This Python package provides multithreaded and asyncio Python clients for the EventStoreDB database.
The multithreaded EventStoreDBClient
is described in detail below. Please scroll
down for information about AsyncEventStoreDBClient
.
These clients have been developed and are being maintained in a collaboration with the EventStoreDB team, and are officially support by Event Store Ltd. Although not all aspects of the EventStoreDB gRPC API are implemented, most features are presented in an easy-to-use interface.
These clients have been tested to work with EventStoreDB LTS versions 22.10, 23.10, and 24.10, without and without SSL/TLS, with both single-server and cluster modes, and with Python versions 3.8, 3.9, 3.10, 3.11, 3.12, and 3.13.
The test suite has 100% line and branch coverage. The code has typing annotations checked strictly with mypy. The code is formatted with black and isort, and checked with flake8. Poetry is used for package management during development, and for building and publishing distributions to PyPI.
For an example of usage, see the eventsourcing-eventstoredb package.
- Synopsis
- Install package
- EventStoreDB server
- EventStoreDB client
- Connection strings
- Event objects
- Streams
- Catch-up subscriptions
- Persistent subscriptions
- Create subscription to all
- Read subscription to all
- How to write a persistent subscription consumer
- Update subscription to all
- Create subscription to stream
- Read subscription to stream
- Update subscription to stream
- Replay parked events
- Get subscription info
- List subscriptions
- List subscriptions to stream
- Delete subscription
- Projections
- Call credentials
- Connection
- Asyncio client
- Notes
- Instrumentation
- Communities
- Contributors
The EventStoreDBClient
class can be imported from the esdbclient
package.
Probably the three most useful methods of EventStoreDBClient
are:
-
append_to_stream()
This method can be used to record new events in a particular "stream". This is useful, for example, when executing a command in an application that mutates an aggregate. This method is "atomic" in that either all or none of the events will be recorded. -
get_stream()
This method can be used to retrieve all the recorded events in a "stream". This is useful, for example, when reconstructing an aggregate from recorded events before executing a command in an application that creates new events. -
subscribe_to_all()
This method can be used to receive all recorded events in the database. This is useful, for example, in event-processing components because it supports processing events with "exactly-once" semantics.
The example below uses an "insecure" EventStoreDB server running locally on port 2113.
import uuid
from esdbclient import EventStoreDBClient, NewEvent, StreamState
# Construct EventStoreDBClient with an EventStoreDB URI. The
# connection string URI specifies that the client should
# connect to an "insecure" server running on port 2113.
client = EventStoreDBClient(
uri="esdb://localhost:2113?Tls=false"
)
# Generate new events. Typically, domain events of different
# types are generated in a domain model, and then serialized
# into NewEvent objects. An aggregate ID may be used as the
# name of a stream in EventStoreDB.
stream_name1 = str(uuid.uuid4())
event1 = NewEvent(
type='OrderCreated',
data=b'{"order_number": "123456"}'
)
event2 = NewEvent(
type='OrderSubmitted',
data=b'{}'
)
event3 = NewEvent(
type='OrderCancelled',
data=b'{}'
)
# Append new events to a new stream. The value returned
# from the append_to_stream() method is the overall
# "commit position" in the database of the last new event
# recorded by this operation. The returned "commit position"
# may be used in a user interface to poll an eventually
# consistent event-processing component until it can
# present an up-to-date materialized view. New events are
# each allocated a "stream position", which is the next
# available position in the stream, starting from 0.
commit_position1 = client.append_to_stream(
stream_name=stream_name1,
current_version=StreamState.NO_STREAM,
events=[event1, event2],
)
# Append events to an existing stream. The "current version"
# is the "stream position" of the last recorded event in a
# stream. We have recorded two new events, so the "current
# version" is 1. The exception 'WrongCurrentVersion' will be
# raised if an incorrect value is given.
commit_position2 = client.append_to_stream(
stream_name=stream_name1,
current_version=1,
events=[event3],
)
# - allocated commit positions increase monotonically
assert commit_position2 > commit_position1
# Get events recorded in a stream. This method returns
# a sequence of recorded event objects. The recorded
# event objects may be deserialized to domain event
# objects of different types and used to reconstruct
# an aggregate in a domain model.
recorded_events = client.get_stream(
stream_name=stream_name1
)
# - stream 'stream_name1' now has three events
assert len(recorded_events) == 3
# - allocated stream positions are zero-based and gapless
assert recorded_events[0].stream_position == 0
assert recorded_events[1].stream_position == 1
assert recorded_events[2].stream_position == 2
# - event attribute values are recorded faithfully
assert recorded_events[0].type == "OrderCreated"
assert recorded_events[0].data == b'{"order_number": "123456"}'
assert recorded_events[0].id == event1.id
assert recorded_events[1].type == "OrderSubmitted"
assert recorded_events[1].data == b'{}'
assert recorded_events[1].id == event2.id
assert recorded_events[2].type == "OrderCancelled"
assert recorded_events[2].data == b'{}'
assert recorded_events[2].id == event3.id
# Start a catch-up subscription from last recorded position.
# This method returns a "catch-up subscription" object,
# which can be iterated over to obtain recorded events.
# The iterator will not stop when there are no more recorded
# events to be returned, but instead will block, and then continue
# when further events are recorded. It can be used as a context
# manager so that the underlying streaming gRPC call to the database
# can be cancelled cleanly in case of any error.
received_events = []
with client.subscribe_to_all(commit_position=0) as subscription:
# Iterate over the catch-up subscription. Process each recorded
# event in turn. Within an atomic database transaction, record
# the event's "commit position" along with any new state generated
# by processing the event. Use the component's last recorded commit
# position when restarting the catch-up subscription.
for event in subscription:
received_events.append(event)
if event.commit_position == commit_position2:
# Break so we can continue with the example.
break
# - events are received in the order they were recorded
assert received_events[-3].type == "OrderCreated"
assert received_events[-3].data == b'{"order_number": "123456"}'
assert received_events[-3].id == event1.id
assert received_events[-2].type == "OrderSubmitted"
assert received_events[-2].data == b'{}'
assert received_events[-2].id == event2.id
assert received_events[-1].type == "OrderCancelled"
assert received_events[-1].data == b'{}'
assert received_events[-1].id == event3.id
# Close the client's gRPC connection.
client.close()
It is recommended to install Python packages into a Python virtual environment.
You can use pip to install this package directly from the Python Package Index.
$ pip install esdbclient
You can use Poetry to add this package to your pyproject.toml and install it.
$ poetry add esdbclient
The EventStoreDB server can be run locally using the official Docker container image.
For development, you can run a "secure" EventStoreDB server using the following command.
$ docker run -d --name eventstoredb-secure -it -p 2113:2113 --env "HOME=/tmp" docker.eventstore.com/eventstore/eventstoredb-ee:24.10.0-x64-8.0-bookworm-slim --dev
As we will see, your client will need an EventStoreDB connection string URI as the value
of its uri
constructor argument. The connection string for this "secure" EventStoreDB
server would be:
esdb://admin:changeit@localhost:2113
To connect to a "secure" server, you will usually need to include a "username" and a "password" in the connection string, so that the server can authenticate the client. With EventStoreDB, the default username is "admin" and the default password is "changeit".
When connecting to a "secure" server, you may also need to provide an SSL/TLS certificate
as the value of the root_certificates
constructor argument. If the server certificate
is publicly signed, the root certificates of the certificate authority may be installed
locally and picked up by the grpc package from a default location. The client uses the
root SSL/TLS certificate to authenticate the server. For development, you can either
use the SSL/TLS certificate of a self-signing certificate authority used to create the
server's certificate. Or, when using a single-node cluster, you can just use the server
certificate itself, getting the server certificate with the following Python code.
import ssl
server_certificate = ssl.get_server_certificate(addr=('localhost', 2113))
Alternatively, you can start an "insecure" server using the following command.
$ docker run -d --name eventstoredb-insecure -it -p 2113:2113 docker.eventstore.com/eventstore/eventstoredb-ee:24.10.0-x64-8.0-bookworm-slim --insecure
The connection string URI for this "insecure" server would be:
esdb://localhost:2113?Tls=false
As we will see, when connecting to an "insecure" server, there is no need to include a "username" and a "password" in the connection string. If you do, these values will be ignored by the client, so that they are not sent over an insecure channel.
Please note, the "insecure" connection string uses a query string with the field-value
Tls=false
. The value of this field is by default true
.
To stop and remove the "secure" container, use the following Docker commands.
$ docker stop eventstoredb-secure
$ docker rm eventstoredb-secure
To stop and remove the "insecure" container, use the following Docker commands.
$ docker stop eventstoredb-insecure
$ docker rm eventstoredb-insecure
This EventStoreDB client is implemented in the esdbclient
package with
the EventStoreDBClient
class.
The EventStoreDBClient
class can be imported from the esdbclient
package.
from esdbclient import EventStoreDBClient
The EventStoreDBClient
class has one required constructor argument, uri
, and three
optional constructor argument, root_certificates
, private_key
, and certificate_chain
.
The uri
argument is expected to be an EventStoreDB connection string URI that
conforms with the standard EventStoreDB "esdb" or "esdb+discover" URI schemes.
The client must be configured to create a "secure" connection to a "secure" server,
or alternatively an "insecure" connection to an "insecure" server. By default, the
client will attempt to create a "secure" connection. And so, when connecting to an
"insecure" server, the connection string must specify that the client should attempt
to make an "insecure" connection by using the URI query string field-value Tls=false
.
The optional root_certificates
argument can be either a Python str
or a Python bytes
object containing PEM encoded SSL/TLS certificate(s), and is used to authenticate the
server to the client. When connecting to an "insecure" service, the value of this
argument will be ignored. When connecting to a "secure" server, it may be necessary to
set this argument. Typically, the value of this argument would be the public certificate
of the certificate authority that was responsible for generating the certificate used by
the EventStoreDB server. It is unnecessary to set this value in this case if certificate
authority certificates are installed locally, such that the Python grpc library can pick
them up from a default location. Alternatively, for development, you can use the server's
certificate itself. The value of this argument is passed directly to grpc.ssl_channel_credentials()
.
An alternative way to supply the root_certificates
argument is through the tlsCaFile
field-value of the connection string URI query string (see below). If the tlsCaFile
field-value is specified, the root_certificates
argument will be ignored.
The optional private_key
and certificate_chain
arguments are both either a Python
str
or a Python bytes
object. These arguments may be used to authenticate the client
to the server. It is necessary to provide correct values for these arguments when connecting
to a "secure" server that is running the commercial edition of EventStoreDB with the
User Certificates plugin enabled. The value of private_key
should be the X.509 user
certificate's private key in PEM format. The value of certificate_chain
should be the
X.509 user certificate itself in PEM format. The values of these arguments are passed
directly to grpc.ssl_channel_credentials()
. When connecting to an "insecure" service,
the values of these arguments will be ignored. Please note, an alternative way of
supplying the client with a user certificate and private key is to use the UserCertFile
and UserKeyFile
field-values of the connection string URI query string (see below).
If the UserCertFile
field-value is specified, the certificate_chain
argument will be
ignored. If the UserKeyFile
field-value is specified, the public_key
argument will be
ignored.
In the example below, constructor argument values for uri
and root_certificates
are
taken from the operating system environment.
import os
client = EventStoreDBClient(
uri=os.getenv("ESDB_URI"),
root_certificates=os.getenv("ESDB_ROOT_CERTIFICATES"),
)
An EventStoreDB connection string is a URI that conforms with one of two possible schemes: either the "esdb" scheme, or the "esdb+discover" scheme.
The syntax and semantics of the EventStoreDB URI schemes are described below. The syntax is defined using EBNF.
The "esdb" URI scheme can be defined in the following way.
esdb-uri = "esdb://" , [ user-info , "@" ] , grpc-target, { "," , grpc-target } , [ "?" , query-string ] ;
In the "esdb" URI scheme, after the optional user info string, there must be at least one gRPC target. If there are several gRPC targets, they must be separated from each other with the "," character.
Each gRPC target should indicate an EventStoreDB gRPC server socket, all in the same EventStoreDB cluster, by specifying a host and a port number separated with the ":" character. The host may be a hostname that can be resolved to an IP address, or an IP address.
grpc-target = ( hostname | ip-address ) , ":" , port-number ;
If there is one gRPC target, the client will simply attempt to connect to this server, and it will use this connection when recording and retrieving events.
If there are two or more gRPC targets, the client will attempt to connect to the Gossip API of each in turn, attempting to obtain information about the cluster from it, until information about the cluster is obtained. A member of the cluster is then selected by the client according to the "node preference" specified by the connection string URI. The client will then close its connection and connect to the selected node without the 'round robin' load balancing strategy. If the "node preference" is "leader", and after connecting to a leader, if the leader becomes a follower, the client will reconnect to the new leader.
The "esdb+discover" URI scheme can be defined in the following way.
esdb-discover-uri = "esdb+discover://" , [ user-info, "@" ] , cluster-domainname, [ ":" , port-number ] , [ "?" , query-string ] ;
In the "esdb+discover" URI scheme, after the optional user info string, there should be a domain name which identifies a cluster of EventStoreDB servers. Individual nodes in the cluster should be declared with DNS 'A' records.
The client will use the cluster domain name with the gRPC library's 'round robin' load balancing strategy to call the Gossip APIs of addresses discovered from DNS 'A' records. Information about the EventStoreDB cluster is obtained from the Gossip API. A member of the cluster is then selected by the client according to the "node preference" option. The client will then close its connection and connect to the selected node without the 'round robin' load balancing strategy. If the "node preference" is "leader", and after connecting to a leader, if the leader becomes a follower, the client will reconnect to the new leader.
