tap-freshservice

tap-freshservice is a Singer tap for Freshservice.

Built with the Meltano Tap SDK for Singer Taps.

Installation

Install from PyPi:

pipx install tap-freshservice

Install from GitHub:

pipx install git+https://github.com/Datateer/tap-freshservice.git@main

Configuration

Settings

Replication behavior

All streams use full-table replication. There is no Singer incremental mode.

Each run requests tickets whose updated_at falls within the configured ticket_lookback_days window (default 45). That value is sent to Freshservice as the updated_since query parameter. Child streams such as time_entries run only for tickets returned in that window.

Note: updated_since filters on ticket updated_at only. It does not reflect activity such as new time entries when the ticket itself was not updated.

Large Singer messages (Meltano line size limit)

Meltano limits each tap output line to half of elt.buffer_size (default 50 MiB). If a run fails with Output line length limit exceeded, a single RECORD or SCHEMA line is too large.

Common causes in this tap:

• tickets with flattening_enabled: true (large nested schemas)
• tickets fields such as description / description_text (large HTML bodies)

Fixes, in order of preference:

1. Keep flattening off for API extraction (recommended for time_entries-only jobs)
2. Exclude large ticket fields with stream maps when syncing tickets
3. Raise the Meltano buffer if large records are expected:

elt:
  buffer_size: 209715200  # 200 MiB → 100 MiB max line size

Or: meltano config set meltano elt.buffer_size 209715200

Example Meltano config

plugins:
  extractors:
    - name: tap-freshservice
      config:
        api_key: $TAP_FRESHSERVICE_API_KEY
        url_base: https://your-org.freshservice.com/api/v2
        ticket_lookback_days: 45
        request_delay_seconds: 1.0

Supported Python versions

Python 3.10–3.13

Capabilities

catalog, discover, stream-maps, schema-flattening, batch, and others. Run tap-freshservice --about for the full list.

A full list of supported settings and capabilities is available by running:

tap-freshservice --about

Configure using environment variables

This Singer tap will automatically import any environment variables within the working directory's .env if the --config=ENV is provided, such that config values will be considered if a matching environment variable is set either in the terminal context or in the .env file.

Usage

You can easily run tap-freshservice by itself or in a pipeline using Meltano.

Executing the Tap Directly

tap-freshservice --version
tap-freshservice --help
tap-freshservice --config CONFIG --discover > ./catalog.json

Developer Resources

Follow these instructions to contribute to this project.

Initialize your Development Environment

pipx install poetry
poetry install

Create and Run Tests

Create tests within the tests subfolder and then run:

poetry run pytest

You can also test the tap-freshservice CLI interface directly using poetry run:

poetry run tap-freshservice --help

Testing with Meltano

Note: This tap will work in any Singer environment and does not require Meltano. Examples here are for convenience and to streamline end-to-end orchestration scenarios.

Next, install Meltano (if you haven't already) and any needed plugins:

# Install meltano
pipx install meltano
# Initialize meltano within this directory
cd tap-freshservice
meltano install

Now you can test and orchestrate using Meltano:

# Test invocation:
meltano invoke tap-freshservice --version
# OR run a test `elt` pipeline:
meltano elt tap-freshservice target-jsonl

SDK Dev Guide

See the dev guide for more instructions on how to use the SDK to develop your own taps and targets.