人类出行行为塑造了人们对资源、机会与服务的可及性，因此出行数据成为研究空间与社会不平等的重要视角。尽管官方开放出行数据集日益丰富，其研究潜力却常因数据获取、标准化与处理所需的技术门槛过高而难以实现，进而挤占实质性分析的时间与精力。为此，我们推出 pySpainMobility——一个 Python 软件包，可自动获取并标准化西班牙多空间分辨率、多人口统计分层的开放出行数据，从而简化全国尺度、可复现的分析流程。利用该工具包，我们基于2023年四季中四个代表性周的街区级起源-目的地（origin-destination）流量数据，研究西班牙省际网络中按收入分层的出行不平等现象。我们构建了收入特异性的出行图层，并发现社会经济分层深度嵌入国家出行系统结构之中：低收入群体的出行高度集中于少数目的地，且空间可达范围较短；而高收入群体则能通达更广、更远的目的地层级。低收入与高收入出行图层在各季节均呈现弱对齐的目的地层级结构，表明不同收入群体并非在共享同一出行地理空间而仅在出行量上存在差异，而是实际遵循各自独立的出行地理格局。进一步分析显示，各目的地省份所接收旅客的收入构成存在系统性差异：若干省份所吸引的旅客收入分布显著偏离全国季节性基线，偏向某一收入群体。这些结果表明，官方开放出行数据结合易用工具，可有效支撑空间不平等研究。

Human mobility shapes access to resources, opportunities, and services, making movement data a powerful lens for studying spatial and social inequality. Yet despite the growing availability of official open mobility datasets, their research potential is rarely realized because the technical overhead of retrieving, harmonizing, and processing them often crowds out substantive analysis. To address this, we introduce pySpainMobility, a Python package that automates the retrieval and harmonization of Spain's open mobility data across spatial resolutions and demographic strata, streamlining national-scale, reproducible analysis. Using the package, we study income-stratified mobility inequality across Spain's inter-province network, drawing on district-level origin-destination flows for four representative weeks spanning the seasons of 2023. We construct income-specific mobility layers and show that socioeconomic stratification is deeply embedded in the structure of the national mobility system: low-income mobility is disproportionately concentrated in a narrow set of destinations and shorter in spatial reach, while high-income groups access a broader and more distant hierarchy of destinations. Low- and high-income layers consistently follow weakly aligned destination hierarchies across seasons, indicating that income groups navigate distinct mobility geographies rather than a shared one at different volumes. We further show that destination provinces themselves differ systematically in the income composition of the travelers they receive, with several provinces attracting arrivals disproportionately skewed toward one income group relative to the national seasonal baseline. These results demonstrate how official open mobility data, combined with accessible tooling, can be operationalized to reveal spatial inequality as a structural property of national mobility networks.