We use Python where it shines: services that move data, expose APIs, and automate the workflows that keep your product and teams running.
ColibriCode is based in Denver, USA. We plug Python into existing Drupal, Symfony/Laravel, JavaScript, and Go stacks—without turning your platform into a science experiment.
Focus
Python APIs & services
FastAPI, Django REST, background workers, CLIs.
Experience
Data & automation
ETL jobs, reporting, bots, and glue code.
Ecosystem
Pandas, Celery, SQL, cloud SDKs
Pragmatic picks, not ten libraries per problem.
Location
Denver, USA
US-based, remote-first engineering workshop.
WHY PYTHON HERE
We don’t force Python into the UI layer. Instead we use it to power the things users feel indirectly: faster reporting, smoother integrations, and fewer manual tasks.
FOR DATA
We help you move from “we have data somewhere” to repeatable flows that serve products and teams.
FOR ENGINEERING
We turn that folder of “just-run-this.py” into something your team can reason about.
FOR THE BUSINESS
We focus Python on the glue and grunt work: reconciliations, imports, syncs, and checks that people shouldn’t do manually.
HOW WE BUILD
We build Python APIs that feel predictable to your React, mobile, or partner clients.
We turn scattered data—CSV dumps, third-party APIs, internal DBs—into reliable pipelines.
We refine your ad-hoc scripts into something your team can actually depend on.
Python is often the glue between SaaS tools. We keep that glue observable and documented.
COMMON PATTERNS
We focus on the pieces that benefit most from Python’s ecosystem: data, glue code, and integration surfaces—while keeping your primary product stack cohesive.
Python jobs that aggregate data from your PHP/Go backends and third-party tools into dashboards or exports.
Python services that sit between your core product and CRMs, billing, support, or marketing stacks.
Scripts and services that reconcile payments, sync inventory, or generate internal reports on a schedule.
Pipelines and APIs that prepare data for models, call external ML services, and surface results into your product.
PLAYING NICE WITH OTHERS
We treat Python as a good citizen in your architecture: clear boundaries, stable interfaces, and observability so the rest of your stack can depend on it.
CONTRACTS & BOUNDARIES
RUNTIME & OBSERVABILITY
FAQ
Which Python frameworks and tools do you typically use?
For APIs we usually lean on FastAPI or Django REST Framework. For background work we use Celery, RQ, or cloud-native queuing. For data we combine Python with SQL, Pandas, and warehouse tools depending on your stack.
How does Python fit into our existing Drupal, Symfony/Laravel, or Go stack?
We often introduce Python as a sidecar for data and automation: ETL jobs, reporting APIs, or integration services that talk to your PHP/Go backends over stable contracts. The goal is to complement your main stack, not replace it.
Can you help us clean up existing scripts and cron jobs?
Yes. We start by inventorying your current scripts and their schedules, then group them into services or flows. From there we add configuration, logging, retries, and tests so they behave more like a product than a collection of one-offs.
Do you also handle deployment and observability for these services?
We can. That typically includes containerization, CI/CD, environment config, and metrics/logging hooks into your preferred observability tools so data jobs and integrations are visible to your team.
TALK ABOUT PYTHON SERVICES
Tell us which systems you need to connect, what data you care about, and which manual tasks you’d like to retire. We’ll outline how Python services can plug into your existing stack without creating a new monolith.
A short description of your current stack (Drupal, Symfony/Laravel, JS, Go, etc.) plus the Python work you’re considering is enough to start a focused conversation.
