I'm looking for a work around to use numpy in AWS lambda. I am not using EC2 just lambda for this so if anyone has a suggestion that'd be appreciated. Currently getting the error:
cannot import name 'multiarray'
Using grunt lambda to create the zip file and upload the function code. All the modules that I use are installed into a folder called python_modules inside the root of the lambda function which includes numpy using pip install and a requirements.txt file.
An easy way to make your lambda function support the numpy library for python 3.7:
Go to your lambda function page
Find the Layers section at the bottom of the page.
Click on Add a layer.
Choose AWS layers as layer source.
Select AWSLambda-Python37-Scipy1x as AWS layers.
Select 37 for version.
And finally click on Add.
Now your lambda function is ready to support numpy.
Updated to include the solution here, rather than a link:
After much effort, I found that I had to create my deployment package from within a python3.6 virtualenv, rather than directly from the host machine. I did the following within a Ubuntu 16.04 docker image. This assumes that you have python3.6, virtualenv and awscli already installed/configured, and that your lambda function code is in the ~/lambda_code directory:
1) cd ~ (We'll build the virtualenv in the home directory)
2) virtualenv venv --python=python3.6 (Create the virtual environment)
3) source venv/bin/activate (Activate the virtual environment)
4) pip install numpy
5) cp -r ~/venv/lib/python3.6/site-packages/* ~/lambda_code (Copy all installed packages into root level of lambda_code directory. This will include a few unnecessary files, but you can remove those yourself if needed)
6) cd ~/lambda_code
7) zip -r9 ~/package.zip . (Zip up the lambda package)
8) aws lambda update-function-code --function-name my_lambda_function --zip-file fileb://~/package.zip (Upload to AWS)
Your lambda function should now be able to import numpy with no problems.
If you want a more out-of-the-box solution, you could consider using serverless to deploy your lambda function. Before I found the above solution, I followed the guide here and was able to run numpy successfully in a python3.6 lambda function.
As of 2018 it's best to just use the inbuilt layers functionality.
AWS have actually released a pre-made one with numpy in it: https://aws.amazon.com/blogs/aws/new-for-aws-lambda-use-any-programming-language-and-share-common-components/
I was unable to find a good solution using serverless plugins, but I did find a good way with layers. See Serverless - Numpy - Unable to find good bind path format
Add numpy layer in this way:
Go on your lambda function
select add a new layer
add it using this arn: arn:aws:lambda:eu-central-1:770693421928:layer:Klayers-p39-numpy:7
(change your zone if you are not in eu-central-1)
Let me know if it will work
I would add this answer as well: https://stackoverflow.com/a/52508839/1073691
Using pipenv includes all of the needed .so files as well.
1.) Do a Pip install of numpy to a folder on your local machine.
2.) once complete, zip the entire folder and create a zip file.
3.) Go to AWS lambda console, create a layer and upload zip file created in step 2 there and save the layer.
4.) After you create your lambda function, click add layer and add the layer you created. That's it, import numpy will start working.
Related
I have a python3.8, and I created a new folder and installed pandas in it using
pip3 install pandas -t .
Next thing - zipped the folder (the zipped folder is 38Mb), and uploaded to s3.
Created a Layer and added the s3 path of zip file in it (also set the runtime env to python3.8 here)
Next I created a lambda function with python3.8 and test its skeleton first and it worked.
Added the layer to the lambda function and imported pandas. And now when I run the test, it does not detect pandas and gives me Module Not Found error.
What can I be doing wrong here?
Did you created a folder named python and put all the package files inside it? Also another supporting package Pytz is required to run panda in lambda. I use MAC OSX to create the zip file but the root folder needs to be named as "python".
The creation of the zip file is little bit lengthy to describe here, I suggest you to go through this document. Also naming convention is equally important. I think if you follow the document and create the zip file and upload it directly (or via S3) to create lambda layer then it will definitely work.
Gettting the below error while running the lambda code , I am using the library called
from flatten_json import flatten
I tried to look for a lambda layer , but did not find any online , please let me know if any one used this before or suggest any alternative
flatten_json library is missing.
Use pip install flatten_json to get it
There are four steps you need to do:
Download the dependency.
Package it in a ZIP file.
Create a new layer in AWS.
Associate the layer with your Lambda.
My answer will focus on 1. and 2. as they are what is most important to your problem. Unfortunately, packaging Python dependencies can be a bit more complicated than for other runtimes.
