Datasets tutorial
Whether you are building quantitative trading algorithms, backtesting historical strategies, or developing financial machine learning models, reliable data is your foundation. The algoseek RESTful API provides seamless integration with a massive library of institutional-grade financial datasets, including tick-by-tick US Equities, OPRA Options, and deep reference data. This guide is designed to get you authenticated and making your first data requests in minutes. By the end of these tutorials, y
Fetch Data#
This tutorial covers how to pull tick-by-tick US Equities Trade and Quote (TAQ) data for a specific ticker and date. The examples below use 2023-03-01, as this falls within the demo data period and is accessible to most clients for free.
Query API Metadata#
A tutorial on navigating the algoseek Datasets API metadata endpoints.
Understand Data Access Rules#
The GET /api/v1/account/my/data-access-rules endpoint helps professional and academic users audit their active subscriptions and constraints. It retrieves a comprehensive list of datasets currently associated with your account, along with specific access constraints such as permitted date ranges and ticker universes.
How to Query Reference Data#
Because tickers can change over time due to corporate events, you should rely on algoseek's unique SecId for historical accuracy. This tutorial shows how to query the Lookup File.
Manage Pagination and Parameters#
Understand how to handle large datasets efficiently using `limit`, `offset`, column filtering, and sorting modifiers.
Customize Data Output#
To make your data processing more efficient, you can use query parameters to select specific columns, sort the results, handle pagination, and download the data directly as a CSV file.
Data Filtering#
When building institutional-grade financial applications, backtesting systematic trading models, or conducting quantitative research, retrieving the exact slice of data you need is critical.
Advanced Filtering#
The following section explains how to apply column-level modifiers to fine-tune your data requests using the algoseek Datasets API. By appending specific operators to column names in your query string, you can filter for specific price ranges, volume thresholds, or ticker patterns directly at the endpoint level.