# Ardan Labs Published articles for Ardan Labs. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## RAG in Go: A Vulnerability Research Tool DevFeed: [RAG in Go: A Vulnerability Research Tool]() Original publisher: [Read original article]() Published: 2026-04-20T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Retrieval Augmented Generation (RAG)](), [Go Language](), [vulnerability](), [DuckDB](), [JSON]() Tags: [api](), [ardan-labs](), [blog](), [code](), [database](), [duckdb](), [embedding](), [go](), [go-programming](), [golang](), [json](), [llm](), [programming](), [rag](), [retrieval](), [technical](), [vulnerability]() ### AI overview This tutorial demonstrates how to build a retrieval-augmented generation tool in Go using the Go Vulnerability Database as internal documents. It covers ingesting zipped JSON data, generating vector embeddings, storing them in DuckDB, and retrieving documents relevant to a user query. ### Source excerpt Introduction In the previous post, you saw how you can use tools to add information to an LLM query. In this post, we'll see another method of adding information to an LLM called RAG, or Retrieval-Augmented Generation. The idea of RAG is that you want the LLM to have access to information that wasn't available to it when it was initially trained. You do it by storing documents in your own database along with their embedding. I won't go into the technical details of embedding, but think of it as a way to convert a piece of text into a vector. The magic is that if two pieces of text have similar meaning, an embedding model can create vectors that mathematically show they are similar. ## Using Tools: A Meeting Scheduler DevFeed: [Using Tools: A Meeting Scheduler]() Original publisher: [Read original article]() Published: 2026-03-16T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Tool](), [LLMs](), [Code]() Tags: [ardan-labs](), [blog](), [function-calling](), [go](), [go-programming](), [golang](), [implementation](), [llms](), [programming](), [server](), [tools]() ### AI overview A tutorial on using LLM function calling to build a meeting-scheduling agent. It explains how tool calls work, covers the setup with the Kronk Model Server, and introduces the system prompt and tool definition. ### Source excerpt Introduction LLMs are great, but they are trained on public data sets. In some cases, you need the LLM to use data that's not publicly available or that's frequently changing. There are several ways to make such data available to LLMs: Tool/function calls Retrieval-augmented generation (aka RAG) MCP In coding agents, you can also add skills. In this post we'll focus on function calling. How Does It Work? When interacting with an LLM, you can provide a description of available tools if the model supports tool calling. If the LLM reasons that the best answer is to use one of the tools, it will return a reply that contains a tool call with the parameters to use. Then you make the function call and return the answer back to the LLM. ## Range-Over Functions in Go DevFeed: [Range-Over Functions in Go]() Original publisher: [Read original article]() Published: 2026-02-16T00:00:00Z Content type: article Language: en Sources: [William Kennedy]() Topics: [Go Language](), [Programming language](), [Programming](), [Data structures]() Tags: [ardan-labs](), [blog](), [code](), [examples](), [generators](), [go](), [go-programming](), [golang](), [programming](), [programming-language](), [syntax]() ### AI overview This article explains Go's range-over-functions experiment, which proposes a standardized iterator model while preserving the familiar for range syntax. It introduces the iter package and sequence abstractions, compares iteration patterns, and uses stack examples to show how iterator logic can be implemented. ### Source excerpt Iteration has long been one of the more fragmented areas of Go, with developers relying on ad hoc patterns to traverse custom data structures. This article explores the range-over-functions experiment, a proposed evolution of the language that introduces a standardized iterator model while preserving Go's familiar for range syntax. Using the new iter package and sequence abstractions, it shows how iteration logic can be expressed more clearly, flexibly, and idiomatically. Originally published in April 2024, the concepts remain highly relevant as Go continues to evolve toward more expressive yet simple language features. ## Query Database Using Plain English DevFeed: [Query Database Using Plain English]() Original publisher: [Read original article]() Published: 2026-02-11T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Databases](), [Large Language Model](), [SQL](), [Code](), [DuckDB](), [Ollama](), [context](), [GitHub](), [API]() Tags: [api](), [ardan-labs](), [blog](), [code](), [context](), [database](), [duckdb](), [github](), [go](), [go-programming](), [golang](), [llms](), [ollama](), [programming](), [sql]() ### AI overview This tutorial shows how