# lampip: Simple CLI tool for creating python custom lambda layers
[](https://python.org/pypi/lampip)
[](https://python.org/pypi/lampip)
[](https://python.org/pypi/lampip)
[](https://github.com/hayashiya18/lampip/actions/workflows/pytest.yml)
---
## Features
- Build Python(3.7, 3.8, 3.9)-compatible custom lambda layers using Docker and pip, and push it to AWS.
- Reduce the package size using some approachs.
- [Byte-Compile](https://docs.python.org/3.8/library/compileall.html) (that remove source comments and docstrings).
- Remove `*.dist-info`.
## Requirements
- Python3
- Docker
- AWS Account
## Installation
You can obtain this packages using pip.
```console
$ pip3 install lampip
```
Then you can use `lampip` command.
```console
$ lampip --help
Usage: lampip [OPTIONS] COMMAND [ARGS]...
Simple CLI tool for creating python custom lambda layers
Options:
--version Show the version and exit.
--help Show this message and exit.
Commands:
deploy Build and push lambda layer
new Create the scaffold
```
## Usage
At the first create the scaffold
```console
$ lampip new science
```
Go to the generated directory
```console
$ cd science
$ ls
lampip-config.toml other_resources requirements.txt
```
Edit `requirements.txt`
```text
numpy
scipy
pandas
```
Edit `lampip-config.toml`
```toml
[lampip]
layername = "science"
description = "numpy, scipy, and pandas"
pyversions = ["3.7", "3.8", "3.9"]
[lampip.shrink]
compile = true
compile_optimize_level = 2
remove_dist_info = true
# [lampip.shrink.plotly]
# remove_jupyterlab_plotly = true
# remove_data_docs = true
```
Before you deploy the lambda layer, be sure you have AWS credentials configured.
```console
(If you do not configure AWS credentials yet, ...)
$ aws configure
AWS Access Key ID: ?????
AWS Secret Acess Key: ?????
Default region name: ?????
```
(Option) You can switch the aws credentials using environments variables.
```console
(Case1: Using AWS CLI profile)
$ export AWS_PROFILE="subaccount"
(Case2: Using AWS access key directly)
$ export AWS_ACCESS_KEY_ID=????
$ export AWS_SECRET_ACCESS_KEY=?????
$ export AWS_DEFAULT_REGION=?????
```
Deploy
```console
$ lampip deploy
Start to make dist/science_1631253196_3.7.zip
...
Publish the custom layer: arn:aws:lambda:ap-northeast-1:XXXXXXXXXXXX:layer:science-py38:1
DONE: dist/science_1631253312_3.8.zip created
$ ls -lh dist
-rw-r--r-- 1 root root 73M 9月 10 23:54 science_1631253254_3.7.zip
-rw-r--r-- 1 root root 73M 9月 10 23:55 science_1631253312_3.8.zip
...
(The --no-upload option suppress uploading zip files)
$ lampip deploy --no-upload
```
Then you can check deployed layers on AWS Console.
Raw data
{
"_id": null,
"home_page": "https://github.com/hayashiya18/lampip",
"name": "lampip",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.6,<4.0",
"maintainer_email": "",
"keywords": "aws,lambda,layer",
"author": "hayashiya18",
"author_email": "sei8haya@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/53/20/77120c073c38fceeb86d3cc6641112ffa6e8c5480c21c2c5c06c1b2445a6/lampip-0.3.0.tar.gz",
"platform": null,
"description": "# lampip: Simple CLI tool for creating python custom lambda layers\n\n[](https://python.org/pypi/lampip)\n[](https://python.org/pypi/lampip)\n[](https://python.org/pypi/lampip)\n[](https://github.com/hayashiya18/lampip/actions/workflows/pytest.yml)\n\n---\n\n## Features\n\n- Build Python(3.7, 3.8, 3.9)-compatible custom lambda layers using Docker and pip, and push it to AWS.\n\n- Reduce the package size using some approachs.\n - [Byte-Compile](https://docs.python.org/3.8/library/compileall.html) (that remove source comments and docstrings).\n - Remove `*.dist-info`.\n\n## Requirements\n\n- Python3\n- Docker\n- AWS Account\n\n## Installation\n\nYou can obtain this packages using pip.\n\n```console\n$ pip3 install lampip\n```\n\nThen you can use `lampip` command.