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YamilQuery-ExcelAnalizer\n\nPermite analizar y procesar grandes volumentes de información de archivos xls, xlsx y csv, mediante archivos de configuración JSON.\n\n+ Este analizador permite lo siguiente.\n  - Leer ficheros xls, xslx y csv\n  - Obtener datos de columnas y celdas especificando criterios o condiciones\n  - Aplicar filtros a los datos obtenidos y almacenar el resultado en un objeto\n\n### Requerimientos\n\nYamilQuery-ExcelAnalizer requiere:\n\n* [YamQuery-Excel](https://www.npmjs.com/package/yamQuery-excel) \n\n### Instalación\n\nYamilQuery-ExcelAnalizer requiere [Node.js](https://nodejs.org/) v4+ para ejecutarse correctamente.\n\n```sh\n$ npm install yamquery-excelanalizer --save\n```\n\n### Uso\n\nEl analizador de archivos utiliza archivos de configuración en formato json.\nA continuación un ejemplo con la estructura requerida:\n\n###### example.json\n```sh\n{\n\t\"file\": \"./test/xlsx/example.xlsx\",\n\t\"resource_name\": \"EXAMPLE YamQuery-ExcelAnalizer\",\n\t\"sheet_name\": \"usageReport (14)\",\n\t\"conditions\": [{\n\t\t\"column\": 0,\n\t\t\"alias\": \"information\",\n\t\t\"where\": {\n\t\t\t\"contains\": \"Account \"\n\t\t}\n\t}],\n\t\"results\": [{\n\t\t\"alias\": \"id_information\",\n\t\t\"column\": 0,\n\t\t\"regex\": \"\\\\d+\"\n\t}, {\n\t\t\"alias\": \"information\",\n\t\t\"column\": 0\n\t}, {\n\t\t\"alias\": \"jan-2016\",\n\t\t\"column\": 10,\n\t\t\"relative_y\": 2\n\t}, {\n\t\t\"alias\": \"feb-2016\",\n\t\t\"column\": 11,\n\t\t\"relative_y\": 2\n\t}, {\n\t\t\"alias\": \"mar-2016\",\n\t\t\"column\": 12,\n\t\t\"relative_y\": 2\n\t}, {\n\t\t\"alias\": \"abr-2016\",\n\t\t\"column\": 13,\n\t\t\"relative_y\": 2\n\t}]\n}\n```\nLas opciones del archivo de configuración son:\n+ __file__ (Opcional): Ruta del archivo a analizar\n+ __directory__ (Opcional): Ruta del directorio donde se localizan los archivos a analizar\n+ __sheet_name__ (Opcional): Nombre de la hoja de excel por analizar\n+ __conditions__: Objeto con criterios o condiciones necesarias que deben cumplir las celdas para obtener los resultados deseados\n  - __column__: Especifica el número de columna donde buscará dentro de la fila en la ejecución actual\n  - __cell__: Especifica una fila y columna en particular\n  - __alias__: Alias para identificar el criterio\n  - __where__: Objeto llave-valor con criterio y valor esperado o puede especificar un solo Criterio como tipo String \n    - __contains__ (Object)\n    - __isNumber__ (String)\n    - __equals__ (Object)\n    - __notEquals__ (Object)\n+ __results__: Objeto con posiciones de las columnas, celdas o rangos a obtener cuando se han cumplido todas las condiciones\n  - __column__: Especifica el número de columna donde buscará dentro de la fila en la ejecución actual\n  - __column_range__: Objecto con dos valores de rango de columnas (Se sumarán para el resultado)\n  - __cell__: Especifica una fila y columna en particular\n  - __alias__: Otorga un alias al resultado, mismo que será devuelto al final\n  - __relative_y__: Cuando el valor que requieres no se encuentra en la fila actual puedes incrementar o disminuir el indice de la fila de donde obtendrá el valor\n\nNota: Al menos una de las opciones file o directory deberán especificarse en el archivo de configuración\n##### Obtener resultados\nInvocamos al analizador para obtener los resultados.\n###### example.js\n```sh\nanalizer = require('yamquery-excelanalizer')\nvar configAnalizer = JSON.parse(fs.readFileSync('./config/example.json', 'utf8'))\nanalizer.getResults(configAnalizer).then(function(data){\n\tconsole.log(data) // Your result is ready!\n})\n```\n\n##### Usar con co generator\nGracias a Promises (https://www.promisejs.org/) podemos utilizar yield de la siguiente forma:\n###### example.js\n```sh\nco = require('co')\nanalizer = require('yamquery-excelanalizer')\nco(function*(){\n\tvar configAnalizer = JSON.parse(fs.readFileSync('./config/example.json', 'utf8'))\n\tvar data = yield analizer.getResults(configAnalizer)\n\tconsole.log(data) // Your result is ready!\n})\n```\n\n\n### Test\nRun ```npm test 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