In both the "esdb" and "esdb+discover" schemes, the URI may include a user info string. If it exists in the URI, the user info string must be separated from the rest of the URI with the "@" character. The user info string must include a username and a password, separated with the ":" character.
user-info = username , ":" , password ;
The user info is sent by the client in a "basic auth" authorization header in each gRPC call to a "secure" server. This authorization header is used by the server to authenticate the client. The Python gRPC library does not allow call credentials to be transferred to "insecure" servers.
In both the "esdb" and "esdb+discover" schemes, the optional query string must be one or many field-value arguments, separated from each other with the "&" character.
query-string = field-value, { "&", field-value } ;
Each field-value argument must be one of the supported fields, and an appropriate value, separated with the "=" character.
field-value = ( "Tls", "=" , "true" | "false" )
| ( "TlsVerifyCert", "=" , "true" | "false" )
| ( "ConnectionName", "=" , string )
| ( "NodePreference", "=" , "leader" | "follower" | "readonlyreplica" | "random" )
| ( "DefaultDeadline", "=" , integer )
| ( "GossipTimeout", "=" , integer )
| ( "MaxDiscoverAttempts", "=" , integer )
| ( "DiscoveryInterval", "=" , integer )
| ( "KeepAliveInterval", "=" , integer )
| ( "KeepAliveTimeout", "=" , integer ) ;
| ( "TlsCaFile", "=" , string ) ;
| ( "UserCertFile", "=" , string ) ;
| ( "UserKeyFile", "=" , string ) ;
The table below describes the query string field-values supported by this client.
Field | Value | Description |
---|---|---|
Tls | "true", "false" (default: "true") | If "true" the client will create a "secure" gRPC channel. If "false" the client will create an "insecure" gRPC channel. This must match the server configuration. |
TlsVerifyCert | "true", "false" (default: "true") | This value is currently ignored. |
ConnectionName | string (default: auto-generated version-4 UUID) | Sent in call metadata for every call, to identify the client to the cluster. |
NodePreference | "leader", "follower", "readonlyreplica", "random" (default: "leader") | The node state preferred by the client. The client will select a node from the cluster info received from the Gossip API according to this preference. |
DefaultDeadline | integer (default: None ) |
The default value (in seconds) of the timeout argument of client "write" methods such as append_to_stream() . |
GossipTimeout | integer (default: 5) | The default value (in seconds) of the timeout argument of gossip read methods, such as read_gossip() . |
MaxDiscoverAttempts | integer (default: 10) | The number of attempts to read gossip when connecting or reconnecting to a cluster member. |
DiscoveryInterval | integer (default: 100) | How long to wait (in milliseconds) between gossip retries. |
KeepAliveInterval | integer (default: None ) |
The value (in milliseconds) of the "grpc.keepalive_ms" gRPC channel option. |
KeepAliveTimeout | integer (default: None ) |
The value (in milliseconds) of the "grpc.keepalive_timeout_ms" gRPC channel option. |
TlsCaFile | string (default: None ) |
Absolute filesystem path to file containing the CA certicate in PEM format. This will be used to verify the server's certificate. |
UserCertFile | string (default: None ) |
Absolute filesystem path to file containing the X.509 user certificate in PEM format. |
UserKeyFile | string (default: None ) |
Absolute filesystem path to file containing the X.509 user certificate's private key in PEM format. |
Please note, the client is insensitive to the case of fields and values. If fields are repeated in the query string, the query string will be parsed without error. However, the connection options used by the client will use the value of the first field. All the other field-values in the query string with the same field name will be ignored. Fields without values will also be ignored.
If the client's node preference is "follower" and there are no follower nodes in the cluster, then the client will raise an exception. Similarly, if the client's node preference is "readonlyreplica" and there are no read-only replica nodes in the cluster, then the client will also raise an exception.
The gRPC channel option "grpc.max_receive_message_length" is automatically
configured to the value 17 * 1024 * 1024
. This value cannot be configured.
Here are some examples of EventStoreDB connection string URIs.
The following URI will cause the client to make an "insecure" connection to
gRPC target 'localhost:2113'
. Because the client's node preference is "follower",
methods that can be called on a follower should complete successfully, methods that
require a leader will raise a NodeIsNotLeader
exception.
esdb://127.0.0.1:2113?Tls=false&NodePreference=follower
The following URI will cause the client to make an "insecure" connection to
gRPC target 'localhost:2113'
. Because the client's node preference is "leader",
if this node is not a leader, then a NodeIsNotLeader
exception will be raised by
all methods.
esdb://127.0.0.1:2113?Tls=false&NodePreference=leader
The following URI will cause the client to make a "secure" connection to
gRPC target 'localhost:2113'
with username 'admin'
and password 'changeit'
as the default call credentials when making calls to the EventStoreDB gRPC API.
Because the client's node preference is "leader", by default, if this node is not
a leader, then a NodeIsNotLeader
exception will be raised by all methods.
esdb://admin:changeit@localhost:2113
The following URI will cause the client to make "secure" connections, firstly to
get cluster info from either 'localhost:2111'
, or 'localhost:2112'
, or 'localhost:2113'
.
Because the client's node preference is "leader", the client will select the leader
node from the cluster info and reconnect to the leader. If the "leader" node becomes
a "follower" and another node becomes "leader", then the client will reconnect to the
new leader.
esdb://admin:changeit@localhost:2111,localhost:2112,localhost:2113?NodePreference=leader
The following URI will cause the client to make "secure" connections, firstly to
get cluster info from either 'localhost:2111'
, or 'localhost:2112'
, or 'localhost:2113'
.
Because the client's node preference is "follower", the client will select a follower
node from the cluster info and reconnect to this follower. Please note, if the "follower"
node becomes the "leader", the client will not reconnect to a follower -- such behavior
may be implemented in a future version of the client and server.
esdb://admin:changeit@localhost:2111,localhost:2112,localhost:2113?NodePreference=follower
The following URI will cause the client to make "secure" connections, firstly to get
cluster info from addresses in DNS 'A' records for 'cluster1.example.com'
, and then
to connect to a "leader" node. The client will use a default timeout
of 5 seconds when making calls to EventStore API "write" methods.
esdb+discover://admin:changeit@cluster1.example.com?DefaultDeadline=5
The following URI will cause the client to make "secure" connections, firstly to get
cluster info from addresses in DNS 'A' records for 'cluster1.example.com'
, and then
to connect to a "leader" node. It will configure gRPC connections with a "keep alive
interval" and a "keep alive timeout".
esdb+discover://admin:changeit@cluster1.example.com?KeepAliveInterval=10000&KeepAliveTimeout=10000
This package defines a NewEvent
class and a RecordedEvent
class. The
NewEvent
class should be used when writing events to the database. The
RecordedEvent
class is used when reading events from the database.
The NewEvent
class should be used when writing events to an EventStoreDB database.
You will need to construct new event objects before calling append_to_stream()
.
The NewEvent
class is a frozen Python dataclass. It has two required constructor
arguments (type
and data
) and three optional constructor arguments (metadata
,
content_type
and id
).
The required type
argument is a Python str
, used to describe the type of
domain event that is being recorded.
The required data
argument is a Python bytes
object, used to state the
serialized data of the domain event that is being recorded.
The optional metadata
argument is a Python bytes
object, used to indicate any
metadata of the event that will be recorded. The default value is an empty bytes
object.
The optional content_type
argument is a Python str
, used to indicate the
kind of data that is being recorded. The default value is 'application/json'
,
which indicates that the data
was serialised using JSON. An alternative value
for this argument is the more general indication 'application/octet-stream'
.
The optional id
argument is a Python UUID
object, used to specify the unique ID
of the event that will be recorded. If no value is provided, a new version-4 UUID
will be generated.
new_event1 = NewEvent(
type='OrderCreated',
data=b'{"name": "Greg"}',
)
assert new_event1.type == 'OrderCreated'
assert new_event1.data == b'{"name": "Greg"}'
assert new_event1.metadata == b''
assert new_event1.content_type == 'application/json'
assert isinstance(new_event1.id, uuid.UUID)
event_id = uuid.uuid4()
new_event2 = NewEvent(
type='ImageCreated',
data=b'01010101010101',
metadata=b'{"a": 1}',
content_type='application/octet-stream',
id=event_id,
)
assert new_event2.type == 'ImageCreated'
assert new_event2.data == b'01010101010101'
assert new_event2.metadata == b'{"a": 1}'
assert new_event2.content_type == 'application/octet-stream'
assert new_event2.id == event_id
The RecordedEvent
class is used when reading events from an EventStoreDB
database. The client will return event objects of this type from all methods
that return recorded events, such as get_stream()
, subscribe_to_all()
,
and read_subscription_to_all()
. You do not need to construct recorded event objects.
Like NewEvent
, the RecordedEvent
class is a frozen Python dataclass. It has
all the attributes that NewEvent
has (type
, data
, metadata
, content_type
, id
)
that follow from an event having been recorded, and some additional attributes that follow
from the recording of an event (stream_name
, stream_position
, commit_position
,
recorded_at
). It also has a link
attribute, which is None
unless the recorded
event is a "link event" that has been "resolved" to the linked event. And it has a
retry_count
which has an integer value when receiving recorded events from persistence
subscriptions, otherwise the value of retry_count
is None
.
The type
attribute is a Python str
, used to indicate the type of an event
that was recorded.
The data
attribute is a Python bytes
object, used to indicate the data of an
event that was recorded.
The metadata
attribute is a Python bytes
object, used to indicate the metadata of
an event that was recorded.
The content_type
attribute is a Python str
, used to indicate the type of
data that was recorded for an event. It is usually 'application/json'
, indicating
that the data can be parsed as JSON. Alternatively, it is 'application/octet-stream'
.
The id
attribute is a Python UUID
object, used to indicate the unique ID of an
event that was recorded.
The stream_name
attribute is a Python str
, used to indicate the name of a
stream in which an event was recorded.
The stream_position
attribute is a Python int
, used to indicate the position in a
stream at which an event was recorded.
In EventStoreDB, a "stream position" is an integer representing the position of a recorded event in a stream. Each recorded event is recorded at a position in a stream. Each stream position is occupied by only one recorded event. New events are recorded at the next unoccupied position. All sequences of stream positions are zero-based and gapless.
The commit_position
attribute is a Python int
, used to indicate the position in the
database at which an event was recorded.
In EventStoreDB, a "commit position" is an integer representing the position of a recorded event in the database. Each recorded event is recorded at a position in the database. Each commit position is occupied by only one recorded event. Commit positions are zero-based and increase monotonically as new events are recorded. But, unlike stream positions, the sequence of successive commit positions is not gapless. Indeed, there are usually large differences between the commit positions of successively recorded events.
Please note, in EventStoreDB 21.10, the commit_position
of all RecordedEvent
objects
obtained from read_stream()
is None
, whereas those obtained from read_all()
have
the actual commit position of the recorded event. This was changed in version 22.10, so
that event objects obtained from both get_stream()
and read_all()
have the actual
commit position. The commit_position
attribute of the RecordedEvent
class is
annotated with the type Optional[int]
for this reason only.
The recorded_at
attribute is a Python datetime
, used to indicate when an event was
recorded by the database.
The link
attribute is an optional RecordedEvent
that carries information about
a "link event" that has been "resolved" to the linked event. This allows access to
the link event attributes when link events have been resolved, for example access
to the correct event ID to be used when acknowledging or negatively acknowledging
link events. Link events are "resolved" when the resolve_links
argument is True
and when replaying parked events (negatively acknowledging an event received from
a persistent subscription with the 'park'
action will create a link event, and
when parked event are replayed they are received as resolved events). The
ack_id
property helps with obtaining the correct event ID to use when acknowledging
or negatively acknowledging events received from persistent subscriptions.
The retry_count
is a Python int
, used to indicate the number of times a persistent
subscription has retried sending the event to a consumer.
from dataclasses import dataclass
from datetime import datetime
@dataclass(frozen=True)
class RecordedEvent:
"""
Encapsulates event data that has been recorded in EventStoreDB.
"""
type: str
data: bytes
metadata: bytes
content_type: str
id: UUID
stream_name: str
stream_position: int
commit_position: Optional[int]
recorded_at: Optional[datetime] = None
link: Optional["RecordedEvent"] = None
retry_count: Optional[int] = None
@property
def ack_id(self) -> UUID:
if self.link is not None:
return self.link.id
else:
return self.id
@property
def is_system_event(self) -> bool:
return self.type.startswith("$")
@property
def is_link_event(self) -> bool:
return self.type == "$>"
@property
def is_resolved_event(self) -> bool:
return self.link is not None
@property
def is_checkpoint(self) -> bool:
return False
The property ack_id
can be used to obtain the correct event ID to ack()
or nack()
events received when reading persistent subscriptions. The returned value is either the
value of the id
attribute of the link
attribute, if link
is not None
, otherwise
it is the value of the id
attribute.
The property is_system_event
indicates whether the event is a "system event". System
events have a type
value that starts with '$'
.
The property is_link_event
indicates whether the event is a "link event". Link
events have a type
value of '$>'
.
The property is_resolve_event
indicates whether the event has been resolved from a
"link event". The returned value is True
if link
is not None
.
The property is_checkpoint
is False
. This can be used to identify Checkpoint
instances returned when receiving events from include_checkpoints=True
.
In EventStoreDB, a "stream" is a sequence of recorded events that all have the same "stream name". There will normally be many streams in a database, each with many recorded events. Each recorded event has a position in its stream (the "stream position"), and a position in the database (the "commit position"). Stream positions are zero-based and gapless. Commit positions are also zero-based, but are not gapless.
The methods append_to_stream()
, get_stream()
and read_all()
can
be used to read and record in the database.
requires leader
The append_to_stream()
method can be used atomically to record a sequence of new events.
