```Dockerfile
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
```

O arquivo com os requisitos de pacote **não muda com frequência**. Então, ao copiar apenas esse arquivo, o Docker será capaz de **usar o cache** para esse passo.

    assertThat(cache.getIfPresent(new Object())).isSameInstanceAs(newValue);
  }

  public void testGetAllPresent_empty() {
    Cache<Object, Object> cache =
        new AbstractCache<Object, Object>() {
          @Override
          public @Nullable Object getIfPresent(Object key) {
            return null;
          }
        };

    assertThat(cache.getAllPresent(ImmutableList.of(new Object()))).isEmpty();
  }

                  }
                });

    // To start, fill up the cache.
    // Each miss both increments the counter and causes the map to grow by one,
    // so until evictions begin, the size of the map is the greatest return
    // value seen so far
    while (cache.getUnchecked(nextRandomKey()) < maximumSize) {}

    requests.set(0);
    misses.set(0);
  }

  @Benchmark
  int time(int reps) {

# ==============================================================================
# Sourcing this enables Bazel remote cache (read and write)
# Note that "_push" cache configs write to GCS buckets and require
# authentication. If you are not a Googler, source "public_cache" to enable the
# public read-only cache.
# The cache configs are different for MacOS and Linux
if [[ $(uname -s) == "Darwin" ]]; then

def test_sub_counter_no_cache():
    counter_holder["counter"] = 0
    response = client.get("/sub-counter-no-cache/")
    assert response.status_code == 200, response.text
    assert response.json() == {"counter": 2, "subcounter": 1}
    response = client.get("/sub-counter-no-cache/")
    assert response.status_code == 200, response.text
    assert response.json() == {"counter": 4, "subcounter": 3}

package cmd

import (
	"context"
)

const (
	memTotal     = "total"
	memUsed      = "used"
	memFree      = "free"
	memBuffers   = "buffers"
	memCache     = "cache"
	memUsedPerc  = "used_perc"
	memShared    = "shared"
	memAvailable = "available"
)

var (
	memTotalMD     = NewGaugeMD(memTotal, "Total memory on the node")

  }

  @Test
  fun cache() {
    val cache = Cache(File("/cache/"), Integer.MAX_VALUE.toLong())
    cache.initialize()
    cache.delete()
    cache.evictAll()
    val urls: MutableIterator<String> = cache.urls()
    val writeAbortCount: Int = cache.writeAbortCount()
    val writeSuccessCount: Int = cache.writeSuccessCount()
    val size: Long = cache.size()
    val maxSize: Long = cache.maxSize()

    /**
     * Creates a copy of the data suitable for storage in the cache. The original data to store can be mutated after the
     * cache is populated but the state of the cache must not change so we need to make a copy.
     *
     * @param data The data to store in the cache, must not be {@code null}.
     * @return The data being stored in the cache, never {@code null}.
     */
    T intoCache(T data);

    /**

#      Ex. no_upload      -- Disable all uploads, usually for temporary CI issues

# Recommended: use a local+remote cache.
#
#   Bazel will cache your builds in tensorflow/build_output/cache,
#   and will also try using public build cache results to speed up
#   your builds. This usually saves a lot of time, especially when
#   re-running tests. However, note that:
#

    /**
     * Get the cache key for this referral
     *
     * @return cache key
     */
    String getKey();

    /**
     * Set the cache key for this referral
     *
     * @param key
     *            cache key
     */
    void setKey(String key);

    /**
     * Set the cache map for this referral
     *
     * @param map the cache map to associate with this referral
     */