Scheduled data jobs
Imports, exports, and reports that run on a schedule, with logs and alerts instead of manual clicks.
The Problem
Python Scripts That Run the Business From Someone's Laptop
Python usually enters a company as a quick script. A few years later, those scripts produce the reports, imports, and prices the whole team depends on.
01 · Manual reports
The weekly report depends on one analyst running a notebook.
A scheduled job builds and sends the report, with a log of every run.
02 · Loose packages
A reinstall pulls new library versions and breaks the script.
Dependencies are locked with uv or Poetry, so every install matches the last.
03 · Silent failures
A failed night job goes unnoticed until a customer calls.
Failures send an alert with the error to your team's email or Slack.
04 · Old Python
Scripts still run on a Python version past end of life.
We move them to a supported Python 3 release and test them there.
Your weekly sales report comes from a Jupyter notebook that one analyst runs by hand every Monday. The customer import is a Python script on an old server, started by a cron job nobody remembers setting up. It still runs on Python 3.8, and its requirements file pins nothing, so a reinstall pulls new library versions and breaks. When the analyst is on holiday, the report doesn't go out. When the script fails at night, nobody notices until a customer calls.
We start by moving those scripts into one repository with locked dependencies and tests. Then we turn manual steps into scheduled jobs with logs and alerts, and put a Django or FastAPI app in front where people need screens or an API. Your reports run on time whether or not the analyst is in, and failures reach you before customers do.
Jobs that run themselves
Manual notebooks and scripts become scheduled jobs with logs and alerts when something fails.
Typed, tested Python
Type hints, Pydantic models, and pytest tests catch bad data before it reaches your reports.
One language, web to data
Your web app, API, data jobs, and AI calls share one Python codebase and one set of models.
Our Python Development Process
From Script Audit to a Running System in Five Steps
Five steps take your Python work from scattered scripts to a tested system. You approve the plan, check real outputs on staging, and own the repository throughout.
You walk us through the manual tasks, scripts, and data sources your team relies on. We note which ones break most and what each one feeds. You get a short plan and a fixed-price proposal.
What's Included
What You Get With Custom Python Development Services
Python backend development, scheduled data jobs, a web app or API where people need one, and the tests and docs that keep it all running after handover.
Compare Options
DeveloperLook vs a No-Code Tool vs an In-House Hire
A no-code tool is quicker for simple app-to-app steps, and an in-house hire suits ongoing data work. Python development outsourcing fits when logic outgrows the first and budget can't carry the second.
| Feature | DeveloperLookBest fit | No-code tool | In-house hire |
|---|---|---|---|
| Setup speed | 1 to 2 weeks per job | Hours for simple steps | Months to hire and onboard |
| Complex logic | Any logic Python can express | Limited to built-in steps | Any logic |
| Data volume | Large files and databases | Per-task limits and fees | Large files and databases |
| Testing | pytest on core flows | Manual checks | Depends on the person |
| AI features | LLM APIs in typed code | Prebuilt AI steps only | Depends on skills |
| Running cost | Your own server or cloud | Monthly per-task pricing | Salary plus tools |
| Support | 30 to 60 days included | Vendor help desk | Full time |
| Code ownership | Your repository | Locked in the vendor | Yours |
DeveloperLook
No-code tool
- Setup speed
- DeveloperLook: 1 to 2 weeks per jobNo-code tool: Hours for simple steps
- Complex logic
- DeveloperLook: Any logic Python can expressNo-code tool: Limited to built-in steps
- Data volume
- DeveloperLook: Large files and databasesNo-code tool: Per-task limits and fees
- Testing
- DeveloperLook: pytest on core flowsNo-code tool: Manual checks
- AI features
- DeveloperLook: LLM APIs in typed codeNo-code tool: Prebuilt AI steps only
- Running cost
- DeveloperLook: Your own server or cloudNo-code tool: Monthly per-task pricing
- Support
- DeveloperLook: 30 to 60 days includedNo-code tool: Vendor help desk
- Code ownership
- DeveloperLook: Your repositoryNo-code tool: Locked in the vendor
Projects We've Built
Web Apps and Data Dashboards We Have Built
Recruitment, finance, payroll, and e-learning platforms from our portfolio, chosen for their data handling and dashboards, not as examples of one language.
CognifyHR AI Recruitment Website and HR Dashboard
- HR & Staffing
- Technology
- Dashboard
Oasic Finance SaaS Web Design & Development
- Finance
- SaaS Platform
- Dashboard
Payrole Global Payroll Website Design & Development
- HR & Staffing
- Dashboard
- SaaS Platform
Edutech E-Learning Web Design & Development
- Education
- Dashboard
- E-commerce
What Our Clients Say
What Clients Say After Launch
Feedback from teams we have built web apps and data tools for.
We had a pretty specific idea of what we wanted our website to become, but I wasn’t sure how easily we could explain all of it to a development team. There were quite a few moving parts, and we were working toward a deadline, so I expected a few things to get lost along the way. That never really happened. They understood what we were trying to achieve, kept us updated throughout the process, and got everything ready within the agreed timeline. The final site feels much easier to navigate, works beautifully on mobile, and is noticeably smoother for our customers. It was a huge relief seeing the original idea actually turn into the website we had in mind.
