====================== Getting started ====================== Welcome to the Cozo Manual. The latest version of this manual can be read at https://cozodb.github.io/current/manual. Alternatively, you can download a PDF version for offline viewing at https://cozodb.github.io/current/manual.pdf. We aim to make sure that this manual at least touches upon all features currently implemented in Cozo, though the coverage of some topics may be sketchy at this stage. This manual assumes that you already know the basics of the Cozo database, at the level of the `Tutorial `_. ------------------------ Downloading Cozo ------------------------ Cozo is distributed as a single executable. Precompiled binaries can be downloaded from the `release page `_ on the GitHub repo, which are currently available for Linux (Intel x64), Mac (Intel x64 and Apple ARM) and Windows (Intel x64). As the build process on Windows is internally very different from UNIX-based systems, the Windows build hasn't received as much attention as the other builds, and may suffer from inferior performance and Windows-specific bugs. For Windows users, we recommend running Cozo under `WSL `_ if possible, especially if your workload is heavy. --------------- Starting Cozo --------------- Run the ``cozoserver`` command in a terminal:: ./cozoserver If ```` does not exist, it will be created. Cozo will then start a web server and bind to address ``127.0.0.1`` and port ``9070``. These two can be customized: run the executable with the ``-h`` option to learn how. To stop Cozo, type ``CTRL-C`` in the terminal, or send ``SIGTERM`` to the process with e.g. ``kill``. ----------------------- The query API ----------------------- Queries are run by sending HTTP POST requests to the server. By default, the API endpoint is ``http://127.0.0.1:9070/text-query``. The structure of the expected JSON payload is:: { "script": "", "params": {} } ``params`` should be an object of named parameters. For example, if you have ``params`` set up to be ``{"num": 1}``, then ``$num`` can be used anywhere in your query string where an expression is expected. Always use ``params`` instead of constructing query strings yourself when you have parametrized queries. As an example, the following runs a system op with the ``curl`` command line tool:: curl -X POST localhost:9070/text-query \ -H 'content-type: application/json' \ -d '{"script": "::running", "params": {}}' .. WARNING:: Cozo is designed to run in a trusted environment and be used by trusted clients, therefore it does not come with elaborate authentication and security features. If you must access Cozo remotely, you are responsible for setting up firewalls, encryptions and proxies yourself. As a guard against users carelessly binding Cozo to any address other than ``127.0.0.1`` and potentially exposing content to everyone on the Internet, in this case, Cozo will generate a token string and require all queries from non-loopback addresses to provide the token string in the HTTP header field ``x-cozo-auth``. The warning printed when you start Cozo with a non-default binding will tell you how to find the token string. Please note that this "security measure" is not considered sufficient for any purpose and is only a last defence when every other security measure that you are responsible for setting up fails. -------------------------------------------------- Running queries -------------------------------------------------- ^^^^^^^^^^^^^^^^^^^^^^^^^^ Making HTTP requests ^^^^^^^^^^^^^^^^^^^^^^^^^^ As Cozo has a web-based API, it is accessible by all languages that are capable of making web requests. The structure of the API is also deliberately kept minimal so that no dedicated clients are necessary. The return values of requests are JSON when requests are successful, or text descriptions when errors occur, so a language only needs to be able to process JSON to use Cozo. ^^^^^^^^^^^^^^^^^^^^^^^^^ JupyterLab ^^^^^^^^^^^^^^^^^^^^^^^^^ `JupyterLab `_ is a web-based notebook interface in the python ecosystem heavily used by data scientists and is the recommended "IDE" of Cozo. First, install JupyterLab by following the install instructions of the project. Then install the pycozo library by running:: pip install "pycozo[pandas]" Now, open the JupyterLab web interface, start a Python 3 kernel, and in a cell run the following `magic command `_:: %load_ext pycozo.ipyext_direct If you need to connect to Cozo using a non-default address or port, or you require an authentication string, you need to run the following magic commands as well:: %cozo_host http://: %cozo_auth Now you can execute cells as you usually do in JupyterLab, and the content of the cells will be sent to Cozo and interpreted as CozoScript. Returned relations will be formatted as `Pandas dataframe `_. The above sets up the notebook in the Direct Cozo mode, where cells are default interpreted as CozoScript. You can still execute python code by starting the first line of a cell with the ``%%py``. There is also an Indirect Cozo mode, started by:: %load_ext pycozo.ipyext In this mode, only cells with the first line content ``%%cozo`` are interpreted as CozoScript. Other cells are interpreted in the normal way (by default, python code). Which mode you use depends on your workflow. We recommend the Indirect mode if you have lots of post-processing and visualizations. When a query is successfully executed, the result will be bound to the python variable ``_`` as a Pandas dataframe (this is a feature of Jupyter notebooks: the Cozo extension didn't do anything extra). There are a few other useful magic commands: * ``%cozo_run_file `` runs a local file as CozoScript. * ``%cozo_run_string `` runs variable containing string as CozoScript. * ``%cozo_set `` sets a parameter with the name ```` to the expression ````. The set parameters will be used by subsequent queries. * ``%cozo_set_params `` replace all parameters by the given expression, which must evaluate to a dictionary with string keys. * ``%cozo_clear`` clears all set parameters. * ``%cozo_params`` returns the parameters currently set. ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The Makeshift JavaScript Console ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The Python and JupyterLab ecosystem is rather heavy-weight. If you are just testing out or running Cozo in an environment that only occasionally requires manual queries, you may be reluctant to install them. In this case, you may find the Makeshift JavaScript Console helpful. As Cozo is running an HTTP service, we assume that the browser on your local machine can reach its network. We recommend `Firefox `_, `Chrome `_, or any Chromium-based browser for best display. If Cozo is running under the default configuration, navigate to ``http://127.0.0.1:9070``. You should be greeted with a mostly empty page telling you that Cozo is running. Now open the Developer Console (`Firefox console `_ or `Chrome console `_) and switch to the "Console" tab. Now you can execute CozoScript by running:: await run("") The returned tables will be properly formatted. If you need to pass in parameters, provide a second parameter with a JavaScript object. If you need to set an auth string, modify the global variable ``COZO_AUTH``. The JavaScript Console is not as nice to use as Jupyter notebooks, but we think that it provides a much better experience than hand-rolled CLI consoles, since you can use JavaScript to manipulate the results. ---------------------------- Building Cozo from source ---------------------------- If for some reason the binary distribution does not work for you, you can build Cozo from source, which is straightforward. First, clone the Cozo git repo:: git clone https://github.com/cozodb/cozo.git --recursive You need to pass the ``--recursive`` flag so that submodules are also cloned. Then you need to install the `Rust toolchain `_ for your system. You also need a C++17 compiler. After these preparations, run:: cargo build --release in the root of the cloned repo, wait for potentially a long time, and you will find the compiled binary in ``target/release`` if everything goes well. You can run ``cargo build --release -F jemalloc`` instead to indicate that you want to compile and use jemalloc as the memory allocator for the RocksDB storage backend, which, depending on your workload, can make a difference in performance. -------------------------------- Embedded use -------------------------------- Here "embedded" means running in the same process as your program. As ``cozoserver`` is just a very thin wrapper around the Cozo rust library, you can use the library directly in your program. For languages other than Rust, you will need to provide custom bindings, but again for `Python `_ and `NodeJS `_ this is trivial. As Cozo uses RocksDB as its storage engine, it probably makes a lot less sense to use embedded Cozo than SQLite, since RocksDB always uses multiple threads and always has background threads running, unlike SQLite for which a connection uses only a single thread.