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DMK ReadMe

This is a simplified, automated build tool for data projects.

The idea behind dmk is to support build files that are easy to read and write, and to support automating a build system for data artifacts. make, scons, and fac all provided inspiration for dmk.

Project Status

dmk does everything that I need it to do, and it is still my go-to project for testing out CI/CD ideas. I'm planning on keeping it around for quite a while because it's fun and it interests me. However, if you are here because you need a tool like this, I think you'll be better served by taking a look at tasks:

• It's an active project with multiple contributors and sponsors
• It now has pretty much all the features I wanted for dmk
• It has some that I think are great (like an internal shell interpreter for Windows)

So go give them some love :)

Who should use this?

This is a tool for data flows and simple projects. Often these projects involve one-time steps for getting the data used for analysis. Often the user manually places that data in the directory after downloading it from Amazon S3 or a research server or whatever. Scripts or programs run in a pipeline fashion: handling cleaning, transformation, analysis, model building, figure production, presentation building, etc.

Pipelines like this are often written Python or R, partially automated with shell scripts, and then tied together with a Makefile (or a SConstruct file if you're an scons fan).

Protip: if you're looking for a command to handle building reports from .tex files (including handling metapost and biblatex), look into rubber.

What is this NOT for?

This is not mean to replace a real automated build tool for a software project. As a general rule:

• If you're building Go software, use the Go tools (and optionally make)
• If you're building Java/Scala use sbt, gradle, mvn, ant, etc
• If you're building .NET, erm, I'm not sure
• There are great tools like scons that understand how to build lots of artifacts (including LaTeX docs)
• If you're not sure, at least understand why you wouldn't use make

For instance, this project (written in Go) is actually built with make + the standard Go tools.

Using

When running dmk, you may specify -h on the command line for information on command line parameters. Specify -v for "verbose" mode to get output you may want for debugging or understanding what is going on.

For each command in a pipeline, you need to supply:

• A name
• The actual command to run (in the shell)
• The inputs required
• The outputs generated

This list is not exhaustive; see below for everything you can specify for a build step.

The file is generally named Pipeline or pipeline.yaml. If you do not specify a pipeline file with the -f command line parameter, dmk looks for the following names in the current directory (in order):

• Pipeline
• Pipeline.yaml
• pipeline
• pipeline.yaml
• .Pipeline.yaml
• .pipeline.yaml

You may also supply a custom name with the -f command line flag. If the pipeline file is in a different directory, dmk will change to that directory before parsing the config file. Note that the bash tab completion logic will show you step names, but it isn't smart enough to know that you've specified -f on the command line.

All build steps run in parallel, but each step waits until other steps build its dependencies. A single build step executes the following in order:

1. The step is "Started"
2. If any of the required inputs are another step's outputs, then wait for a built message.
3. Check to see if any outputs are older than any of the inputs. If not, then the step is "Completed"!
4. If not done, set status to "Executing" and run the command.
5. If the command returns an error code or if any outputs are missing or older than any inputs, the step is "Failed".
6. Send notification messages for each output for any waiting steps.
7. The step is now "Completed"

The outputs for a step must be unique to that step: you can't have two steps both list foo.data as an output. (Note that this applies to expanded output names, and abstract/baseSteps aren't checked.)

dmk provides an automatic "clean" mode that deletes all outputs. To use it, specify -c on the command line. dmk will delete all the outputs for all steps. If you have files to clean not specified as outputs, you can specified them in the clean list for a build step (see the Pipeline file format below). Good candidates for the clean section are intermediate files (such as logs) generated as part of a build process that are not dependencies and should not determine if a build step is up to date.

You may also run dmk with -listSteps to see a list of all steps in the current pipeline file. Currently, this is used for bash completion.

