How to use the cli-progress.SingleBar function in cli-progress

To help you get started, we’ve selected a few cli-progress examples, based on popular ways it is used in public projects.

Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.

github nvuillam / sfdx-essentials / src / commands / essentials / change-dependency-version.ts View on Github external
// Get input arguments or default values
    this.namespace = flags.namespace;
    this.majorversion = flags.majorversion;
    this.minorversion = flags.minorversion;
    this.folder = flags.folder || '.';
    if (flags.verbose) {
      this.verbose = true;
    }
    console.log(`Initialize update of dependencies in ${this.folder} with ${this.namespace} ${this.majorversion}.${this.minorversion}`);

    // Read files
    const fileList = glob.sync('**/*.xml');

    // Progress bar
    // @ts-ignore
    this.progressBar = new cliProgress.SingleBar({
      format: '{name} [{bar}] {percentage}% | {value}/{total} | {file} ',
      stopOnComplete: true
    });
    if (this.progressBar.terminal.isTTY()) {
      this.progressBar.start(fileList.length, 0, { name: 'Progress', file: 'N/A' });
    }

    // Replace dependencies in files
    let updatedNb = 0;
    const parser = new xml2js.Parser();
    const promises = [];
    for (const sfdxXmlFile of fileList) {
      const filePromise = new Promise((resolve, reject) => {
        fs.readFile(sfdxXmlFile, (err, data) => {
          // Parse XML file
          parser.parseString(data, (err2, parsedXmlFile) => {
github nvuillam / sfdx-essentials / src / commands / essentials / uncomment.ts View on Github external
this.verbose = true;
    }

    console.log('Starting sfdx essentials:uncomment with uncomment key "' + this.uncommentKey + '"');

    // List apex classes
    const fetchClassesExpression = this.folder + '/classes/*.cls';
    const customApexClassFileNameList = glob.sync(fetchClassesExpression);

    // List aura items
    const fetchAuraExpression = this.folder + '/aura/**/*.js';
    const customAuraFileNameList = glob.sync(fetchAuraExpression);

    // Progress bar
    // @ts-ignore
    this.progressBar = new cliProgress.SingleBar({
      format: '{name} [{bar}] {percentage}% | {value}/{total} | {file} ',
      stopOnComplete: true
    });
    if (this.progressBar.terminal.isTTY()) {
      this.progressBar.start(customApexClassFileNameList.length + customAuraFileNameList.length, 0, { name: 'Progress', file: 'N/A' });
    }

    // Replace commented lines in each class
    customApexClassFileNameList.forEach((customApexClassFileName) => {
      this.processFile(customApexClassFileName);
      if (!this.verbose && this.progressBar.terminal.isTTY()) {
        this.progressBar.increment();
      }
    });

    // Replace commented lines in each aura item
github alibaba / pipcook / packages / pipcook-plugins-image-class-data-access / src / index.ts View on Github external
const concatenateDataFlows = async (fileNames: string[], imgSize: number[], oneHotMap: any, dataFlows: any[], type: string, imagePath: string) => {
  console.log(`access ${type} image data...`);
  const bar1 = new _cliProgress.SingleBar({}, _cliProgress.Presets.shades_classic);
  bar1.start(fileNames.length, 0);
  for (let j = 0; j < fileNames.length; j++) {
    const jsonData = await parseAnnotation(fileNames[j]);
    bar1.update(j);
    let image = await Jimp.read(path.join(imagePath, jsonData.annotation.filename[0]));
    image = image.resize(imgSize[0], imgSize[1]);
    const trainImageBuffer = await image.getBufferAsync(Jimp.MIME_JPEG);
    const imageArray = new Uint8Array(trainImageBuffer);
    let label:any = jsonData.annotation.object[0].name[0];
    if (Object.keys(oneHotMap).length > 1) {
      label = tf.oneHot(tf.scalar(oneHotMap[label], 'int32'), Object.keys(oneHotMap).length);
    }
    dataFlows.push({
      xs: tf.cast(tf.node.decodeImage(imageArray, 3), 'float32'),
      ys: label
    })
github DSpace / dspace-angular / scripts / sync-i18n-files.js View on Github external
function syncFileWithSource(pathToTargetFile, pathToOutputFile) {
  const progressBar = new _cliProgress.SingleBar({}, _cliProgress.Presets.shades_classic);
  progressBar.start(100, 0);

