文件 AWS 開發套件範例 GitHub 儲存庫中有更多可用的 [AWS SDK 範例](https://github.com/awsdocs/aws-doc-sdk-examples)。
本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。
# 使用 SDK for Python (Boto3) 的 Lambda 範例
下列程式碼範例示範如何使用 適用於 Python (Boto3) 的 AWS SDK 搭配 Lambda 執行動作和實作常見案例。
*基本概念*是程式碼範例，這些範例說明如何在服務內執行基本操作。
*Actions* 是大型程式的程式碼摘錄，必須在內容中執行。雖然動作會告訴您如何呼叫個別服務函數，但您可以在其相關情境中查看內容中的動作。
*案例*是向您展示如何呼叫服務中的多個函數或與其他 AWS 服務組合來完成特定任務的程式碼範例。
每個範例均包含完整原始碼的連結，您可在連結中找到如何設定和執行內容中程式碼的相關指示。
**Topics**
+ [開始使用](#get_started)
+ [基本概念](#basics)
+ [動作](#actions)
+ [案例](#scenarios)
+ [無伺服器範例](#serverless_examples)
## 開始使用
### Hello Lambda
下列程式碼範例示範如何開始使用 Lambda。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
```
import boto3
def main():
"""
List the Lambda functions in your AWS account.
"""
# Create the Lambda client
lambda_client = boto3.client("lambda")
# Use the paginator to list the functions
paginator = lambda_client.get_paginator("list_functions")
response_iterator = paginator.paginate()
print("Here are the Lambda functions in your account:")
for page in response_iterator:
for function in page["Functions"]:
print(f" {function['FunctionName']}")
if __name__ == "__main__":
main()
```
+ 如需 API 詳細資訊，請參閱《*適用於 Python (Boto3) 的AWS 開發套件 API 參考*》中的「[ListFunctions](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/ListFunctions)」。
## 基本概念
### 了解基本概念
以下程式碼範例顯示做法：
+ 建立 IAM 角色和 Lambda 函數，然後上傳處理常式程式碼。
+ 調用具有單一參數的函數並取得結果。
+ 更新函數程式碼並使用環境變數進行設定。
+ 調用具有新參數的函數並取得結果。顯示傳回的執行日誌。
+ 列出您帳戶的函數，然後清理相關資源。
如需詳細資訊，請參閱[使用主控台建立 Lambda 函數](https://docs.aws.amazon.com/lambda/latest/dg/getting-started-create-function.html)。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
定義增量一個數字的 Lambda 處理常式。
```
import logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def lambda_handler(event, context):
"""
Accepts an action and a single number, performs the specified action on the number,
and returns the result. The only allowable action is 'increment'.
:param event: The event dict that contains the parameters sent when the function
is invoked.
:param context: The context in which the function is called.
:return: The result of the action.
"""
result = None
action = event.get("action")
if action == "increment":
result = event.get("number", 0) + 1
logger.info("Calculated result of %s", result)
else:
logger.error("%s is not a valid action.", action)
response = {"result": result}
return response
```
定義可執行算術運算的第二個 Lambda 處理常式。
```
import logging
import os
logger = logging.getLogger()
# Define a list of Python lambda functions that are called by this AWS Lambda function.
ACTIONS = {
"plus": lambda x, y: x + y,
"minus": lambda x, y: x - y,
"times": lambda x, y: x * y,
"divided-by": lambda x, y: x / y,
}
def lambda_handler(event, context):
"""
Accepts an action and two numbers, performs the specified action on the numbers,
and returns the result.
:param event: The event dict that contains the parameters sent when the function
is invoked.
:param context: The context in which the function is called.
:return: The result of the specified action.
"""
# Set the log level based on a variable configured in the Lambda environment.
logger.setLevel(os.environ.get("LOG_LEVEL", logging.INFO))
logger.debug("Event: %s", event)
action = event.get("action")
func = ACTIONS.get(action)
x = event.get("x")
y = event.get("y")
result = None
try:
if func is not None and x is not None and y is not None:
result = func(x, y)
logger.info("%s %s %s is %s", x, action, y, result)
else:
logger.error("I can't calculate %s %s %s.", x, action, y)
except ZeroDivisionError:
logger.warning("I can't divide %s by 0!", x)
response = {"result": result}
return response
```
建立可包裝 Lambda 動作的函數。
```
class LambdaWrapper:
def __init__(self, lambda_client, iam_resource):
self.lambda_client = lambda_client
self.iam_resource = iam_resource
@staticmethod
def create_deployment_package(source_file, destination_file):
"""
Creates a Lambda deployment package in .zip format in an in-memory buffer. This
buffer can be passed directly to Lambda when creating the function.
:param source_file: The name of the file that contains the Lambda handler
function.
:param destination_file: The name to give the file when it's deployed to Lambda.
:return: The deployment package.
"""
buffer = io.BytesIO()
with zipfile.ZipFile(buffer, "w") as zipped:
zipped.write(source_file, destination_file)
buffer.seek(0)
return buffer.read()
def get_iam_role(self, iam_role_name):
"""
Get an AWS Identity and Access Management (IAM) role.
