This article exposes critical flaws in Text-to-SQL benchmarks like BIRD and Spider. An audit of gold queries reveals that several contain incorrect joins, causing mathematically wrong results to be established as ground truth. Since standard execution accuracy measures performance by comparing outputs against these faulty reference answers, models are often penalized for being correct and rewarded for mimicking human errors. To address this, the author proposes a constraint-aware evaluation method that validates SQL logic against declared data semantics rather than relying on potentially incorrect gold results.
- Discrepancies between benchmark gold queries and database schema facts
- The inherent risks of using execution accuracy as the primary metric
- How annotation errors impact model rankings and enterprise deployments
- Introduction of constraint-aware evaluation to ensure semantic validity
- Discrepancies between benchmark gold queries and database schema facts
- The inherent risks of using execution accuracy as the primary metric
- How annotation errors impact model rankings and enterprise deployments
- Introduction of constraint-aware evaluation to ensure semantic validity
Botasaurus is an all-in-one web scraping framework designed to help developers build undetectable scrapers that can bypass sophisticated bot detection systems like Cloudflare, Datadome, and BrowserScan. It simplifies the development process by providing high-level abstractions for browser automation, humane HTTP requests, and general data tasks. Key features include human-like mouse movements, browser-based fetch requests to significantly reduce proxy costs, and built-in utilities for caching, sitemap processing, and data cleaning.
Main topics:
- Bypassing Cloudflare WAF and Turnstile CAPTCHAs.
- Creating UI-based scrapers for non-technical end-users.
- Converting scrapers into standalone desktop applications.
- Scaling scraping infrastructure using Docker and Kubernetes.
- Cost-efficient proxy management and bandwidth reduction strategies.
Main topics:
- Bypassing Cloudflare WAF and Turnstile CAPTCHAs.
- Creating UI-based scrapers for non-technical end-users.
- Converting scrapers into standalone desktop applications.
- Scaling scraping infrastructure using Docker and Kubernetes.
- Cost-efficient proxy management and bandwidth reduction strategies.
This article details the author's experience with Nushell, a terminal shell that presents data in a spreadsheet-like format, improving usability and productivity compared to traditional command-line interfaces. It covers installation, core concepts, benefits for everyday tasks, customization options, and limitations.
This article details how Nubank built its own in-house logging platform to address issues of cost, scalability, and control over their logging infrastructure. Initially reliant on a vendor solution, they found costs rising unpredictably and experienced limitations in observability and data retention.
To solve this, Nubank divided the project into two major steps: **The Observability Stream** (ingestion and processing) and the **Query & Log Platform** (storage and querying).
* **Observability Stream:** Fluent Bit for data collection, a Data Buffer Service for micro-batching, and an in-house Filter & Process Service.
* **Query & Log Platform:** Trino as the query engine, AWS S3 for storage, and Parquet for data format.
The new platform currently ingests 1 trillion logs daily, stores 45 PB of searchable data with a 45-day retention, and handles almost 15,000 queries daily. Nubank reports the platform costs 50% less than comparable market solutions while providing them with greater control, scalability, and the ability to customize features. The project underscored Nubank's value of challenging the status quo and leveraging a combination of open-source and in-house development.
To solve this, Nubank divided the project into two major steps: **The Observability Stream** (ingestion and processing) and the **Query & Log Platform** (storage and querying).
* **Observability Stream:** Fluent Bit for data collection, a Data Buffer Service for micro-batching, and an in-house Filter & Process Service.
* **Query & Log Platform:** Trino as the query engine, AWS S3 for storage, and Parquet for data format.
The new platform currently ingests 1 trillion logs daily, stores 45 PB of searchable data with a 45-day retention, and handles almost 15,000 queries daily. Nubank reports the platform costs 50% less than comparable market solutions while providing them with greater control, scalability, and the ability to customize features. The project underscored Nubank's value of challenging the status quo and leveraging a combination of open-source and in-house development.
APIs let you get at fascinating and useful treasure troves of data. Here’s a look at the wide world of APIs for finding and manipulating data in your applications.
This page details the command-line utility for the Embedding Atlas, a tool for exploring large text datasets with metadata. It covers installation, data loading (local and Hugging Face), visualization of embeddings using SentenceTransformers and UMAP, and usage instructions with available options.
Extract data from websites in LLM ready JSON or CSV format. Crawl or Scrape entire website with Website Crawler
An article discussing the importance of time series databases and data visualization tools like Grafana for managing and interpreting streams of data in various applications.
The author mentions several time series databases (TSDs) and visualization tools, focusing on their features, advantages, and some limitations. The article also provides an example of a Building Management and Control (BMaC) project that uses InfluxDB and Grafana for data visualization.
| Database | Description | Notable Features |
|-------------------|-------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------|
| InfluxDB | Partially open source, with version 3 being an edge data collector. | Shard-based storage, compaction levels, time series index, optional retention. |
| Apache Kudu | Column-based database optimized for multidimensional OLAP workloads. | Part of the Apache Hadoop ecosystem. |
| Prometheus | Developed at SoundCloud for metrics monitoring. | Written in Go, similar to InfluxDB v1 and v2. |
| RRDTool | All-in-one package with a circular buffer TSD that also does graphing. | Language bindings for various programming languages. |
| Graphite | Similar to RRDTool but uses a Django web-based application to render graphs. | Web-based graphing. |
| TimescaleDB | Extends PostgreSQL, supporting typical SQL queries with TSD functionality and optimizations. | Supports all typical SQL queries. |
The article also discusses Grafana as a popular tool for creating dashboards to visualize time series data, mentioning its compatibility with multiple TSDs and SQL databases. It concludes by highlighting the importance of understanding one's specific needs before choosing a TSD and visualization solution.
The author mentions several time series databases (TSDs) and visualization tools, focusing on their features, advantages, and some limitations. The article also provides an example of a Building Management and Control (BMaC) project that uses InfluxDB and Grafana for data visualization.
| Database | Description | Notable Features |
|-------------------|-------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------|
| InfluxDB | Partially open source, with version 3 being an edge data collector. | Shard-based storage, compaction levels, time series index, optional retention. |
| Apache Kudu | Column-based database optimized for multidimensional OLAP workloads. | Part of the Apache Hadoop ecosystem. |
| Prometheus | Developed at SoundCloud for metrics monitoring. | Written in Go, similar to InfluxDB v1 and v2. |
| RRDTool | All-in-one package with a circular buffer TSD that also does graphing. | Language bindings for various programming languages. |
| Graphite | Similar to RRDTool but uses a Django web-based application to render graphs. | Web-based graphing. |
| TimescaleDB | Extends PostgreSQL, supporting typical SQL queries with TSD functionality and optimizations. | Supports all typical SQL queries. |
The article also discusses Grafana as a popular tool for creating dashboards to visualize time series data, mentioning its compatibility with multiple TSDs and SQL databases. It concludes by highlighting the importance of understanding one's specific needs before choosing a TSD and visualization solution.
This video course introduces DuckDB, an open-source database for data analytics in Python. It covers creating databases from files (Parquet, CSV, JSON), querying with SQL and the Python API, concurrent access, and integration with pandas and Polars.
A guide to building a front-end data application using Taipy, comparing it to Streamlit and Gradio, and providing a step-by-step implementation of a sales performance dashboard.
