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Full stack python guide to deployments pdf

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Jul 31, Before joining Twilio, Matt Makai, our San Francisco-based Developer Evangelist , drove across America on a ronin-type quest to learn more. Your web app deployment. Server(s) / Platform-as-a-Service. H Operating system . JavaScript /css. Web server(s). - File system. T.,,.Il 1. HTTP(S) responses. Full Stack Python Guide to Deployments - Ebook download as PDF File .pdf), Text File .txt) or read book online. Python guide to deployments.


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Deploy Python provides details on every Full Stack Python deployments book for Flask and Django. Sep 9, Full Stack Python An open book that explains concepts in plain language and provides the most helpful resources on creating, deploying and. Full Stack Python explains each layer of the web application stack, from the server up through the Learn Python the Hard Way is a free book by Zed Shaw. Dive into Python 3 is an open source book provided under the Creative Commons license and available in HTML or PDF form. I need to know how to deploy it.

The query could be performed in the background on a fixed interval with the results stored in the database. She believes that open-source technologies are the foundation of our modern tech-driven world and that automation is one of the core values that technology offers us. There's a whole other page for editors and IDEs. Activate our environment variables for the application. This can either be under your project or a separate source control repository. Pyramid and Morepath.

Book Site. Want to know the Homepage of a particular airport? Click here to find out. English ISBN Book Description Learn everything you need to know to deploy Python web applications to a server.

About the Authors Guido van Rossum is the inventor of Python. Fred L. Drake, Jr. Reviews and Rating, and Recommendations: Amazon Related Book Categories: Recipes for Mastering Python 3. All Categories. Recent Books. IT Research Library. Miscellaneous Books. Computer Languages. A value for the key 'cyoa' has not been set so the value returned is specified as nil. Let's set it now and get the new set value.

We can test the installation using the following command. However we can perform operations on the value that are more integer-like such as increment and decrement. Values can be retrieved from Redis via the get command followed by the key name.

We'll try that real quick before moving on with our deployment. For example: If you already know how to use Redis you can skip this section if you already know how to use Redis as we're just going to run through a few basic commands. Strings are the basic data type in Redis so we receive back our 1 as a String.

Redis is operating with default settings which will suffice for our web application deployment. We can now continue our manual set up in the next chapter on application dependencies or automate this part of the deployment in the remainder of this chapter. Chapter 6: Installs and configures the PostgreSQL database.

Installs and configures Redis. Make sure to again run our Ansible playbook again with our shell script to install and configure the databases on our server. Application Dependencies In the next chapter we will handle the application dependencies with a virtualenv. Additional Database Resources Numerous resources for relational databases and NoSQL data stores are available to continue learning about the best ways to use these technologies. In most application deployments. The post is an inside look at the evolution of Braintree's usage of the database.

Here are several resources that helped me better understand how to use it. Additional Redis Resources Here are some additional handy tutorials for installing and using Redis. In this chapter we will install our application dependencies via the pip command. Our deployment will continue in this chapter by performing the following configuration: Python's ecosystem facilitates discovery. Application Dependencies in Our Deployment Python web applications are built upon the work done by thousands of open source programmers.

Application dependencies include not only web frameworks but also libraries for scraping. When you build a Python web application you should always include a requirements. The web application then relies only on that virtualenv instance to run. The most common isolation method for Python application is using a virtualenv.

Create a virtualenv for a fresh Python installation environment 2. Storing Dependencies in requirements. The virtualenv stores dependencies in an isolated environment. Isolating Dependencies Dependencies are installed separately from system-level packages to prevent library version conflicts. To use a virtualenv it must first be created with the virtualenv command and then activated.

Install the necessary application dependencies listed in the requirements. Each virtualenv is its own copy of the Python interpreter and dependencies in the site-packages directory.

While it may sound good to always stay up to date. Create a directory to store virtualenvs. Developers should deliberately upgrade and test to make sure there were no backwards-incompatible modifications in newer dependency library versions.

