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Fanuc Robot Backup Call Graph Generator

Please upload a full MD backup in the form of a .zip file.

Backup size is limited to 15mb, and should not contain any directories.

The backup is not stored, and is only used to generate the graph. It is deleted after use.

\n \n

\n \n \n

\n\n \n\n\n `,\n { headers: { \"Content-Type\": \"text/html\" } },\n );\n }\n\n // Handle POST requests (file uploads)\n\n if (req.method === \"POST\") {\n const startTime = performance.now();\n\n const formData = await req.formData();\n const file = formData.get(\"Robot_Backup\") as File;\n\n if (!file) {\n return new Response(\"No file uploaded\", { status: 400 });\n }\n\n const maxSize = 15 * 1024 * 1024; // 15 MB in bytes\n if (file.size > maxSize) {\n return new Response(\"File is too large. Maximum size is 15 MB.\", { status: 400 });\n }\n\n // Read file content\n const fileContent = await file.arrayBuffer();\n\n // Unzip the file\n const zip = new JSZip();\n const contents = await zip.loadAsync(fileContent);\n\n // Check for directories in the zip\n const hasDirectories = Object.keys(contents.files).some(filename => contents.files[filename].dir);\n if (hasDirectories) {\n return new Response(\n \"Upload rejected: The zip file contains directories. Please upload a zip file with files only.\",\n { status: 400, headers: { \"Content-Type\": \"text/plain\" } },\n );\n }\n\n // Check for BACKDATE.DT file (case insensitive)\n const hasBackdateFile = Object.keys(contents.files).some(filename => filename.toLowerCase() === \"backdate.dt\");\n if (!hasBackdateFile) {\n return new Response(\"Upload rejected: The zip file does not contain a BACKDATE.DT file.\", {\n status: 400,\n headers: { \"Content-Type\": \"text/plain\" },\n });\n }\n\n // Set of excluded filenames (case insensitive)\n const excludedFiles = new Set([\n \"errcurr.ls\",\n \"-bckedt-.ls\",\n \"-bcked2-.ls\",\n \"-bcked3-.ls\",\n \"-bcked8-.ls\",\n \"-bcked9-.ls\",\n \"errmot.ls\",\n \"errhist.ls\",\n \"errpwd.ls\",\n \"errsys.ls\",\n \"errext.ls\",\n \"errapp.ls\",\n \"erract.ls\",\n \"errall.ls\",\n \"logbook.ls\",\n \"updtlog.ls\",\n \"errcomm.ls\",\n \"hist.ls\",\n ].map(filename => filename.toLowerCase()));\n\n // Filter .ls and .pc files, excluding the specified files\n const lsFiles = Object.keys(contents.files).filter(filename =>\n filename.toLowerCase().endsWith(\".ls\") && !excludedFiles.has(filename.toLowerCase())\n );\n const pcFiles = Object.keys(contents.files).filter(filename => filename.toLowerCase().endsWith(\".pc\"));\n const allFiles = new Set([...lsFiles, ...pcFiles].map(file => file.toLowerCase()));\n\n console.log(`Found ${lsFiles.length} .ls files and ${pcFiles.length} .pc files (excluding specified files)`);\n\n const relationships = new Map();\n const allNodes = new Set();\n\n // Add all .ls and .pc files as nodes first\n [...lsFiles, ...pcFiles].forEach(filename => {\n const nodeName = filename.slice(0, -3).toLowerCase(); // Remove .ls or .pc and convert to lowercase\n allNodes.add(nodeName);\n });\n\n const callRegex = /CALL\\s+(\\S+?)(?:\\s*\\(|\\s|$)/g;\n\n // Process files in parallel\n await Promise.all(lsFiles.map(async (filename) => {\n const fileContent = await contents.files[filename].async(\"text\");\n const lines = fileContent.split(\"\\n\");\n const callLines = lines.filter(line => line.includes(\"CALL\"));\n\n if (callLines.length > 0) {\n const caller = filename.slice(0, -3).toLowerCase();\n if (!relationships.has(caller)) {\n relationships.set(caller, new Set());\n }\n\n callLines.forEach(line => {\n let match;\n while ((match = callRegex.exec(line)) !== null) {\n const calledFunction = match[1].toLowerCase();\n relationships.get(caller).add(calledFunction);\n allNodes.add(calledFunction);\n }\n });\n }\n }));\n\n const nodes = Array.from(allNodes).map(file => ({\n data: {\n id: file,\n present: allFiles.has(file + \".ls\") || allFiles.has(file + \".pc\"),\n },\n }));\n\n const edges = [];\n relationships.forEach((calledFunctions, file) => {\n calledFunctions.forEach(calledFunction => {\n edges.push({\n data: {\n source: file,\n target: calledFunction,\n },\n });\n });\n });\n\n // Identify nodes with any edges (incoming or outgoing)\n const nodesWithEdges = new Set([\n ...edges.map(edge => edge.data.source),\n ...edges.map(edge => edge.data.target),\n ]);\n\n // Identify completely isolated nodes (no incoming or outgoing edges)\n const isolatedNodes = nodes.filter(node => !nodesWithEdges.has(node.data.id)).map(node => node.data.id);\n\n console.log(`Created ${nodes.length} nodes and ${edges.length} edges`);\n console.log(`Completely isolated nodes: ${isolatedNodes.length}`);\n\n const endTime = performance.now();\n const processingTime = ((endTime - startTime) / 1000).toFixed(2);\n\n // Prepare the text response\n let textResponse = `Thank you! Your Robot Backup file has been processed successfully.\\n`;\n textResponse += `Processing time: ${processingTime} seconds\\n\\n`;\n textResponse += `Nodes: ${nodes.length}, Edges: ${edges.length}\\n`;\n textResponse += `Completely isolated nodes: ${isolatedNodes.length}\\n`;\n\n const graphData = { nodes, edges, isolatedNodes };\n\n // Prepare the full response\n const response = {\n text: textResponse,\n graphData: graphData,\n };\n\n return new Response(JSON.stringify(response), { headers: { \"Content-Type\": \"application/json\" } });\n }\n\n return new Response(\"Method not allowed\", { status: 405 });\n}",["D",1730122543853],"version","currentUserHasLiked","referenceCount","dependencyCount","commentCount","prCount","mergedPr",{"_97":98,"_102":103},"forkedVal",{"_95":150,"_97":151,"_125":126,"_140":152,"_153":-5},"e10b9b42-7aba-11ef-9b9a-de64eea55b61","synapticrobotics",103,"prDisabledHint","interval","description","An interactive, runnable TypeScript val by EnergyAddict","latestEvaluation","slug","EnergyAddict/RobotBackupCallGraph","versions",[162],{"_99":163,"_140":32,"_164":165},["D",1730122543853],"n","1","hasNext","routes/_app","actionData","errors"]