Mastering Delphi: A Step-by-Step Tutorial

Delphi Tutorial: Best Practices and Performance TipsDelphi remains a powerful choice for native Windows (and cross-platform) application development thanks to its fast native compilation, rich VCL/FMX component libraries, and mature tooling. This article collects practical best practices and performance tips for Delphi developers at intermediate to advanced levels: code organization, memory and resource management, compiler and linker settings, UI responsiveness, database access, multithreading, profiling, and deployment. Where appropriate I include concrete code examples and actionable checklists you can apply immediately.

1. Project structure and code organization

Well-structured projects are easier to maintain and optimize.

Keep interface files (.pas) focused: put public types, constants, and procedure signatures in the interface section; hide implementation details in the implementation section.
Prefer small, single-responsibility units. A unit that does one logical thing is easier to test and optimize.
Separate UI code from business logic (use MVC/MVP/MVVM patterns). This reduces dependencies and lets you optimize or replace layers independently.
Use explicit namespaces (unit scopes) in large projects to avoid ambiguous identifiers.
Use meaningful names and consistent naming conventions — they help maintainability and reduce bugs that become performance sinks.

Example structure:

Core units: data models, domain logic
Services: database access, file I/O, network
UI: forms, frames, presentation logic
Helpers: utility routines, shared small components

2. Compiler settings and build configuration

Optimizing compiler settings and build configurations yields immediate performance and size improvements.

Use Release builds for production. Release enables optimization and typically excludes debug data.
In Project Options → Delphi Compiler → Compiling:
- Enable Optimization.
- Disable Assertions (for release) to avoid runtime checks overhead.
- Disable Debug information in final releases to reduce binary size (or keep map files if needed).
In Project Options → Compiler → Linking:
- Enable Smart Linking to remove unused code.
- Consider building with Linker options that reduce size; keep map files for post-build debugging if required.
Use inlining selectively: the compiler’s inlining can speed up hot paths but may increase code size. Enable inlining for small, frequently called routines.
Set range checking and overflow checking off in release. These checks are useful during development but harm runtime speed.

3. Memory management and object lifecycle

Efficient memory use is crucial for responsive apps.

Use interfaces with reference counting (IUnknown/Interface) for many small objects where ownership is shared. This reduces manual free calls.
For objects with a single owner, use try..finally Free pattern or TObject.FreeInstance where appropriate. Example:
```
var MyObj: TMyObject; begin MyObj := TMyObject.Create; try   MyObj.DoWork; finally   MyObj.Free; end; end; 
```
Use TObjectList and TList (Generics.Collections) with OwnsObjects set appropriately to manage collections safely.
Avoid memory fragmentation by reusing objects (object pools) for frequently created/destroyed items, e.g., when frequently creating temporary buffers or UI elements.
For large memory buffers, prefer allocating once and reusing or use TMemoryStream.Realloc to minimize allocations.
Watch out for circular references with interfaces — use weak references or break cycles explicitly.

4. String handling and Unicode considerations

Delphi strings are Unicode (UTF-16). Misuse can introduce performance issues.

Avoid excessive string concatenation in loops. Use TStringBuilder for many small concatenations:


var sb: TStringBuilder; begin sb := TStringBuilder.Create; try   sb.Append('Hello');   sb.AppendLine(' World');   Result := sb.ToString; finally   sb.Free; end; end;

When processing large text data, consider using PChar/PWideChar pointers or TBytes with explicit encoding conversions for critical hot paths.
Use SetLength to preallocate string capacity when possible to avoid repeated reallocations.
Use Ansi strings (carefully) only if you must interoperate with legacy APIs and you measure a real benefit; modern code should work with Unicode.
For formatting many values into a string, measure Format vs. custom concatenation — Format is convenient but slower.

5. Database access and data binding

Database operations are often the biggest performance bottleneck.

