You are viewing the documentation for an older version of boto (boto2).

Boto3, the next version of Boto, is now stable and recommended for general use. It can be used side-by-side with Boto in the same project, so it is easy to start using Boto3 in your existing projects as well as new projects. Going forward, API updates and all new feature work will be focused on Boto3.

For more information, see the documentation for boto3.

Boto Config


There is a growing list of configuration options for the boto library. Many of these options can be passed into the constructors for top-level objects such as connections. Some options, such as credentials, can also be read from environment variables (e.g. AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SECURITY_TOKEN and AWS_PROFILE). It is also possible to manage these options in a central place through the use of boto config files.


A boto config file is a text file formatted like an .ini configuration file that specifies values for options that control the behavior of the boto library. In Unix/Linux systems, on startup, the boto library looks for configuration files in the following locations and in the following order:

  • /etc/boto.cfg - for site-wide settings that all users on this machine will use
  • (if profile is given) ~/.aws/credentials - for credentials shared between SDKs
  • (if profile is given) ~/.boto - for user-specific settings
  • ~/.aws/credentials - for credentials shared between SDKs
  • ~/.boto - for user-specific settings

Comments You can comment out a line by putting a ‘#’ at the beginning of the line, just like in Python code.

In Windows, create a text file that has any name (e.g. boto.config). It’s recommended that you put this file in your user folder. Then set a user environment variable named BOTO_CONFIG to the full path of that file.

The options in the config file are merged into a single, in-memory configuration that is available as boto.config. The boto.pyami.config.Config class is a subclass of the standard Python ConfigParser.SafeConfigParser object and inherits all of the methods of that object. In addition, the boto Config class defines additional methods that are described on the PyamiConfigMethods page.

An example boto config file might look like:

aws_access_key_id = <your_access_key_here>
aws_secret_access_key = <your_secret_key_here>


The following sections and options are currently recognized within the boto config file.


The Credentials section is used to specify the AWS credentials used for all boto requests. The order of precedence for authentication credentials is:

  • Credentials passed into the Connection class constructor.
  • Credentials specified by environment variables
  • Credentials specified as named profiles in the shared credential file.
  • Credentials specified by default in the shared credential file.
  • Credentials specified as named profiles in the config file.
  • Credentials specified by default in the config file.

This section defines the following options: aws_access_key_id and aws_secret_access_key. The former being your AWS key id and the latter being the secret key.

For example:

[profile name_goes_here]
aws_access_key_id = <access key for this profile>
aws_secret_access_key = <secret key for this profile>

aws_access_key_id = <your default access key>
aws_secret_access_key = <your default secret key>

Please notice that quote characters are not used to either side of the ‘=’ operator even when both your AWS access key ID and secret key are strings.

If you have multiple AWS keypairs that you use for different purposes, use the profile style shown above. You can set an arbitrary number of profiles within your configuration files and then reference them by name when you instantiate your connection. If you specify a profile that does not exist in the configuration, the keys used under the [Credentials] heading will be applied by default.

The shared credentials file in ~/.aws/credentials uses a slightly different format. For example:

aws_access_key_id = <your default access key>
aws_secret_access_key = <your default secret key>

aws_access_key_id = <access key for this profile>
aws_secret_access_key = <secret key for this profile>

aws_access_key_id = <access key for this profile>
aws_secret_access_key = <secret key for this profile>
aws_security_token = <optional security token for this profile>

For greater security, the secret key can be stored in a keyring and retrieved via the keyring package. To use a keyring, use keyring, rather than aws_secret_access_key:

aws_access_key_id = <your access key>
keyring = <keyring name>

To use a keyring, you must have the Python keyring package installed and in the Python path. To learn about setting up keyrings, see the keyring documentation

Credentials can also be supplied for a Eucalyptus service:

euca_access_key_id = <your access key>
euca_secret_access_key = <your secret key>

Finally, this section is also be used to provide credentials for the Internet Archive API:

ia_access_key_id = <your access key>
ia_secret_access_key = <your secret key>


The Boto section is used to specify options that control the operation of boto itself. This section defines the following options:


Controls the level of debug messages that will be printed by the boto library. The following values are defined:

0 - no debug messages are printed
1 - basic debug messages from boto are printed
2 - all boto debugging messages plus request/response messages from httplib

The name of the proxy host to use for connecting to AWS.


The port number to use to connect to the proxy host.


The user name to use when authenticating with proxy host.


The password to use when authenticating with proxy host.


The number of times to retry failed requests to an AWS server. If boto receives an error from AWS, it will attempt to recover and retry the request. The default number of retries is 5 but you can change the default with this option.