:param iam_role_name: The name of the role to retrieve.
:return: The IAM role.
"""
role = None
try:
temp_role = self.iam_resource.Role(iam_role_name)
temp_role.load()
role = temp_role
logger.info("Got IAM role %s", role.name)
except ClientError as err:
if err.response["Error"]["Code"] == "NoSuchEntity":
logger.info("IAM role %s does not exist.", iam_role_name)
else:
logger.error(
"Couldn't get IAM role %s. Here's why: %s: %s",
iam_role_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
return role
def create_iam_role_for_lambda(self, iam_role_name):
"""
Creates an IAM role that grants the Lambda function basic permissions. If a
role with the specified name already exists, it is used for the demo.
:param iam_role_name: The name of the role to create.
:return: The role and a value that indicates whether the role is newly created.
"""
role = self.get_iam_role(iam_role_name)
if role is not None:
return role, False
lambda_assume_role_policy = {
"Version":"2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {"Service": "lambda.amazonaws.com"},
"Action": "sts:AssumeRole",
}
],
}
policy_arn = "arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"
try:
role = self.iam_resource.create_role(
RoleName=iam_role_name,
AssumeRolePolicyDocument=json.dumps(lambda_assume_role_policy),
)
logger.info("Created role %s.", role.name)
role.attach_policy(PolicyArn=policy_arn)
logger.info("Attached basic execution policy to role %s.", role.name)
except ClientError as error:
if error.response["Error"]["Code"] == "EntityAlreadyExists":
role = self.iam_resource.Role(iam_role_name)
logger.warning("The role %s already exists. Using it.", iam_role_name)
else:
logger.exception(
"Couldn't create role %s or attach policy %s.",
iam_role_name,
policy_arn,
)
raise
return role, True
def get_function(self, function_name):
"""
Gets data about a Lambda function.
:param function_name: The name of the function.
:return: The function data.
"""
response = None
try:
response = self.lambda_client.get_function(FunctionName=function_name)
except ClientError as err:
if err.response["Error"]["Code"] == "ResourceNotFoundException":
logger.info("Function %s does not exist.", function_name)
else:
logger.error(
"Couldn't get function %s. Here's why: %s: %s",
function_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
return response
def create_function(
self, function_name, handler_name, iam_role, deployment_package
):
"""
Deploys a Lambda function.
:param function_name: The name of the Lambda function.
:param handler_name: The fully qualified name of the handler function. This
must include the file name and the function name.
:param iam_role: The IAM role to use for the function.
:param deployment_package: The deployment package that contains the function
code in .zip format.
:return: The Amazon Resource Name (ARN) of the newly created function.
"""
try:
response = self.lambda_client.create_function(
FunctionName=function_name,
Description="AWS Lambda doc example",
Runtime="python3.9",
Role=iam_role.arn,
Handler=handler_name,
Code={"ZipFile": deployment_package},
Publish=True,
)
function_arn = response["FunctionArn"]
waiter = self.lambda_client.get_waiter("function_active_v2")
waiter.wait(FunctionName=function_name)
logger.info(
"Created function '%s' with ARN: '%s'.",
function_name,
response["FunctionArn"],
)
except ClientError:
logger.error("Couldn't create function %s.", function_name)
raise
else:
return function_arn
def delete_function(self, function_name):
"""
Deletes a Lambda function.
:param function_name: The name of the function to delete.
"""
try:
self.lambda_client.delete_function(FunctionName=function_name)
except ClientError:
logger.exception("Couldn't delete function %s.", function_name)
raise
def invoke_function(self, function_name, function_params, get_log=False):
"""
Invokes a Lambda function.
:param function_name: The name of the function to invoke.
:param function_params: The parameters of the function as a dict. This dict
is serialized to JSON before it is sent to Lambda.
:param get_log: When true, the last 4 KB of the execution log are included in
the response.
:return: The response from the function invocation.
"""
try:
response = self.lambda_client.invoke(
FunctionName=function_name,
Payload=json.dumps(function_params),
LogType="Tail" if get_log else "None",
)
logger.info("Invoked function %s.", function_name)
except ClientError:
logger.exception("Couldn't invoke function %s.", function_name)
raise
return response
def update_function_code(self, function_name, deployment_package):
"""
Updates the code for a Lambda function by submitting a .zip archive that contains
the code for the function.
:param function_name: The name of the function to update.
:param deployment_package: The function code to update, packaged as bytes in
.zip format.
:return: Data about the update, including the status.
"""
try:
response = self.lambda_client.update_function_code(
FunctionName=function_name, ZipFile=deployment_package
)
except ClientError as err:
logger.error(
"Couldn't update function %s. Here's why: %s: %s",
function_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
def update_function_configuration(self, function_name, env_vars):
"""
Updates the environment variables for a Lambda function.
:param function_name: The name of the function to update.
:param env_vars: A dict of environment variables to update.
:return: Data about the update, including the status.
