You can display a Jupyter notebook in an active html setting by running :
$ jupyter nbconvert untitled.ipynb --to slides --post serve
Is there any ways to run a notebook in the same slideshow format in order to allow for a live presentation/execution of your cells ?
Check out the Jupyter plugin RISE using Reveal.JS:
Github Repo: https://github.com/damianavila/RISE
Documentation: https://rise.readthedocs.io/en/maint-5.5/
It's awesome.
Related
I've using Google Colab for computing my Kaggle competition, nowadays I decided to take a look if it'll work faster using services on Google Cloud. I have a *.ipybn file from Google Cloud, downloaded it and try to upload it to Google Cloud instance.
I created all connection on Google Colab using this link: https://towardsdatascience.com/setting-up-kaggle-in-google-colab-ebb281b61463 and it worked fine.
Using this tutorial: https://towardsdatascience.com/how-to-use-jupyter-on-a-google-cloud-vm-5ba1b473f4c2 I started a new instance for Jupyter notebook. Uploaded a *ipybn file, I tried to install Kaggle and run my notebook, but I have usually following errors:
kaggle: command not found error
ensure that your python binaries are on your path
How can I set everything to work on Google Cloud service?
Using this first tutorial mind about changing root directory path from content to /home/jupyter/, for example:
import zipfile
zip_ref = zipfile.ZipFile("/home/jupyter/Airbus_competition/input/test_v2.zip", 'r')
zip_ref.extractall("/home/jupyter/Airbus_competition/input/test_v2")
zip_ref.close()
For problems with installing kaggle, you don't have access to root folder from Jupyter notebooks, but you can install and use Kaggle API, when you change the command from !kaggle to !~/.local/bin/kaggle, for example (commands from tutorial changed to be working on GCS):
!mkdir ~/.kaggle
import json
token = {"your_TOKEN"}
with open('/home/jupyter/.kaggle/kaggle.json', 'w') as file:
json.dump(token, file)!cp /home/jupyter/.kaggle/kaggle.json
~/.kaggle/kaggle.json
!~/.local/bin/kaggle config set -n path -v{home/jupyter/Airbus_competition}
!chmod 600 /home/jupyter/.kaggle/kaggle.json
!~/.local/bin/kaggle competitions download -c airbus-ship-detection -p /home/jupyter/Airbus_competition/input --force
I am running Apache superset on GCP instance and it works fine with Sqlite database which is default in superset and I don't need to configure so many things. But my requirement is that I need superset to connect directly with BigQuery instead of Sqlite and I don't have developer background. So, is there an easy way to do that without heavy codes?
Connecting to BigQuery is very well documented here in Preset's Superset user documentation https://docs.preset.io/docs/big-query-database
Following the steps mentioned at the official Google Cloud page here, you need to do the following
Install pybigquery
pip install pybigquery
Download your Google Cloud authorization json key file
From your terminal instance, set GOOGLE_APPLICATION_CREDENTIALS env. var to the path of your json key file
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/[json_file].json"
Elbehery is right. I don't have enough rep to comment, but I wanted to note that Apache has created docs for this.
FWIW, I couldn't use the UI for importing credentials.json so I set it as an env var in my Docker image. Here are the commands and steps I run locally:
# Setup virtual environment (exit by typing "deactivate")
pip3 install virtualenv
python3 -m virtualenv ./.venv
source ./.venv/bin/activate
# Download Superset
git clone https://github.com/apache/superset.git
cd superset/
# Create a copy of your credentials for docker to use
cp ~/.config/gcloud/application_default_credentials.json docker/credentials.json
echo "GOOGLE_APPLICATION_CREDENTIALS=docker/credentials.json" >> docker/.env-non-dev
# Run Superset
docker-compose -f docker-compose-non-dev.yml pull
docker-compose -f docker-compose-non-dev.yml up
Now that Superset is running locally:
visit http://0.0.0.0:8088/ in your web browser
In the top right of UI, click the +DATABASE button (or + > Data > Connect Database)
In popup window Click Supported Databases then (at the bottom) Other
Set DISPLAY NAME: BigQuery
Set SQLALCHEMY URI: bigquery://my_project_id
Click Test Connection
Click Connect
Now that BigQuery is integrated into Superset:
In the top of page Click SQL Lab > SQL Editor
im using EMR and wanted to use jupyter(ipython) so i added to the cluster the bootstrap action:
s3://elasticmapreduce.bootstrapactions/ipython-notebook/install-ipython-notebook
I performed the port tunelling to access jupyter from my local host and works fine, but it is asking for a login password, tried empty, tried hadoop, but no luck, does any body knows what is the jypyter password?