If the operation is successful, it returns the commit position of the last event in the
sequence that has been recorded.
This method has three required arguments, stream_name
, current_version
and events
.
The required stream_name
argument is a Python str
that uniquely identifies a
stream to which a sequence of events will be appended.
The required current_version
argument is expected to be either a Python int
that indicates the stream position of the last recorded event in the stream, or
StreamState.NO_STREAM
if the stream does not yet exist or has been deleted. The
stream positions are zero-based and gapless, so that if a stream has two events, the
current_version
should be 1. If an incorrect value is given, this method will raise a
WrongCurrentVersion
exception. This behavior is designed to provide concurrency
control when recording new events. The correct value of current_version
for any stream
can be obtained by calling get_current_version()
. However, the typical approach is to
reconstruct an aggregate from the recorded events, so that the version of the aggregate
is the stream position of the last recorded event, then have the aggregate generate new
events, and then use the current version of the aggregate as the value of the
current_version
argument when appending the new aggregate events. This ensures
the consistency of the recorded aggregate events, because operations that generate
new aggregate events can be retried with a freshly reconstructed aggregate if
a WrongCurrentVersion
exception is encountered when recording new events. This
controlling behavior can be entirely disabled by setting the value of the current_version
argument to the constant StreamState.ANY
. More selectively, this behaviour can be
disabled for existing streams by setting the value of the current_version
argument to the constant StreamState.EXISTS
.
The required events
argument is expected to be a sequence of new event objects. The
NewEvent
class should be used to construct new event objects. The append_to_stream()
operation is atomic, so that either all or none of the new events will be recorded. It
is not possible with EventStoreDB atomically to record new events in more than one stream.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
In the example below, a new event, event1
, is appended to a new stream. The stream
does not yet exist, so current_version
is StreamState.NO_STREAM
.
# Construct a new event object.
event1 = NewEvent(type='OrderCreated', data=b'{}')
# Define a new stream name.
stream_name1 = str(uuid.uuid4())
# Append the new events to the new stream.
commit_position1 = client.append_to_stream(
stream_name=stream_name1,
current_version=StreamState.NO_STREAM,
events=[event1],
)
In the example below, two subsequent events are appended to an existing
stream. The stream has one recorded event, so current_version
is 0
.
event2 = NewEvent(type='OrderUpdated', data=b'{}')
event3 = NewEvent(type='OrderDeleted', data=b'{}')
commit_position2 = client.append_to_stream(
stream_name=stream_name1,
current_version=0,
events=[event2, event3],
)
The returned values, commit_position1
and commit_position2
, are the
commit positions in the database of the last events in the recorded sequences.
That is, commit_position1
is the commit position of event1
and
commit_position2
is the commit position of event3
.
Commit positions that are returned in this way can be used by a user interface to poll a downstream component until it has processed all the newly recorded events. For example, consider a user interface command that results in the recording of new events, and an eventually consistent materialized view in a downstream component that is updated from these events. If the new events have not yet been processed, the view might be stale, or out-of-date. Instead of displaying a stale view, the user interface can poll the downstream component until it has processed the newly recorded events, and then display an up-to-date view to the user.
The append_to_stream()
method is "idempotent" with respect to the id
value of a
NewEvent
object. That is to say, if append_to_stream()
is called with events
whose id
values are equal to those already recorded in the stream, then the
method call will successfully return, with the commit position of the last new event,
without making any changes to the database.
This is because sometimes it may happen, when calling append_to_stream()
, that the new
events are successfully recorded, but somehow something bad happens before the method call
can return successfully to the caller. In this case, we cannot be sure that the events have
in fact been recorded, and so we may wish to retry.
If the events were in fact successfully recorded, it is convenient for the retried method call
to return successfully, and without either raising an exception (when current_version
is either StreamState.NO_STREAM
an integer value) or creating further event records
(when current_version
is StreamState.ANY
or StreamState.EXISTS
), as it would
if the append_to_stream()
method were not idempotent.
If the method call initially failed and the new events were not in fact recorded, it
makes good sense, when the method call is retried, that the new events are recorded
and that the method call returns successfully. If the concurrency controls have not been disabled,
that is if the current version
is either StreamState.NO_STREAM
or an integer value, and
if a WrongCurrentVersion
exception is raised when retrying the method call, then we can assume
both that the initial method call did not in fact successfully record the events, and also
that subsequent events have in the meantime been recorded by somebody else. In this case,
an application command which generated the new events may need to be executed again. And
the user of the application may need to be given an opportunity to decide if they still wish to
proceed with their original intention, by displaying a suitable error with an up-to-date view of
the recorded state. In the case where concurrency controls have been disabled, by using StreamState.ANY
or
StreamState.EXISTS
as the value of current_version
, retrying a method call that failed to
return successfully will, more simply, just attempt to ensure the new events are recorded, regardless
of their resulting stream positions. In either case, when the method call does return successfully, we
can be sure the events have been recorded.
The example below shows the append_to_stream()
method being called again with events
event2
and event3
, and with current_version=0
. We can see that repeating the call
to append_to_stream()
returns successfully without raising a WrongCurrentVersion
exception, as it would if the append_to_stream()
operation were not idempotent.
# Retry appending event3.
commit_position_retry = client.append_to_stream(
stream_name=stream_name1,
current_version=0,
events=[event2, event3],
)
We can see that the same commit position is returned as above.
assert commit_position_retry == commit_position2
The example below shows the append_to_stream()
method being called again with events
event2
and event3
, with and current_version=StreamState.ANY
.
# Retry appending event3.
commit_position_retry = client.append_to_stream(
stream_name=stream_name1,
current_version=0,
events=[event2, event3],
)
We can see that the same commit position is returned as above.
assert commit_position_retry == commit_position2
By calling get_stream()
, we can also see the stream has been unchanged.
That is, there are still only three events in the stream.
events = client.get_stream(
stream_name=stream_name1
)
assert len(events) == 3
This idempotent behaviour depends on the id
attribute of the NewEvent
class.
This attribute is, by default, assigned a new and unique version-4 UUID when an
instance of NewEvent
is constructed. To set the id
value of a NewEvent
,
the optional id
constructor argument can be used when constructing NewEvent
objects.
The read_stream()
method can be used to get events that have been appended
to a stream. This method returns a "read response" object.
A "read response" object is a Python iterator. Recorded events can be
obtained by iterating over the "read response" object. Recorded events are
streamed from the server to the client as the iteration proceeds. The iteration
will automatically stop when there are no more recorded events to be returned.
The streaming of events, and hence the iterator, can also be stopped by calling
the stop()
method on the "read response" object.
The get_stream()
method can be used to get events that have been appended
to a stream. This method returns a Python tuple
of recorded event objects.
The recorded event objects are instances of the RecordedEvent
class. It
calls read_stream()
and passes the "read response" iterator into a Python
tuple
, so that the streaming will complete before the method returns.
The read_stream()
and get_stream()
methods have one required argument, stream_name
.
The required stream_name
argument is a Python str
that uniquely identifies a
stream from which recorded events will be returned.
The read_stream()
and get_stream()
methods also have six optional arguments,
stream_position
, backwards
, resolve_links
, limit
, timeout
, and credentials
.
The optional stream_position
argument is a Python int
that can be used to
indicate the position in the stream from which to start reading. The default value
of stream_position
is None
. When reading a stream from a specific position in the
stream, the recorded event at that position will be included, both when reading
forwards from that position, and when reading backwards.
The optional backwards
argument is a Python bool
. The default value of backwards
is False
, which means the stream will be read forwards, so that events are returned
in the order they were recorded. If backwards
is True
, the events are returned in
reverse order.
If backwards
is False
and stream_position
is None
, the stream's events will be
returned in the order they were recorded, starting from the first recorded event. If
backwards
is True
and stream_position
is None
, the stream's events will be
returned in reverse order, starting from the last recorded event.
The optional resolve_links
argument is a Python bool
. The default value of resolve_links
is False
, which means any event links will not be resolved, so that the events that are
returned may represent event links. If resolve_links
is True
, any event links will
be resolved, so that the linked events will be returned instead of the event links.
The optional limit
argument is a Python int
which restricts the number of events
that will be returned. The default value of limit
is sys.maxint
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to override call credentials derived
from the connection string URI. A suitable value for this argument can be constructed
by calling the client method construct_call_credentials()
.
The example below shows the default behavior, which is to return all the recorded events of a stream forwards from the first recorded events to the last.
events = client.get_stream(
stream_name=stream_name1
)
assert len(events) == 3
assert events[0] == event1
assert events[1] == event2
assert events[2] == event3
The example below shows how to use the stream_position
argument to read a stream
from a specific stream position to the end of the stream. Stream positions are
zero-based, and so stream_position=1
corresponds to the second event that was
recorded in the stream, in this case event2
.
events = client.get_stream(
stream_name=stream_name1,
stream_position=1,
)
assert len(events) == 2
assert events[0] == event2
assert events[1] == event3
The example below shows how to use the backwards
argument to read a stream backwards.
events = client.get_stream(
stream_name=stream_name1,
backwards=True,
)
assert len(events) == 3
assert events[0] == event3
assert events[1] == event2
assert events[2] == event1
The example below shows how to use the limit
argument to read a limited number of
events.
events = client.get_stream(
stream_name=stream_name1,
limit=2,
)
assert len(events) == 2
assert events[0] == event1
assert events[1] == event2
The read_stream()
and get_stream()
methods will raise a NotFound
exception if the
named stream has never existed or has been deleted.
from esdbclient.exceptions import NotFound
try:
client.get_stream('does-not-exist')
except NotFound:
pass # The stream does not exist.
else:
raise Exception("Shouldn't get here")
Please note, the get_stream()
method is decorated with the @autoreconnect
and
@retrygrpc
decorators, whilst the read_stream()
method is not. This means that
all errors due to connection issues will be caught by the retry and reconnect decorators
when calling the get_stream()
method, but not when calling read_stream()
. The
read_stream()
method has no such decorators because the streaming only starts
when iterating over the "read response" starts, which means that the method returns
before the streaming starts, and so there is no chance for any decorators to catch
any connection issues.
For the same reason, read_stream()
will not raise a NotFound
exception when
the stream does not exist, until iterating over the "read response" object begins.
If you are reading a very large stream, then you might prefer to call read_stream()
,
and begin iterating through the recorded events whilst they are being streamed from
the server, rather than both waiting and having them all accumulate in memory.
The get_current_version()
method is a convenience method that essentially calls
get_stream()
with backwards=True
and limit=1
. This method returns
the value of the stream_position
attribute of the last recorded event in a
stream. If a stream does not exist, the returned value is StreamState.NO_STREAM
.
The returned value is the correct value of current_version
when appending events
to a stream, and when deleting or tombstoning a stream.
This method has one required argument, stream_name
.
The required stream_name
argument is a Python str
that uniquely identifies a
stream from which a stream position will be returned.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
In the example below, the last stream position of stream_name1
is obtained.
Since three events have been appended to stream_name1
, and because positions
in a stream are zero-based and gapless, so the current version is 2
.
current_version = client.get_current_version(
stream_name=stream_name1
)
assert current_version == 2
If a stream has never existed or has been deleted, the returned value is
StreamState.NO_STREAM
, which is the correct value of the current_version
argument both when appending the first event of a new stream, and also when
appending events to a stream that has been deleted.
current_version = client.get_current_version(
stream_name='does-not-exist'
)
assert current_version is StreamState.NO_STREAM
Snapshots can improve the performance of aggregates that would otherwise be reconstructed from very long streams. However, it is generally recommended to design aggregates to have a finite lifecycle, and so to have relatively short streams, thereby avoiding the need for snapshotting. This "how to" section is intended merely to show how snapshotting of aggregates can be implemented with EventStoreDB using this Python client.
Event-sourced aggregates are typically reconstructed from recorded events by calling
a mutator function for each recorded event, evolving from an initial state
None
to the current state of the aggregate. The function get_aggregate()
shows
how this can be done. The aggregate ID is used as a stream name. The exception
AggregateNotFound
is raised if the aggregate stream is not found.
class AggregateNotFound(Exception):
"""Raised when an aggregate is not found."""
def get_aggregate(aggregate_id, mutator_func):
stream_name = aggregate_id
# Get recorded events.
try:
events = client.get_stream(
stream_name=stream_name,
stream_position=None
)
except NotFound as e:
raise AggregateNotFound(aggregate_id) from e
else:
# Reconstruct aggregate from recorded events.
aggregate = None
for event in events:
aggregate = mutator_func(aggregate, event)
return aggregate
Snapshotting of aggregates can be implemented by recording the current state of an aggregate as a new event.
If an aggregate object has a version number that corresponds to the stream position of the last event that was used to reconstruct the aggregate, and this version number is recorded in the snapshot metadata, then any events that are recorded after the snapshot can be selected using this version number. The aggregate can then be reconstructed from the last snapshot and any subsequent events, without having to replay the entire history.
We will use a separate stream for an aggregate's snapshots that is named after the
stream used for recording its events. The name of the snapshot stream will be
constructed by prefixing the aggregate's stream name with 'snapshot-$'
.
SNAPSHOT_STREAM_NAME_PREFIX = 'snapshot-$'
def make_snapshot_stream_name(stream_name):
return f'{SNAPSHOT_STREAM_NAME_PREFIX}{stream_name}'
def remove_snapshot_stream_prefix(snapshot_stream_name):
assert snapshot_stream_name.startswith(SNAPSHOT_STREAM_NAME_PREFIX)
return snapshot_stream_name[len(SNAPSHOT_STREAM_NAME_PREFIX):]
Now, let's redefine the get_aggregate()
function, so that it looks for a snapshot event,
then selects subsequent aggregate events, and then calls a mutator function for each
recorded event.