"""
try:
response = self.lambda_client.update_function_configuration(
FunctionName=function_name, Environment={"Variables": env_vars}
)
except ClientError as err:
logger.error(
"Couldn't update function configuration %s. Here's why: %s: %s",
function_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
def list_functions(self):
"""
Lists the Lambda functions for the current account.
"""
try:
func_paginator = self.lambda_client.get_paginator("list_functions")
for func_page in func_paginator.paginate():
for func in func_page["Functions"]:
print(func["FunctionName"])
desc = func.get("Description")
if desc:
print(f"\t{desc}")
print(f"\t{func['Runtime']}: {func['Handler']}")
except ClientError as err:
logger.error(
"Couldn't list functions. Here's why: %s: %s",
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
```
建立可執行該案例的函數。
```
class UpdateFunctionWaiter(CustomWaiter):
"""A custom waiter that waits until a function is successfully updated."""
def __init__(self, client):
super().__init__(
"UpdateSuccess",
"GetFunction",
"Configuration.LastUpdateStatus",
{"Successful": WaitState.SUCCESS, "Failed": WaitState.FAILURE},
client,
)
def wait(self, function_name):
self._wait(FunctionName=function_name)
def run_scenario(lambda_client, iam_resource, basic_file, calculator_file, lambda_name):
"""
Runs the scenario.
:param lambda_client: A Boto3 Lambda client.
:param iam_resource: A Boto3 IAM resource.
:param basic_file: The name of the file that contains the basic Lambda handler.
:param calculator_file: The name of the file that contains the calculator Lambda handler.
:param lambda_name: The name to give resources created for the scenario, such as the
IAM role and the Lambda function.
"""
logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
print("-" * 88)
print("Welcome to the AWS Lambda getting started with functions demo.")
print("-" * 88)
wrapper = LambdaWrapper(lambda_client, iam_resource)
print("Checking for IAM role for Lambda...")
iam_role, should_wait = wrapper.create_iam_role_for_lambda(lambda_name)
if should_wait:
logger.info("Giving AWS time to create resources...")
wait(10)
print(f"Looking for function {lambda_name}...")
function = wrapper.get_function(lambda_name)
if function is None:
print("Zipping the Python script into a deployment package...")
deployment_package = wrapper.create_deployment_package(
basic_file, f"{lambda_name}.py"
)
print(f"...and creating the {lambda_name} Lambda function.")
wrapper.create_function(
lambda_name, f"{lambda_name}.lambda_handler", iam_role, deployment_package
)
else:
print(f"Function {lambda_name} already exists.")
print("-" * 88)
print(f"Let's invoke {lambda_name}. This function increments a number.")
action_params = {
"action": "increment",
"number": q.ask("Give me a number to increment: ", q.is_int),
}
print(f"Invoking {lambda_name}...")
response = wrapper.invoke_function(lambda_name, action_params)
print(
f"Incrementing {action_params['number']} resulted in "
f"{json.load(response['Payload'])}"
)
print("-" * 88)
print(f"Let's update the function to an arithmetic calculator.")
q.ask("Press Enter when you're ready.")
print("Creating a new deployment package...")
deployment_package = wrapper.create_deployment_package(
calculator_file, f"{lambda_name}.py"
)
print(f"...and updating the {lambda_name} Lambda function.")
update_waiter = UpdateFunctionWaiter(lambda_client)
wrapper.update_function_code(lambda_name, deployment_package)
update_waiter.wait(lambda_name)
print(f"This function uses an environment variable to control logging level.")
print(f"Let's set it to DEBUG to get the most logging.")
wrapper.update_function_configuration(
lambda_name, {"LOG_LEVEL": logging.getLevelName(logging.DEBUG)}
)
actions = ["plus", "minus", "times", "divided-by"]
want_invoke = True
while want_invoke:
print(f"Let's invoke {lambda_name}. You can invoke these actions:")
for index, action in enumerate(actions):
print(f"{index + 1}: {action}")
action_params = {}
action_index = q.ask(
"Enter the number of the action you want to take: ",
q.is_int,
q.in_range(1, len(actions)),
)
action_params["action"] = actions[action_index - 1]
print(f"You've chosen to invoke 'x {action_params['action']} y'.")
action_params["x"] = q.ask("Enter a value for x: ", q.is_int)
action_params["y"] = q.ask("Enter a value for y: ", q.is_int)
print(f"Invoking {lambda_name}...")
response = wrapper.invoke_function(lambda_name, action_params, True)
print(
f"Calculating {action_params['x']} {action_params['action']} {action_params['y']} "
f"resulted in {json.load(response['Payload'])}"
)
q.ask("Press Enter to see the logs from the call.")
print(base64.b64decode(response["LogResult"]).decode())
want_invoke = q.ask("That was fun. Shall we do it again? (y/n) ", q.is_yesno)
print("-" * 88)
if q.ask(
"Do you want to list all of the functions in your account? (y/n) ", q.is_yesno
):
wrapper.list_functions()
print("-" * 88)
if q.ask("Ready to delete the function and role? (y/n) ", q.is_yesno):
for policy in iam_role.attached_policies.all():
policy.detach_role(RoleName=iam_role.name)
iam_role.delete()
print(f"Deleted role {lambda_name}.")
wrapper.delete_function(lambda_name)
print(f"Deleted function {lambda_name}.")
print("\nThanks for watching!")
print("-" * 88)
if __name__ == "__main__":
try:
run_scenario(
boto3.client("lambda"),
boto3.resource("iam"),
"lambda_handler_basic.py",
"lambda_handler_calculator.py",
"doc_example_lambda_calculator",
)
except Exception:
logging.exception("Something went wrong with the demo!")