The main issue is that some dependencies use C code under the hood, especially performance critical libraries, for example for Machine Learning etc.
C code needs to be compiled and if you run pip install on your machine the code will be compiled for your computer. AWS Lambdas use a linux kernel and amd64 architecture. So if you are running pip install on a Linux machine with AMD or Intel processor, you can indeed just use pip install. But if you use macOS or Windows, your best bet is Docker.
Without Docker
pip install --target python flatten_json
zip -r layer.zip python
With Docker
The lambci project provides great Docker container for building and running Lambdas. In the following example I am using their build-python3.8 image.
docker run --rm -v $(pwd):/var/task lambci/lambda:build-python3.8 pip install --target python flatten_json
zip -r layer.zip python
Be aware that $(pwd) is meant to be your current directoy. On macOS and WSL this should work, but if it does not work you can just replace it with the absolute path to your current directory.
Explanation
Those commands will install the dependency into a target folder called python. The name is important, because it is one of two folders of a layer where Lambda looks for dependencies.
The python folder is than archived recursively (-r) in a file called layer.zip.
Your next step is to create a new Layer in AWS and associated your function with that layer.
There are two options to choose from
Option 1) You can use a deployment package to deploy your function code to Lambda.
The deployment package (For e.g zip) will contain your function's code and any dependencies used to run the function's code.
Hence, you can package flatten_json as your code to the Lambda.
Check Creating a function with runtime dependencies page in aws documentation, it explains the use-case of having requests library. In your scenario, the library would be flatten_json
Option 2) Create a layer that has the library dependencies you need, in your case just flatten_json. And then attach that layer to your Lambda.
Check creating and sharing lambda layers guide provided by AWS.
How to decide between 1) and 2)?
Use Option 1) when you just need the dependencies in just that one Lambda. No need to create an extra step of creating a layer.
Layers are useful if you have some common code that you want to share across different Lambdas. So if you need the library accessible in other Lambdas as well, then it's good to have a layer[Option 2)] that can be attached to different lambdas.
You can do this is in a Lambda if you don´t want to create the layer. Keep in mind it will run slower since it has to install the library in every run:
import sys
import subprocess
subprocess.call('pip install flatten_json -t /tmp/ --no-cache-dir'.split(), stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
sys.path.insert(1, '/tmp/')
import flatten_json
I have a simple Lambda function which is using the numpy library,
I have set up a virtual environment in my local, and my code is able to fetch and use the library locally.
I tried to use AWS Lambda's layer, and zipped the venv folder and uploaded to the layer,
Then I attached the correct layer and version to my function,
But the function is not able to fetch the library
Following is the code which works fine on local -
import numpy as np
def main(event, context):
a = np.array([1, 2, 3])
print("Your numpy array:")
print(a)
Following is the venv structure which I zipped and uploaded -
I get the following error -
{
"errorMessage": "Unable to import module 'handler': No module named 'numpy'",
"errorType": "Runtime.ImportModuleError"
}
My Lambda deployment looks like this -
I'm trying to refer this -
https://towardsdatascience.com/introduction-to-amazon-lambda-layers-and-boto3-using-python3-39bd390add17
I've seen that a few libraries like numpy and pandas don't work in Lambda when installed using pip. I have had success using the .whl package files for these libraries to create the Lambda layer. Refer to the steps below:
NOTE: These steps set up the libraries specific to the Python 3.7 runtime. If using any other version, you would need to download the .whl files corresponding to that Python version.
Create an EC2 instance using Amazon Linux AMI and SSH into this instance. We should create our layer in Amazon Linux AMI as the Lambda Python 3.7 runtime runs on this operating system (doc).
Make sure this instance has Python3 and "pip" tool installed.
Download the numpy .whl file for the cp37 Python version and the manylinux1_x86_64 OS by executing the below command:
$ wget https://files.pythonhosted.org/packages/d6/c6/58e517e8b1fb192725cfa23c01c2e60e4e6699314ee9684a1c5f5c9b27e1/numpy-1.18.5-cp37-cp37m-manylinux1_x86_64.whl
Skip to the next step if you're not using pandas. Download the pandas .whl file for the cp37 Python version and the manylinux1_x86_64 OS by executing the below command:
$ wget https://files.pythonhosted.org/packages/a4/5f/1b6e0efab4bfb738478919d40b0e3e1a06e3d9996da45eb62a77e9a090d9/pandas-1.0.4-cp37-cp37m-manylinux1_x86_64.whl
Next, we will create a directory named "python" and unzip these files into that directory:
$ mkdir python
$ unzip pandas-1.0.4-cp37-cp37m-manylinux1_x86_64.whl -d python/
$ unzip numpy-1.18.5-cp37-cp37m-manylinux1_x86_64.whl -d python/
We also need to download "pytz" library to successfully import numpy and pandas libraries:
$ pip3 install -t python/ pytz
Next, we would remove the “*.dist-info” files from our package directory to reduce the size of the resulting layer.
