Pandas & AWS Lambda - pandas

Does anyone have a fully compiled version of pandas that is compatible with AWS Lambda?
After searching around for a few hours, I cannot seem to find what I'm looking for and the documentation on this subject is non-existent.
I need access to the package in a lambda function however I have been unsuccessful at getting the package to compile properly for usage in a Lambda function.
In lieu of the compilation can anyone provide reproducible steps to create the binaries?
Unfortunately I have not been able to successfully reproduce any of the guides on the subjects as they mostly combine pandas with scipy which I don't need and adds an extra layer of burden.

I believe you should be able to use the recent pandas version (or likely, the one on your machine). You can create a lambda package with pandas by yourself like this,
First find where the pandas package is installed on your machine i.e. Open a python terminal and type
import pandas
pandas.__file__
That should print something like '/usr/local/lib/python3.4/site-packages/pandas/__init__.py'
Now copy the pandas folder from that location (in this case '/usr/local/lib/python3.4/site-packages/pandas) and place it in your repository.
Package your Lambda code with pandas like this:
zip -r9 my_lambda.zip pandas/
zip -9 my_lambda.zip my_lambda_function.py
You can also deploy your code to S3 and make your Lambda use the code from S3.
aws s3 cp my_lambda.zip s3://dev-code//projectx/lambda_packages/
Here's the repo that will get you started

After some tinkering around and lot's of googling I was able to make everything work and setup a repo that can just be cloned in the future.
Key takeaways:
All static packages have to be compiled on an ec2 amazon Linux instance
The python code needs to load the libraries in the lib/ folder before executing.
Github repo:
https://github.com/moesy/AWS-Lambda-ML-Microservice-Skeleton

The repo mthenw/awesome-layers lists several publicly available aws lambda layers.
In particular, keithrozario/Klayers has pandas+numpy and is up-to-date as of today with pandas 0.25.
Its ARN is arn:aws:lambda:us-east-1:113088814899:layer:Klayers-python37-pandas:1

I know the question was asked a couple years ago and Lambda was on a different stage back then.
I faced similar issues lately and I thought it would be a good idea to add the newest solution here for future users facing the same problem.
It turns out that amazon released the concept of layers in the re:Invent 2018. It is a great feature. This post in medium describes it much better than I could here: Creating New AWS Lambda Layer For Python Pandas Library

The easiest way to get pandas working in a Lambda function is to utilize Lambda Layers and AWS Data Wrangler. A Lambda Layer is a zip archive that contains libraries or dependencies. According to the AWS documentation, using layers keeps your deployment package small, making development easier.
The AWS Data Wrangler is an open source package that extends the power of pandas to AWS services.
Follow the instructions (under AWS Lambda Layer) here.

Another option is to download the pre-compiled wheel files as discussed on this post: https://aws.amazon.com/premiumsupport/knowledge-center/lambda-python-package-compatible/
Essentially, you need to go to the project page on https://pypi.org and download the files named like the following:
For Python 2.7: module-name-version-cp27-cp27mu-manylinux1_x86_64.whl
For Python 3.6: module-name-version-cp36-cp36m-manylinux1_x86_64.whl
Then unzip the .whl files to your project directory and re-zip the contents together with your lambda code.
NOTE: The main Python function file(s) must be in the root folder of the resulting deployment package .zip file. Other Python modules and dependencies can be in sub-folders. Something like:
my_lambda_deployment_package.zip
├───lambda_function.py
├───numpy
│ ├───[subfolders...]
├───pandas
│ ├───[subfolders...]
└───[additional package folders...]

#ashtonium's answer actually works and is most likely the easiest, however, a few additional steps are required. Also, Pandas requires Pytz (mentioned in the link provided by #b3rt0) so that package is needed as well.
Download the whl-files from PyPI (the Pandas file ends with ...manylinux1_x86_64.whl, there is only one Pytz file of relevance)
Unzip the whl-files using terminal command, e.g. unzip filename.whl (Linux/MacOS)
Create a new folder structure python/lib/python3.7/site-packages/ (swap 3.7 for version of your choice)
Move folders from step 2 to site-packages folder in step 3
Zip root folder in new structure, i.e. python
Create a new layer in AWS management console where you upload the zip-file
This is a very common question, I hope my solution helps.
Update on Aug 19, 2020:
Wheel-files aren't available for all packages. In these cases you can skip to step 3, go into the site-packages folder and install the package in there with pip3 install PACKAGE_NAME -t . (no venv required). Some packages are easier than others, some are trickier. Psycopg2 for example, requires you to move only one of the two (as of this writing) package folders.
/Cheers

There are some precompiled packages on github by ryfeus.