Move heavy queries to the database server with proper indexing instead of loading and filtering in the client.
Use parameterized queries and prepared statements to improve performance and security.
For large datasets, use server-side paging or efficient dataset providers (e.g., FireDAC features: Array DML, Unidirectional datasets, FetchOptions).
Use FireDAC’s Array DML for bulk inserts/updates; it reduces round-trips.
Disable live data-aware control updates during batch operations. For example, call DataSet.DisableControls before updates and EnableControls after.
Limit dataset fields to only those you need (select specific columns).
Use cached updates and commit transactions in batches rather than per record.
Use caching mechanisms where appropriate (in-memory caches, TDictionary keyed caches) for frequently accessed static lookup data.
Avoid heavy client-side data binding when you only need occasional reads — read values into lightweight objects or records.

Example (FireDAC array DML):

FDQuery.SQL.Text := 'INSERT INTO MyTable (A, B) VALUES (:A, :B)'; FDQuery.Params.ArraySize := 100; for i := 0 to 99 do begin   FDQuery.Params[0].AsIntegers[i] := i;   FDQuery.Params[1].AsStrings[i] := 'Value' + i.ToString; end; FDQuery.Execute(FDQuery.Params.ArraySize);

6. UI responsiveness and VCL/FMX tips

Keeping the UI responsive requires minimizing work on the main thread.

Keep long-running operations off the main thread. Use TTask, TThread, or background services. Synchronize only when updating UI.
Use Application.ProcessMessages sparingly — prefer background tasks and progress reporting.
For heavy UI controls (virtual lists, grids), use virtual mode (owner-draw or virtual datasets) to avoid loading all items in memory.
Use DoubleBuffered for complex forms to reduce flicker, but only where helpful; it increases memory usage.
Minimize repaint area with InvalidateRect/RedrawWindow specifying rectangles when updating only parts of a control.
For FMX, reduce unnecessary style complexity and avoid expensive GPU-bound effects when not needed.
For lists/grids, reuse item controls (like TListView’s appearance adapters) rather than creating/destroying controls per item.

Example: simple background task with TTask

TTask.Run(   procedure   begin     DoLongTask;     TThread.Synchronize(nil,       procedure       begin         Label1.Caption := 'Done';       end);   end);

7. Multithreading and concurrency

Correct concurrency improves throughput but introduces complexity.

Design thread-safe units: protect shared resources with TCriticalSection, TMonitor, TMultiReadExclusiveWriteSynchronizer, or lock-free structures where appropriate.
Prefer message passing and immutable data to reduce locking.
Use thread pools (TTask / TThreadPool in newer RTLs) instead of creating threads for every job to avoid constant thread creation/destruction costs.
Keep UI access limited to the main thread. Use TThread.Queue or TThread.Synchronize for minimal UI updates.
Use reader-writer locks (TMultiReadExclusiveWriteSynchronizer) if your workload has many readers and few writers.
Avoid busy-wait loops; use events (TEvent) or semaphores to wait efficiently.
For high-performance concurrency, consider lock-free algorithms (InterlockedCompareExchange, TAtomic) for small critical sections.

8. Profiling and measuring performance

Measure before optimizing — profiling reveals real hotspots.

Use a profiler: AQtime, Sampling Profiler, or tools built into RAD Studio (Code Coverage & Profilers) to find hotspots.

Add lightweight timing instrumentation for specific functions using TStopwatch (System.Diagnostics).


var sw: TStopwatch; begin sw := TStopwatch.StartNew; DoWork; sw.Stop; Writeln('Elapsed ms: ', sw.ElapsedMilliseconds); end;

Profile memory usage to find leaks and fragmentation: use FastMM (with full debug mode during development) and enable its reporting.
Benchmark I/O, database access, and serialization independently. Often the costs are I/O-bound rather than CPU.
When you profile, run realistic workloads — synthetic microbenchmarks can mislead.

9. Algorithmic and data-structure optimizations

Better algorithms often trump micro-optimizations.

Use appropriate data structures: TDictionary for fast lookups, TList for ordered arrays, and TQueue/TStack for FIFO/LIFO behavior.
Prefer arrays or fixed-size buffers for hot loops to reduce heap allocations.
Avoid repeated computations; cache results (memoization) when inputs repeat frequently.
Consider record types instead of small objects for CPU cache friendliness in tight loops (records can be stack-allocated and avoid heap overhead).
Use pointer arithmetic only when necessary and safe; it can be faster but reduces readability.
Avoid unnecessary virtual method calls in hot paths — consider static/final methods or inline where appropriate.

