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Technology · Data and automation

Python programming and automation

Python is the language of data and repetitive tasks. It reads the files that arrive every week in a different format, matches them against what your systems hold and leaves the report done without anyone copying and pasting. We program those tools around your files.

Tell us about your project See an example

Often combined with

Fig. 01Data sorterRECORDS12DUPLICATES2CLEAN · MATCH · SORTLooping
Cards from two sources pass through cleaning and matching. The repeated ones drop into the bin and the rest come out ordered in the report.

Situations

What you can solve with Python programming

If someone on your team spends a morning a week tidying a spreadsheet, there is probably a job here.

  • Spreadsheets combined by hand

    Two exports someone matches every Monday, hunting for coincidences. A program does it the same way every time and flags what doesn't add up.

  • Dirty data

    Names written three ways, dates in different formats, duplicate rows. They are cleaned with written rules you can read and change.

  • A report redone every month

    The same calculations and tables with new data. It builds itself, in Excel, in PDF or in the format the person receiving it already uses.

  • Tasks that depend on someone remembering

    Download a file, rename it, upload it somewhere else. It is scheduled to happen on time and leave a record.

The cleaning station: the same rules for every card

What to check before starting

  • A real sample of each file, quirks included
  • Which rules the person doing it by hand applies today
  • Where it will run: a workstation, a server or the cloud
  • Who receives the result, and in which format

Services

What we build with Python

Small programs with one clear job. They are chained when the process calls for it.

  • Module 1 · Trays

    Data import

    Reading Excel, CSV, PDF, databases and APIs, even when the format changes from one delivery to the next.

    Examples of deliverables

    • Reading Excel and CSV
    • Tables extracted from PDF
    • Download from an API
  • Module 2 · Cleaning

    Cleaning and normalization

    Rules to unify names, dates, units and codes, and to set aside what can't be corrected without asking.

    Examples of deliverables

    • Unified formats
    • Duplicate detection
    • List of doubtful rows
  • Module 3 · Matching and output

    Matching and reports

    Comparing sources, running the calculations and producing the report in the format already in use.

    Examples of deliverables

    • Reconciling two lists
    • Report in Excel or PDF
    • Summary by email
  • Module 4 · Timer

    Scheduled tasks

    Programs that run on time, log what they did and alert when something fails.

    Examples of deliverables

    • Daily file download
    • Copy and archive
    • Alert when data is missing

A working example

Combine two files and detect duplicates

An illustrative example with two sample files: the store's customers and the CRM's. Run the process step by step and watch them get normalized, matched by email address and merged into one ordered list.

Working example · sample data

store.csv

NameEmailCity
LUCÍA ortega Lucia.Ortega@Ejemplo.com almería
pablo MARÍNpablo.marin@ejemplo.comVera
Inés Carmona INES@EJEMPLO.COMGRANADA
david solerd.soler@ejemplo.commurcia

crm.csv

NameEmailCity
Carmona, Inésines@ejemplo.comGranada
NOELIA VEGAnoelia.vega@ejemplo.comAlmería
Lucía Ortegalucia.ortega@ejemplo.comAlmería
Raúl Peñaraul.pena@ejemplo.com vera

Two files with the same customers written in different ways.

The demo applies the rules in your browser to invented data. In a project, the same process is written in Python and runs on your files.

Integration

How it fits with your systems

A data process lives between what arrives and what someone needs to read. Its value is that what comes out is always comparable.

Where it comes from

  • Excel, CSV and PDFrecurring files
  • ERP, CRM or databaseexports and queries
  • Third-party APIsdownloads
PythonPython processreads, cleans, matches and generates

Where it goes

Dependencies worth checking

  • Whether the files always arrive in the same place, under the same name
  • Which permissions the program needs to read and write
  • What to do with rows that don't meet the rules
  • How often it must run and how long it may take

How we work and what we deliver

How we run a Python process

  1. 01

    Initial review

    We look at the real files and at how the work is done today, step by step.

  2. 02

    Scope

    What comes in, which rules apply, what goes out and what is set aside for review.

  3. 03

    First release

    The process run on a sample of yours, with the result next to the one done by hand.

  4. 04

    Validation

    Comparison against several real periods, until every difference has an explanation.

  5. 05

    Documentation

    The rules in plain language, how to run it, how to change a rule and what each alert means.

What you get when the job closes

  • The code in a repository in your name
  • The cleaning and matching rules, in writing
  • The scheduled run and its log
  • A guide to changing a rule

Questions

Questions about Python

Missing yours? Write it to info@veodar.com and we'll reply with a specific question, not a brochure.

Do I need to know how to program to use it?

No. The program runs on its own or with a double click, depending on the case, and leaves the result where agreed. What you do get is an explanation of the rules, so you can ask for changes precisely.

What if the file format changes?

It depends on how much. Foreseeable changes, like a moved column or a different name, are handled from the start. If the file arrives unrecognizable, the program stops and alerts instead of producing a wrong result.

Can it replace an Excel macro?

Often, especially when the macro has become fragile or depends on one particular computer. If the spreadsheet works and few people use it, it may not be worth it; we weigh that before proposing anything.

Where does the program run?

On an office computer, on a server of yours or in the cloud. That is decided by where the files are and who needs the result.

Does my data leave the company?

It doesn't have to. The process can run entirely inside your network. If an outside service is involved, we state which one, what data it receives and why.

Updated:

Related services

All services

Other technologies

What it is combined with

All technologies
  • Node.js backendAPIs, connections between systems and background processes. We automate the exchange of information between your website and your business tools.
  • Generative AI integrationAssistants over your documents, sorting of information and draft generation. We bring these features into your website and your working tools.
  • JavaScript programmingCalculators, filters, validation and interactions for your website. New features and problem-solving in the code you already have.

Get started

Tell us which file eats your time every week.

A sample of the file and what you do with it, step by step. Even with the data blanked out, it helps.

What helps us assess it

  • A sample of each file, even with the data blanked out
  • What you do with them today, step by step
  • How often they arrive and who uses the result
  • Where the result should end up
Tell us about your project info@veodar.com

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Fig. 07Morse keyH · E · L · L · O