Project
Reverse Dependencies for csv
The projects listed here declare csv as a runtime or development dependency
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plucks each line of the csv input
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returns a csv by unique keys, can be index or name
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sorts csv by keys
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Scripts for converting Digital Scriptorium member data to the DS import spreadsheet format and for extracting values for authority file reconciliation.
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Posts data from automation systems to dubbletrack.com. Requires dubbletrack account
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This module provides CSV table adapter for duckdb. You can access CSV like as duckdb table by using this module.
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Access the dumbstockapi.com website
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Provides a unified interface across data warehouses to connect, execute, and introspect. This is not an ORM but a fast
integrationg solution. It is quite easy to add new database adapters. Supports popular cloud warehouses too.
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A utility for downloading and parsing e621's exports
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EasyCols is a flexible command-line utility for extracting specific columns from
structured text data in various formats (CSV, TSV, table, plain text). It supports
sophisticated parsing options including quote handling, comment stripping, header
processing, and language-specific comment patterns....
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Simplify the way you fetch model data, making coding smoother and data exporting handling a breeze
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A library for easily generating seed data in Ruby on Rails from .CSV files
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Find and parse manifests
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A command line tool to create Pivotal Tracker stories from CSV file
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ElaineCrud provides a reusable BaseController and views to quickly generate CRUD interfaces for any ActiveRecord model with minimal configuration.
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EnumCSV exposes a single method, csv, for easily creating CSV
output/files from enumerable objects.
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Search GitHub code or gists for .env files containing high-entropy secrets like tokens and keys.
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Ruby implementation of the parsing and computation of ephemerides from NASA/JPL Development Ephemerides DE4xx and IMCCE INPOP
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Etl Integrations is a comprehensive Ruby gem designed to facilitate seamless connectivity between various data sources and SaaS platforms.
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Measures quality metrics like faithfulness, relevance, context precision, and answer correctness for LLM and RAG applications. Think Ragas or DeepEval for Ruby.
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