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Python Scripting & Automation: Automate the work nobody should be doing.

Data pipelines, scraping, scheduled jobs and reporting that take repetitive tasks off someone's desk.

Talk to an engineer

Most businesses have at least one job that exists only because software does not talk to software. Someone downloads a report every Monday, reformats it, and emails it on. Someone copies orders from one system into another. Someone checks a supplier site for price changes.

These tasks are small individually and enormous in aggregate. They are also, almost always, automatable in days rather than months.

( What this covers )

Python Scripting & Automation, in practice

Data pipelines

Moving data between systems on a schedule, with the transformations, deduplication and validation that make it trustworthy at the far end.

Web scraping

Collecting public data reliably, handling the sites that change their markup and the ones that would rather you did not.

Scheduled reporting

Reports built and delivered automatically, to an inbox, a spreadsheet or a dashboard, without anyone remembering to run them.

Back office automation

Invoice handling, file processing, bulk updates and the routine tasks that consume mornings.

System synchronisation

Keeping two systems that were never designed to talk to each other in agreement.

Monitoring and alerts

Automation that stays quiet when it works and tells you clearly when it does not, which is the difference between a tool and a liability.

( Worth talking to us if )

Any of this sounds familiar.

  • Someone on your team does the same task every week
  • Data is copied between two systems by hand
  • Reports are assembled manually and are always slightly late
  • You need data from sources that publish no API
  • A script already exists, written by someone who has left

( How we work )

The shape of a typical build

  1. 01

    Watch the task as it is done

    We map the real process, including the judgement calls the person makes without thinking about them.

  2. 02

    Automate the reliable part

    Not everything should be automated. We separate what a script can own from what still needs a person, and say which is which.

  3. 03

    Build to fail loudly

    Logging, retries and alerts, so a broken job announces itself instead of quietly producing wrong numbers for a month.

  4. 04

    Deploy and hand over

    Scheduled on infrastructure you control, with documentation written for whoever inherits it.

( What you end up owning )

Everything, and no strings.

  • The repository, with readable code and comments that explain the why
  • Deployment and scheduling configuration
  • Documentation of every input, output and failure mode
  • Alerting wired to wherever your team actually looks

( Built with )

  • Python
  • Pandas
  • Playwright
  • FastAPI
  • PostgreSQL
  • Celery
  • Docker

Mainstream tools with deep talent pools, chosen so you are never dependent on us to maintain what we built.

Questions about Python Scripting & Automation

How long does a Python automation project take?
A single well defined Python automation job usually takes a few days, and a pipeline spanning several systems with validation and alerting takes one to two weeks. CoreFinity Tech quotes a fixed price once the task is clear.
What happens when a scraped website changes its layout?
Scrapers break when a source website changes, so CoreFinity Tech builds them to fail loudly and alert the client instead of silently returning nothing. The code is written so repairs are quick.
Is web scraping legal?
Web scraping legality depends on the source website, its terms of service and the type of data collected. CoreFinity Tech checks each source before building and advises against sources that carry legal risk.
Can CoreFinity Tech fix an existing Python script?
Usually, yes. CoreFinity Tech reviews the script first and recommends repairing or rewriting it based on value, and for a short script a rewrite is often cheaper.

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