10. I/O, file, and serialization performance

I/O often limits app performance — optimize carefully.

Use buffered I/O: TFileStream with appropriate buffer sizes, or use large Read/Write calls rather than many small ones.
Prefer memory-mapped files (TMemoryMappedFile on supported platforms) for very large files or random access patterns.
For serialization, choose binary formats when speed and size matter; use compact binary for internal data and JSON/XML for external interoperability only as needed.
When parsing text formats, use efficient parsers or incremental processing to avoid loading entire files into memory.
Use compression when storage or network I/O is the bottleneck, but measure CPU cost vs. bandwidth savings.

11. Networking and async I/O

Network latency and blocking calls cause perceived slowness.

Use asynchronous sockets or non-blocking frameworks (Indy supports asynchronous/tuned usage; better: platform-specific APIs or libraries that support asynchronous I/O).
Batch network requests where possible and avoid chattiness.
Use streaming APIs for large uploads/downloads. Save directly to files or streams instead of buffering entire content in memory.
Implement retries with exponential backoff for transient network errors.
Offload network tasks to background threads or tasks; update UI with progress via thread-safe mechanisms.

12. Final binary size and deployment

Smaller binaries load faster and update easier.

Use Smart Linking and remove unused packages and units.
Consider building critical parts as packages (BPLs) only if you share code across multiple apps — otherwise static linking simplifies deployment.
Strip debug info for release builds, or move debug symbol files to separate artifacts.
Use resource compression tools or installer-based compression to reduce download size.
For FMX cross-platform deployment, remove unnecessary platform units and styles.

13. Checklist: Quick wins to apply now

Build Release with Optimization and Smart Linking enabled.
Turn off range/overflow checks in Release.
Replace repeated string concatenation in loops with TStringBuilder.
Move long-running work off the main/UI thread (TTask/TThread).
Use prepared statements and server-side filtering for DB queries.
Disable dataset controls (DisableControls) during batch updates.
Use TStopwatch and a profiler to find real hotspots before optimizing.
Reuse large buffers and avoid frequent alloc/free cycles.

14. Example: Optimizing a slow list population

Problem: filling a TListView with thousands of items is slow and freezes UI.

Steps:

Use virtual mode or OwnerData to provide items on demand instead of adding all items.
Populate data in a background thread into a lightweight in-memory list (records).
When ready, call TThread.Queue to update the UI or set the virtual list’s record-count and let the control request items as needed.
Use BeginUpdate/EndUpdate or DisableControls/EnableControls to avoid repeated repaints.

Pseudo:

TTask.Run(   procedure   var     Data: TArray<TMyRec>;   begin     LoadData(Data); // heavy I/O & parsing     TThread.Queue(nil,       procedure       begin         ListView.Items.BeginUpdate;         try           ListView.Items.Count := Length(Data); // virtual mode         finally           ListView.Items.EndUpdate;         end;       end);   end);

15. When to rewrite vs. optimize

Optimize when hotspots are confined and measurable. Small targeted changes usually win.
Consider rewrite when the architecture prevents necessary changes (e.g., UI and business logic tightly coupled), or when legacy code is bug-ridden and hard to maintain.
Prefer incremental rewrites: refactor modules, introduce interfaces, and replace pieces gradually rather than large rewrites that risk regressions.

16. Resources and tools

Profilers: AQtime, Sampling Profiler, RAD Studio built-in tools.
Memory manager: FastMM (use in debug mode for leak detection).
Database: FireDAC (features like Array DML, Unidirectional datasets).
Concurrency: System.Threading (TTask), TThreadPool.
Tools: Wireshark (network), Process Explorer (resource usage), Windows Performance Analyzer.

17. Closing notes

Performance in Delphi apps is a combination of good architecture, correct use of RTL/Frameworks, efficient algorithms, and careful resource management. Measure, profile, and apply targeted optimizations. Small changes (use of background tasks, prepared DB statements, buffering) often produce the biggest user-visible improvements.