Pipelines

Pipelines batch multiple commands into a single network round-trip.

Basic usage

pipe = r.pipeline()
pipe.set("a", "1")
pipe.set("b", "2")
pipe.get("a")
pipe.get("b")
results = pipe.execute()    # [True, True, '1', '2']

Results are returned in the same order as the commands.

Fluent chaining

All pipeline methods return self, so you can chain:

results = (
    r.pipeline()
    .set("x", "1")
    .set("y", "2")
    .get("x")
    .get("y")
    .execute()
)

Bulk loading

pipe = r.pipeline()
for i in range(10_000):
    pipe.set(f"key:{i}", f"value:{i}")
pipe.execute()

Pipeline size

There's no hard limit, but batches of 1,000–10,000 commands are typical. Extremely large pipelines (100k+) can spike memory on both client and server.

Supported commands

Most Redis commands are available on Pipeline. For any command not directly available, use execute_command:\n\npython\npipe.execute_command(\"OBJECT\", \"ENCODING\", \"mykey\")\n

Error handling

If any command in the pipeline returns a Redis error, execute() raises a ResponseError (or a more specific RedisError subclass like WrongTypeError). All commands are sent to the server, but parsing stops at the first error — partial results are not returned.

import pyrsedis

pipe = r.pipeline()
pipe.set("key", "value")
pipe.execute_command("INVALID_CMD")
pipe.get("key")

try:
    results = pipe.execute()
except pyrsedis.ResponseError as e:
    print(e)  # "ERR unknown command 'INVALID_CMD'..."

Note

Unlike redis-py, pyrsedis does not return partial results with inline exceptions. If you need fault-tolerant pipelines, split commands into separate pipelines or wrap the call in a try/except.

Performance

Pipeline throughput on SET ×5,000 (single round-trip):

Client	Time
pyrsedis	~5 ms
redis-py	~61 ms