Notice that the aggregate events are read from a stream for serialized aggregate events, whilst the snapshot is read from a separate stream for serialized aggregate snapshots. We will use JSON to serialize and deserialize event data.
import json
def get_aggregate(aggregate_id, mutator_func):
stream_name = aggregate_id
recorded_events = []
# Look for a snapshot.
try:
snapshots = client.get_stream(
stream_name=make_snapshot_stream_name(stream_name),
backwards=True,
limit=1
)
except NotFound:
stream_position = None
else:
assert len(snapshots) == 1
snapshot = snapshots[0]
stream_position = deserialize(snapshot.metadata)['version'] + 1
recorded_events.append(snapshot)
# Get subsequent events.
try:
events = client.get_stream(
stream_name=stream_name,
stream_position=stream_position
)
except NotFound as e:
raise AggregateNotFound(aggregate_id) from e
else:
recorded_events += events
# Reconstruct aggregate from recorded events.
aggregate = None
for event in recorded_events:
aggregate = mutator_func(aggregate, event)
return aggregate
def serialize(d):
return json.dumps(d).encode('utf8')
def deserialize(s):
return json.loads(s.decode('utf8'))
To show how get_aggregate()
can be used, let's define a Dog
aggregate class, with
attributes name
and tricks
. The attributes id
and version
will indicate an
aggregate object's ID and version number. The attribute is_from_snapshot
is added
here merely to demonstrate below when an aggregate object has been reconstructed using
a snapshot.
from dataclasses import dataclass
@dataclass(frozen=True)
class Aggregate:
id: str
version: int
is_from_snapshot: bool
@dataclass(frozen=True)
class Dog(Aggregate):
name: str
tricks: list
Let's also define a mutator function mutate_dog()
that evolves the state of a
Dog
aggregate given various different types of events, 'DogRegistered'
,
'DogLearnedTrick'
, and 'Snapshot'
.
def mutate_dog(dog, event):
data = deserialize(event.data)
if event.type == 'DogRegistered':
return Dog(
id=event.stream_name,
version=event.stream_position,
is_from_snapshot=False,
name=data['name'],
tricks=[],
)
elif event.type == 'DogLearnedTrick':
assert event.stream_position == dog.version + 1
assert event.stream_name == dog.id, (event.stream_name, dog.id)
return Dog(
id=dog.id,
version=event.stream_position,
is_from_snapshot=dog.is_from_snapshot,
name=dog.name,
tricks=dog.tricks + [data['trick']],
)
elif event.type == 'Snapshot':
return Dog(
id=remove_snapshot_stream_prefix(event.stream_name),
version=deserialize(event.metadata)['version'],
is_from_snapshot=True,
name=data['name'],
tricks=data['tricks'],
)
else:
raise Exception(f"Unknown event type: {event.type}")
For convenience, let's also define a get_dog()
function that calls get_aggregate()
with the mutate_dog()
function as the value of its mutator_func
argument.
def get_dog(dog_id):
return get_aggregate(
aggregate_id=dog_id,
mutator_func=mutate_dog,
)
We can also define some "command" functions that append new events to the
database. The register_dog()
function appends a DogRegistered
event. The
record_trick_learned()
appends a DogLearnedTrick
event. The function
snapshot_dog()
appends a Snapshot
event. Notice that the
record_trick_learned()
and snapshot_dog()
functions use get_dog()
.
Notice also that the DogRegistered
and DogLearnedTrick
events are appended to a
stream for aggregate events, whilst the Snapshot
event is appended to a separate
stream for aggregate snapshots.
def register_dog(name):
dog_id = str(uuid.uuid4())
event = NewEvent(
type='DogRegistered',
data=serialize({'name': name}),
)
client.append_to_stream(
stream_name=dog_id,
current_version=StreamState.NO_STREAM,
events=event,
)
return dog_id
def record_trick_learned(dog_id, trick):
dog = get_dog(dog_id)
event = NewEvent(
type='DogLearnedTrick',
data=serialize({'trick': trick}),
)
client.append_to_stream(
stream_name=dog_id,
current_version=dog.version,
events=event,
)
def snapshot_dog(dog_id):
dog = get_dog(dog_id)
event = NewEvent(
type='Snapshot',
data=serialize({'name': dog.name, 'tricks': dog.tricks}),
metadata=serialize({'version': dog.version}),
)
client.append_to_stream(
stream_name=make_snapshot_stream_name(dog_id),
current_version=StreamState.ANY,
events=event,
)
We can call register_dog()
to register a new dog.
# Register a new dog.
dog_id = register_dog('Fido')
dog = get_dog(dog_id)
assert dog.name == 'Fido'
assert dog.tricks == []
assert dog.version == 0
assert dog.is_from_snapshot is False
We can call record_trick_learned()
to record that some tricks have been learned.
# Record that 'Fido' learned a new trick.
record_trick_learned(dog_id, trick='roll over')
dog = get_dog(dog_id)
assert dog.name == 'Fido'
assert dog.tricks == ['roll over']
assert dog.version == 1
assert dog.is_from_snapshot is False
# Record that 'Fido' learned another new trick.
record_trick_learned(dog_id, trick='fetch ball')
dog = get_dog(dog_id)
assert dog.name == 'Fido'
assert dog.tricks == ['roll over', 'fetch ball']
assert dog.version == 2
assert dog.is_from_snapshot is False
We can call snapshot_dog()
to record a snapshot of the current state of the Dog
aggregate. After we call snapshot_dog()
, the get_dog()
function will return a Dog
object that has been constructed using the Snapshot
event.
# Snapshot 'Fido'.
snapshot_dog(dog_id)
dog = get_dog(dog_id)
assert dog.name == 'Fido'
assert dog.tricks == ['roll over', 'fetch ball']
assert dog.version == 2
assert dog.is_from_snapshot is True
We can continue to evolve the state of the Dog
aggregate, using
the snapshot both during the call to record_trick_learned()
and
when calling get_dog()
directly.
record_trick_learned(dog_id, trick='sit')
dog = get_dog(dog_id)
assert dog.name == 'Fido'
assert dog.tricks == ['roll over', 'fetch ball', 'sit']
assert dog.version == 3
assert dog.is_from_snapshot is True
We can see from the is_from_snapshot
attribute that the Dog
object was indeed
reconstructed from the snapshot.
Snapshots can be created at fixed version number intervals, fixed time periods, after a particular type of event, immediately after events are appended, or as a background process.
The read_all()
method can be used to get all recorded events
in the database in the order they were recorded. This method returns
a "read response" object, just like read_stream()
.
A "read response" is an iterator, and not a sequence. Recorded events can be
obtained by iterating over the "read response" object. Recorded events are
streamed from the server to the client as the iteration proceeds. The iteration
will automatically stop when there are no more recorded events to be returned.
The streaming of events, and hence the iterator, can also be stopped by calling
the stop()
method on the "read response" object. The recorded event objects
are instances of the RecordedEvent
class.
This method has nine optional arguments, commit_position
, backwards
, resolve_links
,
filter_exclude
, filter_include
, filter_by_stream_name
, limit
, timeout
,
and credentials
.
The optional commit_position
argument is a Python int
that can be used to
specify a commit position from which to start reading. The default value of
commit_position
is None
. Please note, if a commit position is specified,
it must be an actually existing commit position in the database. When reading
forwards, the event at the commit position may be included, depending upon the
filter. When reading backwards, the event at the commit position will not be
included.
The optional backwards
argument is a Python bool
. The default of backwards
is
False
, which means events are returned in the order they were recorded, If
backwards
is True
, then events are returned in reverse order.
If backwards
is False
and commit_position
is None
, the database's events will
be returned in the order they were recorded, starting from the first recorded event.
This is the default behavior of read_all()
. If backwards
is True
and
commit_position
is None
, the database's events will be returned in reverse order,
starting from the last recorded event.
The optional resolve_links
argument is a Python bool
. The default value of resolve_links
is False
, which means any event links will not be resolved, so that the events that are
returned may represent event links. If resolve_links
is True
, any event links will
be resolved, so that the linked events will be returned instead of the event links.
The optional filter_exclude
argument is a sequence of regular expressions that
specifies which recorded events should be returned. This argument is ignored
if filter_include
is set to a non-empty sequence. The default value of this
argument matches the event types of EventStoreDB "system events", so that system
events will not normally be included. See the Notes section below for more
information about filter expressions.
The optional filter_include
argument is a sequence of regular expressions
that specifies which recorded events should be returned. By default, this
argument is an empty tuple. If this argument is set to a non-empty sequence,
the filter_exclude
argument is ignored.
The optional filter_by_stream_name
argument is a Python bool
that indicates
whether the filtering will apply to event types or stream names. By default, this
value is False
and so the filtering will apply to the event type strings of
recorded events.
The optional limit
argument is an integer which restricts the number of events that
will be returned. The default value is sys.maxint
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
The filtering of events is done on the EventStoreDB server. The
limit
argument is applied on the server after filtering.
The example below shows how to get all the events we have recorded in the database
so far, in the order they were recorded. We can see the three events of stream_name1
(event1
, event2
and event3
) are included, along with others.
# Read all events (creates a streaming gRPC call).
read_response = client.read_all()
# Convert the iterator into a sequence of recorded events.
events = tuple(read_response)
assert len(events) > 3 # more than three
# Convert the sequence of recorded events into a set of event IDs.
event_ids = set(e.id for e in events)
assert event1.id in event_ids
assert event2.id in event_ids
assert event3.id in event_ids
The example below shows how to read all recorded events in the database from
a particular commit position, in this case commit_position1
. When reading
forwards from a specific commit position, the event at the specified position
will be included. The value of commit_position1
is the position we obtained
when appending event1
. And so event1
is the first recorded event we shall
receive, event2
is the second, and event3
is the third.
# Read all events forwards from a commit position.
read_response = client.read_all(
commit_position=commit_position1
)
# Step through the "read response" iterator.
assert next(read_response) == event1
assert next(read_response) == event2
assert next(read_response) == event3
# Stop the iterator.
read_response.stop()
The example below shows how to read all events recorded in the database in reverse
order. We can see that the first events we receive are the last events that were
recorded: the events of the Dog
aggregate from the section about snapshotting
and the snapshot.
# Read all events backwards from the end.
read_response = client.read_all(
backwards=True
)
# Step through the "read response" iterator.
assert next(read_response).type == "DogLearnedTrick"
assert next(read_response).type == "Snapshot"
assert next(read_response).type == "DogLearnedTrick"
assert next(read_response).type == "DogLearnedTrick"
assert next(read_response).type == "DogRegistered"
# Stop the iterator.
read_response.stop()
The example below shows how to read a limited number of events forwards from a specific commit position.
events = tuple(
client.read_all(
commit_position=commit_position1,
limit=1,
)
)
assert len(events) == 1
assert events[0] == event1
The example below shows how to read a limited number of the recorded events in the database backwards from the end. In this case, the limit is 1, and so we receive the last recorded event.
events = tuple(
client.read_all(
backwards=True,
limit=1,
)
)
assert len(events) == 1
assert events[0].type == 'DogLearnedTrick'
assert deserialize(events[0].data)['trick'] == 'sit'
Please note, like the read_stream()
method, the read_all()
method
is not decorated with retry and reconnect decorators, because the streaming of recorded
events from the server only starts when iterating over the "read response" starts, which
means that the method returns before the streaming starts, and so there is no chance for
any decorators to catch any connection issues.
The get_commit_position()
method can be used to get the commit position of the
last recorded event in the database. It simply calls read_all()
with
backwards=True
and limit=1
, and returns the value of the commit_position
attribute of the last recorded event.
commit_position = client.get_commit_position()
This method has five optional arguments, filter_exclude
, filter_include
,
filter_by_stream_name
, timeout
and credentials
. These values are passed to
read_all()
.
The optional filter_exclude
, filter_include
and filter_by_stream_name
arguments
work in the same way as they do in the read_all()
method.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to override call credentials
derived from the connection string URI.
This method might be used to measure progress of a downstream component
that is processing all recorded events, by comparing the current commit
position with the recorded commit position of the last successfully processed
event in a downstream component. In this case, the value of the filter_exclude
,
filter_include
and filter_by_stream_name
arguments should equal those used
by the downstream component to obtain recorded events.
The get_stream_metadata()
method returns the metadata for a stream, along
with the version of the stream metadata.
This method has one required argument, stream_name
, which is a Python str
that
uniquely identifies a stream for which a stream metadata will be obtained.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
In the example below, metadata for stream_name1
is obtained.
metadata, metadata_version = client.get_stream_metadata(stream_name=stream_name1)
The returned metadata
value is a Python dict
. The returned metadata_version
value is either an int
if the stream exists, or StreamState.NO_STREAM
if the stream
does not exist and no metadata has been set. These values can be used as the arguments
of set_stream_metadata()
.
requires leader
The method set_stream_metadata()
sets metadata for a stream. Stream metadata
can be set before appending events to a stream.
This method has one required argument, stream_name
, which is a Python str
that
uniquely identifies a stream for which a stream metadata will be set.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
In the example below, metadata for stream_name1
is set.
metadata["foo"] = "bar"
client.set_stream_metadata(
stream_name=stream_name1,
metadata=metadata,
current_version=metadata_version,
)
The current_version
argument should be the current version of the stream metadata
obtained from get_stream_metadata()
.
Please refer to the EventStoreDB documentation for more information about stream metadata.
requires leader
The method delete_stream()
can be used to "delete" a stream.
This method has two required arguments, stream_name
and current_version
.
The required stream_name
argument is a Python str
that uniquely identifies a
stream to which a sequence of events will be appended.