My solution has been to maintain 2 requirements.txt style files of packages that go in my layer, one named provided_packages.txt and one named provided_linux_installs.txt
Before deployment (if the packages are not already installed) I run:
pip install -r provided_packages.txt -t layer_name/python/lib/python3.8/site-packages/.
pip download -r provided_linux_installs.txt --platform manylinux1_x86_64 --no-deps -d layer_name/python/lib/python3.8/site-packages
cd layer_name/python/lib/python3.8/site-packages
unzip \*.whl
rm *.whl
Then deploy normally (I am using cdk synth & cdk deploy \* --profile profile_name)
In case helpful, my provided_linux_installs.txt looks like this:
pandas==1.1.0
numpy==1.19.1
pytz==2020.1
python-dateutil==2.8.1

I have started to maintain a GitHub repo for easy and quick access to layers. https://github.com/kuharan/Lambda-Layers
I have been using these for my open-source projects and stuff.

I managed to deploy a pandas code in aws lambda using python3.6 runtime . this is the step that i follow :
Add required libraries into requirements.txt
Build project in a docker container (using aws sam cli : sam build --use-container)
Run code (sam local invoke --event test.json)
this is a helper : https://github.com/ysfmag/aws-lambda-py-pandas-template

# all the step are done in AWS EC2 Linux Free tier so that all the Libraries are compatible with the Lambda environment
# install the required packages
mkdir packages
pip3 install -t . pandas
pip3 install -t . numpy --upgrade
pip3 install -t . wikipedia --upgrade
pip3 install -t . sklearn --upgrade
pip3 install -t . pickle-mixin --upgrade
pip3 install -t . fuzzywuzzy --upgrade
# Now remove all unnecessary files
sudo rm -r *.whl *.dist-info __pycache__
# Now make a DIR so that lambda function can reconginzes
sudo mkdir -p build/python/lib/python3.6/site-packages
# Now move all the files from packages folder to site-packages folder
sudo mv /home/ec2-user/packages/* build/python/lib/python3.6/site-packages/
# Now move to the build packages
cd build
# Now zip all the files starting from python folder to site-packages
sudo zip -r python.zip .
upload the zip file to lambda layers

python 3.8 windows 10 lambda aws pandas
You need to do the following steps on a linux machine and python 3.8:
sudo mkdir python
sudo pip3 install --target python pandas
sudo zip -r pandas.zip python
create a public s3 bucket, upload pandas.zip, grab the public URL.
create new lambda layer using s3 URL from above.
add layer to lambda function and import pandas as pd like you normally would
No linux machine? Launch an Ubuntu EC2 instance or container:
sudo apt install python3.8 zip unzip python3-pip
run 1-3 above
Now you need to copy the zip to your local machine. Open a command terminal and change directory to the folder containing your EC2 instance's pem file and run: scp -i yourPemFile.pem ubuntu#'EC2.Instance.IP.Here':/home/path/to/pandas.zip C:\Users\YourUser\Desktop
run steps 4-6 from above
*for number 3 above: you need to grab your EC2 IP and insert it. You may get an error about the permissions on the pem file, if you do then right click the pem file > properties > security > advanced > disable inheritance and make sure only your user is in the "permission entries." Lastly, fix the paths to point to where the pandas.zip file is on the EC2 instance and where you want the file to end up locally.
**pay attention to the python runtime of the lambda function. Make sure it matches the version of python you're using to do the pip stuff (which should be 3.8).
***the original folder name "python" is named that for a reason as per AWS documentation.

After lots of googling on this and messing around, the concept of layers are great and seem to work for me.
This github repo from keithrozario has loads of pre-build layers you can simply add to your lambda via the arn which has some great stuff in there like pandas, requests and sqlalchemy.
I've create a template to compile and upload a layer (containing python dependencies) to lambda using the AWS CLI which you can find in my Gitlab repo here.
I'm running this on an Amazon Linux EC2, using a virtual environment (venv) to install libraries from a requirements.txt file and then load the zipped files to lambda using the AWS CLI.
Note the folder structure my_zip_file/python/binaries which is required for lambda.
Note: Pandas is quite a large library. Your zipped layer file must be below 70mb.
You may also encounter the horrible "OpenBLAS WARNING - could not determine the L2 cache size on this system" error message. I had to increase the memory from the default 128mb in order to the lambda to successfully run.

After searching around for a few hours, I cannot seem to find what I’m looking for and the documentation on this subject is non-existent.
So i decided to build the libraries myself to support the Amazon Linux 2 arch.
Read full blog here https://khanakia.medium.com/add-pandas-and-numpy-python-to-aws-lambda-layers-python-3-7-3-8-694db42f6119

Related

Can a pycharm project downloaded from Github be run without installing pycharm?

I have a selenium pytest project in pycharm . I want to export it to github to share it to a friend. What instructions should I give to run the project successfully .
Is installing pycharm needed to run the project .
If i generate requirements.txt file , will it be enough to install all the packages needed for running the project in my friends machine
please give a detailed explanation on what my friend should do
You don't need PyCharm.
Your friend will need a version of Python and an OS that is compatible with your program.
Once you have made the git repo and your friend has cloned the repo, have them type:
$ pip install -r requirements.txt
The command line invocation could be many things. You will need to write this part.

