Developing RedisTimeSeries involves setting up the development environment (which can be either Linux-based or macOS-based), building RedisTimeSeries, running tests and benchmarks, and debugging both the RedisTimeSeries module and its tests.
Cloning the git repository
By invoking the following command, RedisTimeSeries module and its submodules are cloned:
git clone --recursive https://github.com/RedisTimeSeries/RedisTimeSeries.git
Working in an isolated environment
There are several reasons to develop in an isolated environment, like keeping your workstation clean, and developing for a different Linux distribution. The most general option for an isolated environment is a virtual machine (it's very easy to set one up using Vagrant). Docker is even a more agile solution, as it offers an almost instant solution:
ts=$(docker run -d -it -v $PWD:/build debian:bullseye bash) docker exec -it $ts bash
Then, from within the container,
cd /build and go on as usual.
In this mode, all installations remain in the scope of the Docker container.
Upon exiting the container, you can either re-invoke the container with the above
docker exec or commit the state of the container to an image and re-invoke it on a later stage:
docker commit $ts ts1 docker stop $ts ts=$(docker run -d -it -v $PWD:/build ts1 bash) docker exec -it $ts bash
To build and test RedisTimeSeries one needs to install several packages, depending on the underlying OS. Currently, we support the Ubuntu/Debian, CentOS, Fedora, and macOS.
If you have
gnu make installed, you can execute
cd RedisTimeSeries make setup
Alternatively, just invoke the following:
cd RedisTimeSeries git submodule update --init --recursive ./deps/readies/bin/getpy3 ./system-setup.py
system-setup.py will install various packages on your system using the native package manager and pip. This requires root permissions (i.e.
sudo) on Linux.
If you prefer to avoid that, you can:
system-setup.pyand install packages manually,
- Use an isolated environment like explained above,
- Utilize a Python virtual environment, as Python installations known to be sensitive when not used in isolation.
As a rule of thumb, you're better off running the latest Redis version.
If your OS has a Redis package, you can install it using the OS package manager.
Otherwise, you can invoke
make help provides a quick summary of the development features.
Building from source
make will build RedisTimeSeries.
Build artifacts are placed into
bin/linux-x64-release (or similar, according to your platform and build options).
make clean to remove built artifacts.
make clean ALL=1 will remove the entire binary artifacts directory.
Running Redis with RedisTimeSeries
The following will run
redis and load RedisTimeSeries module.
You can open
redis-cli in another terminal to interact with it.
The module includes a basic set of unit tests and integration tests:
- C unit tests, located in
src/tests, run by
- Python integration tests (enabled by RLTest), located in
tests/flow, run by
One can run all tests by invoking
A single test can be run using the
TEST parameter, e.g.
make flow_test TEST=file:name.
To build for debugging (enabling symbolic information and disabling optimization), run
One can the use
make run DEBUG=1 to invoke
In addition to the usual way to set breakpoints in
gdb, it is possible to use the
BB macro to set a breakpoint inside RedisTimeSeries code. It will only have an effect when running under
Similarly, Python tests in a single-test mode, one can set a breakpoint by using the
BB() function inside a test. This will invoke
The two methods can be combined: one can set a breakpoint within a flow test, and when reached, connect
gdb to a
redis-server process to debug the module.