to build a system that lets users query a relational database using plain English. It uses an LLM to generate SQL, executes the query against a database, and then uses the query results to generate an answer. The example uses the Austin Bike Share dataset, Kronk Model Server, and DuckDB, while noting that other model servers and SQL databases can be used. ### Source excerpt Introduction In this post you'll see how you can create a system that allows users to query a relational database using plain English. This allows users not familiar with SQL or business intelligence systems to get insights from data. Setting Up If you want to follow along, you'll need to clone the code from the GitHub repo. This will download the code, and the database file containing the data (bikes.ddb) Note: The data is from the Austin Bike Share dataset. ## Rust Questions Answered in a JetBrains Livestream with Herbert Wolverson DevFeed: [Rust Questions Answered in a JetBrains Livestream with Herbert Wolverson]() Original publisher: [Read original article]() Published: 2026-01-07T00:00:00Z Content type: article Language: en Sources: [William Kennedy]() Topics: [Rust](), [Code]() Tags: [ardan-labs](), [blog](), [developers](), [go](), [go-programming](), [golang](), [jetbrains](), [livestream](), [programming](), [repo](), [rust](), [talk]() ### AI overview This article summarizes 23 questions discussed in a JetBrains livestream with Herbert Wolverson about Rust. Topics include his new book, Rust's memory model, the language's learning curve, and whether beginners should learn C first. ### Source excerpt In a recent livestream with JetBrains, Vitaly Bragilevsky sat down with Herbert Wolverson, our Lead Rust Consultant and Instructor here at Ardan Labs, to talk about everything Rust developers - beginners and pros alike - are curious about. Watch the full livestream replay on the Ardan Labs Channel and check out the GitHub repo with Herbert's prepared answers and code samples. Below is a short summary of the 23 questions that were covered during the livestream. ## Ultimate Go Software Design LIVE: Ep.63 DevFeed: [Ultimate Go Software Design LIVE: Ep.63]() Original publisher: [Read original article]() Author: Carlos Alexandro Becker Published: 2026-01-06T00:00:00Z Content type: article Language: en Sources: [Carlos Becker]() Topics: [Go Language](), [Architecture & Design](), [Ardan Labs]() Tags: [ardan-labs](), [coding](), [design](), [go](), [live](), [software-design]() ### AI overview A live coding stream featuring Bill Kennedy, Kevin Enriquez, Andrey Nering, and the author, focused on adding support for Ardan Labs' Kronk to Charm's fantasy. ### Source excerpt A live coding stream with Bill Kennedy, Kevin Enriquez, Andrey Nering, and me. ## Garbage Collection In Go : Part III - GC Pacing DevFeed: [Garbage Collection In Go : Part III - GC Pacing]() Original publisher: [Read original article]() Published: 2025-08-26T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [benchmarking](), [Concurrency](), [Code](), [Latency]() Tags: [algorithms](), [ardan-labs](), [blog](), [code](), [concurrent](), [garbage-collection](), [go](), [go-programming](), [golang](), [latency](), [low-latency](), [memory](), [performance](), [programming]() ### AI overview This third article in a three-part series explains how Go's garbage collector paces itself according to workload demands. It uses sequential and concurrent examples to examine adaptive behavior and emphasizes reducing allocations per unit of work to reduce garbage-collection latency and improve application performance. ### Source excerpt Go's garbage collector is designed not only to manage memory safely but also to pace itself intelligently, striking a balance between low latency and high throughput. This blogpost explores how the GC adapts its pace to workload demands, demonstrated through both sequential and concurrent program examples, and why reducing allocations per unit of work is the most effective way to lighten its load. Originally published in 2019, its core principles remain just as relevant today, offering Go developers a deeper understanding of the runtime's adaptive behavior and confidence that the GC can find the right rhythm without extensive manual tuning. ## Garbage Collection In Go : Part II - GC Traces DevFeed: [Garbage Collection In Go : Part II - GC Traces]() Original publisher: [Read original article]() Published: 2025-07-14T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [Traces](), [Latency](), [App](), [web applications]() Tags: [ardan-labs](), [article](), [blog](), [go](), [go-programming](), [golang](), [how-to](), [latency](), [performance](), [programming](), [techniques](), [traces]() ### AI overview Part two of a three-part series on Go's garbage collector explains how to generate and interpret GC traces and application profiles. It shows how to identify allocation hotspots and reduce unnecessary allocations to improve latency and throughput. ### Source excerpt Originally