I ran into this problem as well when I used the same bootstrap action. I tried adding in Args=[--password, jupyter] which I also could not get working. That was from this aws forum:
Name='Install Jupyter notebook',Path="s3://aws-bigdata-blog/artifacts/aws-blog-emr-jupyter/install-jupyter-emr5.sh",Args=[--r,--julia,--toree,--torch,--ruby,--ds-packages,--ml-packages,--python-packages,'ggplot nilearn',--port,8880,--password,jupyter,--jupyterhub,--jupyterhub-port,8001,--cached-install,--notebook-dir,s3://<your-s3-bucket>/notebooks/,--copy-samples]
What I did instead was to follow these instructions for installing anaconda directly in the EMR instance using the CLI. If you follow the first part you should be able to get it up and running. To summarize here:
ssh into your master emr instance using the .pem file you saved
once there's you'll want to install anaconda using super user priveledges: sudo wget http://repo.continuum.io/archive/Anaconda3-4.1.1-Linux-x86_64.sh. Then bash Anaconda3–4.1.1-Linux-x86_64.sh
Make sure you're using the anaconda version of python: which python
If you're not, specify your source: source .bashrc
Now make a jupyter config file: jupyter notebook --generate-config
cd into the jupyter folder: cd ~/.jupyter/
update the config file: vi jupyter_notebook_config.py
In the config file add the following lines:
c = get_config()
c.NotebookApp.ip = '*'
c.NotebookApp.open_browser = False
c.NotebookApp.port = 6789 <---pick whichever port you want
exit out of the config editor and run jupyter via: jupyter notebook
this should run a notebook with no active kernels (for now). But it will give you the token you're looking for: http://localhost:6789/?token=xxxxxx
Leave this running, and open a new terminal window. Now you'll want to tunnel to the EMR instance per this aws blog post (make the port the same as the one you specified in the config file). ssh -o ServerAliveInterval=10 -i <<credentials.pem>> -N -L 8192:<<master-public-dns-name>>:8192 hadoop#<<master-public-dns-name>>
Opening localhost:6789 in the browser should prompt you with the jupyter page to enter your password or token. Enter the token that was generated in the above step and you should be good to go.
Hope this helps! There might be a less convoluted way, but this is what ended up working for me.
I can't figure out what's up in my jupyter notebook. Vincent and Bokeh work fine, but in trying out Altair, I must be missing something, but I'm not erroring and the online docs don't mention my problem.
This is what I enter (from documentation page https://altair-viz.github.io/gallery/bar_aggregate.html )
from altair import *
Chart('http://vega.github.io/vega-lite/data/population.json',
description='A bar chart showing the US population distribution of age groups in 2000.',
).mark_bar().encode(
x=X('sum(people):Q',
axis=Axis(
title='population',
),
),
y=Y('age:O',
scale=Scale(
bandSize=17.0,
),
),
).transform_data(
filter='datum.year == 2000',
)
The code executes in my Jupyter notebook with no errors, but also no graph. I do have vega installed, so that's not the issue. It's not specific to this graph, other examples have the same behavior. I'm not sure how to even troubleshoot this!
This solved my problem : Display plots in jupyter
Which points to : How to install properly altair in anaconda and enable ipyvega
Install altair :
conda install altair --channel conda-forge
Run this line in command line before launching jupyter :
jupyter nbextension enable vega --py --sys-prefix
Launch notebook :
jupyter notebook
I'm trying to run IPython on a production ubuntu server. I want to control it with upstart.
I have a bash script that properly invokes it in the foreground but it doesn't work when invoked through upstart. I'm not sure how to debug the problem other than piping the upstart script's output to a file, which just confirms that the IPython console dashboard properly shows up.
I'm using django-extensions with the following configuration:
IPYTHON_ARGUMENTS = [
'--ext', 'django_extensions.management.notebook_extension',
'--pylab=inline',
'--profile=myprofile',
]
My bash script is:
#!/bin/bash
set -e
cd /home/ubuntu/myproject
exec venv/bin/python /home/ubuntu/myproject/manage.py shell_plus --notebook
Any help is appreciated
No idea what can be the reason.
Did you had a look at Hydra that have been designed to launch multiple IPython server?