$ cd python
$ sudo rm -rf *.dist-info
This will install all the required libraries that we need to run pandas and numpy.
Zip the current "python" directory and upload it to your S3 bucket. Ensure that the libraries are present in the hierarchy as given here.
$ cd ..
$ zip -r lambda-layer.zip python/
$ aws s3 cp lambda-layer.zip s3://YOURBUCKETNAME
The "lambda-layer.zip" file can then be used to create a new layer from the Lambda console.
Base on aws lamda layer doc, https://docs.aws.amazon.com/lambda/latest/dg/configuration-layers.html your zip package for the layer must have this structure.
my_layer.zip
| python/numpy
| python/numpy-***.dist-info
So what you have to do is create a folder python, and put the content of site-packages inside it, then zip up that python folder. I tried this out with a simple package and it seem to work fine.
Also keep in mind, some package require c/c++ compilation, and for that to work you must install and package on a machine with similar architecture to lambda. Usually you would need to do this on an EC2 where you install and package where it have similar architecture to the lambda.
That's bit of misleading question, because you at least did not mention you use serverless. I found it going through the snapshot of you project structure you provided. That means you probably use serverless for deployment of your project within AWS provider.
Actually, there are multiple ways you can arrange lambda layer. Let's have a look at each of them.
Native AWS
Once you will navigate to Add a layer, you will find 3 options:
[AWS Layers, Custom Layers, Specify an ARN;].
Specify an ARN Guys, who did all work for you: KLayers
so, you need numpy, okay. Within lambda function navigate to the layers --> create a new layer --> out of 3 options, choose Specify an ARN and as the value put: arn:aws:lambda:eu-west-1:770693421928:layer:Klayers-python38-numpy:12.
It will solve your problem and you will be able to work with numpy Namespace.
Custom Layers
Choose a layer from a list of layers created by your AWS account or organization.
For custom layers the way of implementing can differ based on your requirements in terms of deployment.
If are allowed to accomplish things manually, you should have a glimpse at following Medium article. I assume it will help you!
AWS Layers
As for AWS pre-build layers, all is simple.
Layers provided by AWS that are compatible with your function's runtime.
Can differentiate between runtimes
For me I have list of: Perl5, SciPy, AppConfig Extension
Serverless
Within serverless things are much easier, because you can define you layers directly with lambda definition in serverless.yml file. Afterwards, HOW to define them can differ as well.
Examples can be found at: How to publish and use AWS Lambda Layers with the Serverless Framework
If you will have any questions, feel free to expand the discussion.
Cheers!
I am trying to run the cvxpy package in an AWS lambda function. This package isn't in the SDK, so I've read that I'll have to compile the dependencies into a zip, and then upload the zip into the lambda function.
I've done some research and tried out the links below, but when I try to pip install cvxpy I get error messages - I'm on a Windows box, but I know that AWS Lambda runs on Linux.
Appreciate the help!
http://i-systems.github.io/HSE545/machine%20learning%20all/cvxpy_install/CVXPY%2BInstallation%2BGuide%2Bfor%2BWindows.html
https://programwithus.com/learn-to-code/Pip-and-virtualenv-on-Windows/
https://medium.com/#manivannan_data/import-custom-python-packages-on-aws-lambda-function-5fbac36b40f8
https://www.cvxpy.org/install/index.html
For installing cvxpy on windows it requires c++ build tools (please refer: https://buildmedia.readthedocs.org/media/pdf/cvxpy/latest/cvxpy.pdf)
On Windows:
I created a lambda layer python directory structure python/lib/python3.7/site-packages (refer: https://docs.aws.amazon.com/lambda/latest/dg/configuration-layers.html) and installed my pip packages in that site-packages directory.
pip install cvxpy --target python/lib/python3.7/site-packages
Then, I zipped the python/lib/python3.7/site-packages as cvxpy_layer.zip and uploaded it to an S3 bucket (layer zipped file max limit is only 50 MB https://docs.aws.amazon.com/lambda/latest/dg/limits.html), to attach it to my lambda layers.