```
+ 如需 API 詳細資訊，請參閱下列*《適用於 Python (Boto3) 的AWS 開發套件 API 參考》*中的下列主題。
+ [CreateFunction](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/CreateFunction)
+ [DeleteFunction](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/DeleteFunction)
+ [GetFunction](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/GetFunction)
+ [Invoke](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/Invoke)
+ [ListFunctions](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/ListFunctions)
+ [UpdateFunctionCode](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/UpdateFunctionCode)
+ [UpdateFunctionConfiguration](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/UpdateFunctionConfiguration)
## 動作
### `CreateFunction`
以下程式碼範例顯示如何使用 `CreateFunction`。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
```
class LambdaWrapper:
def __init__(self, lambda_client, iam_resource):
self.lambda_client = lambda_client
self.iam_resource = iam_resource
def create_function(
self, function_name, handler_name, iam_role, deployment_package
):
"""
Deploys a Lambda function.
:param function_name: The name of the Lambda function.
:param handler_name: The fully qualified name of the handler function. This
must include the file name and the function name.
:param iam_role: The IAM role to use for the function.
:param deployment_package: The deployment package that contains the function
code in .zip format.
:return: The Amazon Resource Name (ARN) of the newly created function.
"""
try:
response = self.lambda_client.create_function(
FunctionName=function_name,
Description="AWS Lambda doc example",
Runtime="python3.9",
Role=iam_role.arn,
Handler=handler_name,
Code={"ZipFile": deployment_package},
Publish=True,
)
function_arn = response["FunctionArn"]
waiter = self.lambda_client.get_waiter("function_active_v2")
waiter.wait(FunctionName=function_name)
logger.info(
"Created function '%s' with ARN: '%s'.",
function_name,
response["FunctionArn"],
)
except ClientError:
logger.error("Couldn't create function %s.", function_name)
raise
else:
return function_arn
```
+ 如需 API 詳細資訊，請參閱《*適用於 Python (Boto3) 的AWS 開發套件 API 參考*》中的「[CreateFunction](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/CreateFunction)」。
### `DeleteFunction`
以下程式碼範例顯示如何使用 `DeleteFunction`。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
```
class LambdaWrapper:
def __init__(self, lambda_client, iam_resource):
self.lambda_client = lambda_client
self.iam_resource = iam_resource
def delete_function(self, function_name):
"""
Deletes a Lambda function.
:param function_name: The name of the function to delete.
"""
try:
self.lambda_client.delete_function(FunctionName=function_name)
except ClientError:
logger.exception("Couldn't delete function %s.", function_name)
raise
```
+ 如需 API 詳細資訊，請參閱《*適用於 Python (Boto3) 的AWS 開發套件 API 參考*》中的「[DeleteFunction](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/DeleteFunction)」。
### `GetFunction`
以下程式碼範例顯示如何使用 `GetFunction`。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
```
class LambdaWrapper:
def __init__(self, lambda_client, iam_resource):
self.lambda_client = lambda_client
self.iam_resource = iam_resource
def get_function(self, function_name):
"""
Gets data about a Lambda function.
:param function_name: The name of the function.
:return: The function data.
"""
response = None
try:
response = self.lambda_client.get_function(FunctionName=function_name)
except ClientError as err:
if err.response["Error"]["Code"] == "ResourceNotFoundException":
logger.info("Function %s does not exist.", function_name)
else:
logger.error(
"Couldn't get function %s. Here's why: %s: %s",
function_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
return response
```
+ 如需 API 詳細資訊，請參閱《*適用於 Python (Boto3) 的AWS 開發套件 API 參考*》中的「[GetFunction](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/GetFunction)」。
### `Invoke`
以下程式碼範例顯示如何使用 `Invoke`。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
```
class LambdaWrapper:
def __init__(self, lambda_client, iam_resource):
self.lambda_client = lambda_client
self.iam_resource = iam_resource
def invoke_function(self, function_name, function_params, get_log=False):
"""
Invokes a Lambda function.
:param function_name: The name of the function to invoke.
:param function_params: The parameters of the function as a dict. This dict
is serialized to JSON before it is sent to Lambda.
:param get_log: When true, the last 4 KB of the execution log are included in
the response.
:return: The response from the function invocation.