Pipeline file format

The file is in YAML format where each build step is a named hash. Each build step should specify:

• command - The command to run as part of the build. dmk uses bash to run the command, so it can rely on bash shell niceties (like using ~ for the home directory)
• inputs - a list of inputs needed for the build. These are also the dependencies that must exist before the step can run. An entry can be a glob pattern (like *.txt)
• outputs - a list of outputs generated by the step. Outputs decide if the step must run, and the clean phase deletes them. Glob patterns are ignored for outputs.
• clean - A list of files to clean. These and outputs are the files deleted during a clean. You may use glob patterns for these.
• explicit - Optional, defaults to false. If set to true, the step will run if you specify it on the command line. It will not run by default. Any steps required by steps specified on the command line will also run, regardless of their explicit setting.
• delOnFail - Optional, defaults to false. If set to true and the step fails, then dmk will delete all the step's output files.
• direct - Optional, default to false. If set to true, both stdout and stderr from the step are written to the dmk process standard streams. If set to false (the default), stdout and stderr are written in single blocks after the step completes (stdout is only written if dmk is running in verbose mode). Note in direct mode (direct=True), step output may be interleaved with "normal" output when steps are running in parallel!
• abstract - Optional, defaults to false. If specified, the step is an "base step" and will never be executed (it's only to be used as a baseStep). See below.
• baseStep - Optional, defaults to empty. If specified, it must be the name of a step with abstract: true. In that case the step's properties will be based on the step given. See below.
• vars - Optional, defaults to empty dictionary. If specified, this must be a hash/dictionary with strings as both keys and values. The keys are treated as variables names with are replaced with their corresponding values. See below for variable details.

The res subdirectory contains sample Pipeline files (used for testing), but a quick example would look like:

# You can have comments in a file
step1:                                # first step
    command: "xformxyz i{1,2,3}.txt"  # command with some shell magic
    inputs:                           # 3 inputs (read by our imaginary command)
        - i1.txt
        - i2.txt
        - i3.txt
    outputs:                          # 3 outputs
        - o1.txt
        - o2.txt
        - o3.txt
    clean: [a.aux, b.log]             # two extra clean targets, specified in
                                      # an alternate syntax for YAML lists

step2:                                # second step
    command: cmd1xyz                  # note the lack of inputs - this means
    outputs:                          # the step will run without waiting for
        - output.bin                  # other steps to complete.

depstep:                              # third/final step: it won't run until the
    command: cmd2xyz                  # previous steps finish because their
    inputs:                           # outputs are in the this step's inputs.
        - o3.txt
        - output.bin
    outputs:
        - combination.output
    clean:
        - need-cleaning.*             # An example of using a glob pattern
    delOnFail: true

extrastep:
    command: special-command
    inputs:
        - some-script-file.txt
    outputs:
        - my-special-file.extra
    explicit: true                    # Run if specified on command line (and not by default)

If you were to run dmk -c then it would deleted the following files:

• o1.txt, o2.txt, o3.txt because they are outputs of step1
• a.aux and b.log because they are in the clean list in step1
• output.bin because of step2
• combination.output and any files matching the pattern need-cleaning.* because of depstep

Note that my-special-file.extra from extrastep is not deleted unless you specify extrastep on the command line.

After cleaning, if you run dmk the following steps would occur:

• The commands from step1 (xformxyz i{1,2,3}.txt) and step2 (cmd1xyz) would run
• When they were both finished, depstep would start and cmd2xyz would run.
• As before, extrastep would NOT run.
• If the depstep command (cmd2xyz) fails, then dmk will delete combination.output (if it exists).
• If all the steps succeed, running dmk again would not cause any command to run (because all outputs are newer than their steps' inputs).

If you were to run dmk extrastep then the command special-command would run. Nothing else would run.

If you were to run dmk extrastep depstep then all steps would run (because step1 and step2 are depstep dependencies).

Using Variables

dmk steps support variable expansion.

Before variable expansion begins, both inputs and clean are expanded via globbing (e.g. *.csv expands to all files ending in .csv in the current directory.)

After globbing expansion, dmk will expand variables for all the strings in:

• command
• inputs
• outputs
• clean

Variables are expanded in the following order:

1. Any keys from the current step's vars section (if specified)
2. Any from the vars section of the current step's baseStep if that variable wasn't specified by the current step.
3. Any environment variables - note that you can set environment variables from an env file: see "Build Step Environment" below.

IMPORTANT: DMK_STEPNAME is defined at this point, but the other DMK_ variables described below in "Build Step Environment" are not. However, the command will be executed in bash and they can be evaluated/used by a script at run time.

See "Abstract/Base Steps" below for an example.

