DataRaccoon

TLDR!

Learning how to use Makefile greatly enhances your repository and productivity, and you will never forget how to get projects up and running ever again!

Problem Statement!

If you are deploying data science projects, you might find yourself running multiple commands to get it into production. You end up writing in a readme:

The commands to run.
The order of commands to run.
The different parameters to use depending various factors (perhaps staging/production has a small difference in config or security )

Or, if you are joining a (tech) company, you might notice this Makefile with no file extensions - you wonder what does it exactly do?

Additional Note

Most guides out there covers makefile with python scripts, I added a section with docker coverage. (Thus if your company support CI/CD pipelines or docker deployments it would be extremely useful)

Pre-req

These are the following prerequisites,

Basic knowledge of terminal
Running python scripts
Docker

Introduction

Typically thought in CS majors, Make is a build automation tool that allows you to build from source. If you are installing Xgboost from source, you are already using make!

In the context of using Makefiles with python, it makes it easy to automate projects and sharing build (or execute) steps or re-using commands.

Setup

If you are using mac with brew,

brew install make

If you are using linux,

apt-get install build-essential

If you only need make,

apt-get install make

Using Makefile

To start, create a file named Makefile. It must be with a capital M and spelt correctly like so:

touch Makefile

Hello World!

Using your favorite text editor, and add the following:

echo_cmd:
    echo hello

Note, four spaces does not make a tab. You need to explicitly type out tab. When copying the examples below make sure to convert your spaces to tabs!

Alternatively, if you are using mac, you can just run the following command instead:

cat << "EOF" | pbcopy
echo_cmd:
\techo hello
EOF
echo "$(pbpaste)" > Makefile

The \t actually represents tab.

Rule

The entire blob / chunk, is a called a Rule.

In general, a rule looks like this:

targets : prerequisites
        recipe
        …

Target

In the earlier blob, echo_cmd would represent the target.

Running make

With this, you are now ready to run your first make command!

make echo_cmd

Output:

❯ make echo_cmd
echo hello
hello

The first line is to show the rendered command which is echo hello, followed by the actual output!

Commenting

Commenting in makefile is easy, just place a hex # at the front. There is no multi line commenting in Makefile, so either use # for each line, or use \ to wrap the first line.

Stackoverflow - how to add multi line comments in makefiles

Variables

Variables can be useful when you want to assign custom values.

This is a trivial example:

VARIABLE=hello there

echo_var_cmd:
    echo $(VARIABLE)

Note, in Makefiles, () or {} serves the same purpose.

To run,

make echo_var_cmd

To run it with different default values,

make echo_var_cmd VARIABLE=hi\ there

output:

❯ make echo_var_cmd VARIABLE=hi\ there

echo hi there
hi there

Inheritance/prerequisites

Let's assume that you have a project that you need to deploy, which will require

Different number of nodes
Different environment (dev/stg/prod)

For the purpose of understanding, we will just echo the nodes and env before adding python scripts + docker later on.

NODES=1
ENV=dev
run_test_command:
    echo $(NODES)
    echo $(ENV)

To run,

make run_test_command

Depending on different environments you might have different configurations,

make run_test_command ENV=prod NODES=10

Over writing defaults

If you want to pre-specify the nodes/env depending on the environment, you can do this:

stg_child:ENV=stg
stg_child: run_test_command

prod_child:ENV=prod
prod_child:NODES=10
prod_child: run_test_command

Example output:

❯ make prod_child
echo 10
10
echo prod
prod

Unfortunately, each new variable default overwrites must be specified by a new line (multi overwrites in a single line is not supported - at least to my best knowledge).

Makefile with Python

Now, instead of printing commands, let's execute a python file.

