'low') query = (Select(columns=[subq.c.name, klass_case]) .from_(subq) .order_by(subq.c with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. Method Meaning .regexp(exp) Regular expression match. .bin_and(value)

it will usually be more performant than doing n queries in your application code, which involves latency communicating with the database and may not take advantage of indices or other optimizations employed performance hit. It all depends on the data you are querying, the database you are using, and the latency involved in executing queries and retrieving results. As always when making optimizations, profile with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. .regexp(exp) Regular expression match (case-sensitive). .iregexp(exp)

average, and low based on their revenue. Order by classification and facility name. Postgres ONLY (as written). SELECT name, CASE class WHEN 1 THEN 'high' WHEN 2 THEN 'average' ELSE 'low' END FROM ( join(Booking) .group_by(Facility.name)) klass_case = Case(subq.c.klass, [(1, 'high'), (2, 'average')], 'low') query = (Select(columns=[subq.c.name, klass_case]) .from_(subq) .order_by(subq.c.klass, subq.c.name) with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. .regexp(exp) Regular expression match. .bin_and(value) Binary AND.

average, and low based on their revenue. Order by classification and facility name. Postgres ONLY (as written). SELECT name, CASE class WHEN 1 THEN 'high' WHEN 2 THEN 'average' ELSE 'low' END FROM ( join(Booking) .group_by(Facility.name)) klass_case = Case(subq.c.klass, [(1, 'high'), (2, 'average')], 'low') query = (Select(columns=[subq.c.name, klass_case]) .from_(subq) .order_by(subq.c.klass, subq.c.name) with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. .regexp(exp) Regular expression match (case-sensitive). .iregexp(exp)

with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. .regexp(exp) Regular expression match. .bin_and(value) Binary AND. it will usually be more performant than doing n queries in your application code, which involves latency communicating with the database and may not take advantage of indices or other optimizations employed performance hit. It all depends on the data you are querying, the database you are using, and the latency involved in executing queries and retrieving results. As always when making optimizations, profile

with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. .regexp(exp) Regular expression match. .bin_and(value) Binary AND. it will usually be more performant than doing n queries in your application code, which involves latency communicating with the database and may not take advantage of indices or other optimizations employed performance hit. It all depends on the data you are querying, the database you are using, and the latency involved in executing queries and retrieving results. As always when making optimizations, profile

with prefix. .endswith(suffix) Search for values ending with suffix. .between(low, high) Search for values between low and high. .regexp(exp) Regular expression match (case-sensitive). .iregexp(exp) it will usually be more performant than doing n queries in your application code, which involves latency communicating with the database and may not take advantage of indices or other optimizations employed performance hit. It all depends on the data you are querying, the database you are using, and the latency involved in executing queries and retrieving results. As always when making optimizations, profile