Full Stack Python Guide to Deployments – DevBlog

Install the necessary Choose Your Own Adventure Presentations project dependencies with pip into the cyoa virtualenv. We can also use other commands in the bin directory without activating the virtualenv first though. Now the virtualenv is activated for our shell. We should see a prefix to the shell like the following. Activate the virtualenv. We'll call our new virtualenv cyoa. That prefix helps us remember which virtualenv is currently active.

For example we could run the Python interpreter within that virtualenv by running the following command. Our virtualenv is only activated for the shell we explicitly activate it for. Copy the template. Fill in the following necessary environment variables in the new.

Invoke the environment variables by running the shell script on the command line from the cyoa base directory. Enter the following command at the PostgreSQL prompt and we'll now see that tables have been created in the database for our application. Syncing the Database Schema 1. No output is likely a good sign that the tables created without a problem.

Connect to PostgreSQL with the deployer user. Our database is ready for table creation. If you want to finish off the manual application deployment and populate some of the initial database data. Run the following command to create a user with a username and password of your choice. Handles application dependencies and environment variables Also syncs the application with the database schema. Fill in the following lines. Ensure you created the file in the templates directory and not under tasks like the file we just created in the previous step.

Create a new file named dependencies. Fill in the following lines in the new file. Environment variables for our deployment are set in the Supervisor configuration file instead. Run our Ansible playbook again with our shell script to install the application dependencies.

Additional Application Dependency Resources Application dependencies can be annoying to install on your production server when you just want to get your app up and running.

This provides one perspective on that debate. This chapter walked you through the basic steps for making that happen and automating it in future deployments. Python Package Resources It's useful to browse through these lists in case you come across a library to solve a problem by reusing the code instead of writing it all yourself. A few of the best collections of Python libraries are: In the late s. For several years in the late s and early s. It was just an implementation that allowed Python code to run on a server.

What is WSGI? Traditional web servers such as Apache and Nginx do not understand or have any way to run Python. Flask or Bottle then your application can be deployed in the same way as the Choose Your Own Adventure Presentations application. The following are WSGI servers based on community recommendations. WSGI is now the accepted approach for running Python web applications.

Therefore the Python community came up with WSGI as a standard interface that modules and containers could implement. Our virtualenv active prompt should show up on the command line. In my case. If we see the following screen. Fortunately gunicorn is specified as a dependency in our requirements. Change into the cyoa project directory. Activate the virtualenv if it is not already enabled.

Start up gunicorn manually to ensure the web application is working. Activate our environment variables for the application.

Then we just need to create a configuration file and start the supervisor process once to get it up and running. Install the supervisor package via apt on our remote machine. Supervisor is not yet installed on the system so we need to obtain it via a system package. Start Supervisor with the following command. Save the file and exit. We will fix the no users issue in the next section. Our App is Live! Our app should be up and running at the URL we specified now. If that screen shows up.

Go to http: Automating Gunicorn Setup 1. Sets up and configures Supervisor which runs Green Unicorn. Important note: In order to handle asynchronous background tasks. Task Queue Our application is up and running. As of September WSGI v1. Note that the post is a few years old. Benchmarks should be considered for their specific tested scenarios and not quickly extrapolated as general "this server is definitely faster than this other server" results. In this chapter we'll set up a particular task queue.

We'll connect Celery to Redis. What Are Task Queues For? Tasks are handled asynchronously either because they are not initiated by an HTTP request or because they are long-running jobs that would dramatically reduce the performance of an HTTP response. Another example is when a database query would take too long during the HTTP request-response cycle. The intro post contains information on design decisions and how to use RQ. The query could be performed in the background on a fixed interval with the results stored in the database.

When an HTTP request comes in that needs those results a query would simply fetch the pre-calculated result instead of re- executing the longer query.

The other task queue projects that arise tend to come from the perspective that Celery is overly complicated for simple use cases. My recommendation is to put the effort into Celery's reasonable learning curve as it is worth the time it takes to understand how to use the project. RQ is backed by Redis and is designed to have a low barrier to entry.

