8000 Publish datadog_lambda to PyPI · DataDog/datadog-lambda-python@cb29a0a · GitHub
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Publish datadog_lambda to PyPI
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‎Dockerfile

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@@ -7,12 +7,9 @@ ARG runtime
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RUN mkdir -p /build/python/lib/$runtime/site-packages
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WORKDIR /build
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# Install dependencies
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COPY requirements.txt requirements.txt
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RUN pip install -r requirements.txt -t ./python/lib/$runtime/site-packages
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# Install datadog_lambda
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COPY datadog_lambda ./python/lib/$runtime/site-packages/datadog_lambda
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# Install datadog_lambda and dependencies from local
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COPY . .
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RUN pip install . -t ./python/lib/$runtime/site-packages
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# Remove *.pyc files
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RUN find ./python/lib/$runtime/site-packages -name \*.pyc -delete

‎README.md

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@@ -16,6 +16,15 @@ Replace `<AWS_REGION>` with the AWS region where your Lambda function is publish
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arn:aws:lambda:us-east-1:464622532012:layer:Datadog-Python37:1
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```
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### PyPI
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When developing your Lambda function locally where AWS Layer doesn't work, the Datadog Lambda layer can be installed from [PyPI](https://pypi.org/project/datadog-lambda/) by `pip install datadog-lambda` or adding `datadog-lambda` to your project's `requirements.txt`.
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The minor version of the `datadog-lambda` package always match the layer version. E.g., datadog-lambda v0.5.0 matches the content in layer version 5.
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### Environment Variables
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The Datadog API must be defined as an environment variable via [AWS CLI](https://docs.aws.amazon.com/lambda/latest/dg/env_variables.html) or [Serverless Framework](https://serverless-stack.com/chapters/serverless-environment-variables.html):
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* DD_API_KEY or DD_KMS_API_KEY (if encrypted by KMS)

‎datadog_lambda/__init__.py

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__version__ = "4"
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# The minor version corresponds to the Lambda layer version.
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# E.g.,, version 0.5.0 gets packaged into layer version 5.
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__version__ = '0.5.0'

‎requirements-dev.txt

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‎requirements.txt

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‎scripts/pypi.sh

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#!/bin/sh
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# Unless explicitly stated otherwise all files in this repository are licensed
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# under the Apache License Version 2.0.
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# This product includes software developed at Datadog (https://www.datadoghq.com/).
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# Copyright 2019 Datadog, Inc.
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# Builds the lambda layer and upload to Pypi
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set -e
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# Clear previously built distributions
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if [ -d "dist" ]; then
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echo "Removing folder 'dist' to clear previously built distributions"
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rm -rf dist;
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fi
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# Install build tools
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pip install --upgrade setuptools wheel twine
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# Build distributions
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python setup.py sdist bdist_wheel
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# Upload distributions
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python -m twine upload dist/*

‎scripts/run_tests.sh

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echo "Running tests against python${python_version}"
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docker build -t datadog-lambda-layer-python-test:$python_version \
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-f tests/Dockerfile . \
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--quiet \
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--build-arg python_version=$python_version
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docker run -v `pwd`:/datadog-lambda-layer-python \
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-w /datadog-lambda-layer-python \

‎setup.py

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from os import path
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from io import open
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from datadog_lambda import __version__
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here = path.abspath(path.dirname(__file__))
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with open(path.join(here, 'README.md'), encoding='utf-8') as f:
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long_description = f.read()
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setup(
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name='ddlambda',
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version='0.2.0',
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name='datadog_lambda',
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version=__version__,
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description='The Datadog AWS Lambda Layer',
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long_description=long_description,
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long_description_content_type='text/markdown',
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keywords='datadog aws lambda layer',
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packages=['datadog_lambda'],
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python_requires='>=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, <4',
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install_requires=[
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'aws-xray-sdk==2.4.2',
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'datadog==0.28.0',
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'wrapt==1.11.1',
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'setuptools==40.8.0',
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'boto3==1.9.160'
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],
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extras_require={
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'dev': [
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'nose2==0.9.1',
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'flake8==3.7.7',
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'requests==2.21.0'
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]
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}
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)

‎tests/Dockerfile

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ENV PYTHONDONTWRITEBYTECODE True
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COPY .flake8 .flake8
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COPY requirements.txt requirements.txt
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COPY requirements-dev.txt requirements-dev.txt
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RUN pip install -r requirements.txt
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RUN pip install -r requirements-dev.txt
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RUN mkdir -p /test
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WORKDIR /test
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# Install datadog-lambda with dev dependencies from local
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COPY . .
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RUN pip install .[dev]

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