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Category: Python

Canceling a Power BI Dataflow Gen2 Refresh

Published 2024-01-12 by Kevin Feasel

Sandeep Pawar has a script for us:

At the time of writing this blog, it is not possible to cancel a Dataflow Gen2 (DFg2) refresh using the UI. This is a temporary limitation that I expect will be resolved soon. DFg2 can be resource intensive, and if the refresh takes longer than expected, it may consume a significant amount of CUs. Thankfully, you can use the Power BI Rest API to cancel it. My friend Alex Powers already has a PowerShell script that you can use. You can also use the Power BI VS Code extension by Gerhard Brueckl.

But I would like to show you how you can do this using the PowerBIRestClient in the latest version of Semantic-Link (v0.5.0).

Read on to see what this Python script does and how you can use it.

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An Overview of Polars

Published 2024-01-04 by Kevin Feasel

Dylan Jones talks about a Rust-based data frame library:

Polars is a high-performance DataFrame library implemented in Rust, and can be used with Rust natively or via its Python wrapper. It is designed to handle large datasets with ease, providing an user-friendly interface for data manipulation and analysis. The library offers two modules: polars-core for the core functionality, and polars-io for input/output operations, allowing you to read and write data in various formats such as CSV, JSON, Parquet, Delta and more.

Read on to see how it works in Python compared to Pandas, as well as some speed comparisons.

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Notes on Linear Markov Chains

Published 2024-01-02 by Kevin Feasel

John Mount has some thoughts for us:

I want to collect some “great things to know about linear Markov chains.”

For this note we are working with a Markov chain on states that are the integers 0 through k (k > 0). A Markov chain is an iterative random process with time tracked as an increasing integer t, and the next state of the chain depending only on the current (soon to be previous) state. For our linear Markov chain the only possible next states from state i are: i (called a “self loop” when present), i+1 (called up or right), and i-1 (called down or left). In no case does the chain progress below 0 or above k.

Click through for notes on two variants of this sort of linear Markov chain, as well as a pair of appendices containing derivation notes and Python code.

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Making REST API Calls against Microsoft Fabric

Published 2023-12-21 by Kevin Feasel

Sandeep Pawar digs into the REST API:

Accessing Fabric REST endpoints in Fabric notebooks was already easy but it became easier and straightforward with semantic-link version 0.4.0. You can use the FabricRestClient class from sempy to set up a REST client and call the APIs. Authentication is automatically managed for you.

Click through to see how it works, as well as some warnings or things to keep in mind along the way.

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Creating Charts in Microsoft Fabric Notebooks using Vega

Published 2023-12-14 by Kevin Feasel

Phil Seamark tries out Vega in a Microsoft Fabric notebook:

I recently needed to generate a quick visual inside a Microsoft Fabric notebook. After a little internet searching, I found there are many good quality charting libraries in Python, however it was going to take too long to figure out how to create a very specific type of chart.

This is where Vega came to the rescue. The purpose of this short article is to share a very simple implementation of generating a Vega chart using a Microsoft Fabric notebook.

Click through for the example code.

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Accessing PostgreSQL from Python

Published 2023-12-06 by Kevin Feasel

Semab Tariq connects to Postgres:

Psycopg2, a PostgreSQL adapter for Python, implements the Python Database API Specification v2.0, acting as a bridge between Python applications and PostgreSQL databases. It leverages the libpq library, the official PostgreSQL C interface, to facilitate efficient communication. Psycopg2 provides a robust set of features, including transaction management, and support for PostgreSQL-specific data types. Its implementation of the Python DB API ensures seamless integration, enabling developers to execute SQL queries and transactions with precision in Python applications.

Read on to see how it works using a variety of examples.

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Visualizing a Power BI Refresh with the semantic-link Library

Published 2023-12-06 by Kevin Feasel

Phil Seamark builds a notebook:

A few blogs back I shared a technique using Power BI Profiler (or VS Code) to run and capture a trace over a refresh of a Power BI semantic model (the object formally known as a dataset).

I’ve since received a lot of positive feedback from people saying how useful it was to visualize each internal step within a problematic Power BI refresh. Naturally, in the age of Fabric, I’m keen to share how the same approach works using a Microsoft Fabric Notebook.

Click through to see how you can do it.

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Scraping the Microsoft Fabric Road Map with Microsoft Fabric

Published 2023-11-28 by Kevin Feasel

Prathy Kamasani wants a report, not a webpage:

Like many I am also playing with Fabric, many of my clients are also excited about Fabric and want to know more about it. Being a solution architect in the consulting world one of the most common questions I get asked is: “When certain features will be available, Where are they in the roadmap?”. That’s what sparked the idea of scraping the Microsoft Fabric Roadmap and creating this Power BI report. It is based on a Direct Lake connection, so it has been a bit temperamental.

So, what did I do it? If you are not interested in the whole story. Here is Python code you can run to get a road map. If you are interested in my process carry on reading 

Click through for the process and explanation.

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Building an App with Streamlit

Published 2023-11-28 by Kevin Feasel

Riqo Chaar demonstrates Streamlit:

Off-the-shelf solutions for interactive data app development such as Microsoft Power BI are great – they allow users to easily develop data apps using a GUI. However, Power BI’s ease of use comes at the expense of reduced functionality. This is where programming languages such as Python, JavaScript or C# shine – you can practically code anything you like!

This blog will focus on Streamlit as a means of building interactive data apps. Streamlit is an open-source Python library that enables rapid creation of web apps (including, but not limited to, data apps) with minimal code. It acts as an intermediary between the easy-to-use, but functionally-limited characteristics of Power BI and the functionally-enhanced, but difficult-to-use characteristics of other programming tools such as JavaScript or C#.

I’ve grown to like Streamlit a lot. It’s really simple to put together a good-looking page, similar to Shiny in R.

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