Buildout can seem far more complex than it really is if you're new to it and are trying to understand an existing buildout. A single buildout can grow to do quite a lot, but a buildout also need only be complex as what it's being used to do. This document aims to help the reader understand the core concepts of Buildout starting with the simplest possible buildout and working through increasingly complex buildouts. At the end, the reader should be able to walk up to an existing complex buildout and understand what it does.
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The primary purpose of Buildout is reproducible deployments. A deployment can be a number of things from as simple as installing a python script in an isolated directory and environment to a full web application deployment containing multiple pieces and a lot of configuration. To that end Buildout provides a number of services:
- Describing Deployments
- Buildout is best used to define and describe what a given deployment needs to contain and how to configure it. The buildout can then be used to reliably reproduce that deployment in multiple locations and environments. You can keep your buildout in version control, check it out in multiple locations, such as staging, production, and on each team members workstation and trust that there is consistency between them all.
- Factoring Deployment Configuration
- Another element of reproducible deployments is to allow sharing common pieces of slightly different deployments. For example, when building a web application you often want to use tools for development that should never be deployed to production, but you also need to be able to trust that your development environment otherwise reflects what will be deployed to production. Buildout provides ways to factor deployment configuration such that you can use the same buildout for development and production but specify which variation of the buildout should be used in each environment.
- Deployment Isolation
- Another important element of reproducible deployments is isolation, ensuring that the deployment won't be interfered with or interfere with other things in the same environment. To that end, a buildout deployment provides an isolated Python environment into which Buildout can install Python distributions which won't interfere with anything outside the buildout or be interfered with by things outside the buildout.
- Installing Software
- Finally, a big part of any real-world deployment is retrieving, building and installing software. Another important part of that is doing the same for any dependencies of that software. As such, Buildout uses distribute and provides it's own version of easy_install to do this for Python software.
While built on Python, some of the core services Buildout provides are Python specific, and Buildout is most useful on Python projects, there is nothing necessarily Python specific about using what a buildout deploys and it can be used for non-Python projects.
A common source of confusion is the fact that 'buildout' as a term can apply to two things that a user of Buildout will frequently have to deal with. The first meaning of 'Buildout' is to refer to zc.buildout the software. This includes the bin/buildout script or when referring to running 'Buildout'. The other meaning is to refer to the individual deployment directory as 'a buildout'. IOW, when you checkout from version control into a working copy directory that uses 'Buildout' the software, that directory is 'a buildout'. To limit confusion about this, this tutorial uses 'Buildout' with a capital 'B' to refer to the software and 'a buildout' with a lower case 'b' to refer to a specific copy of a buildout in a specific directory.
A buildout configuration describes a deployment. This description is written in configuration files, named with a .cfg extension by convention. These files use an extended ConfigParser format from the Python standard library. You'll likely recognize this format as a very common configuration file format consisting of named 'sections', defined by a line with the section name in brackets. These sections then contain named variables with values.
The core configuration of any buildout deployment is described in the [buildout] section. A buildout deployment consists of 'parts', which are special configuration sections. The default configuration file is buildout.cfg. As such, to create the simplest possible buildout, which is an empty deployment, create an empty directory and put the following into a buildout.cfg file in that directory:
[buildout] parts =
Now that the deployment is described in the configuration file we can use Buildout to deploy the empty environment described. Deploying a buildout has two steps. The first step defines which Python installation to use for that buildout and establishes the isolated Python environment described in `Why Buildout`_. This step also gets the minimum requirements necessary to use the Buildout software itself. This step is called bootstrapping and is only necessary the first time a given copy of a given buildout is set up, if an existing buildout is moved, or if a different Python installation is used.
To bootstrap, copy into the buildout directory the bootstrap.py script from:
To establish the isolated Python environment, use the Python installation that should be used for the buildout to run the bootstrap.py script. In my opinion, it is best to use the -d option with the bootstrap.py script so that Buildout will use the more actively maintained distribute project. From that point on, Buildout will use that Python installation for all subsequent Buildout operations:
$ /path/to/python bootstrap.py -d Creating directory '/opt/src/buildout-tutorial/bin'. Creating directory '/opt/src/buildout-tutorial/parts'. Creating directory '/opt/src/buildout-tutorial/develop-eggs'. Generated script '/opt/src/buildout-tutorial/bin/Buildout'.
Now the directory has three new directories, whose purposes will be come clear in the next chapter, and a bin/buildout script (or binbuildout.exe on Windows) which is used to apply the deployment configuration. Since this buildout configuration describes an empty deployment, running Buildout does nothing:
Next, we'll move beyond an empty buildout to an example of the simplest possible buildout that actually deploys something.
