Request

Authorization

Provide your bearer token in the

Authorization

header when making requests to protected resources.

Example:

Authorization: Bearer ********************

Body Params application/json

entity

object (TransferConfig)

entity

optional

entity types

credential

object (Credential)

credential

optional

credential_sid stored on table

destination

optional

where we will put the payload if we are triggering a delivery stored as jsonb

source

optional

where we will get the payload if we are triggering a retrieval stored as jsonb

created_on

string <date-time>

created_on

optional

when the config was last created/edited

last_edited

string <date-time>

last_edited

optional

A Timestamp represents a point in time independent of any time zone or local
calendar, encoded as a count of seconds and fractions of seconds at
nanosecond resolution. The count is relative to an epoch at UTC midnight on
January 1, 1970, in the proleptic Gregorian calendar which extends the
Gregorian calendar backwards to year one.

All minutes are 60 seconds long. Leap seconds are "smeared" so that no leap
second table is needed for interpretation, using a 24-hour linear
smear.

The range is from 0001-01-01T00:00:00Z to 9999-12-31T23:59:59.999999999Z. By
restricting to that range, we ensure that we can convert to and from RFC
3339 date strings.

Examples

Example 1: Compute Timestamp from POSIX time().

Timestamp timestamp;
timestamp.set_seconds(time(NULL));
timestamp.set_nanos(0);

Example 2: Compute Timestamp from POSIX gettimeofday().

struct timeval tv;
gettimeofday(&tv, NULL);

Timestamp timestamp;
timestamp.set_seconds(tv.tv_sec);
timestamp.set_nanos(tv.tv_usec * 1000);

Example 3: Compute Timestamp from Win32 GetSystemTimeAsFileTime().

FILETIME ft;
GetSystemTimeAsFileTime(&ft);
UINT64 ticks = (((UINT64)ft.dwHighDateTime) << 32) | ft.dwLowDateTime;

// A Windows tick is 100 nanoseconds. Windows epoch 1601-01-01T00:00:00Z
// is 11644473600 seconds before Unix epoch 1970-01-01T00:00:00Z.
Timestamp timestamp;
timestamp.set_seconds((INT64) ((ticks / 10000000) - 11644473600LL));
timestamp.set_nanos((INT32) ((ticks % 10000000) * 100));

Example 4: Compute Timestamp from Java System.currentTimeMillis().

long millis = System.currentTimeMillis();

Timestamp timestamp = Timestamp.newBuilder().setSeconds(millis / 1000)
.setNanos((int) ((millis % 1000) * 1000000)).build();

Example 5: Compute Timestamp from current time in Python.

timestamp = Timestamp()
timestamp.GetCurrentTime()

JSON Mapping

In JSON format, the Timestamp type is encoded as a string in the
RFC 3339 format. That is, the
format is "{year}-{month}-{day}T{hour}:{min}:{sec}[.{frac_sec}]Z"
where {year} is always expressed using four digits while {month}, {day},
{hour}, {min}, and {sec} are zero-padded to two digits each. The fractional
seconds, which can go up to 9 digits (i.e. up to 1 nanosecond resolution),
are optional. The "Z" suffix indicates the timezone ("UTC"); the timezone
is required. A proto3 JSON serializer should always use UTC (as indicated by
"Z") when printing the Timestamp type and a proto3 JSON parser should be
able to accept both UTC and other timezones (as indicated by an offset).

For example, "2017-01-15T01:30:15.01Z" encodes 15.01 seconds past
01:30 UTC on January 15, 2017.

In JavaScript, one can convert a Date object to this format using the
standard
toISOString()
method. In Python, a standard datetime.datetime object can be converted
to this format using
strftime with
the time format spec '%Y-%m-%dT%H:%M:%S.%fZ'. Likewise, in Java, one can use
the Joda Time's ISODateTimeFormat.dateTime() to obtain a formatter capable of generating timestamps in this format.

name

string

name

optional

the name of this config. Must be unique within the org

description

string

description

optional

optional nofitifications to send out when this config is being used
TODO:
bool transfer_start_notification = 5;
bool transfer_end_notification = 6;

ttl

integer <int32>

ttl

optional

how many hours the files should live in cloud storage for
must always be > 0

sid

integer <int64> | string

sid

optional

snowflake id

mask

string

mask

optional

FieldMask represents a set of symbolic field paths, for example:

paths: "f.a"
paths: "f.b.d"

Here f represents a field in some root message, a and b
fields in the message found in f, and d a field found in the
message in f.b.

Field masks are used to specify a subset of fields that should be
returned by a get operation or modified by an update operation.
Field masks also have a custom JSON encoding (see below).