"""
try:
response = self.lambda_client.invoke(
FunctionName=function_name,
Payload=json.dumps(function_params),
LogType="Tail" if get_log else "None",
)
logger.info("Invoked function %s.", function_name)
except ClientError:
logger.exception("Couldn't invoke function %s.", function_name)
raise
return response
```
+ 如需 API 的詳細資訊，請參閱《*適用於 Python (Boto3) 的AWS 開發套件 API 參考*》中的 [Invoke](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/Invoke)。
### `ListFunctions`
以下程式碼範例顯示如何使用 `ListFunctions`。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
```
class LambdaWrapper:
def __init__(self, lambda_client, iam_resource):
self.lambda_client = lambda_client
self.iam_resource = iam_resource
def list_functions(self):
"""
Lists the Lambda functions for the current account.
"""
try:
func_paginator = self.lambda_client.get_paginator("list_functions")
for func_page in func_paginator.paginate():
for func in func_page["Functions"]:
print(func["FunctionName"])
desc = func.get("Description")
if desc:
print(f"\t{desc}")
print(f"\t{func['Runtime']}: {func['Handler']}")
except ClientError as err:
logger.error(
"Couldn't list functions. Here's why: %s: %s",
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
```
+ 如需 API 詳細資訊，請參閱《*適用於 Python (Boto3) 的AWS 開發套件 API 參考*》中的「[ListFunctions](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/ListFunctions)」。
### `UpdateFunctionCode`
以下程式碼範例顯示如何使用 `UpdateFunctionCode`。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
```
class LambdaWrapper:
def __init__(self, lambda_client, iam_resource):
self.lambda_client = lambda_client
self.iam_resource = iam_resource
def update_function_code(self, function_name, deployment_package):
"""
Updates the code for a Lambda function by submitting a .zip archive that contains
the code for the function.
:param function_name: The name of the function to update.
:param deployment_package: The function code to update, packaged as bytes in
.zip format.
:return: Data about the update, including the status.
"""
try:
response = self.lambda_client.update_function_code(
FunctionName=function_name, ZipFile=deployment_package
)
except ClientError as err:
logger.error(
"Couldn't update function %s. Here's why: %s: %s",
function_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
```
+ 如需 API 詳細資訊，請參閱《*適用於 Python (Boto3) 的AWS 開發套件 API 參考*》中的「[UpdateFunctionCode](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/UpdateFunctionCode)」。
### `UpdateFunctionConfiguration`
以下程式碼範例顯示如何使用 `UpdateFunctionConfiguration`。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#code-examples)中設定和執行。
```
class LambdaWrapper:
def __init__(self, lambda_client, iam_resource):
self.lambda_client = lambda_client
self.iam_resource = iam_resource
def update_function_configuration(self, function_name, env_vars):
"""
Updates the environment variables for a Lambda function.
:param function_name: The name of the function to update.
:param env_vars: A dict of environment variables to update.
:return: Data about the update, including the status.
"""
try:
response = self.lambda_client.update_function_configuration(
FunctionName=function_name, Environment={"Variables": env_vars}
)
except ClientError as err:
logger.error(
"Couldn't update function configuration %s. Here's why: %s: %s",
function_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
```
+ 如需 API 詳細資訊，請參閱《*適用於 Python (Boto3) 的AWS 開發套件 API 參考*》中的「[UpdateFunctionConfiguration](https://docs.aws.amazon.com/goto/boto3/lambda-2015-03-31/UpdateFunctionConfiguration)」。
## 案例
### 建立 REST API 以追蹤 COVID-19 資料
以下程式碼範例示範如何建立 REST API，此 API 使用虛構資料模擬追蹤美國 COVID-19 每日病例的系統。
**適用於 Python 的 SDK (Boto3)**
示範如何使用 AWS Chalice 搭配 適用於 Python (Boto3) 的 AWS SDK 來建立使用 Amazon API Gateway AWS Lambda和 Amazon DynamoDB 的無伺服器 REST API。REST API 使用虛構資料模擬追蹤美國 COVID-19 每日病例的系統。了解如何：
+ 使用 AWS Chalice 定義 Lambda 函數中的路由，這些函數稱為 來處理透過 API Gateway 發出的 REST 請求。