The mobile experience is probably my favourite part of the new site. We had spent a lot of time making sure the desktop version looked right, and the team kept pushing us to think about how everything would actually feel on a phone too. They were right. The navigation is clean, the interactions feel natural, and everything we’ve tested so far works exactly as it should. They also went through the links, forms, integrations, and other details more than once before launch, which I really appreciated. And even after going live, we could still reach out when something came up. The whole process felt friendly, organised, and surprisingly straightforward.
What I appreciate most is that the website is actually easy for us to manage now. We can update content ourselves instead of sending a developer a message every time we need to change something small. They also paid attention to the technical SEO side, which mattered to us because we didn’t want a new website to create problems for the traffic we already had. I’ve probably asked more questions than I should have since launch, but every question has been handled patiently and without any fuss. The team is easy to work with, they explain things clearly, and when we need something changed, they focus on getting it done rather than making the process complicated.
1,250+
Projects shipped
10+
Years of experience
Top 3%
Upwork Top Rated Plus
5 stars
Average review score
Want results like these?
Tell us what you are building. You get a reply within 24 hours on business days, then a written estimate.
Work Culture
Why Data-Heavy Teams Trust Us With Their Python Code
Python work fails quietly: a job stops, a report goes stale, a number drifts. These habits keep your Python systems honest and easy to hand over.
Old and new outputs compared
Before a job replaces a manual process, we run both on the same data and compare the results. You switch over only when the numbers match.
Dependencies locked
Every project gets a lock file from uv or Poetry. A reinstall next year gives you the same libraries, not a surprise upgrade.
Failures you hear about
Jobs report failures to your email or Slack, with the error and the input that caused it. You find out before your customers do.
Types on every boundary
Pydantic models check data coming from APIs, files, and forms. Bad rows get flagged and logged instead of quietly corrupting a report.
Framework choice explained
Django for admin-heavy apps, FastAPI for APIs, plain scripts where that's enough. We explain the choice in your proposal, in plain English.
Your code, your cloud
Code lives in your GitHub, and jobs run on your server or cloud account. Switching teams later doesn't mean rebuilding anything.
Overview
Who provides Python development services for web apps and data work?
DeveloperLook provides Python development services for teams that run web apps, APIs, and data jobs on Python. We turn manual scripts into scheduled, tested jobs, build Django or FastAPI apps, and connect data sources and AI APIs. Prices start at $1,150, automations take 1 to 2 weeks, apps 5 to 15 weeks, and you own the repository.
DEVELOPERLOOK
Project facts · Python Development Services
- Service
- Python Development Services (automation, web apps, APIs, data jobs)
- Typical timeline
- 1 to 2 weeks for an automation, 5 to 15 weeks for a web app or platform
- Platforms
- Django, FastAPI, and Flask, on AWS or your own server
- Built with
- Python 3, pytest, Pydantic, PostgreSQL, Celery, and uv
- Experience
- 10+ years of development experience and 1,250+ shipped projects
- Post-launch support
- 30 days, or 60 days on the Python Data Platform plan
- Communication
- Calls in US, UK, and AU business hours
- Starting price
- From $1,150 USD, fixed scope after discovery
Reviewed 8 Oct 2026 by Saimul Islam
Good fit
Teams running reports by hand
Your weekly report or data import depends on one person running a notebook, and the work stalls whenever they're away.
Companies ready to hire Python developers
You want to hire Python developers for a web app or API, but a full-time hire takes months and the work starts now.
Product teams adding data features
Your product needs imports, scheduled syncs, or an AI feature, and your current backend makes each one awkward to add.
Startups choosing a backend language
You're comparing Python software development services for a new product whose roadmap includes data work and AI features.
Agencies needing Python capacity
Your agency won a data-heavy web project and needs a Python team that builds under your brand and hands over clean code.
Not a fit
Simple app-to-app steps
Your automation is a few steps between apps you already use, like a form to your CRM. Our Make.com Automation Consultant page covers that for less.
AI chatbot only
You only need a customer-facing AI chatbot on your website. Our AI Chatbot Development Services page covers that build directly.
Budget under $1,150
Your budget is under $1,150, or a spreadsheet formula already does the job. If a simple tool already covers your case, we'll tell you before we quote.
PHP or WordPress site
Your site runs on PHP or WordPress and the work stays inside it. Our PHP Development Services page is the better place to start.
Not sure we're the right fit?
Book a free call or message us. We'll tell you honestly whether we're the right team.
Pricing
Transparent Starting Prices for Python Development Services
These are starting points in USD. Your final price depends on the data sources, jobs, and screens you need, and you get a fixed proposal after a free discovery call.
For one manual data task, like a weekly report or a spreadsheet import. About 1 to 2 weeks.