Supervisor will run both the celery command. For numeric values. Configuring Celery To set up our task queue Celery. Log into your production server. As with previous chapter. Let's set up Celery manually now. Pause just a moment to make sure Supervisor is completely stopped. Stop Supervisor. Start Supervisor so the new configuration files take effect. Automating Celery Installation We can add a few files to our Ansible playbook to automate the task queue configuration. Create two new templates for Supervisor.

PDFs Sets up and configures Supervisor for Celery and Celerybeat. Re-run our Ansible playbook with our shell script from the base directory of our deployment project. Next up we will use our Ansible playbooks to automate the entire deployment to production whenever code is committed and pushed to the master branch of our repository on GitHub.

Additional Task Queue Resources Task queues are critical for creating performant web applications by shifting workloads into the background instead of trying to handle everything during the HTTP request-response cycle. Here are more resources for learning about task queue concepts. The task queues are not all compatible with Python but ones that work with it are tagged with the "Python" keyword.

Additional Celery Resources Celery is a fantastic open source implementation of task queues. Here are few further resources on when and when not to use Celery in your projects. Part One and Part Two are great reads for understanding the difference between a task queue and why you shouldn't use your database as one.

Best Practices explains things you should not do with Celery and shows some underused features for making task queues easier to work with. Continuous Integration Continuous integration CI automates building. CI combined with unit and integration tests check that code modifications do not break existing tests ensure the software works as intended. When CI is set up well it can dramatically reduce deployment times by eliminating manual steps and ensure code does not have bugs that are being checked by automated tests.

Source code changes as a project evolves. Jenkins is widely used and open source. The continuous integration and deployment environment we set up will look like the following diagram.

Jenkins will pull the latest code from GitHub. When we push changes to our remote source control repository on GitHub. Execute the following command on your local machine to create a new public-private key pair just for the continuous integration server.

In a larger environment continuous integration would typically deploy the newest code to a test server for some manual checks before going to production. Modify line 77 in fabfile. Obtain a new separate server on Linode. As with our previous keys. We will not use a passphrase for the Jenkins server user's keys. We provisioned our Linode production server all the way back in chapter 2 so you may want to review those steps if you run into trouble.

Copy the fabfile Modify the values in the script with the new IP address. The public key can be shared with anyone and does not need to be kept secret. Edit the IP address found on line 21 of fabfile. Edit line 35 in fabfile. Execute the following command to create a new file with the newly created key as an authorized key.

To guide deployments pdf stack full python

SSH into the continuous integration server with the new user. Run the copied Fabric file with the following command. Now we need to actually get Jenkins up and running on the server. Currently Ansible asks for the sudo password of the deployer user when we execute the playbook. In the above Ansible variables file. Test out the script locally by setting an environment variable with the password to the remote deployer user.

This is a much better security practice than keeping plaintext passwords in the variables file itself. We're ready to update the available packages list and install our jenkins package. We need to install Jenkins.

Add the new package repository into our source. Now that we're logged in make sure the necessary packages are installed on this server. We need to secure the installation so only we can use it. You should see a screen like this one. Once the package installations finish start up Jenkins as a system service. Securing Jenkins with Authentication Jenkins is open to the whole world until we secure it.

Add the GitHub OAuth plugin. Go to https: Install the plugins and click for Jenkins to restart. Add the GitHub plugin. Set up a new application for Jenkins on the GitHub screen. Fill in http: Log in and out of Jenkins to confirm that a logged out user cannot access anything inside the application and is simply redirected to GitHub to determine if she should have access to this Jenkins CI user interface.

This deploy key will grant read-only access from the Jenkins server to the forked repository that we want to use the commands git clone and git pull to grab our code. Execute the following command to create a new key pair. When prompted for a file in which to save the keys you can use the default values. Creating a CI Deploy Key We need to create one more deploy key separate from the production server deploy key and the other private keys we use to log into the server. If the directory already exists you can ignore the error message.