Python argparse

Create a python script named app.py in the same directory with Makefile with the following code (take a while to understand the code)

import argparse

# todo
# makefile with python
print("starting python script")

parser = argparse.ArgumentParser()

parser.add_argument("--environment", default="dev")

parser.add_argument("--num_nodes", default=1, type=int)

known_args, other_args = parser.parse_known_args()

print(known_args.environment)
print(known_args.num_nodes)
print("done with python code")

Running with make

Add the following commands to Makefile

run_specific_py:
    python app.py \
    --environment=stg \
    --num_nodes=2

run_generic_py:
    python app.py \
    --environment=$(ENV) \
    --num_nodes=$(NODES)

The execution & output can be seen below:

❯ make run_generic_py ENV=prod NODES=123
python app.py \
    --environment=prod \
    --num_nodes=123
starting python script
prod
123
done with python code

Adding Docker

Adding Docker is useful for various reasons, such as making the execution environment consistent or moving into a cluster / container runner in the cloud.

Define dockerfile

Define a Dockerfile, in my case, I named it Df_Mkfile with the following content:

FROM continuumio/miniconda3:4.8.2

RUN apt-get update -y \
    &&  apt-get install -y build-essential make pkg-config

WORKDIR $HOME/src
COPY requirements.txt Makefile app.py $HOME/src/
RUN pip install -r requirements.txt

ENTRYPOINT ["make", "run_generic_py"]
CMD ["ENV=dev","NODES=123"]

And requirements.txt (just an example - you do not actually need the libraries):

pandas==1.2.4
numpy==1.20.2
matplotlib==3.1.3

Docker run with make

Edit Makefile with these additional lines

IMAGE_NAME=my_image
build_image:
    docker build -t $(IMAGE_NAME) --file Df_Mkfile .

run_image: build_image
run_image:
    docker run --rm -it $(IMAGE_NAME) ENV=$(ENV) NODES=$(NODES)

This is the output when running:

make run_image ENV=prod NODES=567

output:

docker build -t my_image --file Df_Mkfile .
docker run --rm -it my_image ENV=prod NODES=567
python app.py \
--environment=prod \
--num_nodes=567
starting python script
prod
567
done with python code

Visual Representation

graph TD terminal--run-->make make--run-->run_image run_image--triggers <br> pre-req-->build_image run_image--executes-->docker build_image--feeds-->docker docker--runs entrypoint <br> based on Dockerfile--> run_generic_py

Docker entrypoint

Sometimes when running a docker application (such as a flask app) and you encounter errors which requires debugging in the container, you can introduce a new rule in the makefile:

run_image_bash:
    docker run --rm -it --entrypoint bash $(IMAGE_NAME)

That way, you can alternate between running docker with different entrypoints or deployments pending on your use-case/cotnext.

Other examples

In one of the references, you can also set commands that are often used in python projects, such as cleaning pyc or running tests, black, or flake8 etc.

clean-pyc:
    find . -name '*.pyc' -exec rm --force {} +
    find . -name '*.pyo' -exec rm --force {} +
   name '*~' -exec rm --force  {} 

clean-build:
    rm --force --recursive build/
    rm --force --recursive dist/
    rm --force --recursive *.egg-info

lint:
    flake8 --exclude=.tox

test: clean-pyc
    py.test --verbose --color=yes $(TEST_PATH)

Additional topics

There are additional topics that are not covered that are useful, such as (but not limited to), perhaps it will be added in the future.

PHONY
- Useful when your directory intersects with certain keywords.
- Check out the gnu documentation if your makefile targets intersect with directories over here
CMake
- Useful to generate makefile with other benefits.
- Check out stackoverflow for quick explanation over here
Wildcards
Running bash commands within Makefile rules
Setting defaults makes

TLDR!

Problem Statement!

Additional Note

Pre-req

Introduction

Setup

Using Makefile

Hello World!

Rule

Target

Running make

Commenting

Variables

Inheritance/prerequisites

Over writing defaults

Makefile with Python

Python argparse

Running with make

Adding Docker

Define dockerfile

Docker run with make

Visual Representation

Docker entrypoint

Other examples

Additional topics

References