\n\n```console\n$ lampip --help\nUsage: lampip [OPTIONS] COMMAND [ARGS]...\n\n Simple CLI tool for creating python custom lambda layers\n\nOptions:\n --version Show the version and exit.\n --help Show this message and exit.\n\nCommands:\n deploy Build and push lambda layer\n new Create the scaffold\n\n```\n\n## Usage\n\nAt the first create the scaffold\n\n```console\n$ lampip new science\n```\n\nGo to the generated directory\n\n```console\n$ cd science\n$ ls\nlampip-config.toml other_resources requirements.txt\n```\n\nEdit `requirements.txt`\n\n```text\nnumpy\nscipy\npandas\n```\n\nEdit `lampip-config.toml`\n\n```toml\n[lampip]\nlayername = \"science\"\ndescription = \"numpy, scipy, and pandas\"\npyversions = [\"3.7\", \"3.8\", \"3.9\"]\n\n[lampip.shrink]\ncompile = true\ncompile_optimize_level = 2\nremove_dist_info = true\n\n# [lampip.shrink.plotly]\n# remove_jupyterlab_plotly = true\n# remove_data_docs = true\n```\n\nBefore you deploy the lambda layer, be sure you have AWS credentials configured.\n\n```console\n(If you do not configure AWS credentials yet, ...)\n$ aws configure\nAWS Access Key ID: ?????\nAWS Secret Acess Key: ?????\nDefault region name: ?????\n```\n\n(Option) You can switch the aws credentials using environments variables.\n\n```console\n(Case1: Using AWS CLI profile)\n$ export AWS_PROFILE=\"subaccount\"\n\n(Case2: Using AWS access key directly)\n$ export AWS_ACCESS_KEY_ID=????\n$ export AWS_SECRET_ACCESS_KEY=?????\n$ export AWS_DEFAULT_REGION=?????\n```\n\nDeploy\n\n```console\n$ lampip deploy\nStart to make dist/science_1631253196_3.7.zip\n...\nPublish the custom layer: arn:aws:lambda:ap-northeast-1:XXXXXXXXXXXX:layer:science-py38:1\nDONE: dist/science_1631253312_3.8.zip created\n\n$ ls -lh dist\n-rw-r--r-- 1 root root 73M 9\u6708 10 23:54 science_1631253254_3.7.zip\n-rw-r--r-- 1 root root 73M 9\u6708 10 23:55 science_1631253312_3.8.zip\n...\n\n\n(The --no-upload option suppress uploading zip files)\n$ lampip deploy --no-upload\n```\n\nThen you can check deployed layers on AWS Console.\n\n\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Simple CLI tool for creating custom python lambda layers",
"version": "0.3.0",
"split_keywords": [
"aws",
"lambda",
"layer"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "5ef17daa793e2a75a8a9a725706f391526f3a7f1248d19ea91f5511cb2d76593",
"md5": "fe08f23abffe0c0d3a574ecdc2bd042b",
"sha256": "25da01d70e18b98b16f8566aa2c455a900ba78e1067b7aa4d57e987d32ead95a"
},
"downloads": -1,
"filename": "lampip-0.3.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "fe08f23abffe0c0d3a574ecdc2bd042b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6,<4.0",
"size": 8994,
"upload_time": "2023-01-15T07:55:49",
"upload_time_iso_8601": "2023-01-15T07:55:49.757466Z",
"url": "https://files.pythonhosted.org/packages/5e/f1/7daa793e2a75a8a9a725706f391526f3a7f1248d19ea91f5511cb2d76593/lampip-0.3.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "532077120c073c38fceeb86d3cc6641112ffa6e8c5480c21c2c5c06c1b2445a6",
"md5": "e2d239af0c1a636dd20285318be27f63",
"sha256": "0ba167f01f423f1ee4df71246a243fe4b5912da7eb3b52a8e3b3d66b5b953d4f"
},
"downloads": -1,
"filename": "lampip-0.3.0.tar.gz",
"has_sig": false,
"md5_digest": "e2d239af0c1a636dd20285318be27f63",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6,<4.0",
"size": 7844,
"upload_time": "2023-01-15T07:55:51",
"upload_time_iso_8601": "2023-01-15T07:55:51.112465Z",
"url": "https://files.pythonhosted.org/packages/53/20/77120c073c38fceeb86d3cc6641112ffa6e8c5480c21c2c5c06c1b2445a6/lampip-0.3.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-01-15 07:55:51",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "hayashiya18",
"github_project": "lampip",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "lampip"
}
JSON