For example:

debug = 0
num_retries = 10

proxy =
proxy_port = 8080
proxy_user = foo
proxy_pass = bar
 Amount of time to wait in seconds before a connection will stop getting reused. AWS will disconnect connections which have been idle for 180 seconds.
is_secure:Is the connection over SSL. This setting will override passed in values.
 Validate HTTPS certificates. This is on by default
 Location of CA certificates or the keyword “system”. Using the system keyword lets boto get out of the way and makes the SSL certificate validation the responsibility the underlying SSL implementation provided by the system.
 Timeout used to overwrite the system default socket timeout for httplib .
 Change line ending behaviour with proxies. For more details see this discussion
endpoints_path:Allows customizing the regions/endpoints available in Boto. Provide an absolute path to a custom JSON file, which gets merged into the defaults. (This can also be specified with the BOTO_ENDPOINTS environment variable instead.)
 Allows using endpoint heuristics to guess endpoints for regions that aren’t built in. This can also be specified with the BOTO_USE_ENDPOINT_HEURISTICS environment variable.

These settings will default to:

connection_stale_duration = 180
is_secure = True
https_validate_certificates = True
ca_certificates_file = cacerts.txt
http_socket_timeout = 60
send_crlf_after_proxy_auth_headers = False
endpoints_path = /path/to/my/boto/endpoints.json
use_endpoint_heuristics = False

You can control the timeouts and number of retries used when retrieving information from the Metadata Service (this is used for retrieving credentials for IAM roles on EC2 instances):

 Number of seconds until requests to the metadata service will timeout (float).
 Number of times to attempt to retrieve information from the metadata service before giving up (int).

These settings will default to:

metadata_service_timeout = 1.0
metadata_service_num_attempts = 1

This section is also used for specifying endpoints for non-AWS services such as Eucalyptus and Walrus.

 Select a default endpoint host for eucalyptus
walrus_host:Select a default host for Walrus

For example:

eucalyptus_host =
walrus_host =

Finally, the Boto section is used to set defaults versions for many AWS services

AutoScale settings:

options: :autoscale_version: Set the API version :autoscale_endpoint: Endpoint to use :autoscale_region_name: Default region to use

For example:

autoscale_version = 2011-01-01
autoscale_endpoint =
autoscale_region_name = us-west-2

Cloudformation settings can also be defined:

cfn_version:Cloud formation API version
 Default region name
 Default endpoint

For example:

cfn_version = 2010-05-15
cfn_region_name = us-west-2
cfn_region_endpoint =

Cloudsearch settings:

cs_region_name:Default cloudsearch region
 Default cloudsearch endpoint

For example:

cs_region_name = us-west-2
cs_region_endpoint =

Cloudwatch settings:

 Cloudwatch API version
 Default region name
 Default endpoint

For example:

cloudwatch_version = 2010-08-01
cloudwatch_region_name = us-west-2
cloudwatch_region_endpoint =

EC2 settings:

ec2_version:EC2 API version
 Default region name
 Default endpoint

For example:

ec2_version = 2012-12-01
ec2_region_name = us-west-2
ec2_region_endpoint =

ELB settings:

elb_version:ELB API version
 Default region name
 Default endpoint

For example:

elb_version = 2012-06-01
elb_region_name = us-west-2
elb_region_endpoint =

EMR settings:

emr_version:EMR API version
 Default region name
 Default endpoint

For example:

emr_version = 2009-03-31
emr_region_name = us-west-2
emr_region_endpoint =


Even if you have your boto config setup, you can also have credentials and options stored in environmental variables or you can explicitly pass them to method calls i.e.:

>>> boto.ec2.connect_to_region(
...     'us-west-2',
...     aws_access_key_id='foo',
...     aws_secret_access_key='bar')

In these cases where these options can be found in more than one place boto will first use the explicitly supplied arguments, if none found it will then look for them amidst environment variables and if that fails it will use the ones in boto config.


If you are using notifications for boto.pyami, you can specify the email details through the following variables.

smtp_from:Used as the sender in notification emails.
smtp_to:Destination to which emails should be sent
smtp_host:Host to connect to when sending notification emails.
smtp_port:Port to connect to when connecting to the :smtp_host:

Default values are:

smtp_from = boto
smtp_to = None
smtp_host = localhost
smtp_port = 25
smtp_tls = True
smtp_user = john
smtp_pass = hunter2


The SWF section allows you to configure the default region to be used for the Amazon Simple Workflow service.

region:Set the default region


region = us-west-2


The Pyami section is used to configure the working directory for PyAMI.

working_dir:Working directory used by PyAMI


working_dir = /home/foo/


The DB section is used to configure access to databases through the boto.sdb.db.manager.get_manager() function.

db_type:Type of the database. Current allowed values are SimpleDB and XML.
db_user:AWS access key id.
db_passwd:AWS secret access key.
db_name:Database that will be connected to.
db_table:Table name :note: This doesn’t appear to be used.
db_host:Host to connect to
db_port:Port to connect to
enable_ssl:Use SSL

More examples:

db_type = SimpleDB
db_user = <aws access key id>
db_passwd = <aws secret access key>
db_name = my_domain
db_table = table
db_host =
enable_ssl = True
debug = True

db_type = SimpleDB
db_user = <another aws access key id>
db_passwd = <another aws secret access key>
db_name = basic_domain
db_port = 1111


This section is used to configure SimpleDB

region:Set the region to which SDB should connect


region = us-west-2


This section is used to configure DynamoDB

region:Choose the default region
 Check checksums returned by DynamoDB


region = us-west-2
validate_checksums = True