Project
Reverse Dependencies for csv
The projects listed here declare csv as a runtime or development dependency
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Daru (Data Analysis in RUby) is a library for analysis, manipulation and visualization
of data. Daru works seamlessly accross interpreters and leverages interpreter-specific
optimizations whenever they are available.
It is the default data storage gem for all the statsample gems (glm, timeseries...
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Execute SQL statements against Databricks SQL Warehouse with synchronous and asynchronous polling support, inline results, and external link downloads.
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INPUT, FILTER, OUTPUT data with RULES and code
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Scaffolding to make importing data easy
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DSL for manipulating tabular data
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Parse German DATANORM files like you belong to the 90s
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A mountable Rails engine providing a complete data import workflow: upload/configure, preview with validation, and import. Supports CSV, JSON, XLSX, and API sources with a simple DSL for defining import targets.
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将 Rails 项目的数据库 schema 导出为文档,支持 ruby, sql, csv, excel 格式
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DBViewer is a mountable Rails engine that provides a simple interface to view database tables and their records.
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A production-grade decision agent that provides deterministic rule evaluation, conflict resolution, and full audit replay capabilities. Framework-agnostic and AI-optional.
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DSL for rendering CSVs from an array of objects
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Handling of references and definitions with asciidoctor
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This gem provides a suite of utilities for developers to enhance their productivity.
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A production-grade Ruby SDK for Dhan API v2 built for algo trading, portfolio monitoring, and live trading systems. Provides typed models, token lifecycle management, dry-validation contracts, resilient WebSocket streaming, and safety-focused order workflows for Ruby applications.
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Returns a report on the health of your markdown documentation. The generated report is a CSV.
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a collection of gems
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evaluates some ruby code on all lines of the csv input
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evaluates some ruby code on each line of the csv input
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maps a csv file to another csv file
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merges multiple csv files with headers
e.g. `csv-merge users_1.csv users_2.csv users.csv`
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