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flask-todoapp

The example TODOapp developed using Flask, Vertabelo, SQLAlchemy and Bootstrap.

flask-todolist

exemplary flask application - small to-do list WebApp example

flask-todomvc

Flask tutorial buiding on Backbone TodoMVC.

flask-track-usage

Basic metrics tracking for the Flask framework.

flask-tracking

Tracking app for Flask that logs HTTP request and response information in a capped MongoDB collection

flask-website

The Flask website, built with Flask!

flask_api

Creating a Machine Learning API using Flask - Repository for AV Article

flask_ishuhui

Comic reading website built by flask.

flask_video__client_server_resize-pic

AnyVision Dev. Interview Task You should spend 1-2 hours on this task. Code should be written in python. You may use 3rd party libraries as needed. Scenario: You need to provide a service that can resize images. By service, we mean that independent software client processes should be able can ‘connect’ to the service in some way. These clients may be local (on the same machine), or (for extra points), your service could allow connections from a mixture of both local and remote clients. Note that the service should process images (single video frames), not complete videos. The service needs to scale so that many clients can use it concurrently. You might consider using message/task system architectures scale your service via distributed processing. It must be possible for multiple requests to be processed concurrently and all computational resources available should be utilised. You should try to make use of the system’s GPUs if possible. To test your service you should create a test program that uses your service to concurrently resize N instances of a video, where N is passed as a command line argument to the test application. Note we are using N instances of the same video for simplicity, in reality it would be N different videos. The scaling of each video instance should start M seconds after the previous. For example, if N = 2 and M = 10, you test should start using your service to process one instance of the video immediately, and 10 seconds later it should start using your service to process the second instance. The values of N and M will be passed as command line parameters, as will the video path. Split the video into frames and make multiple calls to your service. The test program should create N sets of output frames, saved to disk as images, e.g. /tmp/vid-instance1/Frame00001.jpg /tmp/vid-instance1/Frame00002.jpg /tmp/vid-instance1/Frame00003.jpg /tmp/vid-instance2/Frame00001.jpg /tmp/vid-instance2/Frame00002.jpg /tmp/vid-instance2/Frame00003.jpg … and so on. You should write the re-sized images to disk as soon as they have been processed (as opposed to converting all frames and then writing them to disk at the end). Make your test report runtime metrics including the frame-rate of the conversion (a running average) for each video instance, report when each video instance has been completely converted, and display the total amount of time taken for each instance. Remember, a key requirement is to process all data as quickly as possible. You will be expected to talk through your approach, explain it’s advantages and limitations, discuss what other options you considered, and what other approaches could be considered in the future. Tip: Focus on all elements of the problem – try not to get bogged down on one particular bit. It is more important to show how you tackled the problem and what solutions you have come up with rather than having 100% running code covering all aspects – although that obviously helps :). Manage your time. Please ask for any clarifications as needed.

flask_weather

☀️ ☔️ Flask app to auto-detect local weather based off of user's IP address.

flaskapiecommerce

Python Ecommerce Api application built with Flask + Flask SQlAlchemy

flaskdatingwebapplication

Software Engineering CUS1166

flasklocator

Python Geolocator, Ip Tracker, Device Info by URL (Ngrok Hosting)

flaskmvaapp

Sample app with Flask, SQL Server and Redis. Tutorial is from a youtube video called Creating Websites using SQL, Python and Flask 2016

flaskshope

testing e-commerce

flasktodo

Example of using Flask on App Engine to make a simple todo list.

food-tracker-app

Food Tracker App: python-flask-sqlite based app to trace the calories you can consume at a particular date

fortnite-health-tracker

A python application that tracks your health in fortnite that has an optional nerf gun shooting flask server.

freecodecamp

freeCodeCamp.org's open source codebase and curriculum. Learn to code at home.

go

The Open Source Data Science Masters

hellin-worki

A video conferencing platform which seamlessly dials your coworkers when you call out their name, a "Yes" and you are connected.

hookups-rebooted

A modern rewrite of the classic Hookups💋 app

how-to-build-a-chatbot

Learn to build a facebook chatbot using Python and Flask

httpbin

HTTP Request & Response Service, written in Python + Flask.

inventory-management-system

Insanely lightweight Inventory tracker

ireporter2

iReporter enables any/every citizen to bring any form of corruption to the notice of appropriate authorities and the general public. Users can also report on things that needs government intervention. Corruption is a huge bane to Africa’s development. African countries must develop novel and localised solutions that will curb this menace, hence the birth of iReporter. ### Features 1. Users can create an account and log in. 2. Users can create a red-flag record (An incident linked to corruption). 3. Users can create intervention record (a call for a government agency to intervene e.g repair bad road sections, collapsed bridges, flooding e.t.c). 4. Users can edit their red-flag or intervention records. 5. Users can delete their red-flag or intervention records. 6. Users can add geolocation (Lat Long Coordinates) to their red-flag or intervention records . 7. Users can change the geolocation (Lat Long Coordinates) attached to their red-flag or intervention records . 8. Admin can change the status of a record to either under investigation, rejected (in the event of a false claim) or resolved (in the event that the claim has been investigated and resolved) . Optional Features 1. Users can add images to their red-flag or intervention records, to support their claims. 2. Users can add videos to their red-flag or intervention records, to support their claims. 3. The application should display a Google Map with Marker showing the red-flag or intervention location. 4. The user gets real-time email notification when Admin changes the status of their record. 5. The user gets real-time SMS notification when Admin changes the status of their record. ## Built With * HTML, CSS, Javascript * Python, Flask APIs * Postgres SQL ## Tools Used * Pivotal Tracker * github * Postman * Heroku ## Version v1.0 ## Authors * **Baker Sentamu** ## iReporter Demo UI Link ## Acknowledgments * Andela Learning Facilitators

issue-tracker-flask

maple-blog

a blog website based on flask

matcha-wtc

A dating app for wethinkcode

me

Personal website powered by Flask, supports GAE, SAE and BAE.