A COBOL-to-Python programme is an application and platform modernisation project, not simply a way to translate source code. Teams must account for business rules, data formats, transactions, runtime dependencies, operational requirements and a controlled cutover. Python may be a suitable target for some services, but the available UK evidence does not establish that it is universally better than Java, C# or another option.
What does COBOL-to-Python migration actually involve?
It means changing how a business capability is implemented and operated, while preserving the behaviours and service obligations that matter. Rewriting a COBOL program in Python may be one part of that work; it does not, on its own, replace the surrounding platform or prove that the new system behaves equivalently.
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IBM executive Rob Thomas captured IBM’s position in February 2026: “Translating code is one thing. Modernizing a platform is something else entirely.” IBM sells mainframe modernisation products and services, so this is vendor commentary rather than a neutral standards-body finding. It is nevertheless a useful distinction to test against a programme’s actual scope. Thomas also wrote: “The real work is data architecture redesign, runtime replacement, transaction processing integrity, and non-functional requirements baked into the platform itself.” IBM Newsroom, 23 February 2026.
For each application or service in scope, establish what must change and what must remain true: inputs and outputs, data ownership, transaction boundaries, security controls, integrations, batch schedules, recovery behaviour, performance expectations and service levels. IBM’s article identifies operating systems, transaction managers, databases, security, messaging and storage as dependencies that a code translation alone does not move. Map those dependencies in your own estate rather than assuming the same components or risks apply everywhere.
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Why choose Python rather than Java or C#?
The evidence available for this guide does not compare Python with Java or C# on cost, performance, skills availability or long-term maintainability, so it cannot support a general claim that one is the best target. Make the language decision in the context of the intended system: the capabilities and runtime it needs, its integration environment, the team’s ability to support it, and the non-functional requirements it must meet.
Python is a candidate target, not an outcome in itself. A programme should be able to explain why its chosen implementation fits the services being modernised and how it will meet their operational requirements. If the rationale is only that a translator can generate Python, the case has not addressed platform fit or the work required to own the resulting system.
Which migration approach fits the programme?
The approaches below are described in Mecanik’s June 2026 UK guide. They are practical options, not the results of an independently validated comparative study. A programme can also use more than one pattern across different applications.
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|---|---|---|
| Automated conversion | A tool parses COBOL and generates Python. | Can accelerate translation and cover boilerplate, but generated code may retain COBOL-shaped patterns. Teams still need to review, test and, where appropriate, refactor it for readability and maintainability. Output quality depends on the tool and the code; it should not be assumed to be uniform. |
| Parallel rewrite | Build the Python implementation alongside the COBOL system, run both against the same inputs, compare results, then retire the old system after validation. | Creates a direct opportunity to compare outputs for critical workloads, but requires reconciliation, duplicate operating capacity and clear controls over which system is authoritative during the overlap. |
| Incremental replacement | Replace programs or modules in stages while the new and existing systems coexist. | Limits the size of individual changes and allows teams to learn as they go. The cost is interface and operating complexity across the hybrid estate, which can persist if replacement stages stall. |
Choose based on the boundaries you can safely test and operate, not on a label alone. For each option, assess continuity risk, the evidence required to validate behaviour, the duration and cost of parallel operation, the maintainability of the target, and the consequences if the programme pauses before completion. Mecanik recommends incremental replacement for many UK projects, but that is the publisher’s recommendation, not an independently established rule.
How should a team plan the migration?
Build the evidence for each decision before committing a whole estate to a conversion method. The following sequence is a practical planning framework derived from the risks identified in the source material; it is not a universal prescribed standard.
- Set the service boundary. List the business capabilities, programs, batch jobs, interfaces and data stores in scope. Record upstream and downstream dependencies, transaction managers, security controls, messaging, storage and operating arrangements.
- Document behaviour and rules. Identify transaction boundaries, business rules, exception paths, schedules and operational expectations. Treat undocumented behaviour as a discovery risk: interview knowledgeable users and operators, inspect available artefacts, and observe current processing before changing it.
- Map data explicitly. Inventory record layouts, fixed-width files, character encodings and numeric representations, including COMP-3 packed decimal where present. Define how every relevant value will be decoded, represented, rounded, validated and written in the target. Do not assume that a successful file read means values retain their original meaning.
- Choose representative test cases. Include normal, boundary, exceptional and high-volume workloads, along with real or representative data that is anonymised where required. Identify expected results and business owners who can resolve discrepancies.
- Build comparison and reconciliation early. Run matched inputs through the existing and target implementations where the approach permits it. Compare records and business outcomes, not just whether a process exits successfully. Define acceptable differences explicitly and investigate unexplained mismatches.
- Measure operational behaviour. Compare elapsed time, throughput, resource use, batch completion windows and other service-specific measures against representative workloads. A Python implementation that matches outputs but misses an operational requirement is not ready for production.
- Test recovery and cutover. Exercise failure handling, restart and recovery, rollback, data reconciliation and the decision process for returning to the existing service. Set named approval gates and evidence required at each gate before production transition.
Regression coverage is especially important where the existing system’s rules are poorly documented. A large number of translated lines is not evidence of equivalent behaviour; the useful evidence is repeatable comparison against agreed cases and operating conditions.
How do COMP-3, EBCDIC and fixed-width data affect the work?