The required current_version
argument is expected to be either a Python int
that indicates the stream position of the last recorded event in the stream.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
In the example below, stream_name1
is deleted.
commit_position = client.delete_stream(stream_name=stream_name1, current_version=2)
After deleting a stream, it's still possible to append new events. Reading from a deleted stream will return only events that have been appended after it was deleted.
requires leader
The method tombstone_stream()
can be used to "tombstone" a stream.
This method has two required arguments, stream_name
and current_version
.
The required stream_name
argument is a Python str
that uniquely identifies a
stream to which a sequence of events will be appended.
The required current_version
argument is expected to be either a Python int
that indicates the stream position of the last recorded event in the stream.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
In the example below, stream_name1
is tombstoned.
commit_position = client.tombstone_stream(stream_name=stream_name1, current_version=2)
After tombstoning a stream, it's not possible to append new events.
A "catch-up" subscription can be used to receive events that have already been recorded and events that are recorded subsequently. A catch-up subscription can be used by an event-processing component that processes recorded events with "exactly-once" semantics.
The subscribe_to_all()
method starts a catch-up subscription that can receive
all events in the database. The subscribe_to_stream()
method starts a catch-up
subscription that can receive events from a specific stream. Both methods return a
"catch-up subscription" object, which is a Python iterator. Recorded events can be
obtained by iteration. Recorded event objects obtained in this way are instances
of the RecordedEvent
class.
Before the "catch-up subscription" object is returned to the caller, the client will
firstly obtain a "confirmation" response from the server, which allows the client to
detect that both the gRPC connection and the streaming gRPC call is operational. For
this reason, the subscribe_to_all()
and subscribe_to_stream()
methods are both
usefully decorated with the reconnect and retry decorators. However, once the method
has returned, the decorators will have exited, and any exceptions that are raised
due to connection issues whilst iterating over the subscription object will have to
be handled by your code.
A "catch-up subscription" iterator will not automatically stop when there are no more
events to be returned, but instead the iteration will block until new events are
subsequently recorded in the database. Any subsequently recorded events will then be
immediately streamed to the client, and the iteration will then continue. The streaming
of events, and hence the iteration, can be stopped by calling the stop()
method on the
"catch-up subscription" object.
Thesubscribe_to_all()
method can be used to start a catch-up subscription
from which all events recorded in the database can be obtained in the order
they were recorded. This method returns a "catch-up subscription" iterator.
This method also has ten optional arguments, commit_position
, from_end
, resolve_links
,
filter_exclude
, filter_include
, filter_by_stream_name
, include_checkpoints
,
include_caught_up
, timeout
and credentials
.
The optional commit_position
argument specifies a commit position. The default
value of commit_position
is None
, which means the catch-up subscription will
start from the first recorded event in the database. If a commit position is given,
it must match an actually existing commit position in the database. Only events
recorded after that position will be obtained.
The optional from_end
argument specifies whether or not the catch-up subscription
will start from the last recorded event in the database. By default, this argument
is False
. If from_end
is True
, only events recorded after the subscription
is started will be obtained. This argument will be disregarded if commit_position
is not None
.
The optional resolve_links
argument is a Python bool
. The default value of resolve_links
is False
, which means any event links will not be resolved, so that the events that are
returned may represent event links. If resolve_links
is True
, any event links will
be resolved, so that the linked events will be returned instead of the event links.
The optional filter_exclude
argument is a sequence of regular expressions that
specifies which recorded events should be returned. This argument is ignored
if filter_include
is set to a non-empty sequence. The default value of this
argument matches the event types of EventStoreDB "system events", so that system
events will not normally be included. See the Notes section below for more
information about filter expressions.
The optional filter_include
argument is a sequence of regular expressions
that specifies which recorded events should be returned. By default, this
argument is an empty tuple. If this argument is set to a non-empty sequence,
the filter_exclude
argument is ignored.
The optional filter_by_stream_name
argument is a Python bool
that indicates
whether the filtering will apply to event types or stream names. By default, this
value is False
and so the filtering will apply to the event type strings of
recorded events.
The optional include_checkpoints
argument is a Python bool
which indicates
whether "checkpoint" messages should be included when recorded events are received.
Checkpoints have a commit_position
value that can be used by an event processing component to
update its recorded commit position value, so that, when lots of events are being
filter out, the subscriber does not have to start from the same old position when
the event processing component is restarted.
The optional include_caught_up
argument is a Python bool
which indicates
whether "caught up" messages should be included when recorded events are
received. The default value of include_caught_up
is False
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
The example below shows how to start a catch-up subscription that starts from the first recorded event in the database.
# Subscribe from the first recorded event in the database.
catchup_subscription = client.subscribe_to_all()
The example below shows that catch-up subscriptions do not stop automatically, but block when the last recorded event is received, and then continue when subsequent events are recorded.
from time import sleep
from threading import Thread
# Append a new event to a new stream.
stream_name2 = str(uuid.uuid4())
event4 = NewEvent(type='OrderCreated', data=b'{}')
client.append_to_stream(
stream_name=stream_name2,
current_version=StreamState.NO_STREAM,
events=[event4],
)
# Receive events from the catch-up subscription in a different thread.
received_events = []
def receive_events():
for event in catchup_subscription:
received_events.append(event)
def wait_for_event(event):
for _ in range(100):
for received in reversed(received_events):
if event == received:
return
else:
sleep(0.1)
else:
raise AssertionError("Event wasn't received")
thread = Thread(target=receive_events, daemon=True)
thread.start()
# Wait to receive event4.
wait_for_event(event4)
# Append another event whilst the subscription is running.
event5 = NewEvent(type='OrderUpdated', data=b'{}')
client.append_to_stream(
stream_name=stream_name2,
current_version=0,
events=[event5],
)
# Wait for the subscription to block.
wait_for_event(event5)
# Stop the subscription.
catchup_subscription.stop()
thread.join()
The example below shows how to subscribe to events recorded after a particular commit position, in this case from the commit position of the last recorded event that was received above. Then, another event is recorded before the subscription is restarted. And three more events are recorded whilst the subscription is running. These four events are received in the order they were recorded.
# Append another event.
event6 = NewEvent(type='OrderDeleted', data=b'{}')
client.append_to_stream(
stream_name=stream_name2,
current_version=1,
events=[event6],
)
# Restart subscribing to all events after the
# commit position of the last received event.
catchup_subscription = client.subscribe_to_all(
commit_position=received_events[-1].commit_position
)
thread = Thread(target=receive_events, daemon=True)
thread.start()
# Wait for event6.
wait_for_event(event6)
# Append three more events to a new stream.
stream_name3 = str(uuid.uuid4())
event7 = NewEvent(type='OrderCreated', data=b'{}')
event8 = NewEvent(type='OrderUpdated', data=b'{}')
event9 = NewEvent(type='OrderDeleted', data=b'{}')
client.append_to_stream(
stream_name=stream_name3,
current_version=StreamState.NO_STREAM,
events=[event7, event8, event9],
)
# Wait for events 7, 8 and 9.
wait_for_event(event7)
wait_for_event(event8)
wait_for_event(event9)
# Stop the subscription.
catchup_subscription.stop()
thread.join()
The catch-up subscription call is ended as soon as the subscription object's
stop()
method is called. This happens automatically when it goes out of scope,
or when it is explicitly deleted from memory using the Python del
keyword.
The subscribe_to_stream()
method can be used to start a catch-up subscription
from which events recorded in a single stream can be obtained. This method
returns a "catch-up subscription" iterator.
This method has a required stream_name
argument, which specifies the name of the
stream from which recorded events will be received.
This method also has six optional arguments, stream_position
, from_end
,
resolve_links
, include_caught_up
, timeout
and credentials
.
The optional stream_position
argument specifies a position in the stream from
which to start subscribing. The default value of stream_position
is None
,
which means that all events recorded in the stream will be obtained in the
order they were recorded, unless from_end
is set to True
. If a stream
position is given, then only events recorded after that position will be obtained.
The optional from_end
argument specifies that the subscription will start
from the last position in the stream. The default value of from_end
is False
.
If from_end
is True
, then only events recorded after the subscription was
created will be obtained. This argument if ignored is stream_position
is set.
The optional resolve_links
argument is a Python bool
. The default value of resolve_links
is False
, which means any event links will not be resolved, so that the events that are
returned may represent event links. If resolve_links
is True
, any event links will
be resolved, so that the linked events will be returned instead of the event links.
The optional include_caught_up
argument is a Python bool
which indicates
whether "caught up" messages should be included when recorded events are
received. The default value of include_caught_up
is False
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
The example below shows how to start a catch-up subscription from the first recorded event in a stream.
# Subscribe from the start of 'stream2'.
subscription = client.subscribe_to_stream(stream_name=stream_name2)
The example below shows how to start a catch-up subscription from a particular stream position.
# Subscribe to stream2, from the second recorded event.
subscription = client.subscribe_to_stream(
stream_name=stream_name2,
stream_position=1,
)
The commit positions of recorded events that are received and processed by a downstream component are usefully recorded by the downstream component, so that the commit position of last processed event can be determined when processing is resumed.
The last recorded commit position can be used to specify the commit position from which to subscribe when processing is resumed. Since this commit position will represent the position of the last successfully processed event in a downstream component, so it will be usual to want the next event after this position, because that is the next event that has not yet been processed. For this reason, when subscribing for events from a specific commit position using a catch-up subscription in EventStoreDB, the recorded event at the specified commit position will NOT be included in the sequence of recorded events that are received.
To accomplish "exactly-once" processing of recorded events in a downstream component when using a catch-up subscription, the commit position of a recorded event should be recorded atomically and uniquely along with the result of processing recorded events, for example in the same database as materialised views when implementing eventually-consistent CQRS, or in the same database as a downstream analytics or reporting or archiving application. By recording the commit position of recorded events atomically with the new state that results from processing recorded events, "dual writing" in the consumption of recorded events can be avoided. By also recording the commit position uniquely, the new state cannot be recorded twice, and hence the recorded state of the downstream component will be updated only once for any recorded event. By using the greatest recorded commit position to resume a catch-up subscription, all recorded events will eventually be processed. The combination of the "at-most-once" condition and the "at-least-once" condition gives the "exactly-once" condition.
The danger with "dual writing" in the consumption of recorded events is that if a recorded event is successfully processed and new state recorded atomically in one transaction with the commit position recorded in a separate transaction, one may happen and not the other. If the new state is recorded but the position is lost, and then the processing is stopped and resumed, the recorded event may be processed twice. On the other hand, if the commit position is recorded but the new state is lost, the recorded event may effectively not be processed at all. By either processing an event more than once, or by failing to process an event, the recorded state of the downstream component might be inaccurate, or possibly inconsistent, and perhaps catastrophically so. Such consequences may or may not matter in your situation. But sometimes inconsistencies may halt processing until the issue is resolved. You can avoid "dual writing" in the consumption of events by atomically recording the commit position of a recorded event along with the new state that results from processing that event in the same atomic transaction. By making the recording of the commit positions unique, so that transactions will be rolled back when there is a conflict, you will prevent the results of any duplicate processing of a recorded event being committed.
Recorded events received from a catch-up subscription cannot be acknowledged back to the EventStoreDB server. Acknowledging events, however, is an aspect of "persistent subscriptions". Hoping to rely on acknowledging events to an upstream component is an example of dual writing.
In EventStoreDB, "persistent" subscriptions are similar to catch-up subscriptions, in that reading a persistent subscription will block when there are no more recorded events to be received, and then continue when new events are subsequently recorded.
Persistent subscriptions can be consumed by a group of consumers operating with one of the supported "consumer strategies".
The significant different with persistent subscriptions is the server will keep track of the progress of the consumers. The consumer of a persistent subscription will therefore need to "acknowledge" when a recorded event has been processed successfully, and otherwise "negatively acknowledge" a recorded event that has been received but was not successfully processed.
All of this means that for persistent subscriptions there are "create", "read", "update" "delete", "ack", and "nack" operations to consider.
Whilst there are some advantages of persistent subscriptions, in particular the concurrent processing of recorded events by a group of consumers, by tracking in the server the position in the commit sequence of events that have been processed, the issue of "dual writing" in the consumption of events arises. Reliability in the processing of recorded events by a group of persistent subscription consumers will rely on their idempotent handling of duplicate messages, and their resilience to out-of-order delivery.
requires leader
The create_subscription_to_all()
method can be used to create a "persistent subscription"
to all the recorded events in the database across all streams.
This method has a required group_name
argument, which is the
name of a "group" of consumers of the subscription.
This method has nineteen optional arguments, from_end
, commit_position
, resolve_links
,
filter_exclude
, filter_include
, filter_by_stream_name
, consumer_strategy
,
message_timeout
, max_retry_count
, min_checkpoint_count
, max_checkpoint_count
,
checkpoint_after
, max_subscriber_count
, live_buffer_size
, read_batch_size
,
history_buffer_size
, extra_statistics
, timeout
and credentials
.
The optional from_end
argument can be used to specify that the group of consumers
of the subscription should only receive events that were recorded after the subscription
was created.
Alternatively, the optional commit_position
argument can be used to specify a commit
position from which the group of consumers of the subscription should
receive events. Please note, the recorded event at the specified commit position might
be included in the recorded events received by the group of consumers.
If neither from_end
nor commit_position
are specified, the group of consumers
of the subscription will potentially receive all recorded events in the database.
The optional resolve_links
argument is a Python bool
. The default value of resolve_links
is False
, which means any event links will not be resolved, so that the events that are
returned may represent event links. If resolve_links
is True
, any event links will
be resolved, so that the linked events will be returned instead of the event links.
The optional filter_exclude
argument is a sequence of regular expressions that
specifies which recorded events should be returned. This argument is ignored
if filter_include
is set to a non-empty sequence. The default value of this
argument matches the event types of EventStoreDB "system events", so that system
events will not normally be included. See the Notes section below for more
information about filter expressions.