Make sure you are in the jenkins home directory to execute the following commands. Log back into the Jenkins server via SSH. Change over to the jenkins user. On the remote server create a new directory for our SSH keys. Press the "Add deploy key" button. We just need to put the public key into GitHub so they function as deploy keys. There are a couple of ways to do this. Next we need to load our Ansible playbook onto the Jenkins CI server so the jenkins user can access them. The first option is to use the secure copy command from your local machine to put the automation files onto the server.

Back on the server as the Jenkins user. Run these commands from your local machine and make sure to replace the IP address with the IP address of your Jenkins machine. Test out the Ansible playbook while logged into the jenkins user. For testing purposes. Create a virtualenv for the Jenkins account so it can use Fabric and Ansible to perform the deployment.

The other option is to clone the Ansible playbook automated deployment repository. When you get the Ansible playbook on the continuous integration server.

ECDSA key fingerprint is 7a: Click Save and the project settings will immediately take effect. Push Some New Code Modify some code in your local project. Click the build button on the dashboard to kick off a new build. Go Ahead. If the build is successful.

Full service automated deployment by the Jenkins continuous integration server is complete! There are many directions this book can continue to expand into and your feedback is valuable for making sure the right content for the community is written.

For more future directions. It's written in Python and intended for development teams that want more control over their build and deployment pipeline. Hosted CI Services If you want to skip setting up your own continuous integration server.

They make setting up CI on one or more projects easier than deploying your own Jenkins instance. It's free for public repositories. The BuildBot source code is on GitHub as well. These articles should give you further insight into CI and where you could take the infrastructure from here. Additional Continuous Integration Resources The CI set up we created in this chapter is just the beginning for deployment automation.

Illustrated uses well done drawings to show how continuous integration and delivery works for testing and managing data. Our deployment is now automated and runs continuously whenever code is committed and pushed into the remote Git repository.

Deployment Enhancements Our deployment process right now is simple. Yet there are a whole bunch of ways to make it better by incorporating additional steps into the Ansible playbook.

Most large-scale web application deployments use a suite of further techniques that increase the capabilities of their infrastructure. Here are several possibilities for scaling up server and application performance: What content would you like to see added to the book? Send me an email at matthew. All updates to this book will be available for free to current purchasers. Continuous integration server implementations include Jenkins. TeamCity and Go. Continuous integration Continuous integration is the concept of building and testing code upon every change a developer checks into version control.

The theory is that if code is not integrated together until the end of the project. Application dependencies Application dependencies are the libraries other than your own project code that are required to create and run your application. These dependencies are referenced in a requirements. Glossary This glossary provides plain language definitions of the concepts found throughout this book. Some deployments are just to a development server for fellow developers to test their code.

Cassandra and HBase. The last stage in a deployment is usually to one or more production servers that host the canonical version of an application. Flask Flask is a Python web framework created with a small core and easy-to-extend philosophy. Flask pieces together several open source projects.

There are many types of NoSQL database implementations. Jinja2 and SQLAlchemy for relational database object-relational mapping to make it easier to build WSGI-compatible web applications with the framework. Flask is the web framework used by the Choose Your Own Adventure Presentations example application deployed throughout this book. PyPI is There can be many environments for development and testing.

Production server A production server or production environment hosts the canonical version of the running code for your application. PostgreSQL is the primary data storage backend for the application.

Pip is often used with a requirements. In this book. The work performed by a task queue would often take too long to process when a HTTP request came in or would need to be performed on a regular interval and are not initiated by HTTP requests. Mercurial and Subversion. Source control Source control. Examples of source control implementations include Git. Source control systems allow developers to modify code without worrying about permanently screwing something up.

Python task queue implementations include Celery. Unwanted changes can be easily rolled back to previous working versions of the code. RQ and Taskmaster. Task queue A task queue is a concept for a piece of software that executes work in the background outside the HTTP request-response cycle of a web application.