These formats need explicit treatment at system boundaries. COMP-3 is a packed-decimal representation, EBCDIC is a character encoding, and fixed-width files rely on position and field layout rather than delimiters. A receiving Python program must interpret the source representation correctly and preserve the business meaning of values when reading, processing and writing data.
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How can teams prove Python matches COBOL output?
Use a controlled comparison process that makes differences visible and actionable. Run both implementations against the same representative inputs, preserve the input set and execution conditions, and compare the resulting business records and outcomes. Where systems have time-dependent, random or externally supplied inputs, control or record those inputs so that a difference is not mistaken for a language-conversion defect.
- Agree in advance which fields and outcomes must match exactly and which differences are acceptable under documented business rules.
- Compare numeric values with the required precision and rounding rules; a displayed value that looks alike may still differ in stored precision or downstream effect.
- Reconcile counts, totals, control records and exceptions as well as individual outputs.
- Repeat tests across normal and boundary cases, failures, recovery scenarios and representative volumes.
- Record every mismatch, its cause, resolution and approval. Unexplained differences should block the relevant cutover gate.
For services where parallel execution is safe and feasible, continuing comparison in an operationally representative environment can strengthen the evidence before retirement of the COBOL implementation. It also creates duplicate operating work and needs clear data-authority controls; the architecture and risk profile determine whether it is appropriate.
Does the mainframe need to be decommissioned first?
No. A programme can retain the COBOL system while building and validating replacements, then decide when it is safe to retire the old capability. This can reduce the pressure to make a single irreversible change, but it introduces a hybrid period in which teams must manage interfaces, data consistency, operational ownership and potentially duplicate costs.
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Decommissioning is a separate decision from replacing a program’s language. Establish which remaining workloads, data, integrations and operational services still depend on the mainframe, and identify a tested destination or retirement plan for each before closing it down. Mecanik’s guide describes parallel operation and later decommissioning as an option; the right sequence depends on the architecture and programme risks.
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What does UK evidence show—and what does it not show?
A UK public-sector example illustrates the scale and continuity demands of legacy modernisation, but it is not a Python precedent. The Management Consultancies Association’s 1 May 2026 case study, “Capgemini Invent with HMRC,” says HMRC’s VAT mainframe had more than 3.1 million lines of COBOL, supported over 80 services and 325 data feeds, and was around 50 years old. The account says the programme shifted from like-for-like migration to broader service transformation, used a Model Office for continuous user validation, reached beta in April 2025 and completed transition in December 2025 with no disruption to critical services. It describes cloud-ready service replacements; it does not say Python was the target, and the case-study account is not an external audit. Read the MCA case study.
IBM executive commentary says roughly 40 percent of COBOL runs on Windows, Linux and other distributed platforms. IBM does not provide a separate methodology for that estimate in the cited article, so treat it as IBM’s figure, not an independently verified measure of the UK estate. It is a reminder that COBOL does not automatically mean a workload is on a mainframe; discover the actual deployment environment before defining the programme as a mainframe exit. IBM’s February 2026 commentary.
The UK Government Digital Marketplace lists IBM United Kingdom Limited’s “IBM Mainframe Migration and Modernisation Services” under G-Cloud 14. Its service description covers advice, cloud migration and modernisation, rationalisation, quality engineering and testing, and security services; it does not specify Python conversion. Framework listings and availability can change, so check the live listing and scope when procuring. View the G-Cloud 14 listing.
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Mecanik’s June 2026 guide gives the following indicative estimates. They are publisher-provided figures, not independently verified UK market rates or quotes for a particular estate. The guide says the amounts include analysis, migration, testing and go-live support, but exclude ongoing operational costs, training and downstream integration work.
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| Project category in the guide | Indicative estimate from Mecanik, June 2026 |
|---|---|
| Small parallel rewrite | £80,000–£200,000 |
| Medium strangler-fig project | £200,000–£800,000 |
| Large automated/incremental project | £500,000–£2,000,000+ |
| Full mainframe decommission programme | £1,000,000–£10,000,000+ |
Use these ranges only as an initial discussion point. A credible estimate for a specific organisation requires discovery of its program and data dependencies, business-rule uncertainty, interfaces, test coverage, service obligations, target architecture and cutover plan. The figures should not be used as a cost-per-line formula or as a substitute for scoped estimates. Mecanik’s UK guide.
How long does a COBOL-to-Python migration take?
The cited UK guide provides cost ranges, not a defensible duration for a particular migration. Neither COBOL line count nor an automated translation rate is enough to predict a finish date: discovery, data conversion, dependency removal, validation, operational overlap and cutover all affect the schedule. Build a timeline after establishing service boundaries and test evidence, and stage commitments around demonstrated readiness rather than an assumed whole-estate conversion speed.
When should the programme pause or change course?
Revisit the approach if discovery reveals that a supposedly bounded component has undocumented business rules, unresolved data semantics, unknown dependencies or no representative tests. The same applies if generated code cannot be maintained confidently, parallel outputs cannot be reconciled, or measured performance misses the service requirement. These are programme decision points: reduce scope, improve evidence, change the replacement boundary or reconsider the target design before expanding the migration.
A compiler-version upgrade can also be considered separately from a language change when the need is to maintain or update the existing COBOL environment. IBM’s Enterprise COBOL for z/OS V6.5 Migration Guide is about compiler migration, not COBOL-to-Python conversion; consult IBM’s document directly before relying on its instructions. IBM Enterprise COBOL for z/OS 6.5 Migration Guide.
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