(See below for more explanation of base steps)

Abstract/Base Steps

dmk provides a way to create small template steps so that you can simplify pipeline files. Often you'll have a few steps that have similar structures. In that case you can specify a step with abstract: true. These steps will never be executed, but provide a "template" for "concrete" steps.

If a step specified another step with baseStep then:

• If the step has command specified, it takes the command of its base step
• The base step's values for explicit, delonFail, and direct are all used, regardless of the child step's settings
• The base step's inputs, outputs, and clean entries are all added to the child step's lists.
• The base step's vars section provides the "defaults" for the child step (The child's vars section always wins)

Some rules:

• A step named in baseStep must have abstract: true
• An abstract step may not specify a baseStep

Example (note that inputs and outputs are missing):

base:
    command: "echo $A $B $C"
    abstract: true
    vars:
        - A: Hello
        - B: World
stepa:
    baseStep: base
    vars:
        - B: There
        - C: Everyone
stepb:
    command: "echo $A $B $C"
    vars:
        - B: Anything
        - C: Missing

When stepa is executed, it will echo Hello There Everyone because it inherits A from it's baseStep. Note that it does not use B from its baseStep.

When stepb is executed it will echo the string Anything Missing because the command echo $A Anything Missing will be executed by bash, which will expand $A to an empty string.

Build Step Environment

Before reading the pipeline file, dmk will load the env file specified by the (optional) -e command line parameter. This functionality comes from the excellent GoDotEnv library, which is based on the Ruby dotenv project.

When a build step runs, dmk sets environment variables in the step command's process:

• DMK_VERSION - version string for dmk
• DMK_PIPELINE - absolute path to the pipeline file running
• DMK_STEPNAME - the name of the current step
• DMK_INPUTS - a colon (":") delimited list of inputs for this step
• DMK_OUTPUTS - a colon (":") delimited list of outputs for this step
• DMK_CLEAN - a colon (":") delimited list of extra clean files for this step

IMPORTANT! These DMK_ variables are setup after config file processing and will override any variables set in the environment before startup or via an env file.

Also note that although bash evaluates the command, dmk does it's own variable expansion before executing the command. However, only DMK_STEPNAME will be defined for dmk variable expansion. See "Using Variables" above for details.

When the command for a step is activated, it will inherit the original environment that dmk is running in, modified in this order:

1. Start with the original environment
2. Set DMK_VERSION
3. Optionally load an .env file, which will update the environment
4. Set DMK_PIPELINE
5. For each step, add the build step environment variables
6. For each step, add the step variables (as defined above)

Some helpful hints to remember

A pipeline file is a YAML document, and a JSON document is valid YAML. For instance, res/slowbuild.yaml and res/slowbuild.json are semantically identical pipeline files. If you need a customized build, you can generate the pipeline file in the language of your choice in JSON or YAML and then call dmk. As example, if you have a script named custom.py that outputs a JSON pipeline on stdout, you can run the JIT pipeline with: python3 custom.py | dmk -f -.

Commands run in a new bash shell (which also means you need bash).

dmk changes to the directory of the Pipeline file, so you can specify file names relative to the Pipeline file's directory. Of course, the current directory is not changed if the Pipeline file is stdin.

You may use globbing patterns for the inputs and clean.

Building

Currently, dependencies are managed with go modules. Before that dependencies were vendored and managed with dep. And before that, dependencies were managed with godep. Both were excellent tools, but now we have a standard way to manage dependencies in Go - and we no longer have a vendor dir.

You shouldn't need to worry about dependencies if you are building with the Makefile. Also note the fact that we use make to build dmk. We are serious about using the correct build tool for the job.

Yes, we currently regenerate version.go too frequently. If we ever get a single contributor or pull request, we'll make it better :)

You should also have Python 3 installed (for script/versiongen and for the test script res/slow).

make dist will build cross-platform binaries in ./dist. Yes, we commit them to the repo. Deal with it, they're small.

make release handles tagging and pushing to GitHub.

make install will perform the standard go install but will also install the bash completions we make available for dmk. Note that this will use sudo and it currently the only way to get the bash completions.

Before submiting a pull-request or merging into a mainline branch, you should be sure that make lint passes with no errors. Originally we used gometalinter with some customizations. Now we use golangci-lint with default settings. Use make lint-install to install any tools necessary for linting.

Currently we do testing and linting in our CI pipeline via GitHub Actions.