+ 使用 Lambda 函式在 DynamoDB 資料表中擷取和存放資料，以便為 REST 請求提供服務。
+ 在 AWS CloudFormation 範本中定義資料表結構和安全角色資源。
+ 使用 AWS Chalice 和 CloudFormation 封裝和部署所有必要的資源。
+ 使用 CloudFormation 清理所有已建立的資源。
如需完整的原始碼和如何設定及執行的指示，請參閱 [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/apigateway_covid-19_tracker) 上的完整範例。
**此範例中使用的服務**
+ API Gateway
+ CloudFormation
+ DynamoDB
+ Lambda
### 建立出借圖書館 REST API
下列程式碼範例顯示如何使用 Amazon Aurora 資料庫支援的 REST API 來建立出借圖書館，讓贊助人可以借書與還書。
**適用於 Python 的 SDK (Boto3)**
示範如何使用 適用於 Python (Boto3) 的 AWS SDK 搭配 Amazon Relational Database Service (Amazon RDS) API 和 AWS Chalice 來建立由 Amazon Aurora 資料庫支援的 REST API。Web 服務是完全無伺服器的，表示這是一種贊助人可以借書與還書的簡單出借圖書館。了解如何：
+ 建立與管理無伺服器的 Aurora 資料庫叢集。
+ 使用 AWS Secrets Manager 管理資料庫登入資料。
+ 實作資料儲存層，該層使用 Amazon RDS 將資料移入和移出資料庫。
+ 使用 AWS Chalice 將無伺服器 REST API 部署至 Amazon API Gateway 和 AWS Lambda。
+ 使用 Request 套件來將請求傳送到 Web 服務。
如需完整的原始碼和如何設定及執行的指示，請參閱 [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/aurora_rest_lending_library) 上的完整範例。
**此範例中使用的服務**
+ API Gateway
+ Aurora
+ Lambda
+ Secrets Manager
### 建立傳訊應用程式
下列程式碼範例示範如何建立 AWS Step Functions 訊息應用程式，從資料庫資料表擷取訊息記錄。
**適用於 Python 的 SDK (Boto3)**
示範如何使用 適用於 Python (Boto3) 的 AWS SDK 搭配 AWS Step Functions 來建立訊息應用程式，從 Amazon DynamoDB 資料表擷取訊息記錄，並使用 Amazon Simple Queue Service (Amazon SQS) 傳送它們。狀態機器會與 AWS Lambda 函數整合，以掃描資料庫是否有未傳送的訊息。
+ 建立從 Amazon DynamoDB 資料表擷取和更新訊息記錄的狀態機器。
+ 更新狀態機器定義，以便也向 Amazon Simple Queue Service (Amazon SQS) 傳送訊息。
+ 開始和停用狀態機器執行。
+ 使用服務整合從狀態機器連接至 Lambda、DynamoDB 和 Amazon SQS。
如需完整的原始碼和如何設定及執行的指示，請參閱 [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/stepfunctions_messenger) 上的完整範例。
**此範例中使用的服務**
+ DynamoDB
+ Lambda
+ Amazon SQS
+ 步驟函數
### 建立 websocket 聊天應用程式
下列程式碼範例示範如何建立由建置於 Amazon API Gateway 上的 websocket API 提供服務的聊天應用程式。
**適用於 Python 的 SDK (Boto3)**
示範如何使用 適用於 Python (Boto3) 的 AWS SDK 搭配 Amazon API Gateway V2 來建立與 AWS Lambda 和 Amazon DynamoDB 整合的 Websocket API。
+ 建立由 API Gateway 提供服務的 websocket API。
+ 定義 Lambda 處理常式，該常式將連接存放在 DynamoDB 中，並將訊息傳送給其他聊天參與者。
+ 連接至 websocket 聊天應用程式，並使用 Websockets 套件傳送訊息。
如需完整的原始碼和如何設定及執行的指示，請參閱 [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/apigateway_websocket_chat) 上的完整範例。
**此範例中使用的服務**
+ API Gateway
+ DynamoDB
+ Lambda
### 使用 API Gateway 來調用 Lambda 函式
下列程式碼範例示範如何建立 Amazon API Gateway 調用的 AWS Lambda 函數。
**適用於 Python 的 SDK (Boto3)**
此範例顯示如何建立和使用目標為 AWS Lambda 函數的 Amazon API Gateway REST API。Lambda 處理常式會展示如何根據 HTTP 方法來路由；如何從查詢字串、標頭和本文中取得資料；以及如何傳回 JSON 回應。
+ 部署 Lambda 函式。
+ 建立 API Gateway REST API。
+ 建立目標為 Lambda 函式的 REST 資源。
+ 授與許可讓 API Gateway 調用 Lambda 函式。
+ 使用 Request 套件來將請求傳送到 REST API。
+ 清理示範期間建立的所有資源。
這個範例在 GitHub 上的檢視效果最佳。如需完整的原始碼和如何設定及執行的指示，請參閱 [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#readme) 上的完整範例。
**此範例中使用的服務**
+ API Gateway
+ DynamoDB
+ Lambda
+ Amazon SNS
### 使用排程事件來調用 Lambda 函式
下列程式碼範例示範如何建立由 Amazon EventBridge 排程事件呼叫的 AWS Lambda 函數。
**適用於 Python 的 SDK (Boto3)**
此範例說明如何將 AWS Lambda 函數註冊為排程 Amazon EventBridge 事件的目標。Lambda 處理常式會將合適的訊息和完整的事件資料寫入 Amazon CloudWatch Logs 中以供日後擷取。
+ 部署 Lambda 函式。
+ 建立一個 EventBridge 排程事件，並將 Lambda 函式做為目標。
+ 授予許可讓 EventBridge 調用 Lambda 函式。
+ 列印 CloudWatch Logs 中的最新資料，以顯示排程調用的結果。
+ 清理示範期間建立的所有資源。
這個範例在 GitHub 上的檢視效果最佳。如需完整的原始碼和如何設定及執行的指示，請參閱 [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/lambda#readme) 上的完整範例。
**此範例中使用的服務**
+ CloudWatch Logs
+ DynamoDB
+ EventBridge
+ Lambda
+ Amazon SNS
## 無伺服器範例
### 連線至 Lambda 函數中的 Amazon RDS 資料庫
以下程式碼範例示範如何實作連線至 RDS 資料庫的 Lambda 函式。該函數會提出簡單的資料庫請求並傳回結果。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/lambda-function-connect-rds-iam)儲存庫中設定和執行。
使用 Python 連線至 Lambda 函數中的 Amazon RDS 資料庫。
```
import json
import os
import boto3
import pymysql
# RDS settings
proxy_host_name = os.environ['PROXY_HOST_NAME']
port = int(os.environ['PORT'])
db_name = os.environ['DB_NAME']
db_user_name = os.environ['DB_USER_NAME']
aws_region = os.environ['AWS_REGION']
