zarr-python
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
按技能名称、说明或 GitHub 作者匹配的结果。
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data mode...
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
AWS DynamoDB single-table design, GSI patterns, SDK v3 TypeScript/Python
Master Temporal workflow orchestration with Python SDK. Implements durable workflows, saga patterns, and distributed transactions. Covers async/await, testing strategies, and production deployment. Use PROACTIV...
Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.
Creates bauplan data pipeline projects with SQL and Python models. Use when starting a new pipeline, defining DAG transformations, writing models, or setting up bauplan project structure from scratch.
Use when Python data modeling with dataclasses, attrs, and Pydantic. Use when creating data structures and models.
Develops data processing pipelines, integrations, and machine learning scenarios in SAP Data Intelligence Cloud. Use when building graphs/pipelines with operators, integrating ABAP/S4HANA systems, creating repl...
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migra...
Use bigquery CLI (instead of `bq`) for all Google BigQuery and GCP data warehouse operations including SQL query execution, data ingestion (streaming insert, bulk load, JSONL/CSV/Parquet), data extraction/expor...
Data processing, analysis, and visualization with Python/JavaScript. Use for data exploration, pandas operations, chart generation, and insights extraction.
Python backend developer for FastAPI, Django, Flask APIs with SQLAlchemy, Django ORM, Pydantic validation. Implements REST APIs, async operations, database integration, authentication, data processing with pand...
Activates when working with Python data pipelines, GCS operations, or medallion architecture (Bronze/Silver/Gold). Use this skill for: running pipelines, debugging data transformations, GCS uploads/downloads, d...
Choosing and implementing dbt materializations (ephemeral, view, table, incremental, snapshots, Python models). Use this skill when deciding on materialization strategy, implementing incremental models, setting...
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
Expert in high-performance CSV processing, parsing, and data cleaning using Python, DuckDB, and command-line tools. Use when working with CSV files, cleaning data, transforming datasets, or processing large tab...
This skill should be used when the user asks about Polars DataFrame library (Apache Arrow) for Python or Rust. Triggers: "polars expressions", "lazy vs eager", "scan_parquet streaming", "convert pandas to polar...
Apply Grey Haven database conventions - snake_case fields, multi-tenant with tenant_id and RLS, proper indexing, migrations for Drizzle (TypeScript) and SQLModel (Python). Use when designing schemas, writing da...
Implement a Python connector that conforms to the LakeflowConnect interface for data ingestion.
Helps write Python code using the everyrow SDK for AI-powered data processing - transforming, deduping, merging, ranking, and screening dataframes with natural language instructions
PyTiDB (pytidb) setup and usage for TiDB from Python. Covers connecting, table modeling (TableModel), CRUD, raw SQL, transactions, vector/full-text/hybrid search, auto-embedding, custom embedding functions, and...
Analyze datasets to extract insights, identify patterns, and generate reports. Use when exploring data, creating visualizations, or performing statistical analysis. Handles CSV, JSON, SQL queries, and Python pa...
Expert assistance for using pytd (Python SDK) to query and import data with Treasure Data. Use this skill when users need help with Python-based data analysis, querying Presto/Hive, importing pandas DataFrames,...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。