This repo contains some of the examples applications using python flask server. To run the python files:
1. Open your terminal
2. Navigate to the current directory
3. Make sure you have installed all the requirements . If not, most modules can be downloaded via
pip install module_name
But make sure you have installed pip before. The manual for installation can be found here
4. Run the python script by typing:
python filename.py
5. The host url and port number can be found in the terminal if the server starts correctly. They can also be found in the source code of the corresponding python file.
6. Navigate to your browser and type the host url and the port number to see the result of script.
7. The folder 'outputs' contains a demo file 'data.csv' which is used for the purpose of demonstrating the download.py script.
8. The folder 'templates' contains the corresponding html files which will be rendered depending upon the script running.
9. The folder 'uploads' is the directory where the files that are uploaded in the 'file.py' are stored.
10. The folder 'Matplotlib_with_flask' consists of files that make use of matplotlib to render plots via flask.
11. The folder 'plotly' contains various sub-directories which have python files making use of plotly to plot the graphs. It also contains a folder named 'Python dashboard' which makes use of plotly along with a template provided by keen.io to make the dashboard. Just click on the index.html and view it in your local browser. A video of its demo can be found here.
12. The folder 'keen' contains two sub-directories. The 'js' subdirectory consists of js files that contain the codes for recording events and plotting. It is in essence, an implementation of the API for visualisation of data. The 'dashboard_sample' subdirectory consists of a sample dashboard that makes use keen API with bootstrap.

Important
13. The folder 'Prototypes_v0.9' contains:
7 directories in total which target various features of a prototype. The directory type7FFT is a very important one as it makes use of the features present in the above 6 directories as well as it has its features of its own. All of the prototypes do make use of matplotlib along with flask. A demo video of the prototype under this directory type7FFT can be found here.

More Important
14. The folder 'FFT-type-Prototype' contains:
This makes use of again a visualisation interface similar to that of the prototype described in the 11th point. However, here, an additional package for Machine Learning is astronomy namely AstroML has been used to plot various functionalities. It just represents the functionality and its functioning can be combined with that of prototype mentioned earlier to achieve an efficient tool. To run the files in this directory, install all the packages associated with AstroML. The installation link is this. Once all the packages are installed, just open the terminal, navigate to the current directory, and type python app.py. Then open your browser pointing at 127.0.0.1:5000
The demo video for this prototype can be found here.