91 lines
2.6 KiB
TypeScript
91 lines
2.6 KiB
TypeScript
/**
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*/
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async function main(
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args_raw : Array<string>
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) : Promise<void>
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{
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const outputs : Record<string, type_output> = {
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"sqlite": output_sqlite,
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"mysql": output_mysql,
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"backend-typescript": output_typescript,
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"jsonschema": output_jsonschema,
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};
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const arg_handler = new lib_plankton.args.class_handler(
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{
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"format": new lib_plankton.args.class_argument({
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"name": "format",
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"type": lib_plankton.args.enum_type.string,
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"kind": lib_plankton.args.enum_kind.volatile,
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"mode": lib_plankton.args.enum_mode.replace,
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"default": "sqlite",
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"parameters": {
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"indicators_long": ["format"],
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"indicators_short": ["f"],
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},
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"info": "output format",
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}),
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"schema": new lib_plankton.args.class_argument({
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"name": "schema",
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"type": lib_plankton.args.enum_type.boolean,
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"kind": lib_plankton.args.enum_kind.volatile,
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"mode": lib_plankton.args.enum_mode.replace,
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"default": false,
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"parameters": {
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"indicators_long": ["schema"],
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"indicators_short": ["s"],
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},
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"info": "print sindri JSON schema to stdout and exit",
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}),
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"help": new lib_plankton.args.class_argument({
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"name": "help",
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"type": lib_plankton.args.enum_type.boolean,
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"kind": lib_plankton.args.enum_kind.volatile,
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"mode": lib_plankton.args.enum_mode.replace,
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"default": false,
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"parameters": {
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"indicators_long": ["help"],
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"indicators_short": ["h"],
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},
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"info": "print help to stdout and exit",
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}),
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}
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);
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const args : Record<string, any> = arg_handler.read(lib_plankton.args.enum_environment.cli, args_raw.join(" "));
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if (args["help"]) {
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process.stdout.write(
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arg_handler.generate_help(
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{
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"programname": "sindri",
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"author": "Christian Fraß <frass@greenscale.de>",
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"description": "create data model scripts in different output formats (MySQL, SQLite, …) on basis of an abstract description; feed with .sindri.json file via stdin!",
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"executable": "sindri",
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}
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)
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);
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}
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else {
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if (args["schema"]) {
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process.stdout.write(
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JSON.stringify(input_schema(), undefined, "\t")
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);
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}
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else {
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const input_content : string = await lib_plankton.file.read_stdin();
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const input_data_raw : any = lib_plankton.json.decode(input_content);
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const input_data : type_input = input_normalize(input_data_raw);
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if (! outputs.hasOwnProperty(args["format"])) {
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throw (new Error("unhandled output format: " + args["format"]));
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}
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else {
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const output_content : string = outputs[args["format"]].render(input_data);
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process.stdout.write(output_content);
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}
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}
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}
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}
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main(process.argv.slice(2));
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