The optional filter_include
argument is a sequence of regular expressions
that specifies which recorded events should be returned. By default, this
argument is an empty tuple. If this argument is set to a non-empty sequence,
the filter_exclude
argument is ignored.
The optional filter_by_stream_name
argument is a Python bool
that indicates
whether the filtering will apply to event types or stream names. By default, this
value is False
and so the filtering will apply to the event type strings of
recorded events.
The optional consumer_strategy
argument is a Python str
that defines
the consumer strategy for this persistent subscription. The value of this argument
can be 'DispatchToSingle'
, 'RoundRobin'
, 'Pinned'
, or 'PinnedByCorrelation'
. The
default value is 'DispatchToSingle'
.
The optional message_timeout
argument is a Python float
which sets a maximum duration,
in seconds, from the server sending a recorded event to a consumer of the persistent
subscription until either an "acknowledgement" (ack) or a "negative acknowledgement"
(nack) is received by the server, after which the server will retry to send the event.
The default value of message_timeout
is 30.0
.
The optional max_retry_count
argument is a Python int
which sets the number of times
the server will retry to send an event. The default value of max_retry_count
is 10
.
The optional min_checkpoint_count
argument is a Python int
which sets the minimum
number of "acknowledgements" (acks) received by the server before the server may record
the acknowledgements. The default value of min_checkpoint_count
is 10
.
The optional max_checkpoint_count
argument is a Python int
which sets the maximum
number of "acknowledgements" (acks) received by the server before the server must
record the acknowledgements. The default value of max_checkpoint_count
is 1000
.
The optional checkpoint_after
argument is a Python float
which sets the maximum
duration in seconds between recording "acknowledgements" (acks). The default value of
checkpoint_after
is 2.0
.
The optional max_subscriber_count
argument is a Python int
which sets the maximum
number of concurrent readers of the persistent subscription, beyond which attempts to
read the persistent subscription will raise a MaximumSubscriptionsReached
error.
The optional live_buffer_size
argument is a Python int
which sets the size of the
buffer (in-memory) holding newly recorded events. The default value of live_buffer_size
is 500.
The optional read_batch_size
argument is a Python int
which sets the number of
recorded events read from disk when catching up. The default value of read_batch_size
is 200.
The optional history_buffer_size
argument is a Python int
which sets the number of
recorded events to cache in memory when catching up. The default value of history_buffer_size
is 500.
The optional extra_statistics
argument is a Python bool
which enables tracking of
extra statistics on this subscription. The default value of extra_statistics
is False
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
The method create_subscription_to_all()
does not return a value. Recorded events are
obtained by calling the read_subscription_to_all()
method.
In the example below, a persistent subscription is created to operate from the first recorded non-system event in the database.
# Create a persistent subscription.
group_name1 = f"group-{uuid.uuid4()}"
client.create_subscription_to_all(group_name=group_name1)
requires leader
The read_subscription_to_all()
method can be used by a group of consumers to receive
recorded events from a persistent subscription that has been created using
the create_subscription_to_all()
method.
This method has a required group_name
argument, which is
the name of a "group" of consumers of the subscription specified
when create_subscription_to_all()
was called.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
This method returns a PersistentSubscription
object, which is an iterator
giving RecordedEvent
objects. It also has ack()
, nack()
and stop()
methods.
subscription = client.read_subscription_to_all(group_name=group_name1)
The ack()
method should be used by a consumer to "acknowledge" to the server that
it has received and successfully processed a recorded event. This will prevent that
recorded event being received by another consumer in the same group. The ack()
has an item
argument which can be either a RecordedEvent
or a UUID
. If you pass
in a RecordedEvent
, the value of its ack_id
attribute will be used to acknowledge
the event to the server. If you pass in a UUID, then used the value of the ack_id
of the RecordedEvent
that is being acknowledged, in case the event has been resolved
from a link event (which can happen both when persistent subscription setting
resolve_links
is True
and also when replaying parked events regardless of the
resolve_links
setting).
The example below iterates over the subscription object, and calls ack()
with the
received RecordedEvent
objects. The subscription's stop()
method is called when
we have received event9
, stopping the iteration, so that we can continue with the
examples below.
received_events = []
for event in subscription:
received_events.append(event)
# Acknowledge the received event.
subscription.ack(event)
# Stop when 'event9' has been received.
if event == event9:
subscription.stop()
The nack()
should be used by a consumer to "negatively acknowledge" to the server that
it has received but not successfully processed a recorded event. The nack()
method has
an item
argument that works in the same way as ack()
. Use the recorded event or its
ack_id
attribute. The nack()
method also has an action
argument, which should be
a Python str
: either 'unknown'
, 'park'
, 'retry'
, 'skip'
or 'stop'
.
The stop()
method can be used to stop the gRPC streaming operation.
The reading of a persistent subscription can be encapsulated in a "consumer" that calls
a "policy" function when a recorded event is received and then automatically calls
ack()
if the policy function returns normally, and nack()
if it raises an exception,
perhaps retrying the event for a certain number of times before parking the event.
The simple example below shows how this might be done. We can see that 'event9' is acknowledged before 'event5' is finally parked.
The number of time a RecordedEvent
has been retried is presented by the its
retry_count
attribute.
acked_events = {}
nacked_events = {}
class ExampleConsumer:
def __init__(self, subscription, max_retry_count, final_action):
self.subscription = subscription
self.max_retry_count = max_retry_count
self.final_action = final_action
self.error = None
def run(self):
with self.subscription:
for event in self.subscription:
try:
self.policy(event)
except Exception:
if event.retry_count < self.max_retry_count:
action = "retry"
else:
action = self.final_action
self.subscription.nack(event, action)
self.after_nack(event, action)
else:
self.subscription.ack(event)
self.after_ack(event)
def stop(self):
self.subscription.stop()
def policy(self, event):
# Raise an exception when we see "event5".
if event == event5:
raise Exception()
def after_ack(self, event):
# Track retry count of acked events.
acked_events[event.id] = event.retry_count
def after_nack(self, event, action):
# Track retry count of nacked events.
nacked_events[event.id] = event.retry_count
if action == self.final_action:
# Stop the consumer, so we can continue with the examples.
self.stop()
# Create subscription.
group_name = f"group-{uuid.uuid4()}"
client.create_subscription_to_all(group_name, commit_position=commit_position1)
# Read subscription.
subscription = client.read_subscription_to_all(group_name)
# Construct consumer.
consumer = ExampleConsumer(
subscription=subscription,
max_retry_count=5,
final_action="park",
)
# Run consumer.
consumer.run()
# Check 'event5' was nacked and never acked.
assert event5.id in nacked_events
assert event5.id not in acked_events
assert nacked_events[event5.id] == 5
# Check 'event9' was acked and never nacked.
assert event9.id in acked_events
assert event9.id not in nacked_events
requires leader
The update_subscription_to_all()
method can be used to update a
"persistent subscription". Please note, the filter options and consumer
strategy cannot be adjusted.
This method has a required group_name
argument, which is the
name of a "group" of consumers of the subscription.
This method also has sixteen optional arguments, from_end
, commit_position
,
resolve_links
, consumer_strategy
, message_timeout
, max_retry_count
,
min_checkpoint_count
, max_checkpoint_count
, checkpoint_after
,
max_subscriber_count
, live_buffer_size
, read_batch_size
, history_buffer_size
,
extra_statistics
, timeout
and credentials
.
The optional arguments from_end
, commit_position
,
resolve_links
, consumer_strategy
, message_timeout
, max_retry_count
,
min_checkpoint_count
, max_checkpoint_count
, checkpoint_after
,
max_subscriber_count
, live_buffer_size
, read_batch_size
, history_buffer_size
,
amd extra_statistics
can be used to adjust the values set on previous calls to
create_subscription_to_all()
and update_subscription_to_all()
. If any of
these arguments are not mentioned in a call to update_subscription_to_all()
,
the corresponding settings of the persistent subscription will be unchanged.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
The method update_subscription_to_all()
does not return a value.
In the example below, a persistent subscription is updated to run from the end of the database.
# Create a persistent subscription.
client.update_subscription_to_all(group_name=group_name1, from_end=True)
requires leader
The create_subscription_to_stream()
method can be used to create a persistent
subscription to a stream.
This method has two required arguments, group_name
and stream_name
. The
group_name
argument names the group of consumers that will receive events
from this subscription. The stream_name
argument specifies which stream
the subscription will follow. The values of both these arguments are expected
to be Python str
objects.
This method also has sixteen optional arguments, stream_position
, from_end
,
resolve_links
, consumer_strategy
, message_timeout
, max_retry_count
,
min_checkpoint_count
, max_checkpoint_count
, checkpoint_after
,
max_subscriber_count
, live_buffer_size
, read_batch_size
, history_buffer_size
,
extra_statistics
, timeout
and credentials
.
The optional stream_position
argument specifies a stream position from
which to subscribe. The recorded event at this stream
position will be received when reading the subscription.
The optional from_end
argument is a Python bool
.
By default, the value of this argument is False
. If this argument is set
to True
, reading from the subscription will receive only events
recorded after the subscription was created. That is, it is not inclusive
of the current stream position.
The optional resolve_links
argument is a Python bool
. The default value of resolve_links
is False
, which means any event links will not be resolved, so that the events that are
returned may represent event links. If resolve_links
is True
, any event links will
be resolved, so that the linked events will be returned instead of the event links.
The optional consumer_strategy
argument is a Python str
that defines
the consumer strategy for this persistent subscription. The value of this argument
can be 'DispatchToSingle'
, 'RoundRobin'
, 'Pinned'
, or 'PinnedByCorrelation'
. The
default value is 'DispatchToSingle'
.
The optional message_timeout
argument is a Python float
which sets a maximum duration,
in seconds, from the server sending a recorded event to a consumer of the persistent
subscription until either an "acknowledgement" (ack) or a "negative acknowledgement"
(nack) is received by the server, after which the server will retry to send the event.
The default value of message_timeout
is 30.0
.
The optional max_retry_count
argument is a Python int
which sets the number of times
the server will retry to send an event. The default value of max_retry_count
is 10
.
The optional min_checkpoint_count
argument is a Python int
which sets the minimum
number of "acknowledgements" (acks) received by the server before the server may record
the acknowledgements. The default value of min_checkpoint_count
is 10
.
The optional max_checkpoint_count
argument is a Python int
which sets the maximum
number of "acknowledgements" (acks) received by the server before the server must
record the acknowledgements. The default value of max_checkpoint_count
is 1000
.
The optional checkpoint_after
argument is a Python float
which sets the maximum
duration in seconds between recording "acknowledgements" (acks). The default value of
checkpoint_after
is 2.0
.
The optional max_subscriber_count
argument is a Python int
which sets the maximum
number of concurrent readers of the persistent subscription, beyond which attempts to
read the persistent subscription will raise a MaximumSubscriptionsReached
error.
The optional live_buffer_size
argument is a Python int
which sets the size of the
buffer (in-memory) holding newly recorded events. The default value of live_buffer_size
is 500.
The optional read_batch_size
argument is a Python int
which sets the number of
recorded events read from disk when catching up. The default value of read_batch_size
is 200.
The optional history_buffer_size
argument is a Python int
which sets the number of
recorded events to cache in memory when catching up. The default value of history_buffer_size
is 500.
The optional extra_statistics
argument is a Python bool
which enables tracking of
extra statistics on this subscription. The default value of extra_statistics
is False
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
This method does not return a value. Events can be received by calling
read_subscription_to_stream()
.
The example below creates a persistent stream subscription from the start of the stream.
# Create a persistent stream subscription from start of the stream.
group_name2 = f"group-{uuid.uuid4()}"
client.create_subscription_to_stream(
group_name=group_name2,
stream_name=stream_name2,
)
requires leader
The read_subscription_to_stream()
method can be used to read a persistent
subscription to a stream.
This method has two required arguments, group_name
and stream_name
, which
should match the values of arguments used when calling create_subscription_to_stream()
.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
This method returns a PersistentSubscription
object, which is an iterator
giving RecordedEvent
objects, that also has ack()
, nack()
and stop()
methods.
subscription = client.read_subscription_to_stream(
group_name=group_name2,
stream_name=stream_name2,
)
The example below iterates over the subscription object, and calls ack()
.
The subscription's stop()
method is called when we have received event6
,
stopping the iteration, so that we can continue with the examples below.
events = []
for event in subscription:
events.append(event)
# Acknowledge the received event.
subscription.ack(event)
# Stop when 'event6' has been received.
if event == event6:
subscription.stop()
We can check we received all the events that were appended to stream_name2
in the examples above.
assert len(events) == 3
assert events[0] == event4
assert events[1] == event5
assert events[2] == event6
requires leader
The update_subscription_to_stream()
method can be used to update a persistent
subscription to a stream. Please note, the consumer strategy cannot be adjusted.
This method has a required group_name
argument, which is the
name of a "group" of consumers of the subscription, and a required
stream_name
argument, which is the name of a stream.
This method also has sixteen optional arguments, from_end
, stream_position
,
resolve_links
, consumer_strategy
, message_timeout
, max_retry_count
,
max_subscriber_count
, live_buffer_size
, read_batch_size
, history_buffer_size
,
extra_statistics
, min_checkpoint_count
, max_checkpoint_count
, checkpoint_after
,
timeout
and credentials
.
The optional arguments from_end
, stream_position
,
resolve_links
, consumer_strategy
, message_timeout
, max_retry_count
,
min_checkpoint_count
, max_checkpoint_count
, checkpoint_after
,
max_subscriber_count
, live_buffer_size
, read_batch_size
, history_buffer_size
,
and extra_statistics
can be used to adjust the values set on previous calls to
create_subscription_to_stream()
and update_subscription_to_stream()
. If any of
these arguments are not mentioned in a call to update_subscription_to_stream()
,
the corresponding settings of the persistent subscription will be unchanged.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
The update_subscription_to_stream()
method does not return a value.
