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        "author": "Germ\u00e1n Mu\u00f1oz",
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        "description": "# BanRep: Anal\u00edtica de Texto\n\n[banrep][pypi_banrep] es una librer\u00eda en Python para analizar conjuntos de documentos textuales.\n\n[pypi_banrep]: https://pypi.org/project/banrep/\n\n----\n\n## \ud83d\udcd6C\u00f3mo usar\n\nVisite la [documentaci\u00f3n][web_docs] para informaci\u00f3n detallada de uso.\n\n[web_docs]: https://munozbravo.github.io/banrep/\n\n| Gu\u00eda                       |                                  |\n|----------------------------|----------------------------------|\n| [Introducci\u00f3n][intro]      | Motivaci\u00f3n de la librer\u00eda        |\n| [Instalaci\u00f3n][instalacion] | C\u00f3mo instalar en su equipo       |\n| [Extracci\u00f3n][extraccion]     | C\u00f3mo usar para extracci\u00f3n de documentos    |\n| [Uso general][general]  | Funcionalidad principal de la librer\u00eda       |\n\n[intro]: https://munozbravo.github.io/banrep/intro/\n[instalacion]: https://munozbravo.github.io/banrep/instalacion/\n[extraccion]: https://munozbravo.github.io/banrep/uso_extraccion/\n[general]: https://munozbravo.github.io/banrep/uso_general/\n\n----\n\n## Instalaci\u00f3n\n\nSe requiere tener instalado [Python 3.7][web_python].\n\nSi es la primera vez que va a instalar este lenguaje de programaci\u00f3n, se recomienda instalarlo usando [Anaconda3][web_anaconda] o [Miniconda3][web_conda]. Siga las instrucciones de instalaci\u00f3n para su sistema.\n\n[web_python]: https://www.python.org/downloads/\n[web_anaconda]: https://www.anaconda.com/distribution/\n[web_conda]: https://conda.io/miniconda.html\n\nSe recomienda instalar en un entorno virtual para no interferir con otras instalaciones de python.\n\nTanto Anaconda como Miniconda instalan un programa llamado `conda`, para crear y activar un entorno virtual que instale `pip`.\n\nDesde la *l\u00ednea de comandos* ([Terminal][terminal] en macOS, [Anaconda Prompt][anacondocs] en windows):\n\n[terminal]: https://support.apple.com/guide/terminal/welcome/mac\n[anacondocs]: https://docs.anaconda.com/anaconda/install/verify-install/\n\n```bash\n# crear un entorno...\n~$ conda create --name entorno python=3.7 pip jupyterlab\n```\n\n```bash\n# confirmar que quiere descargar lo solicitado...\nProceed ([y]/n)? y\n```\n\n```bash\n# activar el entorno creado...\n~$ conda activate entorno\n```\n\n### pip\n\nUna vez activado el entorno, instalar usando `pip`. Esto instalar\u00e1 autom\u00e1ticamente las librer\u00edas que [banrep][pypi_banrep] requiere.\n\n```bash\n~$ pip install --upgrade banrep\n```\n\n### Modelo de Lenguaje Natural\n\nSe requiere un modelo pre-entrenado de [Spacy][spacy_models], que depende del idioma del texto que se quiera procesar.\n\n[spacy_models]: https://spacy.io/models\n\nExisten diversas formas de instalar, la m\u00e1s f\u00e1cil es usando `download`.\n\n```bash\n~$ python -m spacy download es_core_news_md\n```\n\nCuando se piensa usar el mismo modelo para diferentes proyectos, una alternativa es hacer una [instalaci\u00f3n manual][spacy_manual]: descargar el [archivo del modelo][spacy_esmd], guardarlo en el directorio deseado, y crear un [v\u00ednculo simb\u00f3lico][spacy_link] a dicho modelo.\n\n[spacy_manual]: https://spacy.io/usage/models#download-manual\n[spacy_esmd]: https://github.com/explosion/spacy-models/releases/download/es_core_news_md-2.1.0/es_core_news_md-2.1.0.tar.gz\n[spacy_link]: https://spacy.io/usage/models#usage-link\n\n### Verificar instalaci\u00f3n\nPuede verificar si [banrep][pypi_banrep] instal\u00f3 correctamente usando `python` o `jupyter lab` desde la l\u00ednea de comandos:\n\n```bash\n~$ python\n>>> from banrep.corpus import MiCorpus\n>>>\n```\n\nSi no aparece ning\u00fan error quiere decir que la instalaci\u00f3n fue exitosa.\n\n----\n\n\n",
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