published in 2019, this article is part two of a three-part series exploring Go's garbage collector. Though the Go runtime has continued to evolve, the performance principles covered here remain highly relevant today. This installment focuses on practical techniques for analyzing and reducing garbage collection (GC) overhead in real-world Go applications. It walks through how to interpret GC traces using GODEBUG=gctrace=1 and uncover allocation hotspots with pprof, with a clear message: reducing unnecessary allocations, especially in tight loops, has a direct and measurable impact on latency and throughput. Whether you're optimizing high-performance services or just becoming GC-aware, the insights here are as applicable now as ever. ## Garbage Collection In Go : Part I - Semantics DevFeed: [Garbage Collection In Go : Part I - Semantics]() Original publisher: [Read original article]() Published: 2025-06-10T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [Programming language](), [Algorithm](), [Software]() Tags: [algorithm](), [ardan-labs](), [blog](), [garbage-collection](), [go](), [go-programming](), [golang](), [guide](), [internals](), [memory](), [performance](), [programming]() ### AI overview This tutorial explains the semantics of Go's garbage collector, including heap allocation tracking, concurrent tri-color mark-and-sweep collection, and Stop The World events. It presents a behavioral model intended to remain useful despite changes to runtime implementation details. ### Source excerpt This article was originally published in 2018, yet its core insights into Go's garbage collection model remain highly relevant for developers today. While some implementation details of Go's runtime have evolved, the foundational concepts explored here--such as the semantics of the tri-color mark and sweep algorithm, Stop The World (STW) events, and GC trace interpretation--are still essential to understanding how Go manages memory. Whether you're optimizing performance or deepening your knowledge of Go internals, this post continues to offer a clear and practical guide to working with the garbage collector, not against it. ## Scheduling In Go : Part III - Concurrency DevFeed: [Scheduling In Go : Part III - Concurrency]() Original publisher: [Read original article]() Published: 2025-05-12T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Concurrency](), [Go Language](), [benchmarking](), [IO](), [Sorting]() Tags: [ardan-labs](), [benchmarks](), [blog](), [concepts](), [concurrency](), [go](), [go-programming](), [golang](), [io](), [parallelism](), [performance](), [programming](), [sorting](), [technical]() ### AI overview This third post in a series about the Go scheduler explains concurrency as out-of-order execution and distinguishes it from parallelism. It discusses how CPU-bound and I/O-bound workloads affect the decision to use concurrency, using practical examples and benchmarks to show that parallelism can improve CPU-bound performance while concurrency alone can benefit I/O-bound work. ### Source excerpt Although originally written in 2018, the following concepts remain essential for developers working with concurrency. This blogpost focuses on concurrency, distinguishing it from parallelism by defining it as "out of order" execution. It emphasizes the importance of understanding workload types--CPU bound (e.g., summing, sorting) and IO bound (e.g., file reading)--to assess when concurrency is appropriate. Through practical examples and benchmarks, it shows that parallelism boosts performance for CPU bound tasks, while concurrency alone benefits IO bound workloads. The post underscores that identifying workload type is key to applying concurrency effectively without added complexity. ## Scheduling In Go : Part II - Go Scheduler DevFeed: [Scheduling In Go : Part II - Go Scheduler]() Original publisher: [Read original article]() Published: 2025-04-14T00:00:00Z Content type: article Language: en Sources: [William Kennedy]() Topics: [Go Language](), [Concurrency](), [Optimization](), [systems]() Tags: [ardan-labs](), [blog](), [concurrency](), [concurrent](), [context](), [go](), [go-programming](), [golang](), [optimization](), [os](), [parallel](), [programming](), [scheduler](), [switching](), [systems](), [threads]() ### AI overview The second article in a three-part series explains the Go scheduler at a semantic level. It covers logical processors, global and local run queues, context switching, work stealing, and synchronous and asynchronous system calls. ### Source excerpt This blogpost is the second installment in a three-part series exploring the mechanics and semantics of the Go scheduler. Despite being published in 2018, the content remains relevant today, as the Go scheduler's design continues to influence the development of efficient and scalable concurrent systems. In this post, we will go into the inner workings of the Go scheduler, discussing its components, such as the Global Run Queue (GRQ) and Local Run Queue (LRQ), and its behavior, including context switching, work stealing, and the handling of synchronous and asynchronous system calls. By understanding these concepts, developers can make informed decisions about concurrency and optimization in their Go applications. ## Scheduling In Go : Part I - OS Scheduler DevFeed: [Scheduling In Go : Part I - OS Scheduler]() Original publisher: [Read original article]() Published: 2025-03-04T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [Operating system](), [Concurrency](), [Kernel]() Tags: [ardan-labs](), [blog](), [concurrency](), [cpu](), [engineering](), [fundamentals](), [go](), [go-programming](), [golang](), [hardware](), [numa](), [os](), [programming]() ### AI overview This first article in a three-part series explains operating-system scheduling as a foundation for understanding Go's scheduler. It discusses how schedulers interact with multithreaded Go programs and introduces hardware considerations such as processors, CPU caches, and NUMA. ### Source excerpt Although this blogpost was originally published in 2018, the concepts and principles discussed remain crucial for building efficient and performant multithreaded applications in Go now in 2025 (Go 1.24.0). As the Go ecosystem continues to evolve, understanding how the Go scheduler interacts with the operating system scheduler is more important than ever. This three-part series provides a comprehensive overview of the mechanics and semantics behind Go's scheduling, starting with the fundamentals of the operating system scheduler. ## Context Package Semantics In Go DevFeed: [Context Package Semantics In Go]() Original publisher: [Read original article]() Published: 2025-02-10T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [context](), [Programming](), [Software]() Tags: [api](), [ardan-labs](), [blog](), [cancellation](), [go](), [go-programming](), [golang](), [goroutines](), [latency](), [pitfalls](), [programming]() ### AI overview This tutorial explains the semantics of Go's Context package, including request-scoped data, deadlines, cancellation signals, and how to introduce contexts early when designing APIs. It also discusses managing goroutine lifetime and latency in services. ### Source excerpt Although first introduced in 2014, the Context package remains a crucial component of Go programming, enabling efficient management of request-scoped data, deadlines, and cancellation signals. As the Go ecosystem continues to evolve, understanding the Context package's semantics is vital for developing reliable and maintainable software. This blogpost provides an in-depth exploration of the Context package's semantics, highlighting best practices and common pitfalls to help developers effectively leverage this powerful tool. ## Elevate with Encore and Ardan Labs DevFeed: [Elevate with Encore and Ardan Labs]() Original publisher: [Read original article]() Author: Marcus Kohlberg Published: 2024-05-09T00:00:00Z Content type: release Language: en Sources: [Encore Updates]() Topics: [Go Language](), [Development]() Tags: [ardan-labs](), [developer-relations](), [go](), [launch](), [partnership](), [training]() ### AI overview Encore announces a partnership with Ardan Labs as its official Go training partner. The program offers advanced Go training, community connections, presentation coaching, and financial support for developers. ### Source excerpt Grow Your Expertise, Expand Your Influence ## For Loops and More in Go DevFeed: [For Loops and More in Go]() Original publisher: [Read original article]() Published: 2024-03-12T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [Assembly]() Tags: [ardan-labs](), [assembly](), [blog](), [bugs](), [compiler](), [go](), [go-programming](), [golang](), [loops](), [programming](), [syntax]() ### AI overview A tutorial on writing for loops in Go, covering loop termination, the assembly generated for an empty loop, loops with multiple variables, and labeled breaks around switch statements. It explains how these forms work and how understanding them can help prevent bugs. ### Source excerpt Introduction Looping seems like a basic topic: Write a for loop with a termination condition, and you're done. However there's a lot of ways you can write a for loop in Go. Knowing more about the different versions of for will help you choose the best option to accomplish your tasks and it will help you prevent some bugs. Some Assembly Required What kind of code is generated by the compiler for a for loop? To keep things simple, I will produce the assembly for an empty loop: ## Visualizing Map Data with Go and Leaflet JS DevFeed: [Visualizing Map Data with Go and Leaflet JS]() Original publisher: [Read original article]() Published: 2023-11-23T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [API](), [browser](), [XML]() Tags: [api](), [ardan-labs](), [blog](), [browser](), [go](), [go-programming](), [golang](), [programming](), [xml]() ### AI overview A tutorial on building a Go service that