# Fetch RDS Auth Token
def get_auth_token():
client = boto3.client('rds')
token = client.generate_db_auth_token(
DBHostname=proxy_host_name,
Port=port
DBUsername=db_user_name
Region=aws_region
)
return token
def lambda_handler(event, context):
token = get_auth_token()
try:
connection = pymysql.connect(
host=proxy_host_name,
user=db_user_name,
password=token,
db=db_name,
port=port,
ssl={'ca': 'Amazon RDS'} # Ensure you have the CA bundle for SSL connection
)
with connection.cursor() as cursor:
cursor.execute('SELECT %s + %s AS sum', (3, 2))
result = cursor.fetchone()
return result
except Exception as e:
return (f"Error: {str(e)}") # Return an error message if an exception occurs
```
### 使用 Kinesis 觸發條件調用 Lambda 函數
以下程式碼範例示範如何實作 Lambda 函式，該函式會透過接收 Kinesis 串流的記錄來接收所觸發的事件。此函數會擷取 Kinesis 承載、從 Base64 解碼，並記錄記錄內容。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-kinesis-to-lambda)儲存庫中設定和執行。
使用 Python 搭配 Lambda 來使用 Kinesis 事件。
```
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
import base64
def lambda_handler(event, context):
for record in event['Records']:
try:
print(f"Processed Kinesis Event - EventID: {record['eventID']}")
record_data = base64.b64decode(record['kinesis']['data']).decode('utf-8')
print(f"Record Data: {record_data}")
# TODO: Do interesting work based on the new data
except Exception as e:
print(f"An error occurred {e}")
raise e
print(f"Successfully processed {len(event['Records'])} records.")
```
### 使用 DynamoDB 觸發條件調用 Lambda 函式
以下程式碼範例示範如何實作 Lambda 函式，該函式會透過接收 DynamoDB 串流的記錄來接收所觸發的事件。函數會擷取 DynamoDB 承載並記下記錄內容。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-ddb-to-lambda)儲存庫中設定和執行。
使用 Python 搭配 Lambda 來使用 DynamoDB 事件。
```
import json
def lambda_handler(event, context):
print(json.dumps(event, indent=2))
for record in event['Records']:
log_dynamodb_record(record)
def log_dynamodb_record(record):
print(record['eventID'])
print(record['eventName'])
print(f"DynamoDB Record: {json.dumps(record['dynamodb'])}")
```
### 使用 Amazon DocumentDB 觸發條件調用 Lambda 函數
以下程式碼範例示範如何實作 Lambda 函式，該函式會透過接收 DocumentDB 變更串流的記錄來接收所觸發的事件。函數會擷取 DocumentDB 承載並記下記錄內容。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-docdb-to-lambda)儲存庫中設定和執行。
使用 Python 搭配 Lambda 使用 Amazon DocumentDB 事件。
```
import json
def lambda_handler(event, context):
for record in event.get('events', []):
log_document_db_event(record)
return 'OK'
def log_document_db_event(record):
event_data = record.get('event', {})
operation_type = event_data.get('operationType', 'Unknown')
db = event_data.get('ns', {}).get('db', 'Unknown')
collection = event_data.get('ns', {}).get('coll', 'Unknown')
full_document = event_data.get('fullDocument', {})
print(f"Operation type: {operation_type}")
print(f"db: {db}")
print(f"collection: {collection}")
print("Full document:", json.dumps(full_document, indent=2))
```
### 使用 Amazon MSK 觸發條件調用 Lambda 函數
以下程式碼範例示範如何實作 Lambda 函式，該函式會透過接收 Amazon MSK 叢集的記錄來接收所觸發的事件。函數會擷取 MSK 承載並記下記錄內容。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-msk-to-lambda)儲存庫中設定和執行。
使用 Python 搭配 Lambda 來取用 Amazon MSK 事件。
```
import base64
def lambda_handler(event, context):
# Iterate through keys
for key in event['records']:
print('Key:', key)
# Iterate through records
for record in event['records'][key]:
print('Record:', record)
# Decode base64
msg = base64.b64decode(record['value']).decode('utf-8')
print('Message:', msg)
```
### 使用 Amazon S3 觸發條件調用 Lambda 函數
下列程式碼範例示範如何實作 Lambda 函式，該函式接收透過上傳物件至 S3 儲存貯體時所觸發的事件。此函數會從事件參數擷取 S3 儲存貯體名稱和物件金鑰，並呼叫 Amazon S3 API 以擷取和記錄物件的內容類型。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-s3-to-lambda)儲存庫中設定和執行。
使用 Python 搭配 Lambda 來使用 S3 事件。
```
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
import json
import urllib.parse
import boto3
print('Loading function')
s3 = boto3.client('s3')
def lambda_handler(event, context):
#print("Received event: " + json.dumps(event, indent=2))
