bouclem

Generate Python SDK setup + CRUD + bulk + paging snippets using official patterns.

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Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads

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Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.

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Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.

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Data pipeline architecture, ETL/ELT patterns, data modeling, and production data platform design

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Guidelines for data analysis and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.

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Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

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Snowflake, BigQuery, Redshift, dimensional modeling, and modern data warehouse architecture

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Best practices and guidelines for Apache Kafka event streaming and distributed messaging

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Best practices for SciPy scientific computing, optimization, signal processing, and statistical analysis in Python

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Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods.

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