parses GPX route data, aggregates location points, and returns data for an interactive browser map rendered with Leaflet JS. ### Source excerpt Introduction This year I set a personal goal of walking for a total of 1,000 kilometers and I'm proud to say I'm close to hitting that goal. I've been tracking all the different routes I take in an app named Strava. One nice feature of Strava is that the app provides access to the raw data in a format called GPX. Starva can visualize the route in their app, but I wanted to try and perform my own visualization. That brought me to this blog post about using Leaflet JS to plot one of my walks on a map. ## Calculating Download MD5 Hash DevFeed: [Calculating Download MD5 Hash]() Original publisher: [Read original article]() Published: 2023-03-09T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [HTTP](), [cURL](), [Google Cloud Platform (GCP)](), [dataset](), [Code]() Tags: [ardan-labs](), [blog](), [cloud](), [code](), [curl](), [dataset](), [go](), [go-programming](), [golang](), [google-cloud](), [hash](), [http](), [programming]() ### AI overview This tutorial explains how to validate a downloaded file's MD5 signature using HTTP headers and Go. It demonstrates obtaining file metadata with an HTTP HEAD request, reading the MD5 value reported by Google Cloud Storage, and implementing the request and header parsing in Go. ### Source excerpt Introduction One of the exercises I give to students is to download a single big file over HTTP concurrently using several goroutines using HTTP Range requests. An extra part of the exercise is to validate the downloaded file from a known MD5 signature. This extra part turns out to be interesting, let's have a look. Getting Download Information Let's make an HTTP HEAD request to get information about a file located in a public dataset stored on Google Cloud Storage (GCS). ## Visualization in Go - Plotting Stock Information DevFeed: [Visualization in Go - Plotting Stock Information]() Original publisher: [Read original article]() Published: 2022-01-17T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [CSV](), [HTML]() Tags: [ardan-labs](), [blog](), [build](), [data](), [development](), [format](), [go](), [go-programming](), [golang](), [html](), [plotting](), [programming](), [visualization]() ### AI overview A tutorial on visualizing historical stock data in Go. It surveys charting options, chooses Plotly for interactive features, parses CSV data downloaded from Yahoo! Finance, and begins building the URL used to fetch the data. ### Source excerpt Introduction You'd like to visualize some stock data using Go, but after looking at the Go ecosystem you see very little in charting. You find gonum, which has some plotting capabilities, but it generates static charts. It's 2022, and you'd like to have interactive features such as zooming, panning, and more. You turn to the HTML landscape, and see many more options and decide to take this path. After a short survey, you decide to use plotly. ## GIS in Go DevFeed: [GIS in Go]() Original publisher: [Read original article]() Published: 2021-11-01T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Geographic Information System](), [Go Language](), [CSV]() Tags: [ardan-labs](), [blog](), [csv](), [gis](), [go](), [go-programming](), [golang](), [programming]() ### AI overview A Go tutorial that loads GPS route data from a CSV file, resamples it into fewer time-based points, and generates an HTML map using Leaflet. ### Source excerpt Introduction You are jogging and want to show off your route to your friends. Let's imagine the data you have for your route is a CSV file in the following format: Listing 1: track.csv time,lat,lng,height 2015-08-20 03:48:07.235,32.519585,35.015021,136.1999969482422 2015-08-20 03:48:24.734,32.519606,35.014954,126.5999984741211 2015-08-20 03:48:25.660,32.519612,35.014871,123.0 2015-08-20 03:48:26.819,32.519654,35.014824,120.5 2015-08-20 03:48:27.828,32.519689,35.014776,118.9000015258789 2015-08-20 03:48:29.720,32.519691,35.014704,119.9000015258789 2015-08-20 03:48:30.669,32.519734,35.014657,120.9000015258789 Listing 1 shows the first few lines of track.csv. Each line contains a time stamp in UTC, latitude, longitude and height above sea level in meters. ## Extract, Transform, and Load in Go DevFeed: [Extract, Transform, and Load in Go]() Original publisher: [Read original article]() Published: 2021-09-13T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [CSV](), [SQL](), [Databases](), [Grafana]() Tags: [ardan-labs](), [blog](), [data](), [database](), [dataset](), [download](), [etl](), [go](), [go-programming](), [golang](), [grafana](), [programming](), [sql]() ### AI overview This tutorial explains extract, transform, and load (ETL) in Go using a food-violations dataset. It covers loading CSV data into an SQL database, querying it, and preparing fields through parsing, renaming, type conversion, and enrichment. ### Source excerpt Introduction You are about to visit Boston, and