Install dependencies from requirements.txt in Google Colaboratory - google-colaboratory

How to install python dependencies using a requirements file in Google Colab?
Like the equivalent of pip install -r requirements.txt

With Daniel's hint above, I was able to solve it.
Using the "uploading files from local computer script" I uploaded my requirements.txt file onto Google Colab platform. Script is found here. This is the script,
from google.colab import files
uploaded = files.upload()
for fn in uploaded.keys():
print('User uploaded file "{name}" with length {length} bytes'.format(
name=fn, length=len(uploaded[fn])))
The output on executing, clearly says that, it is saving this file as 'requirements.txt'. I couldn't however find this file in Google Drive, which is fine by me. Then,
!pip install -r requirements.txt
worked!

You can write a file using the IPython magic function %%writefile then just do a !pip install -r requirements.txt
ie:
Cell 1
%%writefile requirements.txt
<contents of your requiements.txt>
Cell 2
!pip install -r requirements.txt

You Cannot find the Uploaded file in Google Drive. Because it is uploaded in the Python 3 Google Backend Compute Engine. When you Terminate the Session the all the files and data will be deleted.

try;
python -m pip install -r requirements.txt

U can use
pip install -r"path"

Related

Is that possible to copy a folder without zipping from Google Cloud Storage to Google Colab?

Colab don't like to use a simple copy like this :
!gsutil cp gs://Bucket/Folder_to_be_copied Destination_colab
Should I add -r ?
Mounting the bucket to the colab makes it easier for you. You can use the regular linux commands in the place of gsutil commands. These are the steps for mounting the bucket in colab.
from google.colab import auth
auth.authenticate_user()
Once you run this, a link will be generated, you can click on it and get the signing in done.
!echo "deb http://packages.cloud.google.com/apt gcsfuse-bionic main" > /etc/apt/sources.list.d/gcsfuse.list
!curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
!apt -qq update
!apt -qq install gcsfuse
Use this to install gcsfuse on colab. Cloud Storage FUSE is an open source FUSE adapter that allows you to mount Cloud Storage buckets as file systems on Colab, Linux or macOS systems.
!mkdir folderOnColab
!gcsfuse folderOnBucket/content/folderOnColab
Use this to mount the directories.
You can use this docs for further reading. https://cloud.google.com/storage/docs/gcs-fuse
Answering you question, GSUtil can be used to copy entire directories without zipping its content. And your command looks fine. I wonder what the Destination_colab part in your command is.

No module named install

Yes you read it right!
I am trying to install pygame, so I downloaded the whl file and copied it to my project's folder, in the command prompt I navigated to the folder and entered
python -m install --user pygame-1.9.2-cp35-cp35m-win32.whl
Now if you can help me here that would be really appreciated, why is the error so rare that I couldn't find it anywhere.
Python doesn't have a module called "install". The module you're looking for is probably pip.
Just type in the command prompt:
python -m pip install --user pygame-1.9.2-cp35-cp35m-win32.whl
And pygame should start being installed.

PIP install pandas not working

I am trying to install pandas with .whl file in a work computer but I get " cannot fetch URL" error. I have up to date version of PIP installed.How can I get this to work.I'm using Python 3.5.Any help will be appreciated.
I just used the following which was quite simple. First open a console then cd to where you've downloaded your file like some-package.whl and use
pip install some-package.whl
python -m pip install some-package.whl also works if pip is not found in PATH
Note: if pip.exe is not recognized, you may find it in the "Scripts" directory from where python has been installed. If pip is not installed, this page can help:
How do I install pip on Windows?
Note: for clarification
If you copy the *.whl file to your local drive (ex. C:\some-dir\some-file.whl) use the following command line parameters --
pip install C:/some-dir/some-file.whl
I guess since you are on a work computer
try this
sudo pip --proxy=http://username:password#proxyURL:portNumber install yolk
for example:
sudo pip --proxy=http://202.194.64.89:8000 install elasticsearch
202.194.64.89:8000 is my PROXY,

translate.py can't be found in /rnn/translate folder

I installed tensorflow with method:
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl
sudo pip install --upgrade $TF_BINARY_URL
But when I go into the tensorflow folder, I can't found the translate.py file in translate folder, all the files in the translate are list:
It seems that example files were excluded from the pip installation packages of tensorflow (see issue #4574) without updating the docs.
Cloning the model repo should help as it contains all the tutorial files.

Pandas & AWS Lambda

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