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分类目录: tools data engineering

显示第 1–24 个,共 65 个

tools data engineering Python 清除筛选

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GitHub

zarr-python

davila7

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.

GitHub

senior-data-engineer

davila7

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...

GitHub

zarr-python

K-Dense-AI

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.

GitHub

temporal-python-pro

rmyndharis

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...

GitHub

databricks-python-sdk

databricks-solutions

Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.

GitHub

creating-bauplan-pipelines

aiskillstore

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.

GitHub

python-data-classes

TheBushidoCollective

Use when Python data modeling with dataclasses, attrs, and Pydantic. Use when creating data structures and models.

GitHub

sap-hana-cloud-data-intelligence

secondsky

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...

GitHub

data-transform

vuralserhat86

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...

GitHub

bigquery

lanej

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...

GitHub

data-analysis

lovedragonball

Data processing, analysis, and visualization with Python/JavaScript. Use for data exploration, pandas operations, chart generation, and insights extraction.

GitHub

python-backend

anton-abyzov

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...

GitHub

data-pipeline-operations

Klimabevaegelsen

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...

GitHub

dbt-materializations

sfc-gh-dflippo

Choosing and implementing dbt materializations (ephemeral, view, table, incremental, snapshots, Python models). Use this skill when deciding on materialization strategy, implementing incremental models, setting...

GitHub

zarr-python

lifangda

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.

GitHub

csv-data-wrangler

404kidwiz

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...

GitHub

polars-expertise

DeevsDeevs

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...

GitHub

grey-haven-database-conventions

greyhaven-ai

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...

GitHub

everyrow-sdk

futuresearch

Helps write Python code using the everyrow SDK for AI-powered data processing - transforming, deduping, merging, ranking, and screening dataframes with natural language instructions

GitHub

pytidb

pingcap

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...

GitHub

data-analysis

supercent-io

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...

GitHub

pytd

treasure-data

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。

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