Web frameworks take care of common web development issues. Web framework Web frameworks are code libraries that make it easier to build web applications. URL routing. The web framework implementation in this book is Flask. Nginx serves static and provides a reverse proxy. Other common Python-based web frameworks include Django. Pyramid and Morepath. The web server implementation used in this book is Nginx.

The virtualenv creates a separate copy of the Python installation that is clean of existing code libraries and provides a directory for new application dependencies on a per- project basis a programmer can technically use a virtualenv for many projects at once but that practice is discouraged. The interface was created to promote web application portability between different WSGI server implementations such as Green Unicorn.

Developers learning Python as a second or later language should skip down to the next section for "experienced developers". More Python Resources This appendix wraps up the book with a collection of the best Python resources I've found.

There's so many resources out there though that it can be difficult to know how to find them. This chapter aggregates the best Python resources with a brief description of its one's learning purpose. Many of these resources are free and the ones that cost money are well worth the investment to purchase them. The Best Python Resources The Python community is amazing at sharing detailed resources and helping beginners learn to program with the language.

New to Programming If you're learning your first programming language these books were written with you in mind. In those cases it makes sense to use resources that spend less words on computer science fundamentals and more effort on explaining the specifics of the Python syntax.

The following resources do a good job of teaching Python to those who already program in other other languages. It's a great introduction to web development concepts through coding. An Introduction provides context for virtual machines. The following resources are useful for understanding the broader ecosystem and more advanced subjects.

Python packaging. The guide is especially useful if you're coming in with previous software development experience and want to quickly grasp how the language is structured.

Screencasts and Presentations If you prefer to watch videos and screencasts instead of reading through more text. There are also slides available from the talk with all the diagrams. I typically prefer to learn by reading.

The talk slides are also available. Rather than you having to spend your time searching the web for these helpful resources. It's well worth subscribing to all three so you don't miss So far I've found this newsletter covers different sources from other newsletters.

The best resources are generally covered in both newsletters but they often cover different articles and projects from around the web. Newsletters Email newsletters are good for keeping up with the latest open source projects and articles.

Curated Python Packages Lists The following Git repositories aggregate open source libraries into categories. Note that this tutorial will take you up to the tutorial-step-6 tag but I kept working on the project so for this book you should use the master branch for the deployment. App Code Tutorial This chapter is a streamlined version of the original code tutorial for the example application we deployed in this book.

Going through this appendix is not required to do the deployment in this book. This Choose Your Own Adventure Presentations Flask web app provides a reasonable example for deployment because it is open source and relies on many widely used web application technologies such as PostgreSQL.

WebSockets and Green Unicorn. If you decide to build a childhood nostalgia-packed Choose Your Own Adventure presentation. If you choose to create another passe linear slide deck. Our final product will have decision screens like the following screenshot where SMS votes from the audience are counted and displayed in real-time to determine the next step in the presentation story.

Once Our base directory name and Flask app directory name will be cyoa. Check out this open source repository on GitHub. The Git repository contains the final code as well as intermediate tags named tutorial-step The nested subdirectories will look like the following screenshot.

The Flask-Script extension will assist us in creating a manage. The Flask-SocketIO extension handles the server-side websockets communication.

Setting up environment variables depends on your operating system. There are guides for every major operating system. Mac OS X or Windows. The Redis and Twilio environment variables will be set in the next section. If a matching file is found. An HTML template file along with some static files are necessary for displaying the presentation.

Create a Reveal. If no file name matches the presentation name in the URL. Add the following HTML inside this file. Download these files from GitHub or download and extract this cyoa. Fire up Flask with the following command. Sign up for Ngrok and download the Ngrok tunneling application. Now we can view the initial version of the presentation by going to http: Fire up ngrok on port where our Flask application is running.

Flask will find the cyoa. Take note of the unique https: Now we need a way for the audience to vote on which path they want the presentation to go. The Twilio number screen should look like the following. Paste in your Ngrok forwarding URL. Ensure that the Redis server is installed on your system since that will be our temporary vote storage system.