The simplest buildout will deploy a Python distribution in an isolated environment. In this case we'll add the sphinx distribution to our empty buildout and Buildout will retrieve that distribution, build it, install it isolated in the buildout, and add any console scripts to the bin directory.
We tell Buildout what the pieces of a deployment are by adding special sections to the configuration called 'parts'. Since deployments often need to do many different kinds of things in the same deployment, different parts need to be able to use different variables as options and perform different logic and actions. As such, Buildout uses different Python code for different kinds of parts to provide specific deployment behavior. The Python code that handles a given buildout part is called a recipe.
In the configuration file, a 'part' is just a named section that provides a recipe variable, and whose section name is listed in the [buildout] section's parts variable:
[buildout] parts = sphinx [sphinx] recipe = zc.recipe.egg
In this case, we use the zc.recipe.egg recipe which is a part of the Buildout project itself. This recipe retrieves Python distributions, installs them isolated to the buildout, and also handles installing console scripts. Later, we'll use part variables as options to control the behavior of the recipe, but for now we'll make use of the default behavior of zc.recipe.egg which is to get the name of a single distribution to install from the part name.
Since we have already bootstrapped the buildout, haven't moved the buildout directory, and we're using the same python, we do not need to run the bootstrap.py script again. We can just update our buildout by re-running bin/buildout:
$ bin/buildout Getting distribution for 'zc.recipe.egg'. Got zc.recipe.egg 1.3.2. Installing sphinx. Getting distribution for 'sphinx'. Got Sphinx 1.1.3. Getting distribution for 'docutils>=0.7'. warning: ... zip_safe flag not set; analyzing archive contents... docutils.parsers.rst.directives.misc: module references __file__... Got docutils 0.8.1. Getting distribution for 'Jinja2>=2.3'. warning: ... Got Jinja2 2.6. Getting distribution for 'Pygments>=1.2'. Got Pygments 1.5. Generated script '/opt/src/buildout-tutorial/bin/sphinx-apidoc'. Generated script '/opt/src/buildout-tutorial/bin/sphinx-build'. Generated script '/opt/src/buildout-tutorial/bin/sphinx-quickstart'. Generated script '/opt/src/buildout-tutorial/bin/sphinx-autogen'.
Buildout tells us a bit about what it did while updating the deployment to add the new part. It retrieved, built, and installed the Python distributions for the recipe, the distribution required by the part, and all of their dependencies. Note that it also reports the versions it chose for the distributions it retrieved. We'll discuss how to specify and control those versions later. Finally, it installs the console_scripts specified in the setup.py of the distribution specified in the part.
We've omitted some of the output that comes from building the eggs. For context, that output most often occurs when building as setuptools eggs Python distributions which only use Python's distutils. The warnings come from distribute and are often not important but do on occasion indicate a genuine problem. Unfortunately, there's no clear way for a user who isn't an expert in Buildout and distribute to interpret whether or not there is a problem. With apologies, the best answer is to ignore such messages until you have reason to think there is a problem.
At this point we can safely run the sphinx console scripts in an isolated evnironment:
$ bin/sphinx-apidoc --help Usage: sphinx-apidoc [options] -o <output_path> <module_path> [exclude_paths, ...] Look recursively in <module_path> for Python modules and packages and create one reST file with automodule directives per package in the <output_path>...
So far, this buildout is just being used as an isolated distribution installer, but a reproducible deployment is more often much more than that. Buildout is most useful for capturing and documenting the specific details required by the deployment. Recipes are responsible for supporting those details and expect to be given options to that end. In the configuration file, those options are just the section variables in the part that are recognized by the recipe.
The zc.recipe.egg recipe, for example, has a dependent-scripts option. If true, this option causes the recipe to install the console scripts for any of the distribution's dependencies that define console scripts:
[buildout] parts = sphinx [sphinx] recipe = zc.recipe.egg dependent-scripts = true
Now when bin/buildout is run, the pygmentize console script from the Pygments dependency of sphinx is also installed:
$ bin/buildout Uninstalling sphinx. Installing sphinx. Generated script '/opt/src/buildout-tutorial/bin/sphinx-apidoc'. Generated script '/opt/src/buildout-tutorial/bin/sphinx-build'. Generated script '/opt/src/buildout-tutorial/bin/sphinx-quickstart'. Generated script '/opt/src/buildout-tutorial/bin/sphinx-autogen'. Generated script '/opt/src/buildout-tutorial/bin/pygmentize'. $ bin/pygmentize --help Usage: bin/pygmentize [-l <lexer> | -g] [-F <filter>[:<options>]] [-f <formatter>] [-O <options>] [-P <option=value>] [-o <outfile>] [<infile>]...
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