# Get the object from the event and show its content type
bucket = event['Records'][0]['s3']['bucket']['name']
key = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['key'], encoding='utf-8')
try:
response = s3.get_object(Bucket=bucket, Key=key)
print("CONTENT TYPE: " + response['ContentType'])
return response['ContentType']
except Exception as e:
print(e)
print('Error getting object {} from bucket {}. Make sure they exist and your bucket is in the same region as this function.'.format(key, bucket))
raise e
```
### 使用 Amazon SNS 觸發條件調用 Lambda 函數
下列程式碼範例示範如何實作 Lambda 函式，該函式會透過接收 SNS 主題的訊息來接收所觸發的事件。函數會從事件參數擷取訊息，並記錄每一則訊息的內容。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-sns-to-lambda)儲存庫中設定和執行。
使用 Python 搭配 Lambda 來使用 SNS 事件。
```
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def lambda_handler(event, context):
for record in event['Records']:
process_message(record)
print("done")
def process_message(record):
try:
message = record['Sns']['Message']
print(f"Processed message {message}")
# TODO; Process your record here
except Exception as e:
print("An error occurred")
raise e
```
### 使用 Amazon SQS 觸發條件調用 Lambda 函數
下列程式碼範例示範如何實作 Lambda 函式，該函式會透過接收 SQS 佇列的訊息來接收所觸發的事件。函數會從事件參數擷取訊息，並記錄每一則訊息的內容。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-sqs-to-lambda)儲存庫中設定和執行。
使用 Python 搭配 Lambda 來使用 SQS 事件。
```
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def lambda_handler(event, context):
for message in event['Records']:
process_message(message)
print("done")
def process_message(message):
try:
print(f"Processed message {message['body']}")
# TODO: Do interesting work based on the new message
except Exception as err:
print("An error occurred")
raise err
```
### 使用 Kinesis 觸發條件報告 Lambda 函數的批次項目失敗
下列程式碼範例示範如何針對接收來自 Kinesis 串流之事件的 Lambda 函式，實作部分批次回應。此函數會在回應中報告批次項目失敗，指示 Lambda 稍後重試這些訊息。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-kinesis-to-lambda-with-batch-item-handling)儲存庫中設定和執行。
透過使用 Python 的 Lambda 報告 Kinesis 批次項目失敗。
```
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def handler(event, context):
records = event.get("Records")
curRecordSequenceNumber = ""
for record in records:
try:
# Process your record
curRecordSequenceNumber = record["kinesis"]["sequenceNumber"]
except Exception as e:
# Return failed record's sequence number
return {"batchItemFailures":[{"itemIdentifier": curRecordSequenceNumber}]}
return {"batchItemFailures":[]}
```
### 使用 DynamoDB 觸發條件報告 Lambda 函式的批次項目失敗
下列程式碼範例示範如何針對接收來自 DynamoDB 串流之事件的 Lambda 函式，實作部分批次回應。此函數會在回應中報告批次項目失敗，指示 Lambda 稍後重試這些訊息。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/integration-ddb-to-lambda-with-batch-item-handling)儲存庫中設定和執行。
使用 Python 搭配 Lambda 報告 DynamoDB 批次項目失敗。
```
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def handler(event, context):
records = event.get("Records")
curRecordSequenceNumber = ""
for record in records:
try:
# Process your record
curRecordSequenceNumber = record["dynamodb"]["SequenceNumber"]
except Exception as e:
# Return failed record's sequence number
return {"batchItemFailures":[{"itemIdentifier": curRecordSequenceNumber}]}
return {"batchItemFailures":[]}
```
### 使用 Amazon SQS 觸發條件報告 Lambda 函數的批次項目失敗
下列程式碼範例示範如何為接收從 SQS 佇列接收事件的 Lambda 函式，實作部分批次回應。此函數會在回應中報告批次項目失敗，指示 Lambda 稍後重試這些訊息。
**適用於 Python 的 SDK (Boto3)**
GitHub 上提供更多範例。尋找完整範例，並了解如何在[無伺服器範例](https://github.com/aws-samples/serverless-snippets/tree/main/lambda-function-sqs-report-batch-item-failures)儲存庫中設定和執行。
使用 Python 搭配 Lambda 報告 SQS 批次項目失敗。
```
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def lambda_handler(event, context):
if event:
batch_item_failures = []
sqs_batch_response = {}
for record in event["Records"]:
try:
print(f"Processed message: {record['body']}")
except Exception as e:
batch_item_failures.append({"itemIdentifier": record['messageId']})
sqs_batch_response["batchItemFailures"] = batch_item_failures
return sqs_batch_response
```