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First we need to ensure Redis is running and write Python code to persist votes to it. Look for the line like the following and replace it with your Twilio number. At this point those inbound text message votes are also being stored in Redis. In our presentation that allows the vote counts to be updated on the presentation slide as soon as the server emits a new message. Websockets allow streams of communication between the client and server.

Adding WebSockets for Real-time Updates We need one more new Python file to handle the server-side websockets communication. This code relies on the websockets JavaScript library and JQuery that was included with the file when we originally created it.

Choose Your Own Adventure Presentations: Check out http: Wrapping it up You now have a Flask app that can serve up Reveal. A sign lies in the road ahead. Think of it as an administrative interface that grants you. If you accept the challenge. The interface will only be accessible by authorized wizards through the sign-in page which will look like the following screenshot. How do you proceed? If you choose to run from the PyCon challenge. PostgreSQL and several additional Python libraries.

Wizards Only: There are three posts in this tutorial series where we will incrementally build out functionality: Voting with a Wand. Even Wizards Need Web Forms: First though we need a way to sort wizards from non-wizards in the form of a sign-in screen. Update the requirements. These new libraries are highlighted below. Create a new file named models.

String Column db. The login manager will allow us to control access to wizard settings. The file should have the following contents: We need to configure where the database is located in a configuration parameter so our SQLAlchemy database loads properly. Make sure you have PostgreSQL installed on your system. Our new configuration variable will reside in our config.

In our original Choose Your Own Adventure Presentations blog post we set the other environment variables listed in the above config. In our application the Flask- WTF library is going to handle form generation and input sanitization. Create a new file named forms. The above code creates a Python representation of the sign-in page form. If the form input passes the validation function then True is returned and the form processing continues along in our views. There are three additional functions:.

We have the code to run the app but there are no templates to render yet. There are a few extra styles and a background image we will include in our app. Our sign-in page and our wizard landing page will both extend base. Change the existing manage. On the command line create PostgreSQL database using this command: Start up the shell and enter the following code to create and save a wizard. Now we can authenticate as a wizard with the name and password we just added to the database.

Within the base directory of our application run the built-in server using the following command: You can modify the credentials as you see fit. Wizard Mode Part 2 of 3 In the first part of our Choose Your Own Adventure Presentations Wizard Mode tutorial we set up the necessary code for separating authorized wizards from non- wizards. In part two of the Wizard Mode tutorial. Note that if you make a typo somewhere along the way in this section.

Time to get coding and create our Wizards Only mode. Next up we need to modify the temporary markup in the landing page template file so it displays the presentations we will create through the Wizards Only user interface. You should see the unchanged Wizards Only sign in page.

Log in with your existing Wizard credentials created in part 1. If one or more presentation objects do exist.

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From the base directory of our project. If not. Occasionally there are issues installing the required gevent library the first time the dependencies are obtained via pip. Open http: Make sure your virtualenv is activated and environment variables are set as we established in part 1 of the tutorial. When you get into the application. Creating and Modifying Presentation Metadata We built a page to display all presentations to logged in Wizards.

Length 1. Just like with our Wizard model. We also need a new form to handle the creating and editing of presentation metadata. In other words. Now that we have presentations in the database. Now we need to tie together our new Presentation database model and PresentationForm form. Add the following HTML template within the new file: Bring up the application with the runserver command.

Run the following manage. You should again see the unchanged Wizards Only sign in page. At the presentations landing screen after signing in. Use your wizard credentials to sign in.

We can edit existing presentations by clicking on the links within the Name column. The presentations can still be accessed from the same URL as before. Listing Available Presentations There have been a slew of code changes in this blog post.

Otherwise an HTTP status code is returned. The second function. Add the following line as a new import to the top of the file so that our new code can use the Presentation database model for the queries in the functions we just wrote: Check out the simple listing of presentations available to the audience. We will write code to keep track of audience votes from web browsers using All Prepared for Part 3! We now have a working Wizards Only set of screens for managing our presentations.

