The Bit Bucket

I recently received a review copy of Python for Algorithmic Trading Cookbook (2nd Edition): Recipes for designing, building, and deploying algorithmic trading strategies with Python by Jason Strimpel from my friends at PackT.

Author

Jason Strimpel is the founder of PyQuant News, co-founder of Quant Science, and Managing Director of Global AI and Advanced Analytics at a top-tier consulting firm.

Content

This book is an ambitious, highly practical guide to building the complete research-to-execution workflow for systematic trading. It treats algorithmic trading as an engineering discipline involving data acquisition, storage, analysis, backtesting, risk measurement, execution, and deployment. I was surprised by the breadth of modern tools that are discussed: 68 recipes, 51 Jupyter notebooks, 17 modular trading applications, and four GPU-focused scripts.

2026-08-08

In real-time systems, reliability and resilience are essential. Unlike batch workloads, where you can retry a job later, streaming pipelines are continuous — they must keep running even when parts of the system fail.

The first design principle is to ensure that streams keep flowing.

That often means building redundancy into both your data sources and destinations. For example, you might configure multiple input connections or have failover routes so that data can still be processed if one stream or endpoint goes offline.

2026-08-07

I recently posted about rebuilding clustered columnstore indexes when they needed maintenance . One of the questions that a reader asked was:

Which is best in performance and CCI packing for fast query:

• Truncate table, drop CCI, insert data, create CCI.
• Truncate table, insert data and therefore keep CCI.

And of course, that’s a great question. Here are the issues:

If I had to just pick one of those, for best query performance and best CCI packing, the first option is usually better:

2026-08-06

When designing a real-time architecture, scalability is one of the most important considerations. Real-time systems must handle both high volume and high velocity, which means designing for continuous data flow rather than occasional spikes.

One of the key strategies for scale is partitioning. Partitioning divides the event stream into multiple independent segments, allowing processing to happen in parallel. This is essential when you have large numbers of events arriving simultaneously — for example, telemetry from thousands of IoT devices or transaction logs from multiple systems. The more effectively you partition your data, the better you can distribute the workload across compute resources.

2026-08-05

There is an endless discussion in the development community about whether databases should include declared foreign key constraints or not.

As a consultant, I regularly visit a wide variety of client sites. Many of these have applications designed without constraints. When I ask why there are no constraints, the response is invariably one of the following:

• We don’t need them because the app ensures that it’s right
• They don’t work well with our application development
• They are too slow
• What’s a foreign key constraint?

Most of the sites that I work with have sizeable databases. This discussion is important in those situations.

2026-08-04

Once Activator is running, you’ll want to monitor how your triggers behave and manage them effectively.

Each time a rule condition is met, Activator generates a trigger event. These can be viewed in the monitoring interface, where you’ll see a history of rule activations, timestamps, and outcomes.

Monitoring this activity helps confirm that your rules are working as intended — and also lets you catch unexpected behavior, such as overly frequent triggers or false positives.

2026-08-03

Even more SQL love !

Another popular SQL dialect is for Google BigQuery. And we’ve just completed our first course using it.

Creating reports, analytics, or applications? And need to get data out of Google BigQuery? Learn to write SQL queries like a pro !

We now have very popular SQL courses, for all the most important SQL dialects. There’s our flagship course for T-SQL, then already courses for PostgreSQL, Snowflake, Oracle, DB2, MySQL, and Azure HorizonDB. We’ve just added our new course Writing SQL Queries for BigQuery and you can enrol in it now. It’s just $95 USD.

2026-08-02

While Activator supports many types of actions, some of the most common and useful ones are notifications — such as sending a message to Microsoft Teams, generating an email, or updating an existing workflow.

These actions help keep people in the loop. Even when automation is in place, there are times when human awareness or approval is still essential. For example, sending an alert to a Teams channel can immediately notify support engineers that something unusual has happened, while still allowing automated responses to continue in parallel.

2026-08-01

I recently received a review copy of The Orange Book of Machine Learning: Green Edition by Carl McBride Ellis from my friends at PackT.

Author

Carl McBride Ellis wrote this book as a Green Edition of the material he had been teaching across a whole range of Spanish cities.

Content

This is the sort of technical book that feels less like a formal textbook and more like spending a few very productive days with an experienced instructor. That makes sense: the book grew out of a five-day course, and its examples are built around Python, pandas, scikit-learn and Jupyter notebooks. The result is practical, opinionated and surprisingly personable. The language is quite precise but a little less conversational than I would have liked. It’s very to the point.

2026-07-31

Logic Apps are closely related to Power Automate, but they’re designed for enterprise IT teams that need more control, scalability, and governance.

Like Power Automate, Logic Apps let you automate workflows across systems using a visual, low-code designer.

However, Logic Apps are built on Azure, which gives them access to more advanced capabilities — such as higher throughput, better integration with on-premises systems, and enterprise-grade reliability.

You can think of Power Automate as being focused on business users and citizen developers, while Logic Apps are aimed at IT professionals and developers who build and maintain enterprise integrations.

2026-07-30