would like to taste some good food. You ask your friend who lives there what are good places to eat. They reply with "Everything is good, you can't go wrong". Which makes you think, maybe I should check where not to eat. The data geek in you arises, and you find out that the city of Boson has a dataset of food violations. You download it and decide to have a look. ## Data Science in Go: How Much To Tip DevFeed: [Data Science in Go: How Much To Tip]() Original publisher: [Read original article]() Published: 2021-07-27T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Data Science](), [CSV](), [dataset](), [Go Language](), [SQLite]() Tags: [ardan-labs](), [article](), [blog](), [code](), [command-line](), [data-science](), [dataset](), [go](), [go-programming](), [golang](), [programming]() ### AI overview A tutorial that uses Go and a sample of the NYC Taxi dataset to explore how much passengers should tip. It covers initial data inspection, CSV parsing, loading selected fields, and calculating statistics. ### Source excerpt The Question When you work on data science problems, you always start with a question you're trying to answer. This question will affect the data you pick, your exploration process, and how you interpret the results. The question for this article is: How much (in percentage) should you tip your taxi driver? To answer the question, we'll use a portion of the NYC Taxi dataset. The data file we'll be using is taxi-01-2020-sample.csv.bz2 ## Using Bitmasks In Go DevFeed: [Using Bitmasks In Go]() Original publisher: [Read original article]() Published: 2021-04-09T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [Server]() Tags: [ardan-labs](), [blog](), [go](), [go-programming](), [golang](), [how-to](), [introduction](), [learn](), [programming]() ### AI overview A tutorial explains how bitmasks can store and process sets of keys efficiently in Go. It introduces binary representation, bitwise AND, OR, NOT, and shift operations, then applies them to representing three keys with three bits. ### Source excerpt Introduction You write a server for a massively multiplayer online role-playing game (MMORPG). In the game, players collect keys and you want to design how to store the set of keys each player has. As an example, imagine the set of keys are copper, jade and crystal. You consider the following options for storing a player key sets: []string map[string]bool Both options will work, but did you consider a third option of using a bitmask? Using a bitmask will make storing and processing keys more efficient. Once you learn the mechanics, it will be readable and maintainable as well. ## Writing Simulations Using Go DevFeed: [Writing Simulations Using Go]() Original publisher: [Read original article]() Published: 2021-01-13T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Simulation](), [Go Language](), [Programming](), [Randomizer](), [Statistics]() Tags: [ardan-labs](), [blog](), [go](), [go-programming](), [golang](), [how-to](), [programming](), [random](), [simulation](), [statistics]() ### AI overview A practical tutorial on writing simulations in Go using a random number generator. It demonstrates a Catan dice-roll simulation that estimates how often each sum occurs and explains why seeding affects repeated results. ### Source excerpt Introduction If you can write a for-loop, you can do statistics. - Jake Vanderplas A lot of developers shy away from problems which involve statistics or probability. Which is shameful since in today's data-rich environment, you can gain a lot of insights from data. In this blog post, I'll show you how to write a simulation tool which requires no knowledge in statistics or probability. Simulations are easy to write and can be a very effective tool in research. You only need some basic programming skills and a random number generator. ## Working with SQLite using Go and Python DevFeed: [Working with SQLite using Go and Python]() Original publisher: [Read original article]() Published: 2020-11-30T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [SQLite](), [Go Language](), [Python](), [Databases](), [SQL](), [pandas](), [HTTP]() Tags: [ardan-labs](), [blog](), [code](), [database](), [go](), [go-programming](), [golang](), [http](), [pandas](), [programming](), [python](), [sql](), [sqlite]() ### AI overview A tutorial on using SQLite with Go and Python. It explains SQLite, transactions, schemas, and SQL, then builds a Go HTTP server that stores trade notifications in SQLite and a Python program that processes the data. ### Source excerpt Introduction I prefer to use relational (SQL) databases in general since they provide several features that are very useful when working with data. SQLite is a great choice since the database is a single file, which makes it easier to share data. Even though it's a single file, SQLite can handle up to 281 terabytes of data. SQLite also comes with a command line client called sqlite3 which is great for quick prototyping. [Next page]()