bms-tools VS plotly

The code in question: bms-tools.

In my learning journey I have come to realize that BMSes do exist and my silly setup is both redundant and not very good at keeping the battery safe. I found a smart BMS by a company called JBD that has several 3rd party libraries written for it, including the one I'm using by a fellow redditor here called /u/MrSurly. Here's a link to his BMS library. The BMS library allows me to communicate with the BMS using the RPi, I get information such as the voltage of each cell, current output, and more information. It also automatically stops the discharging when the battery is about to die.

You can use the BMS Tools Python library, but I'm biased, as I wrote this.

So, I went down a rabbit hole of creating an open-source app for the somewhat popular JBD / XiaoXiang BMS. I was messing about with the features provided by the somewhat clunky official Windows app, and tried to do a firmware update on the BMS, and promptly bricked it.

Thank you! Yeah, I've tried a variety of edits to the function call, it's from the backend of a very professionally done python package with the reverse-engineered protocol for this pretty ubiquitous type of BMS; It is very cleanly written but also broken out into a ton of little stepwise functions many of which I don't understand... Enum types, lots of decorators (@staticmethod, @serial.setter, @property) and dunder enter/exit's... but I get the gist of it, every time I ask it it to read data it opens the port, constructs the bytes for the read command, sends them over the port, then collects the response byte-by-byte, verifies the final checksum byte, if ok then converts the payload to a dict otherwise raises an exception, and finally returns the data dict.

The serial protocol is now available here: https://gitlab.com/bms-tools/bms-tools/-/blob/master/JBD_REGISTER_MAP.md

Hey, here's the v1.1.0 release page -- should fix that issue.

Github: https://github.com/plotly/plotly.py

First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.

my good dude wake up and smell the plotly. Knowing the ins and outs of matplotlib is helpful but doing interactive stuff with jupyter I always use plotly.

Plotly documentation (https://plotly.com/python/)

I don´t know your workflow, but I use 2 markdown based presentations: obsidian advance slides and Quarto presentations. The former is a plugin for Obsidian, which is the software I use to take all my notes, write my thesis, etc., so It makes it extremely easy to make presentations since all my information is in Obsidian. In the other hand, Quarto is a publishing system (articles, presentations, websites books) that can be easily integrated with python and R. This makes it supper convenient for showing my data to my PI since I can analyze my data and at the same time make a presentation for the data. Besides this, Quarto also integrates with my Zotero library, so I can insert citations. Lastly, one thing that made my Quarto presentations infinitely better that the powerpoints, Is that I can insert interactive graphs with plotly, so when I'm showing my data, my PI is able to explore the data inside the presentation.

Plotly GitHub repository: https://github.com/plotly/plotly.py

I'm using plotly.py now. This is why I love this community.

Depending on the nature of your reporting requirements, you could output a formatted Excel document with Python and a library such as openpyxl, and shove that into your SharePoint environment. This would be less dynamic than PBI reports can be, but may be sufficient. If you want viz as well, you can use something like ggplot or Plotly. Again, less dynamic than PBI for the same effort.