  const sourceLines = [];
  const targetLines = [];
  const existingTargetFile = readFileIfExists(pathToTargetFile);
  existingTargetFile.toString().split("\n").forEach((function (line) {
    targetLines.push(line.trim());
  }));
  progressBar.update(10);
  const sourceFile = readFileIfExists(program.sourceFile);
  sourceFile.toString().split("\n").forEach((function (line) {
    sourceLines.push(line.trim());
  }));
  progressBar.update(20);
  const sourceChunks = createChunks(sourceLines, progressBar, false);
  const targetChunks = createChunks(targetLines, progressBar, true);
github fuzz-lightyear / fuzz-lightyear / bin / cmds / run.js View on Github external
exports.handler = async function (argv) {
  const userFunctions = require(argv.module)

  var userConfig = require(argv.config)
  if (argv.operations) userConfig.numOperations = argv.operations
  if (argv.seed) userConfig.seedNumber = argv.seed
  if (argv.debug) userConfig.debug = argv.debug
  if (argv.iterations) userConfig.numIterations = argv.iterations

  const failingTestRoot = p.join(p.dirname(argv.module), 'test', 'autogenerated','failing')

  const { events, run } = create(userFunctions, userConfig)
  var bar = null

  if (!argv.debug) {
    bar = new progress.SingleBar()
    bar.start(argv.iterations || userConfig.numIterations, 0)
    events.on('progress', () => bar.increment())
  }
  try {
    await run()
    if (bar) bar.stop()
    console.log()
    console.log('Fuzzing Succeeded.')
    console.log()
  } catch (err) {
    if (bar) bar.stop()
    if (!err[consts.FuzzError]) {
      console.error('Fuzzing produced unexpected error:', err)
    } else {
      const { testCase, signature } = await generateTestCase(err, failingTestRoot, argv)
      console.log('\nFailing Test:\n')
github alibaba / pipcook / packages / pipcook-plugins-bayesian-classifier-model-train / src / index.ts View on Github external
const bayesianClassifierModelTrain: ModelTrainType = async (data: UniformTfSampleData, model: PipcookModel): Promise => {
  const {trainData, metaData} = data;
  assertionTest(data, trainData, metaData);
  
  const trainModel = model.model;

  let count = 0;
  await trainData.forEachAsync((e: any) => {
    count++;
  });
  const bar1 = new _cliProgress.SingleBar({}, _cliProgress.Presets.shades_classic);
  bar1.start(count, 0);
  count = 0;
  await trainData.forEachAsync((e: any) => {
    count = count + 1;
    bar1.update(count);
    const trainX = e[metaData.feature.name].dataSync()[0];
    const trainY = e[metaData.label.name].dataSync()[0];
    trainModel.learn(trainX, trainY);
  });
  bar1.stop();

  return {
    ...model,
    model: trainModel
  }
}
github ChiChou / bagbak / go.js View on Github external
constructor(session, size, fd) {
    this.session = session
    this.size = size
    this.fd = fd

    if (size > 4 * 1024 * 1024) {
      this.bar = new progress.SingleBar(BAR_OPTS)
      this.bar.start(size, 0)
      this.verbose = true
    }

  }
github alibaba / pipcook / packages / pipcook-core / src / utils / publicUtils.ts View on Github external
return new Promise((resolve, reject) => {
    const bar1 = new _cliProgress.SingleBar({}, _cliProgress.Presets.shades_classic);
    const file = fs.createWriteStream(fileName);
    let receivedBytes = 0
    request.get(url)
      .on('response', (response: any) => {
        const totalBytes = response.headers['content-length'];
        bar1.start(totalBytes, 0);
      })
      .on('data', (chunk: any) => {
        receivedBytes += chunk.length;
        bar1.update(receivedBytes);
      })
      .pipe(file)
      .on('error', (err: Error) => {
          fs.unlink(fileName);
          bar1.stop();
          reject(err);

cli-progress

easy to use progress-bar for command-line/terminal applications

MIT
Latest version published 2 years ago

Package Health Score

73 / 100
Full package analysis