How I customize the sam build to pass a ssh and access my private repo on GitHub?

I created a stack of lambda functions and I use the ide pycharm to test them on my localhost. In the requirements.txt file I added a reference to a private repository on github.
The repository works and I was able to install it through the requirements.txt of other projects.
But when I start the local test, using aws sam cli, sam buil fails, because the container does not have the ssh key to access the repository.
Is there any way to customize the sam build process and give it my ssh key to the container access my private repo and install the package?
Or any another solution?
This solution is written for Python, but it's probably applicable one way or another to node.js, Java etc.
I'm using the following workaround. At first it seems to defeat the purpose of building in a container, but if your private repositories are not compiled natively you should be fine. Direct dependencies that are compiled natively will be properly installed in the context of the container.
grep -v "git+" requirements.txt > public_requirements.txt
sam build --template-file "$TEMPLATE_FILE" --build-dir build --use-container --manifest public_requirements.txt
echo "Adding private dependencies"
grep "git+" requirements.txt | xargs python -m pip install --no-deps -t build/LambdaFunction/
If your private dependencies depend on libraries that are compiled natively, you can either add them to the temporary public_requirements.txt, or install them in another container and then copy to build/LambdaFunction/.

What is the setup.py file in github repository used for?

How can I run the code in this repository without following their steps, I want to run the main.py file, from the Demo, directly.
What are the setup.py and install.sh files used for?
setup.py is the canonical name for the installer of a Python package. For example, when you run pip install x, pip runs the setup.py of the package you installed. In this case, install.sh is just a shortcut for running setup.py.
There's no way to use a package without installing it, since it won't have what it needs to operate properly.

How to use python boto3 inside of an AWS CodeBuild build?

I need to send SNS notifications directly from inside my CodeBuild script, but I'm getting this error:
ImportError: No module named boto3
Is it possible to fix? Or is the CodeBuild environment just too restrictive to allow this sort of thing?
CodeBuild curated images for Python don't have boto3 installed. You could use pip install boto3 to install this module during the build by specifying this command in the buildspec.yml. For example, if your python file is main.py, you buildspec.yml should look like this:
version: 0.2
phases:
install:
- pip install boto3
- [other install commands if needed]
build:
- python main.py

Error Installing Microsoft CNTK

During installation I received the following error:
This script will setup the CNTK prequisites and the CNTK Python
environment onto the machine. More help is given by calling 'get-help
.\install.ps1' in your powershell environment.
The script will analyse your machine and will determine which
components are required. The required components will be downloaded in
[C:\local\Scripts\windows\InstallCache] Repeated operation of this
script will reuse already downloaded components.
If required VS2012 Runtime and VS2013 Runtime will be installed
If required MSMPI will be installed
If required the standard Git tool will be installed
CNTK source will be cloned from Git into [c:\repos\CNTK]
Anaconda3 will be installed into [C:\local\Anaconda3-4.1.1-Windows-x86_64]
A CNTK-PY34 environment will be created in [C:\local\Anaconda3-4.1.1-Windows-x86_64\envs]
CNTK will be installed into the CNTK-PY34 environment
1 - I agree and want to continue Q - Quit the installation process
1 Determining Operations to perform. This will take a moment...
The following operations will be performed: * Setup/Update CNTK Wheel
* Clone CNTK from Github repository
Do you want to continue? (y/n) y Performing download operations
Download operations finished
Performing install operations Setup/Update of CNTK Wheel environment.
Please be patient.... You are using pip version 8.1.2, however version
9.0.0 is available. You should consider upgrading via the 'python -m pip install --upgrade pip' command. Cloning CNTK (branch v2.0.beta2.0)
repository....
Fatal error during script execution!
System.InvalidOperationException: This command cannot be run due to
the error: The system cannot find the file specifie d. at
System.Management.Automation.MshCommandRuntime.ThrowTerminatingError(ErrorRecord
errorRecord)
PS C:\local\Scripts\windows>
I'm not familiar with powershell, so I am not sure where to go from here.
Couple of questions. Are you using beta1 or beta2?
If you are using beta1, just a reminder that there is a beta2 now available with bug fixes and also some improvements to the install script, but I don't think this particular problem has been addressed!
It looks like the clone of the cntk git repository is failing.
Was Git installed on your machine? Is there a GIT.EXE in c:\Program Files\Git\bin\?
I think the install found an existing git.exe (in a different location), and is now trying to call it at the 'wrong' location.
The easiest workaround for you (if you have git installed), from a command prompt:
cd c:/
md \repos
cd repos
clone --branch v2.0.beta1.0 --recursive https://github.com/Microsoft/CNTK
If you have moved to beta2, replace the v2.0.beta1.0 with v2.0.beta2.0