Use vendored version of requests package in layer.

Author: purple4reina

Dockerfile

@@ -30,6 +30,15 @@ RUN rm ./python/lib/$runtime/site-packages/ddtrace/internal/datadog/profiling/dd
 RUN rm ./python/lib/$runtime/site-packages/ddtrace/internal/datadog/profiling/stack_v2/_stack_v2.*.so
 RUN find . -name "*.dist-info" -type d | xargs rm -rf
 
+# The requests package is available in the lambda runtime already as
+# pip._vendor.requests.  Before importing requests, `/path/to/pip/_vendor` must
+# be added to `sys.path`.
+RUN rm -rf \
+        ./python/lib/$runtime/site-packages/requests* \
+        ./python/lib/$runtime/site-packages/certifi* \
+        ./python/lib/$runtime/site-packages/idna* \
+        ./python/lib/$runtime/site-packages/charset_normalizer*
+
 # Precompile all .pyc files and remove .py files. This speeds up load time.
 # Compile with optimization level 2 (-OO) and PYTHONNODEBUGRANGES=1 to redtce
 # size of .pyc files.

datadog_lambda/__init__.py

@@ -1,3 +1,13 @@
+import sys
+
+
+# The requests package is no longer included in the lambda layer, instead use
+# the vendored version of requests included in the pip package.  Appending to
+# sys.path will make the vendered requests package discoverable.
+for i in range(len(sys.path)):
+    path = sys.path[i]
+    sys.path.append(f"{path}/pip/_vendor")
+
 from datadog_lambda.cold_start import initialize_cold_start_tracing
 import os
 

scripts/check_layer_size.sh

@@ -9,7 +9,7 @@
 
 set -e
 MAX_LAYER_COMPRESSED_SIZE_KB=$(expr 5 \* 1024)
-MAX_LAYER_UNCOMPRESSED_SIZE_KB=$(expr 13 \* 1024)
+MAX_LAYER_UNCOMPRESSED_SIZE_KB=$(expr 12 \* 1024)
 
 
 LAYER_FILES_PREFIX="datadog_lambda_py"

tests/integration/handle.py

@@ -1,8 +1,9 @@
-import requests
-
 from datadog_lambda.metric import lambda_metric
 from datadog_lambda.wrapper import datadog_lambda_wrapper
 
+import requests
+import time
+
 
 @datadog_lambda_wrapper
 def handle(event, context):
@@ -20,7 +21,11 @@ def handle(event, context):
             record_ids.append(record["Sns"]["MessageId"])
 
     # Generate custom metrics
+    timestamp = time.time() - 60
     lambda_metric("hello.dog", 1, tags=["team:serverless", "role:hello"])
+    lambda_metric(
+        "hello.cat", 1, tags=["team:serverless", "role:hello"], timestamp=timestamp
+    )
     lambda_metric(
         "tests.integration.count", 21, tags=["test:integration", "role:hello"]
     )