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If you’re a current follower of this blog then you may already know that I’m a bit of a fan of using plain text accounting for managing finances.
I mainly use the Ledger text file format and CLI tool for bookkeeping and reporting on finances. This works great, and I can quickly and easily generate different kinds of reports using a range of simple Ledger commands.
For example, to generate a quick income/expenses balance sheet for a particular date range I can run ledger balance income expense -b 2022/03/01 -e 2022/03/31, which produces something along the lines of the following:
Many services - including web and mobile apps - allow for their users to upload imagery. This could be to enable users to upload an avatar image or perhaps create a gallery of image files.
Either way, many photos contain some degree of sensitive metadata information as part of their EXIF data. For example, if you take photos using your phone, it is likely that the camera application will embed metadata into the image file it creates. This could include the geocoordinates of the position from where the photo was taken, the make and model of the camera device, as well as lots of other data (exposure time, focus, balances, etc).
Python’s Flask framework is an easy and excellent tool for writing web applications. Its in-built features and ecosystem of supporting packages let you create extensible web APIs, handle data and form submissions, render HTML, handle websockets, set-up secure account-management, and much more.
It’s no wonder the framework is used by individuals, small teams and all the way through to large enterprise applications. A very simple, yet still viable, Flask app with a couple of endpoints looks as follows.
Over the last few months, I’ve started to use Weka more and more. Weka is a toolkit, written in Java, that I use to create models with which to make classifications on data sets.
It features a wide variety of different machine learning algorithms (although I’ve used the logistic regressions and Bayesian networks most) which can be trained on data in order to make classifications (or ‘predictions’) for sets of instances.
The Heroku Dev Center is a repository of guides and articles to provide support for those writing applications to be run on the Heroku platform.
I recently contributed an article for carrying out Direct to S3 File Uploads in Python, as I have previously used a very similar approach to interface with Amazon’s Simple Storage Service in one of my apps running on Heroku.
The approach discussed in the article focuses on avoiding as much server-side processing as possible, with the aim of preventing the app’s web dynos from becoming too tied up and unable to respond to further requests. This is done by using client-side JavaScript to asynchronously carry out the upload directly to S3 from the web browser. The only necessary server-side processing involves the generation of a temporarily-signed (using existing AWS credentials) request, which is returned to the browser in order to allow the JavaScript to successfully make the final PUT request.
I wanted a way in which users can seamlessly upload images for use in the Heroku application discussed in previous posts.
Ideally, the image would be uploaded through AJAX as part of a data-entry form, but without having to refresh the page or anything else that would disrupt the user’s experience. As far as I know, barebones JQuery does not support AJAX uploads, but this handy plugin does.
styled the file input nicely (in a similar way to this guy) and added the JS so that the upload is sent properly (and to the appropriate URL) when a change is detected to the input (i.e. the user does not need to click the ‘upload’ button to start the upload).