versions](https://square.github.io/okhttp/4.x/okhttp/okhttp3/-tls-version/) and [cipher suites](https://square.github.io/okhttp/4.x/okhttp/okhttp3/-cipher-suite/) to offer. A client that wants to maximize connectivity would include obsolete TLS versions and weak-by-design cipher suites. A strict client that wants to maximize security would be limited to only the latest TLS version and strongest cipher suites.

Specific security vs. connectivity decisions are implemented by [ConnectionSpec](https://...

on(){return n.default.fn[i]=l,f._jQueryInterface};var u="CardWidget",c="lte.cardwidget",h=n.default.fn[u],g="card",p="collapsed-card",m="collapsing-card",v="expanding-card",_="was-collapsed",b="maximized-card",y='[data-card-widget="remove"]',C='[data-card-widget="collapse"]',w='[data-card-widget="maximize"]',x={animationSpeed:"normal",collapseTrigger:C,removeTrigger:y,maximizeTrigger:w,collapseIcon:"fa-minus",expandIcon:"fa-plus",maximizeIcon:"fa-expand",minimizeIcon:"fa-compress"},I=function(){function...

 * of the elapsed times reported. {@code Stopwatch} is still suitable for logging and metrics where
 * reasonably accurate values are sufficient. If the uncommon case that you need to maximize
 * accuracy, use {@code System.nanoTime()} directly instead.
 *
 * <p>Basic usage:
 *
 * <pre>{@code
 * Stopwatch stopwatch = Stopwatch.createStarted();
 * doSomething();
 * stopwatch.stop(); // optional
 *

gger","maximizeTrigger","collapseIcon","expandIcon","maximizeIcon","minimizeIcon","CardWidget","collapse","addClass","children","SELECTOR_CARD_BODY","slideUp","removeClass","expand","slideDown","toggle","maximize","css","height","width","transition","delay","queue","$element","dequeue","minimize","style","toggleMaximize","card","_this3","click","SELECTOR_CONTROL_SIDEBAR","SELECTOR_CONTROL_SIDEBAR_CONTENT","SELECTOR_DATA_TOGGLE","SELECTOR_HEADER","SELECTOR_FOOTER","CLASS_NAME_CONTROL_SIDEBAR_ANIM...

want to use any base image, and instead **build a container image from scratch** based on the official Python Docker image.

Taking care of the **order** of instructions in the `Dockerfile` and the **Docker cache** you can **minimize build times**, to maximize your productivity (and avoid boredom). 😎...

        CacheBuilder.newBuilder()
            .maximumSize(MAX_SIZE)
            .removalListener(removalListener)
            .build(loader);
    for (int i = 0; i < 2 * MAX_SIZE; i++) {
      cache.getUnchecked(i);
      assertTrue(cache.size() <= MAX_SIZE);
    }

    assertEquals(MAX_SIZE, CacheTesting.accessQueueSize(cache));
    assertEquals(MAX_SIZE, cache.size());
    CacheTesting.processPendingNotifications(cache);

    }

    public void setMaxSize_Equal(Integer maxSize) {
        setMaxSize_Term(maxSize, null);
    }

    public void setMaxSize_Equal(Integer maxSize, ConditionOptionCall<TermQueryBuilder> opLambda) {
        setMaxSize_Term(maxSize, opLambda);
    }

    public void setMaxSize_Term(Integer maxSize) {
        setMaxSize_Term(maxSize, null);
    }

        this.createdTime = value;
    }

    public Integer getMaxSize() {
        checkSpecifiedProperty("maxSize");
        return maxSize;
    }

    public void setMaxSize(Integer value) {
        registerModifiedProperty("maxSize");
        this.maxSize = value;
    }

    public String getQuery() {
        checkSpecifiedProperty("query");
        return convertEmptyToNull(query);

    }

    public void setMaxSize_Avg(ConditionOptionCall<AvgAggregationBuilder> opLambda) {
        setMaxSize_Avg("maxSize", opLambda);
    }

    public void setMaxSize_Avg(String name, ConditionOptionCall<AvgAggregationBuilder> opLambda) {
        AvgAggregationBuilder builder = regAvgA(name, "maxSize");
        if (opLambda != null) {
            opLambda.callback(builder);
        }
    }

 * small portion of these would be in use.
 *
 * <p>Prior to this class, one might be tempted to use {@code Map<K, Lock>}, where {@code K}
 * represents the task. This maximizes concurrency by having each unique key mapped to a unique
 * lock, but also maximizes memory footprint. On the other extreme, one could use a single lock for
 * all tasks, which minimizes memory footprint but also minimizes concurrency. Instead of choosing