Organizing tests in R packages – cynkra blog

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ai-angineers-handbook/building_agents_from_scratch/deep_research_agent at main · swirl-ai/ai-angineers-handbook
Contribute to swirl-ai/ai-angineers-handbook development by creating an account on GitHub.
State of AI Coding - Engineering with Exponentials
Your value as an engineer scales directly with the amount of compute you can harness. Learn to maximize your Compute Advantage in this comprehensive guide.
Designing Empty States in Complex Applications: 3 Guidelines
Empty states provide opportunities for designers to communicate system status, increase learnability of the system, and deliver direct pathways for key tasks. This article provides guidance for designing empty-state dialogues for content-less containers.
Solutions - ScraperAPI
Get access to these core solutions with ScraperAPI, and take your web scraping efforts to the next level. Read more about each solution.
Ferrous Systems Donates Ferrocene Language Specification to Rust Project - The Rust Foundation
Rust 1.0 was published in May 2015. As the language approaches its 10th anniversary, Rust has become one of the fastest growing and most-loved languages [1] among developers, thanks to a combination of speed, safety and a vibrant community. Like any growing open source language, Rust has a considerable amount…
Improve your fantasy baseball team with AI – Microsoft 365
Learn how to use AI to make projections, find fantasy baseball team names, analyze trades, adjust your roster, and more.
A Look at PostgreSQL User-defined Data Types
This tutorial shows you how to create PostgreSQL user-defined data type using CREATE DOMAIN and CREATE TYPE statements.
PostgreSQL Foreign Key
In this tutorial, you will learn about PostgreSQL foreign key and how to add foreign keys to tables using foreign key constraints.
The following illustrates a foreign key constraint syntax:
[CONSTRAINT fk_name]
FOREIGN KEY(fk_columns)
REFERENCES parent_table(parent_key_columns)
[ON DELETE delete_action]
[ON UPDATE update_action]
In this syntax:
First, specify the name for the foreign key constraint after the CONSTRAINT keyword. The CONSTRAINT clause is optional. If you omit it, PostgreSQL will assign an auto-generated name.
Second, specify one or more foreign key columns in parentheses after the FOREIGN KEY keywords.
Third, specify the parent table and parent key columns referenced by the foreign key columns in the REFERENCES clause.
Finally, specify the desired delete and update actions in the ON DELETE and ON UPDATE clauses.
Since the primary key is rarely updated, the ON UPDATE action is infrequently used in practice. We’ll focus on the ON DELETE action.
PostgreSQL supports the following actions:
SET NULL
SET DEFAULT
RESTRICT
NO ACTION
CASCADE
PostgreSQL Copy Table: A Step-by-Step Guide
In this tutorial, you will learn how to copy an existing table to a new one using various PostgreSQL copy table statements.
To copy a table completely, including both table structure and data, you use the following statement:
CREATE TABLE new_table AS
TABLE existing_table;
PostgreSQL Temporary Table
You will learn about the PostgreSQL temporary table and how to manage it using the CREATE TEMP TABLE and DROP TABLE statements.
When to use temporary tables
Isolation of data: Since the temporary tables are session-specific, different sessions or transactions can use the same table name for temporary tables without causing a conflict. This allows you to isolate data for a specific task or session.
Intermediate storage: Temporary tables can be useful for storing the intermediate results of a complex query. For example, you can break down a complex query into multiple simple ones and use temporary tables as the intermediate storage for storing the partial results.
Transaction scope: Temporary tables can be also useful if you want to store intermediate results within a transaction. In this case, the temporary tables will be visible only to that transaction
PostgreSQL Generated Columns
In this tutorial, you will learn about PostgreSQL generated columns whose values are automatically calculated from other columns.
In PostgreSQL, a generated column is a special type of column whose values are automatically calculated based on expressions or values from other columns.
A generated column is referred to as a computed column in the SQL Server
or a virtual column in Oracle
.
There are two kinds of generated columns:
Stored: A stored generated column is calculated when it is inserted or updated and occupies storage space.
Virtual: A virtual generated column is computed when it is read and does not occupy storage space.
A virtual generated column is like a view, whereas a stored generated column is similar to a materialized view. Unlike a material view, PostgreSQL automatically updates data for stored generated columns.
PostgreSQL currently implements only stored generated columns.
PostgreSQL Sequences
In this tutorial, you will learn about the PostgreSQL sequences and how to use a sequence object to generate a sequence of numbers.
In PostgreSQL, a sequence is a database object that allows you to generate a sequence of unique integers.
Typically, you use a sequence to generate a unique identifier for a primary key in a table. Additionally, you can use a sequence to generate unique numbers across tables.
To create a new sequence, you use the CREATE SEQUENCE statement.