Now, the layer is ready but the lambda is failing to import the packages as they were installed on a windows machine. (refer: AWS Lambda - unable to import module 'lambda_function')
On Linux:
I created the same directory structure as earlier python/lib/python3.7/site-packages and installed the cvxpy and zipped it as shown below.
Later I uploaded the zip file to an S3 bucket and created a new lambda layer.
Attaching that lambda layer to my lambda function, I colud able to resolve the import issues failing earlier and run the basic cvxpy program on lambda.
mkdir -p alley/python/lib/python3.7/site-packages
pip install cvxpy --target alley/python/lib/python3.7/site-packages
cd alley
zip -rqvT cvxpy_layer.zip .
Lambda layer Image:
Lambda function execution:
You can wrap all your dependencies along with lambda source into a single zipfile and deploy it. Doing this, you will end up having additional repetitive code in multiple lambda functions. Suppose, if more than one of your lambda functions needs the same package cvxpy, you will have to package it twice for both the functions individually.
Instead a better option would be to try Labmda Layers, where you put all your dependencies into a package and deploy a layer into your Lambda. Then attach that layer to your function to fetch its dependencies from there. The layers can even be versioned. :)
Please refer the below links:
https://docs.aws.amazon.com/lambda/latest/dg/configuration-layers.html
https://dev.to/vealkind/getting-started-with-aws-lambda-layers-4ipk
I am trying to import a python deployment package in aws lambda. The python code uses numpy. I followed the deployment package instructions for virtual env but it still gave Missing required dependencies ['numpy']. I followed the instruction given on stack overflow (skipped step 4 for shared libraries, could not find any shared libraries) but no luck. Any suggestions to make it work?
The easiest way is to use AWS Cloud9, there is no need to start EC2 instances and prepare deployment packages.
Step 1: start up Cloud9 IDE
Go to the AWS console and select the Cloud9 service.
Create environment
enter Name
Environment settings (consider using t2.small instance type, with the default I had sometimes problems to restart the environment)
Review
click Create environment
Step 2: create Lambda function
Create Lambda Function (bottom of screen)
enter Function name and Application name
Select runtime (Python 3.6) and blueprint (empty-python)
Function trigger (none)
Create serverless application (keep defaults)
Finish
wait couple of seconds for the IDE to open
Step 3: install Numpy
at the bottom of the screen there is a command prompt
go to the Application folder, for me this is
cd App
install the package (we have to use pip from the virtual environment, because the default pip points to /usr/bin/pip and this is python 2.7)
venv/bin/pip install numpy -t .
Step4: test installation
you can test the installation by editing the lambda_function.py file:
import numpy as np
def lambda_handler(event, context):
return np.sin(1.0)
save the changes and click the green Run button on the top of the screen
a new tab should appear, now click the green Run button inside the tab
after the Lambda executes I get:
Response
0.8414709848078965
Step 5: deploy Lambda function
on the right hand side of the screen select your Lambda function
click the upwards pointing arrow to deploy
go to the AWS Lambda service tab
the Lambda function should be visible, the name has the format
cloud9-ApplicationName-FunctionName-RandomString
Using Numpy is a real pain.
Numpy needs to be properly compiled on the same OS as it runs. This means that you need to install/compile Numpy on an AMI image in order for it erun properly in Lambda.
The easiest way to do this is to start a small EC2 instance and install it there. Then copy the compiled files (from /usr/lib/python/site-packages/numpy). These are the files you need to include in your Lambda package.
I believe you can also use the serverless tool to achieve this.
NumPy must be compiled on the platform that it will be run on. Easiest way to do this is to use Docker. Docker has a lambda container. Compile NumPy locally in Docker with the lambda container, then push to AWS lambda.
The serverless framework handles all this for you if you want an easy solution. See https://stackoverflow.com/a/50027031/1085343
I was having this same issue and pip install wasn't working for me. Eventually, I found some obscure posts about this issue here and here. They suggested going to pypi, downloading the .whl file (select py version and manylinux1_x86_64), uploading, and unzipping. This is what ultimately worked for me. If nothing else is working for you, I would suggest trying this.
For Python 3.6, you can use a Docker image as someone already suggested. Full instructions for that here: https://medium.com/i-like-big-data-and-i-cannot-lie/how-to-create-an-aws-lambda-python-3-6-deployment-package-using-docker-d0e847207dd6
The key piece is:
docker run -it dacut/amazon-linux-python-3.6