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This repository contains a few small files that allow to easily deploy Python (cf. http://python.org) and Jupyter Notebook (cf. http://jupyter.org) in the cloud.
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It all works (apart from the parallel computation example) even on the smallest **DigitalOcean droplet** (cf. https://www.digitalocean.com/?refcode=fbe512dd3dac).
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It all works even on the smallest **DigitalOcean droplet** (cf. https://m.do.co/c/fbe512dd3dac) which currently costs 5 USD per month with 1 CPU core, 512 MB of RAM and 20 GB of SSD storage.
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When setting up such a droplet it is recommended to use the latest version of **Ubuntu**.
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When setting up such a droplet it is recommended to use a current version of **Ubuntu**.
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I assume that you have **cloned the repository** to your local machine (Linux or Mac):
You will start with 10 USD worth of compute power (= e.g. 2 monthly fees for the smallest droplet).
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You will start with 10 USD worth of compute power (= e.g. 2 monthly fees for the smallest droplet) although you'll only get charged the hours your droplet is alive.
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Now **create a droplet** giving it a name like "cloud-python" and chosing the size, location and operating system (e.g. Ubuntu 14.04).
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Then navigate to the **repository folder** and do:
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```
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cd path-to/cloud-python
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cd your-path-to/cloud-python
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bash setup_server.sh THE-IP-ADDRESS
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```
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The setup might take a while. The last step in the setup fires up a **Jupyter Notebook** server on the **port 8888**. You can access it in the browser under
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The setup might take a while (about 4 minutes; you'll see the progress on the shell). The last step in the setup fires up a **Jupyter Notebook** server on the **port 8888**. You can access it in the browser under
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```
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http://THE-IP-ADDRESS:8888
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https://THE-IP-ADDRESS:8888
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```
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You can now click on the example notebooks and play around.
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There is **SSL encryption** enabled which uses by default the certificate files as provided in the repo (you should replace them by your own; see the comments in the respective Jupyter Notebook configuration file). This feature might require you to add a security exception in your browser due to the nature of the certificate files used.
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There is also **password protection** enabled (the password is by default **jupyter**). You should also replace the password hash key in the Jupyter Notebook config file by one of your own (again see the comments in the configuration file itself).
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After a successful login, you can now click on the example notebooks and play around.
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## Flask Web app
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## Security
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Note that all this is **really insecure**. All is run as root user, no password protection or encryption is in place. It is only for illustration purposes. However, security features can easily be added to the set-up.
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Note that all this is quite **insecure**. All is run as root user and there is only password protection and encryption for the notebook server in place. It is only for illustration purposes. However, additional security features (e.g. for the Flask app) can easily be added to the set-up.
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## datapark.io
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http://tpq.io\|team@tpq.io\|
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http://twitter.com/dyjh
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**Python for Finance Training**\|http://training.tpq.io
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**datapark.io**\|http://datapark.io
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**Quant Platform**\|http://quant-platform.com
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**Derivatives Analytics with Python (Wiley Finance)**\|
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http://derivatives-analytics-with-python.com
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**Python for Finance (O'Reilly)**\|
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http://python-for-finance.com
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**Derivatives Analytics with Python (Wiley Finance)**\|
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