Wizard Mode Part 3 of 3 with Flask. Each presentation has a checkbox to enable websockets-based voting to complement SMS voting. In part three of this series. The Manage choices link takes the wizard user to a new screen where decisions that have been created can be edited. After we write the code in this section and fire up our development server. Manage Decisions View We need to create new Wizards Only screens to set up the web browser voting when we want to enable it for presentations.

When we create a presentation there will be an option to manage web browser-based voting as shown above. The Decision model will hold the slugs to the webpages that will allow someone in the audience to vote on a decision. Add the new line to Presentation and create the new Decision model as shown below. Decisions can be created and saved via the simple form as seen below. Must map directly into what is stored in Redis. ForeignKey 'presentations. EqualTo from wtforms import ValidationError from.

The new models code above allows us to save and manipulate web browser-based decisions that can be associated with specific presentations. IntegerField from wtforms. In part two of our tutorial. Regexp '[a-z] '. No spaces. Make sure to remove the pass keyword from the body of those functions and insert the highlighted code shown below. Decision from. These are standard operations for an administrative interface that any self-respecting wizard would expect.

Now we need to create some new templates to generate the HTML for our decision screens. We added code to list. There also needs to be a template file for creating new decisions and editing existing ones. Create the new Decision database table by running the following command at the base directory of our project.

To accomplish that we have to Although we created the new Decision table with the syncdb command. If there are existing presentations in your application. Head to http: So far so good. How do we fix this problem? We need to ensure the Presentation table has the appropriate column in the database. It looks like the new foreign key relationship in thePresentation table is causing a database error.

Kill the development server process with Ctrl-C and execute the following commands to recreate the PostgreSQL database. Note that unfortunately the existing wizards and presentations in the database will be deleted when we blow away the database so we will also walk through recreating them. Those votes are calculated just like SMS votes as long as the user stays on the page. Note however one downside of the web browser-based voting is that the websocket connection may not be immediately recognized as closed.

These decision pages allow an audience member to vote by clicking one of two buttons on a page and staying on the voting page. An active websocket connection increments the vote counter for that choice in Redis and when a user leaves the page the websocket connection is cleaned up and the Redis value for that choice is decremented.

It can take a few seconds before the websocket is cleaned up and the vote counter decremented. To accomplish this task. Next create a decision point using the new code we wrote in this tutorial. This decision will allow the audience to vote with their web browser. Create a decision like the following and save it. Select one of the two options on the screen and your vote will be tallied along with any other browser and SMS-based votes. Click the link in the rightmost column to view the new decision.

With our battle-ready upgrades. We now have far more control over presentations and a new mechanism for audience voting via web browsers in addition to SMS. Contact me via: Wizard Mode Engaged! Our Wizard Mode is complete. In fact. Flag for inappropriate content. Related titles. Alboukadel Kassambara - ggplot2: Jump to Page. Search inside document. Copyright Matthew Makai. All rights reserved. Revision History Typo and link fixes throughout the book.

First edition. Initial release. There are several scenarios that seem ripe for updates: Write new content and chapters to expand the deployment in the book. Fix or clarify issues with the walkthrough based on community feedback.

Web Servers in Our Deployment The web server in our deployment will perform two roles: Handle requests for static files and respond with appropriate files 2. Please make sure you have the correct access rights and the repository exists. Now the repository is stored on the production server.

Full Stack Python Guide to Deployments

Exit out of the psql prompt by pressing CTRL-d. Log off the postgres user by again pressing CTRL-d. Now let's try out our PostgreSQL connection with the deployer user. Key-value pair 2. Document-oriented 3. Column-family table 4. Graph These persistent data storage representations are commonly used to augment, rather than completely replace, relational databases. There are three additional functions: John James.

Jaime Rangel Ojeda. David Cantrell. Tom Leslie. Heart Fragile.

Anonymous P2ZN8X. Yusuf Parak. Addison-Wesley Node.