Field Masks in Projections

When used in the context of a projection, a response message or
sub-message is filtered by the API to only contain those fields as
specified in the mask. For example, if the mask in the previous
example is applied to a response message as follows:

f {
a : 22
b {
d : 1
x : 2
}
y : 13
}
z: 8

The result will not contain specific values for fields x,y and z
(their value will be set to the default, and omitted in proto text
output):

f {
a : 22
b {
d : 1
}
}

A repeated field is not allowed except at the last position of a
paths string.

If a FieldMask object is not present in a get operation, the
operation applies to all fields (as if a FieldMask of all fields
had been specified).

Note that a field mask does not necessarily apply to the
top-level response message. In case of a REST get operation, the
field mask applies directly to the response, but in case of a REST
list operation, the mask instead applies to each individual message
in the returned resource list. In case of a REST custom method,
other definitions may be used. Where the mask applies will be
clearly documented together with its declaration in the API. In
any case, the effect on the returned resource/resources is required
behavior for APIs.

Field Masks in Update Operations

A field mask in update operations specifies which fields of the
targeted resource are going to be updated. The API is required
to only change the values of the fields as specified in the mask
and leave the others untouched. If a resource is passed in to
describe the updated values, the API ignores the values of all
fields not covered by the mask.

If a repeated field is specified for an update operation, new values will
be appended to the existing repeated field in the target resource. Note that
a repeated field is only allowed in the last position of a paths string.

If a sub-message is specified in the last position of the field mask for an
update operation, then new value will be merged into the existing sub-message
in the target resource.

For example, given the target message:

f {
b {
d: 1
x: 2
}
c: [1]
}

And an update message:

f {
b {
d: 10
}
c: [2]
}

then if the field mask is:

paths: ["f.b", "f.c"]

then the result will be:

f {
b {
d: 10
x: 2
}
c: [1, 2]
}

An implementation may provide options to override this default behavior for
repeated and message fields.

In order to reset a field's value to the default, the field must
be in the mask and set to the default value in the provided resource.
Hence, in order to reset all fields of a resource, provide a default
instance of the resource and set all fields in the mask, or do
not provide a mask as described below.

If a field mask is not present on update, the operation applies to
all fields (as if a field mask of all fields has been specified).
Note that in the presence of schema evolution, this may mean that
fields the client does not know and has therefore not filled into
the request will be reset to their default. If this is unwanted
behavior, a specific service may require a client to always specify
a field mask, producing an error if not.

As with get operations, the location of the resource which
describes the updated values in the request message depends on the
operation kind. In any case, the effect of the field mask is
required to be honored by the API.

Considerations for HTTP REST

The HTTP kind of an update operation which uses a field mask must
be set to PATCH instead of PUT in order to satisfy HTTP semantics
(PUT must only be used for full updates).

JSON Encoding of Field Masks

In JSON, a field mask is encoded as a single string where paths are
separated by a comma. Fields name in each path are converted
to/from lower-camel naming conventions.

As an example, consider the following message declarations:

message Profile {
User user = 1;
Photo photo = 2;
}
message User {
string display_name = 1;
string address = 2;
}

In proto a field mask for Profile may look as such:

mask {
paths: "user.display_name"
paths: "photo"
}

In JSON, the same mask is represented as below:

{
mask: "user.displayName,photo"
}

Field Masks and Oneof Fields

Field masks treat fields in oneofs just as regular fields. Consider the
following message:

message SampleMessage {
oneof test_oneof {
string name = 4;
SubMessage sub_message = 9;
}
}

The field mask can be:

mask {
paths: "name"
}

Or:

mask {
paths: "sub_message"
}

Note that oneof type names ("test_oneof" in this case) cannot be used in
paths.

Field Mask Verification

The implementation of any API method which has a FieldMask type field in the
request should verify the included field paths, and return an
INVALID_ARGUMENT error if any path is unmappable.

Example

{
  "entity": {
    "credential": {
      "data": {},
      "created_on": "2019-08-24T14:15:22Z",
      "last_edited": "2019-08-24T14:15:22Z",
      "name": "string",
      "description": "string",
      "sid": 0
    },
    "destination": {},
    "source": {},
    "created_on": "2019-08-24T14:15:22Z",
    "last_edited": "2019-08-24T14:15:22Z",
    "name": "string",
    "description": "string",
    "ttl": 0,
    "sid": 0
  },
  "mask": "string"
}

Request samples

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

DeleteTransferConfig

Request

Examples

JSON Mapping

Field Masks in Projections

Field Masks in Update Operations

Considerations for HTTP REST

JSON Encoding of Field Masks

Field Masks and Oneof Fields

Field Mask Verification

Request samples

Responses