Top 10 Examples of "spark-md5 in functional component" in JavaScript

function compareHashMD5({
    obj,
    clone
}) {
    // equal
    const hash1 = hash(JSON.stringify(obj));
    const hash2 = hash(JSON.stringify(clone));
    assert.equal(hash1, hash2);

    // not equal
    const hash3 = hash(JSON.stringify(obj));
    const hash4 = hash(JSON.stringify(checkObj));
    assert.notEqual(hash3, hash4);

    return;
}

function compareHashMD5({
    obj,
    clone
}) {
    // equal
    const hash1 = hash(JSON.stringify(obj));
    const hash2 = hash(JSON.stringify(clone));
    assert.equal(hash1, hash2);

    // not equal
    const hash3 = hash(JSON.stringify(obj));
    const hash4 = hash(JSON.stringify(checkObj));
    assert.notEqual(hash3, hash4);

    return;
}

text: "Married"
        },
        managingOrganization: {
          identifier: {
            $class: "org.fhir.datatypes.Identifier",
            use: "usual",
            system: "Blockchain:Provider",
            value: "Provider::Provida"
          }
        }
      };
      // Hash the object and set the ID to the hash. This creates a unique ID with low chance of collision, which is good enough for our purposes here.
     
      // USE THIS TO CREATE NEW PATIENTS. THIS IS COMMENTED OUT TO REUSE THE SAME DEFAULT PATIENT ID
      json.id = "resource:org.fhir.core.Patient#com.instamed.patient.".concat(this.first_name, "_", this.last_name, "_",
        Spark.hash(JSON.stringify(json)).toString().substring(0,8)
      );
     
      
      json.identifier[0].value = json.id;
      this.patient_id = json.id.toString();
      this.$emit("saveFhir", {name: 'fhir_patient', data: json})
      return json;
    },
    savePatient() {

export const hashFile = (file, callback) => {
	let blobSlice = File.prototype.slice || File.prototype.mozSlice || File.prototype.webkitSlice,
		chunkSize = 2097152,                             // Read in chunks of 2MB
		chunks = Math.ceil(file.size / chunkSize),
		currentChunk = 0,
		spark = new SparkMD5.ArrayBuffer(),
		fileReader = new FileReader();

	fileReader.onload = function (e) {
		spark.append(e.target.result);                   // Append array buffer
		currentChunk++;

		if (currentChunk < chunks) {
			loadNext();
		} else {
			callback(spark.end());
		}
	};

	fileReader.onerror = function () {
		console.warn('oops, something went wrong.');
	};

return (dispatch, getState) => {
    // If the text box is empty
    if (text.trim().length <= 0) return;

    const id = md5.hash(text);
    // Redux thunk's middleware receives the store methods `dispatch`
    // and `getState` as parameters
    const { topic } = getState();
    const data = {
      count: 1,
      id,
      text
    };

    // Conditional dispatch
    // If the topic already exists, make sure we emit a dispatch event
    if (topic.topics.filter(topicItem => topicItem.id === id).length > 0) {
      // Currently there is no reducer that changes state for this
      // For production you would ideally have a message reducer that
      // notifies the user of a duplicate topic
      return dispatch(createTopicDuplicate());

exports.MD5 = function (string) {
  /* istanbul ignore else */
  if (!process.browser) {
    return crypto.createHash('md5').update(string).digest('hex');
  } else {
    return Md5.hash(string);
  }
};

.then(function (results) {
        removeCirculars(results.resolved);

        // Fix circular references
        _.each(results.refs, function (refDetails, refPtr) {
          if (refDetails.circular) {
            _.set(results.resolved, JsonRefs.pathFromPtr(refPtr), {});
          }
        });

        cacheEntry.referencesMetadata = results.refs;
        cacheEntry.resolved = results.resolved;
        cacheEntry.resolvedId = SparkMD5.hash(JSON.stringify(results.resolved));

        callback();
      })
      .catch(callback);

function md5SingleFile(file: object, cb): string {
  const blobSlice =
    File.prototype.slice ||
    File.prototype.mozSlice ||
    File.prototype.webkitSlice;
  const chunkSize = 2097152; // Read in chunks of 2MB
  const chunks = Math.ceil(file.size / chunkSize);
  let currentChunk = 0;
  const spark = new SparkMD5.ArrayBuffer();
  const fileReader = new FileReader();

  function loadNext() {
    const start = currentChunk * chunkSize;
    const end = start + chunkSize >= file.size ? file.size : start + chunkSize;

    fileReader.readAsArrayBuffer(blobSlice.call(file, start, end));
  }

  fileReader.onload = event => {
    // 该值记录了对某个文件进行MD5操作的进度
    const percent = parseFloat((currentChunk / chunks * 100).toFixed(1));

    spark.append(event.target.result); // Append array buffer

    currentChunk++;

return new Promise(function(resolve, reject) {
        var totalSize = src.size;
        var chunkSize = opts && opts.chunkSize || DEFAULT_CHUNK_SIZE;
        var file = src;
        var count = Math.ceil (totalSize/chunkSize);
        var current = 0;

        var blobSlice = File.prototype.slice || File.prototype.mozSlice || File.prototype.webkitSlice;
        var startTime = new Date().getTime();
        var spark = new SparkMD5.ArrayBuffer();
        var reader = new FileReader();
        reader.onerror = function (e) {
            reject (new Error("file read error!"));
        }
        reader.onload = function (e) {
            spark.append( e.target.result);                 // append array buffer
            //xdebug ("e:",e);
            var percent = Math.floor(100 * (current * chunkSize + e.loaded) / src.size);
            if (opts && opts.onProgress) opts.onProgress (percent);

            current += 1;
            if (current < count) {
                loadNext();
            } else {
                var hash = spark.end().toUpperCase();
                var endTime = new Date().getTime();

benefit: service.unitPrice * this.elgibilityPercentage
          }
        };
        adjudications.push(s);
      }

      let json = {
        txDate: this.claim_timestamp.toISOString().slice(0, 10),
        uid: "resource:org.fhir.core.ClaimResponse#",
        claimUid: this.claim.claim_uid,
        accountUid: "resource:org.fhir.core.Account#",
        invoiceUid: "resource:org.fhir.core.Invoice#",
        adjudications: adjudications
      };

      let id1 = Spark.hash(JSON.stringify(json))      
      json.accountUid = json.accountUid.concat(id1);
      json.uid = json.uid.concat(id1);
      json.invoiceUid = json.invoiceUid.concat(id1, "-1");
      this.invoice_uid = json.invoiceUid;
      this.account_uid =json.accountUid;
      this.claim_response_uid = json.uid
      this.$emit("saveFhir", {name: 'fhir_adjudication', data: json})
      return json;
    },
    approveClaim() {