{ "cells": [ { "cell_type": "markdown", "id": "e1c3b239-d45e-43f6-9d2d-64ee46e75e61", "metadata": {}, "source": [ "1. Find available DBs\n", "2. Save list\n", "3. Refine selection\n", "4. Save selection\n", " 1. Generate `databases.json` for use in vs code extension\n", " 2. Generate `list-databases.json` for use by gh-mrva client\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "042947ea-8514-4318-a768-7826e494dd43", "metadata": {}, "outputs": [], "source": [ "from db_load_fs import dbdf_from_tree" ] }, { "cell_type": "code", "execution_count": 2, "id": "43a7f75f-c3ac-4e23-b30a-096f7119edf6", "metadata": {}, "outputs": [], "source": [ "df = dbdf_from_tree()" ] }, { "cell_type": "code", "execution_count": 5, "id": "e13adbb1-c876-4712-a010-36983f6b56b6", "metadata": { "editable": true, "scrolled": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2024-07-10 08:33:35 [DEBUG] /Users/hohn/work-gh/mrva/mrvacommander/client/venv/lib/python3.11/site-packages/ipykernel_launcher.py -f /Users/hohn/Library/Jupyter/runtime/kernel-8e934521-9e0d-469f-aa73-3fa1f8b9808a.json\n", "2024-07-10 08:33:35 [DEBUG] Hostname: ghm3\n", "2024-07-10 08:33:35 [DEBUG] pytest: False, flask-debug: False\n", "2024-07-10 08:33:35 [DEBUG] pre-locking index columns ([]) to settings[2]\n", "2024-07-10 08:33:35 [DEBUG] Starting new HTTP connection (1): ghm3:40000\n", "2024-07-10 08:33:35 [DEBUG] http://ghm3:40000 \"GET /health HTTP/11\" 200 2\n", "2024-07-10 08:33:35 [DEBUG] Starting new HTTP connection (1): ghm3:40000\n", "2024-07-10 08:33:35 [DEBUG] http://ghm3:40000 \"GET /health HTTP/11\" 200 2\n" ] }, { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ " import dtale\n", " dtale.show(df)\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "29beb747-fbff-4bc9-b304-3d921ca0232b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[]], dtype=object)" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df.hist(column='size', bins=100)\n" ] }, { "cell_type": "code", "execution_count": 12, "id": "2441f24c-e5c9-42da-9728-d7b115675648", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2024-07-10 08:36:32 [DEBUG] Loaded backend widget version unknown.\n" ] }, { "data": { "text/plain": [ "array([[]], dtype=object)" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "bbacd6711fb74eeea6325aea9bb38a86", "version_major": 2, "version_minor": 0 }, "image/png": 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