In the example below, a persistent subscription to a stream is updated to run from the end of the stream.
# Create a persistent subscription.
client.update_subscription_to_stream(
group_name=group_name2,
stream_name=stream_name2,
from_end=True,
)
requires leader
The replay_parked_events()
method can be used to "replay" events that have
been "parked" (negatively acknowledged with the action 'park'
) when reading
a persistent subscription. Parked events will then be received again by consumers
reading from the persistent subscription.
This method has a required group_name
argument and an optional stream_name
argument. The values of these arguments should match those used when calling
create_subscription_to_all()
or create_subscription_to_stream()
.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
The example below replays parked events for group group_name1
.
client.replay_parked_events(
group_name=group_name1,
)
The example below replays parked events for group group_name2
.
client.replay_parked_events(
group_name=group_name2,
stream_name=stream_name2,
)
requires leader
The get_subscription_info()
method can be used to get information for a
persistent subscription.
This method has a required group_name
argument and an optional stream_name
argument, which should match the values of arguments used when calling either
create_subscription_to_all()
or create_subscription_to_stream()
.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
The example below gets information for the persistent subscription group_name1
which
was created by calling create_subscription_to_all()
.
subscription_info = client.get_subscription_info(
group_name=group_name1,
)
The example below gets information for the persistent subscription group_name2
on
stream_name2
which was created by calling create_subscription_to_stream()
.
subscription_info = client.get_subscription_info(
group_name=group_name2,
stream_name=stream_name2,
)
The returned value is a SubscriptionInfo
object.
requires leader
The list_subscriptions()
method can be used to get information for all
existing persistent subscriptions, both "subscriptions to all" and
"subscriptions to stream".
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
The example below lists all the existing persistent subscriptions.
subscriptions = client.list_subscriptions()
The returned value is a list of SubscriptionInfo
objects.
requires leader
The list_subscriptions_to_stream()
method can be used to get information for all
the persistent subscriptions to a stream.
This method has one required argument, stream_name
.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
subscriptions = client.list_subscriptions_to_stream(
stream_name=stream_name2,
)
The returned value is a list of SubscriptionInfo
objects.
requires leader
The delete_subscription()
method can be used to delete a persistent
subscription.
This method has a required group_name
argument and an optional stream_name
argument, which should match the values of arguments used when calling either
create_subscription_to_all()
or create_subscription_to_stream()
.
This method has an optional timeout
argument, which is a Python float
that sets a maximum duration, in seconds, for the completion of the gRPC operation.
This method has an optional credentials
argument, which can be used to
override call credentials derived from the connection string URI.
The example below deletes the persistent subscription group_name1
which
was created by calling create_subscription_to_all()
.
client.delete_subscription(
group_name=group_name1,
)
The example below deleted the persistent subscription group_name2
on
stream_name2
which was created by calling create_subscription_to_stream()
.
client.delete_subscription(
group_name=group_name2,
stream_name=stream_name2,
)
Please refer to the EventStoreDB documentation for more information on projections in EventStoreDB.
requires leader
The create_projection()
method can be used to create a "continuous" projection.
This method has two required arguments, name
and query
.
This required name
argument is a Python str
that specifies the name of the projection.
This required query
argument is a Python str
that defines what the projection will do.
This method also has four optional arguments, emit_enabled
,
track_emitted_streams
, timeout
, and credentials
.
The optional emit_enabled
argument is a Python bool
which specifies whether a
projection will be able to emit events. If a True
value is specified, the projection
will be able to emit events, otherwise the projection will not be able to emit events.
The default value of emit_enabled
is False
.
Please note, emit_enabled
must be True
if your projection query includes a call to
emit()
, otherwise the projection will not run.
The optional track_emitted_streams
argument is a Python bool
which specifies whether
a projection will have its emitted streams tracked. If a True
value is specified, the
projection will have its emitted streams tracked, otherwise the projection will not
have its emitted streams tracked. The default value of track_emitted_streams
is False
.
The purpose of tracking emitted streams is that they can optionally be deleted when
a projection is deleted (see the delete_projection()
method for more details).
Please note, if you set track_emitted_streams
to True
, then you must also set
emit_enabled
to True
, otherwise an error will be raised by this method.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
In the example below, a projection is created that processes events appended to
stream_name2
. The "state" of the projection is initialised to have a "count" that
is incremented once for each event.
projection_name = str(uuid.uuid4())
projection_query = """fromStream('%s')
.when({
$init: function(){
return {
count: 0
};
},
OrderCreated: function(s,e){
s.count += 1;
},
OrderUpdated: function(s,e){
s.count += 1;
},
OrderDeleted: function(s,e){
s.count += 1;
}
})
.outputState()
""" % stream_name2
client.create_projection(
name=projection_name,
query=projection_query,
)
Please note, the outputState()
call is optional, and causes the state of the
projection to be persisted in a "result" stream. If outputState()
is called, an
event representing the state of the projection will immediately be written to a
"result" stream.
The default name of the "result" stream for a projection with name projection_name
is $projections-{projection_name}-result
. This stream name can be used to read from
and subscribe to the "result" stream, with the get_stream()
, or read_stream()
,
or subscribe_to_stream()
, or create_subscription_to_stream()
and
read_subscription_to_stream()
methods.
If your projection does not call outputState()
, then you won't be able to read or
subscribe to a "result" stream, but you will still be able to get the projection
"state" using the get_projection_state()
method.
The "type" string of events recorded in "result" streams is 'Result'
. You may want to
include this in a filter_exclude
argument when filtering events by type whilst reading
or subscribing to "all" events recorded in the database (with read_all()
,
subscribe_to_all()
, etc).
Additionally, and in any case, from time to time the state of the projection will be
recorded in a "state" stream, and also the projection will write to a "checkpoint"
stream. The "state" stream, the "checkpoint" stream, and all "emitted" streams that
have been "tracked" (as a consequence of the track_emitted_streams
argument having
been True
) can optionally be deleted when the projection is deleted. See
delete_projection()
for details.
Unlike the "result" and "emitted" streams, the "state" and the "checkpoint" streams cannot be read or subscribed to by users, or viewed in the "stream browser" view of EventStoreDB's Web interface.
requires leader
The get_projection_state()
method can be used to get a projection's "state".
This method has a required name
argument, which is a Python str
that
specifies the name of a projection.
This method also has two optional arguments, timeout
and credentials
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
In the example below, after sleeping for 1 second to allow the projection to process all the recorded events, the projection "state" is obtained. We can see that the projection has processed three events.
sleep(1) # allow time for projection to process recorded events
projection_state = client.get_projection_state(name=projection_name)
assert projection_state.value == {'count': 3}
requires leader
The get_projection_statistics()
method can be used to get projection statistics.
This method has a required name
argument, which is a Python str
that specifies the
name of a projection.
This method also has two optional arguments, timeout
and credentials
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
This method returns a ProjectionStatistics
object that represents
the named projection.
statistics = client.get_projection_statistics(name=projection_name)
A ProjectionStatistics
object is returned. The attributes of this object
have values that represent the progress of the projection.
requires leader
The update_projection()
method can be used to update a projection.
This method has two required arguments, name
and query
.
The required name
argument is a Python str
which specifies the name of the projection
to be updated.
The required query
argument is a Python str
which defines what the projection will do.
This method also has three optional arguments, emit_enabled
, timeout
, and credentials
.
The optional emit_enabled
argument is a Python bool
which specifies whether a
projection will be able to emit events. If a True
value is specified, the projection
will be able to emit events. If a False
value is specified, the projection will not
be able to emit events. The default value of emit_enabled
is False
.
Please note, emit_enabled
must be True
if your projection query includes a call
to emit()
, otherwise the projection will not run.
Please note, it is not possible to update track_emitted_streams
via the gRPC API.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
client.update_projection(name=projection_name, query=projection_query)
requires leader
The enable_projection()
method can be used to enable (start running) a projection
that was previously disabled (stopped).
This method has a required name
argument, which is a Python str
that
specifies the name of the projection to be enabled.
This method also has two optional arguments, timeout
and credentials
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
client.enable_projection(name=projection_name)
requires leader
The disable_projection()
method can be used to disable (stop running) a projection.
This method has a required name
argument, which is a Python str
that
specifies the name of the projection to be disabled.
This method also has two optional arguments, timeout
, and credentials
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
client.disable_projection(name=projection_name)
requires leader
The reset_projection()
method can be used to reset a projection.
This method has a required name
argument, which is a Python str
that
specifies the name of the projection to be reset.
This method also has two optional arguments, timeout
, and credentials
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
client.reset_projection(name=projection_name)
Please note, a projection must be disabled before it can be reset.
requires leader
The delete_projection()
method can be used to delete a projection.
This method has a required name
argument, which is a Python str
that
specifies the name of the projection to be deleted.
This method also has five optional arguments, delete_emitted_streams
,
delete_state_stream
, delete_checkpoint_stream
, timeout
, and credentials
.
The optional delete_emitted_streams
argument is a Python bool
which specifies
that all "emitted" streams that have been tracked will be deleted. For emitted streams
to be deleted, they must have been tracked (see the track_emitted_streams
argument of
the create_projection()
method.)
The optional delete_state_stream
argument is a Python bool
which specifies that
the projection's "state" stream should also be deleted. The "state" stream is like
the "result" stream, but events are written to the "state" stream occasionally, along
with events written to the "checkpoint" stream, rather than being written immediately
in the way a call outputState()
immediately writes events to the "result" stream.
The optional delete_checkpoint_stream
argument is a Python bool
which specifies
that the projection's "checkpoint" stream should also be deleted.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
client.delete_projection(name=projection_name)
Please note, a projection must be disabled before it can be deleted.
requires leader
The restart_projections_subsystem()
method can be used to restart the projections subsystem.
This method also has two optional arguments, timeout
and credentials
.
The optional timeout
argument is a Python float
which sets a
maximum duration, in seconds, for the completion of the gRPC operation.
The optional credentials
argument can be used to
override call credentials derived from the connection string URI.
client.restart_projections_subsystem()
Default call credentials are derived by the client from the user info part of the connection string URI.
Many of the client methods described above have an optional credentials
argument,
which can be used to set call credentials for an individual method call that override
those derived from the connection string URI.
Call credentials are sent to "secure" servers in a "basic auth" authorization header. This authorization header is used by the server to authenticate the client. The authorization header is not sent to "insecure" servers.
The client method construct_call_credentials()
can be used to construct a call
credentials object from a username and password.
call_credentials = client.construct_call_credentials(
username='admin', password='changeit'
)
The call credentials object can be used as the value of the credentials
argument in other client methods.
The reconnect()
method can be used to manually reconnect the client to a
suitable EventStoreDB node. This method uses the same routine for reading the
cluster node states and then connecting to a suitable node according to the
client's node preference that is specified in the connection string URI when
the client is constructed. This method is thread-safe, in that when it is called
by several threads at the same time, only one reconnection will occur. Concurrent
attempts to reconnect will block until the client has reconnected successfully,
and then they will all return normally.
client.reconnect()
An example of when it might be desirable to reconnect manually is when (for performance reasons) the client's node preference is to be connected to a follower node in the cluster, and, after a cluster leader election, the follower becomes the leader. Reconnecting to a follower node in this case is currently beyond the capabilities of this client, but this behavior might be implemented in a future release.
Reconnection will happen automatically in many cases, due to the @autoreconnect
decorator.
The close()
method can be used to cleanly close the client's gRPC connection.
client.close()
The esdbclient
package also provides an asynchronous I/O gRPC Python client for
EventStoreDB. It is functionally equivalent to the multithreaded client. It uses
the grpc.aio
package and the asyncio
module, instead of grpc
and threading
.
It supports both the "esdb" and the "esdb+discover" connection string URI schemes, and can connect to both "secure" and "insecure" EventStoreDB servers.
The class AsyncEventStoreDBClient
can be used to construct an instance of the
asynchronous I/O gRPC Python client. It can be imported from esdbclient
. The
async method connect()
should be called after constructing the client.
The asyncio client has exactly the same methods as the multithreaded EventStoreDBClient
.
These methods are defined as async def
methods, and so calls to these methods will
return Python "awaitables" that must be awaited to obtain the method return values.
The methods have the same behaviors, the same arguments and the same or equivalent
return values. The methods are similarly decorated with reconnect and retry decorators,
that selectively reconnect and retry when connection issues or server errors are
encountered.
When awaited, the methods read_all()
and read_stream()
return an AsyncReadResponse
object. The methods subscribe_to_all()
and subscribe_to_stream()
return an
AsyncCatchupSubscription
object. The methods read_subscription_to_all()
and
read_subscription_to_stream()
return an AsyncPersistentSubscription
object.
These objects are asyncio iterables, which you can iterate over with Python's async for
syntax to obtain RecordedEvent
objects. They are also asyncio context managers,
supporting the async with
syntax. They also have a stop()
method which can be
used to terminate the iterator in a way that actively cancels the streaming gRPC call
to the server. When used as a context manager, the stop()
method will be called when
the context manager exits.
The methods read_subscription_to_all()
and read_subscription_to_stream()
return
instances of the class AsyncPersistentSubscription
, which has async methods ack()
,
nack()
that work in the same way as the methods on PersistentSubscription
,
supporting the acknowledgement and negative acknowledgement of recorded events that
have been received from a persistent subscription. See above for details.
