Haki Benita

“Haki Benita” delves into the intricacies of Python programming speed, AI applications with short-term memory in databases, and the significance of data augmentation in machine learning. It explores the challenges of understanding and utilizing generative AI in enterprise settings, emphasizing the importance of contextual understanding over mere data retrieval. The document also highlights the pitfalls of treating data as static in the realm of Big Data and the necessity for responsive, data-driven solutions. Overall, “Haki Benita” offers insights into optimizing Python performance, leveraging AI for conversation history, and enhancing machine learning models through dynamic data augmentation techniques.

Visit Haki Benita

Unconventional PostgreSQL Optimizations

Haki Benita

When it comes to database optimization, developers often reach for the same old tools: rewrite the query slightly differently, slap an index on a column, denormalize, analyze, vacuum, cluster, repeat....

Reliable Django Signals

Haki Benita

Django signals are extremely useful for decoupling modules and implementing complicated workflows. However, the underlying transport for signals makes them unreliable and subject to unexpected failure...

How to Get Foreign Keys Horribly Wrong

Haki Benita

Constraints keep the integrity of your system and prevent you from shooting yourself in the foot. Foreign keys are a special type of constraint because, unlike unique, check, and primary keys, they sp...

How to Get or Create in PostgreSQL

Haki Benita

"Get or create" is a very common operation for syncing data in the database, but implementing it correctly may be trickier than you may expect. If you ever had to implement it in a real system with re...

Fastest Way to Read Excel in Python

Haki Benita

I'm fairly sure that Excel is the most common way to store data, manipulate data, and yes(!), even pass data around. This is why it's not uncommon to find yourself reading Excel in Python. In this art...

When Good Correlation is Not Enough

Haki Benita

Choosing to use a block range index (BRIN) to query a field with high correlation is a no-brainer for the optimizer. However, under some easily reproducible circumstances, a BRIN index can result in s...

Future Proofing SQL with Carefully Placed Errors

Haki Benita

There are many best practices for maintaining backward and forward compatibility in application code, but it's not very commonly mentioned in relation to SQL. SQL is used to produce critical business ...

Handling Concurrency Without Locks

Haki Benita

Concurrency is not very intuitive - you need to train your brain to consider what happens when multiple processes execute a certain code block at the same time. In this article I present common concur...

2021 Year in Review

Haki Benita

What I've been up to in 2021...

Lesser Known PostgreSQL Features

Haki Benita

A list of useful features you already have, but may not know about! In this article I share lesser known features of PostgreSQL.

One Database Transaction Too Many

Haki Benita

A story about how I ended up sending hundreds of users messages saying they got paid when they didn't! In the process we've learned a valuable lesson about nested transactions and Django signals.

Practical SQL for Data Analysis

Haki Benita

Pandas is by far the most popular tool for data analysis. It's packed with useful features, it's battle tested and widely accepted. However, pandas comes at a cost which is often overlooked. SQL datab...