$1,150one-time, USD
- One scheduled job replacing a manual task
- Data from up to 2 sources
- Typed code with pytest tests
- Dependencies locked with uv
- Failure alerts by email or Slack
- 30 days of fixes after launch
Recommended
For teams that need a Python web app or API alongside a few data jobs. About 5 to 9 weeks.
$3,600one-time, USD
- Everything in Python Automation
- Web app in Django or API in FastAPI
- User login and roles
- Admin screens or interactive API docs
- Up to 3 scheduled data jobs
- 30 days of post-launch support
For products that combine a web app, data pipelines, and AI features. About 10 to 15 weeks.
$7,900one-time, USD
- Everything in Python Web App or API
- Data pipeline into PostgreSQL or a warehouse
- Background workers with Celery
- One AI feature through an LLM API
- Dashboards for your team
- 60 days of post-launch support
For Agencies
White-Label Python Development for Agencies and Studios
You keep the client relationship. We supply the Python engineering behind it: scheduled data jobs, Django or FastAPI apps, and AI connections, delivered under your brand with code in your client's repository.
How the partnership works
White label: your client only ever sees your brand
- Your client
- You, the agency
- DeveloperLook
Share the brief
Send the manual tasks, the data sources, and your client's deadline.
- Client needs
- You share the details
- Details received
We plan and quote
You get a job list, a framework choice, and a fixed price to resell.
- Scope and plan
- Proposal to resell
- Your quoteYOUR LOGO
Build and hand off
We build, test against real data, and deploy under your client's accounts.
- Done by our team
- Your brand on it
- Handed to your clientDone
Partner with DeveloperLookDelivered under your brand
Stay client-facing
Your client sees your brand on every report and handover.
Predictable delivery
Fixed scope, two-week sprints, and staging outputs your client can check.
Senior Python engineers
Django, FastAPI, pytest, and data pipeline work from experienced developers.
Flexible capacity
One automation, a full app, or a few months of Python work.
The Right Technology for Your Project
Technology Stack
Python 3 with the framework that fits the job, the data and queue tools behind scheduled work, and packaging tools that keep installs repeatable.
Python
Django- FastAPI
- Flask
- Pydantic
PostgreSQL- Redis
- Celery
- pandas
- pytest
- uv
- Poetry
- GitHub Actions
OpenAI
AWS
Docker- Sentry
FAQ
Frequently Asked Questions
Straight answers on Python costs, hiring Python developers, web and backend use, and Python for AI.
Saimul IslamFounder & CEO, DeveloperLookStill have questions?
Send a message or book a call with the team.
Python development services at DeveloperLook start at $1,150 for one scheduled automation that replaces a manual data task. A Django web app or FastAPI service with login, roles, and up to 3 data jobs starts at $3,600. Platforms that add data pipelines, background workers, and an AI feature start at $7,900. You get a fixed quote after a free call.
Hire a Python developer by asking for tested code with type hints and a lock file, not just a list of frameworks. Ask how they'd structure a scheduled job and how they'd know when it fails. A Python development company adds design, testing, and backup developers, which matters once real business data depends on the code.
The best custom Python developer is one who has already built your kind of system: data jobs, a Django admin, or an API. Ask for a short paid trial on a real task, then review the tests and the handover notes. Strong candidates explain trade-offs plainly and tell you when a simpler tool would do.
Yes, Python is good for web development, especially for apps with complex data, admin screens, or AI features. Django ships with an admin, an ORM, and authentication, while FastAPI builds API documentation from type hints. Python web development is weaker for real-time apps with many open connections, where Node.js is often the simpler fit.
Use Python for web development when your app works closely with data, reports, or AI. The same language runs your web app, your scheduled jobs, and your data analysis, so models and business rules are written once. Its data and machine learning libraries are mature and widely used, which saves build time.
Yes, Python is good for most business software: internal tools, data platforms, APIs, and automation. Readable syntax keeps code easy to hand over, and type hints checked by a tool like mypy catch many bugs before release. It's a weaker choice for mobile apps and for games or systems where raw speed decides everything.
Yes, on the server you can use Python instead of JavaScript, with Django, FastAPI, or Flask. In the browser, JavaScript is still needed for interactive screens, though Django templates or htmx keep that to a minimum. Many teams pair a Python backend with a React or Vue front end.
Yes, Python is widely used for backend work: APIs, authentication, databases, background jobs, and integrations. Django covers full web backends with an admin panel, and FastAPI suits fast, typed APIs for mobile apps and front ends. Our Python backend development usually pairs one of them with PostgreSQL, Redis, and Celery for background tasks.
Python can build mobile apps through tools like Kivy or BeeWare, but it's rarely the best choice for the app itself. Most teams build the app in Swift, Kotlin, Flutter, or React Native and use Python for the backend API behind it. That's where we'd usually put Python in a mobile project.
Yes, Python is the main language of AI development. PyTorch, TensorFlow, and scikit-learn are Python libraries, and OpenAI and Anthropic both publish official Python SDKs. So an AI feature, such as document summaries or smarter search, can live in the same codebase as your web app and data jobs.
Saimul IslamFounder & CEO, DeveloperLookStill have questions?
Send a message or book a call with the team.
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