The example below demonstrates the async append_to_stream()
, get_stream()
and
subscribe_to_all()
methods. These are the most useful methods for writing
an event-sourced application, allowing new aggregate events to be recorded, the
recorded events of an aggregate to be obtained so aggregates can be reconstructed,
and the state of an application to propagated and processed with "exactly-once"
semantics.
import asyncio
from esdbclient import AsyncEventStoreDBClient
async def demonstrate_async_client():
# Construct client.
client = AsyncEventStoreDBClient(
uri=os.getenv("ESDB_URI"),
root_certificates=os.getenv("ESDB_ROOT_CERTIFICATES"),
)
# Connect to EventStoreDB.
await client.connect()
# Append events.
stream_name = str(uuid.uuid4())
event1 = NewEvent("OrderCreated", data=b'{}')
event2 = NewEvent("OrderUpdated", data=b'{}')
event3 = NewEvent("OrderDeleted", data=b'{}')
commit_position = await client.append_to_stream(
stream_name=stream_name,
current_version=StreamState.NO_STREAM,
events=[event1, event2, event3]
)
# Get stream events.
recorded = await client.get_stream(stream_name)
assert len(recorded) == 3
assert recorded[0] == event1
assert recorded[1] == event2
assert recorded[2] == event3
# Subscribe to all events.
received = []
async with await client.subscribe_to_all(commit_position=0) as subscription:
async for event in subscription:
received.append(event)
if event.commit_position == commit_position:
break
assert received[-3] == event1
assert received[-2] == event2
assert received[-1] == event3
# Close the client.
await client.close()
# Run the demo.
asyncio.run(
demonstrate_async_client()
)
The example below shows how to use AsyncEventStoreDBClient
with FastAPI.
from contextlib import asynccontextmanager
from fastapi import FastAPI
from esdbclient import AsyncEventStoreDBClient
client: AsyncEventStoreDBClient
@asynccontextmanager
async def lifespan(_: FastAPI):
# Construct the client.
global client
client = AsyncEventStoreDBClient(
uri="esdb+discover://localhost:2113?Tls=false",
)
await client.connect()
yield
# Close the client.
await client.close()
app = FastAPI(lifespan=lifespan)
@app.get("/commit_position")
async def commit_position():
commit_position = await client.get_commit_position()
return {"commit_position": commit_position}
If you put this code in a file called fastapi_example.py
and then run command
uvicorn fastapi_example:app --host 0.0.0.0 --port 80
, then the FastAPI application
will return something like {"commit_position":628917}
when a browser is pointed
to http://localhost/commit_position
. Use Ctrl-c to exit the process.
The read_all()
, subscribe_to_all()
, create_subscription_to_all()
and get_commit_position()
methods have filter_exclude
and filter_include
arguments. This section provides some more details about the values of these
arguments.
The first thing to note is that the values of these arguments should be sequences of regular expressions.
Please note, they are concatenated together by the client as bracketed alternatives in a larger
regular expression that is anchored to the start and end of the strings being
matched. So there is no need to include the '^'
and '$'
anchor assertions.
You should use wildcards if you want to match substrings, for example '.*Snapshot'
to match all strings that end with 'Snapshot
', or 'Order.*'
to match all strings
that start with 'Order'
.
System events generated by EventStoreDB have type
strings that start with
the $
sign. Persistence subscription events generated when manipulating
persistence subscriptions have type
strings that start with PersistentConfig
.
For example, to match the type of EventStoreDB system events, use the regular
expression string r'\$.+'
. Please note, the constant ESDB_SYSTEM_EVENTS_REGEX
is
set to this value. You can import this constant from esdbclient
and use it when
building longer sequences of regular expressions.
Similarly, to match the type of EventStoreDB persistence subscription events, use the
regular expression r'PersistentConfig\d+'
. The constant ESDB_PERSISTENT_CONFIG_EVENTS_REGEX
is set to this value. You can import this constant from esdbclient
and use it when
building longer sequences of regular expressions.
The constant DEFAULT_EXCLUDE_FILTER
is a sequence of regular expressions that includes
both ESDB_SYSTEM_EVENTS_REGEX
and ESDB_PERSISTENT_CONFIG_EVENTS_REGEX
. It is used
as the default value of filter_exclude
so that the events generated internally by
EventStoreDB are excluded by default.
In all methods that have a filter_exclude
argument, the default value of the argument
is the constant DEFAULT_EXCLUDE_FILTER
, which is designed to match (and therefore
to exclude) both "system" and "persistence subscription config" event types, which
would otherwise be included.
This value can be extended. For example, if you want to exclude system events and
persistent subscription events and also events that have a type that ends with
'Snapshot'
, then you can use DEFAULT_EXCLUDE_FILTER + ['.*Snapshot']
as the
filter_exclude
argument.
The filter_include
and filter_exclude
arguments are designed to have exactly
the opposite effect from each other, so that a sequence of strings given to
filter_include
will return exactly those events which would be excluded if
the same argument value were used with filter_exclude
. And vice versa, so that
a sequence of strings given to filter_exclude
will return exactly those events
that would not be included if the same argument value were used with filter_include
.
Please note, nearly all the client methods are decorated with the @autoreconnect
and
the @retrygrpc
decorators.
The @autoreconnect
decorator will reconnect to a suitable node in the cluster when
the server to which the client has been connected has become unavailable, or when the
client's gRPC channel happens to have been closed. The client will also reconnect when
a method is called that requires a leader, and the client's node preference is to be
connected to a leader, but the node that the client has been connected to stops being
the leader. In this case, the client will reconnect to the current leader. After
reconnecting, the failed operation will be retried.
The @retrygrpc
decorator selectively retries gRPC operations that have failed due to
a timeout, network error, or server error. It doesn't retry operations that fail due to
bad requests that will certainly fail again.
Please also note, the aspects not covered by the reconnect and retry decorator
behaviours have to do with methods that return iterators. For example, consider
the "read response" iterator returned from the read_all()
method. The
read_all()
method will have returned, and the method decorators will therefore
have exited, before iterating over the "read response" begins. Therefore, if a
connection issue occurs whilst iterating over the "read response", it isn't possible
for any decorator on the read_all()
method to trigger a reconnection.
With the "catch-up subscription" objects, there is an initial "confirmation" response
from the server which is received and checked by the client. And so, when a call is
made to subscribe_to_all()
or subscribe_to_stream()
, if the server is unavailable,
or if the channel has somehow been closed, or if the request fails for some other reason,
then the client will reconnect and retry. However, if an exception is raised when iterating over a
successfully returned "catch-up subscription" object, the catch-up subscription will
need to be restarted. Similarly, when reading persistent subscriptions, if there are
connection issues whilst iterating over a successfully received response, the consumer
will need to be restarted.
Instrumentation is the act of modifying software so that analysis can be performed on it. Instrumentation helps enterprises reveal areas or features where users frequently encounter errors or slowdowns in their software or platform.
Instrumentation helps you understand the inner state of your software systems. Instrumented applications measure what code is doing when it responds to active requests by collecting data such as metrics, events, logs, and traces.
Instrumentation provides immediate visibility into your application, often using charts and graphs to illustrate what is going on “under the hood.”
This package supports instrumenting the EventStoreDB clients with OpenTelemetry.
The OpenTelemetry project provides a collection of APIs, SDKs, and tools for instrumenting, generating, collecting, and exporting telemetry data, that can help you analyze your software’s performance and behavior. It is vendor-neutral, 100% Free and Open Source, and adopted and supported by industry leaders in the observability space.
This package provides OpenTelemetry instrumentors for both the EventStoreDBClient
and the AsyncEventStoreDBClient
clients. These instrumentors depend on various
OpenTelemetry Python packages, which you will need to install, preferably with this
project's "opentelemetry" package extra to ensure verified version compatibility.
For example, you can install the "opentelemetry" package extra with pip.
$ pip install esdbclient[opentelemetry]
Or you can use Poetry to add it to your pyproject.toml file and install it.
$ poetry add esdbclient[opentelemetry]
You can then use the OpenTelemetry instrumentor EventStoreDBClientInstrumentor
to
instrument the EventStoreDBClient
.
from esdbclient.instrumentation.opentelemetry import EventStoreDBClientInstrumentor
# Activate instrumentation.
EventStoreDBClientInstrumentor().instrument()
# Deactivate instrumentation.
EventStoreDBClientInstrumentor().uninstrument()
You can also use the OpenTelemetry instrumentor AsyncEventStoreDBClientInstrumentor
to instrument the AsyncEventStoreDBClient
.
from esdbclient.instrumentation.opentelemetry import AsyncEventStoreDBClientInstrumentor
# Activate instrumentation.
AsyncEventStoreDBClientInstrumentor().instrument()
# Deactivate instrumentation.
AsyncEventStoreDBClientInstrumentor().uninstrument()
The instrumentors use a global OpenTelemetry "tracer provider", which you will need to initialise in order to export telemetry data.
For example, to export data to the console you will need to install the Python
package opentelemetry-sdk
, and use the class TracerProvider
, BatchSpanProcessor
,
and ConsoleSpanExporter
in the following way.
from opentelemetry.sdk.resources import SERVICE_NAME, Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter
from opentelemetry.trace import set_tracer_provider
resource = Resource.create(
attributes={
SERVICE_NAME: "eventstoredb",
}
)
provider = TracerProvider(resource=resource)
provider.add_span_processor(BatchSpanProcessor(ConsoleSpanExporter()))
set_tracer_provider(provider)
Or to export to an OpenTelemetry compatible data collector, such as
Jaeger, you will need to install the Python package
opentelemetry-exporter-otlp-proto-http
, and then use the class OTLPSpanExporter
from the opentelemetry.exporter.otlp.proto.http.trace_exporter
module, with an
appropriate endpoint
argument for your collector.
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.resources import SERVICE_NAME, Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.trace import set_tracer_provider
resource = Resource.create(
attributes={
SERVICE_NAME: "eventstoredb",
}
)
provider = TracerProvider(resource=resource)
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter(endpoint="http://localhost:4318/v1/traces")))
set_tracer_provider(provider)
You can start Jaeger locally by running the following command.
$ docker run -d -p 4318:4318 -p 16686:16686 --name jaeger jaegertracing/all-in-one:latest
You can then navigate to http://localhost:16686
to access the Jaeger UI. And telemetry
data can be sent by an OpenTelemetry tracer provider to http://localhost:4318/v1/traces
.
At this time, the instrumented methods are append_to_stream()
, subscribe_to_stream()
subscribe_to_all()
, read_subscription_to_stream()
, read_subscription_to_all()
.
The append_to_stream()
method is instrumented by spanning the method call with a
"producer" span kind. It also adds span context information to the new event metadata
so that consumers can associate "consumer" spans with the "producer" span.
The subscription methods are instrumented by instrumenting the response iterators, creating a "consumer" span for each recorded event received. It extracts span context information from the recorded event metadata and associates the "consumer" spans with a "producer" span, by making the "consumer" span a child of the "producer" span.
The first thing is to check you have Poetry installed.
$ poetry --version
If you don't, then please install Poetry.
$ curl -sSL https://install.python-poetry.org | python3 -
It will help to make sure Poetry's bin directory is in your PATH
environment variable.
But in any case, make sure you know the path to the poetry
executable. The Poetry
installer tells you where it has been installed, and how to configure your shell.
Please refer to the Poetry docs for guidance on using Poetry.
You can easily obtain the project files using PyCharm (menu "Git > Clone..."). PyCharm will then usually prompt you to open the project.
Open the project in a new window. PyCharm will then usually prompt you to create a new virtual environment.
Create a new Poetry virtual environment for the project. If PyCharm doesn't already
know where your poetry
executable is, then set the path to your poetry
executable
in the "New Poetry Environment" form input field labelled "Poetry executable". In the
"New Poetry Environment" form, you will also have the opportunity to select which
Python executable will be used by the virtual environment.
PyCharm will then create a new Poetry virtual environment for your project, using
a particular version of Python, and also install into this virtual environment the
project's package dependencies according to the project's poetry.lock
file.
You can add different Poetry environments for different Python versions, and switch between them using the "Python Interpreter" settings of PyCharm. If you want to use a version of Python that isn't installed, either use your favourite package manager, or install Python by downloading an installer for recent versions of Python directly from the Python website.
Once project dependencies have been installed, you should be able to run tests
from within PyCharm (right-click on the tests
folder and select the 'Run' option).
Because of a conflict between pytest and PyCharm's debugger and the coverage tool,
you may need to add --no-cov
as an option to the test runner template. Alternatively,
just use the Python Standard Library's unittest
module.
You should also be able to open a terminal window in PyCharm, and run the project's Makefile commands from the command line (see below).
Obtain the project files, using Git or suitable alternative.
In a terminal application, change your current working directory to the root folder of the project files. There should be a Makefile in this folder.
Use the Makefile to create a new Poetry virtual environment for the project and install the project's package dependencies into it, using the following command.
$ make install-packages
It's also possible to also install the project in 'editable mode'.
$ make install
Please note, if you create the virtual environment in this way, and then try to open the project in PyCharm and configure the project to use this virtual environment as an "Existing Poetry Environment", PyCharm sometimes has some issues (don't know why) which might be problematic. If you encounter such issues, you can resolve these issues by deleting the virtual environment and creating the Poetry virtual environment using PyCharm (see above).
You can start EventStoreDB using the following command.
$ make start-eventstoredb
You can run tests using the following command (needs EventStoreDB to be running).
$ make test
You can stop EventStoreDB using the following command.
$ make stop-eventstoredb
You can check the formatting of the code using the following command.
$ make lint
You can reformat the code using the following command.
$ make fmt
Tests belong in ./tests
. Code-under-test belongs in ./esdbclient
.
Edit package dependencies in pyproject.toml
. Update installed packages (and the
poetry.lock
file) using the following command.
$ make update-packages