Listing all sequences in a database
To list all sequences in the current database, you use the following query:
SELECT
relname sequence_name
FROM
pg_class
WHERE
relkind = 'S';
PostgreSQL Identity Column
This tutorial shows you how to use the GENERATED AS IDENTITY constraint to create the PostgreSQL identity column for a table.
PostgreSQL version 10 introduced a new constraint GENERATED AS IDENTITY that allows you to automatically assign a unique number to a column.
The GENERATED AS IDENTITY constraint is the SQL standard-conforming variant of the good old SERIAL column.
The following illustrates the syntax of the GENERATED AS IDENTITY constraint:
column_name type
GENERATED { ALWAYS | BY DEFAULT }
AS IDENTITY[ ( sequence_option ) ]
In this syntax:
The type can be SMALLINT, INT, or BIGINT.
The GENERATED ALWAYS instructs PostgreSQL to always generate a value for the identity column. If you attempt to insert (or update) values into the GENERATED ALWAYS AS IDENTITY column, PostgreSQL will issue an error.
The GENERATED BY DEFAULT instructs PostgreSQL to generate a value for the identity column. However, if you supply a value for insert or update, PostgreSQL will use that value to insert into the identity column instead of using the system-generated value.
PostgreSQL allows a table to have more than one identity column. Like the SERIAL, the GENERATED AS IDENTITY constraint also uses the SEQUENCE object internally.
To fix the error, you can use the OVERRIDING SYSTEM VALUE clause as follows:
INSERT INTO color (color_id, color_name)
OVERRIDING SYSTEM VALUE
VALUES(2, 'Green');
Alternatively, you can use GENERATED BY DEFAULT AS IDENTITY instead.
Because the GENERATED AS IDENTITY constraint uses the SEQUENCE object, you can specify the sequence options for the system-generated values.
For example, you can specify the starting value and the increment as follows:
DROP TABLE color;
CREATE TABLE color (
color_id INT GENERATED BY DEFAULT AS IDENTITY
(START WITH 10 INCREMENT BY 10),
color_name VARCHAR NOT NULL
);
In this example, the system-generated value for the color_id column starts with 10 and the increment value is also 10.
{relay}: an R Package for workflows
If I was being presumptuous, I would assume that the R programming language is primarily used for scripting tasks, especially in the field of Public Health. The R language is definitely capable of more complex tasks but, in terms of day-to-day use, creating scripts is most commonplace. Part of this is because R excels in this area, making it very easy for data analysts and epidemiologists to create reports quickly without the requirement to deeply understand software engineering principles and concepts.
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Retrieval-Augmented Generation (RAG) Workflows
Provides tools for implementing Retrieval-Augmented Generation (RAG) workflows with Large Language Models (LLMs). Includes functions for document processing, text chunking, embedding generation, storage management, and content retrieval. Supports various document types and embedding providers (Ollama, OpenAI), with DuckDB as the default storage backend. Integrates with the ellmer package to equip chat objects with retrieval capabilities. Designed to offer both sensible defaults and customization options with transparent access to intermediate outputs.
Globstar by DeepSource - The Open-Source Static Analysis Toolkit
Fast, feature-rich, open-source static analysis toolkit for writing and running code quality and SAST checkers.
GMH DataHub
My LLM codegen workflow atm
A detailed walkthrough of my current workflow for using LLms to build software, from brainstorming through planning and execution.
Github-Ranking/Top100/R.md at master · EvanLi/Github-Ranking
:star:Github Ranking:star: Github stars and forks ranking list. Github Top100 stars list of different languages. Automatically update daily. | Github仓库排名,每日自动更新 - EvanLi/Github-Ranking
Proxy Pattern
Intercept and control interactions to target objects
JohnCoene/mjml: 📨 Create responsive emails with R
📨 Create responsive emails with R. Contribute to JohnCoene/mjml development by creating an account on GitHub.
JohnCoene/awn: Awesome notifications for shiny
Awesome notifications for shiny. Contribute to JohnCoene/awn development by creating an account on GitHub.
dreamRs/apexcharter: :bar_chart: R Htmlwidget for ApexCharts.js
:bar_chart: R Htmlwidget for ApexCharts.js. Contribute to dreamRs/apexcharter development by creating an account on GitHub.
dreamRs/shinybusy: Minimal busy indicator for Shiny apps
Minimal busy indicator for Shiny apps. Contribute to dreamRs/shinybusy development by creating an account on GitHub.
dreamRs/shinytreeview: Hierarchical tree input for Shiny apps
Hierarchical tree input for Shiny apps. Contribute to dreamRs/shinytreeview development by creating an account on GitHub.
Agents Object Oriented Structure
reg.finalizer function - RDocumentation
Registers an R function to be called upon garbage collection of
object or (optionally) at the end of an R session.