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  1. Freelancers

Vitaly Matsiborka

Reliable Plus holder
Offer Vitaly work on your next project.

Ukraine Mukachevo, Ukraine
currently online
Available for hire available for hire
15 Safes completed
16 days 18 hours back
14 clients
3 proposals made
age 48 years
on the service 8 years
Client profile
Freelancer Vitaly M. — Ukraine, Mukachevo. Core skill — Python, PHP

Rating

Successful projects
100%
Average rating
10 out of 10
Rating
2326
Python
43 place out of 4457
PHP
121 place out of 1676
7 projects
Python
4 projects
Online Stores & E-commerce
3 projects
PHP
2 projects
Databases & SQL

CV

Profile

A Strategic Solutions Architect with over 20 years of IT experience, spanning technology leadership, software development, and infrastructure design. I specialize in building intelligent automation systems that optimize business processes, integrate complex systems, and deliver measurable business value. After 15 years in management positions, I am returning to a hands-on architectural role to apply a unique blend of deep technical knowledge (Python, Django, Docker, API) and strategic business vision to solve the most complex challenges. My philosophy: "If a process can be automated, it must be automated."

Core Competencies

CategorySkills
Architecture & StrategySolution Design, Business Process Automation, IT Consulting, Requirements Analysis, System Integration, API Architecture, Stakeholder Management
Back-End DevelopmentPython, Django, FastAPI, PHP, Laravel, RESTful APIs, Microservices Architecture
Infrastructure & DevOpsDocker, VPS Management, CI/CD, Network Design and Configuration, Server Administration (Linux, Windows, Mac OS), Virtualization (Proxmox)
Databases & CRMPostgreSQL, MySQL, Redis, Deep knowledge of CRM implementation and integration
Emerging TechnologiesAI Agent Development, AI/ML Model Integration
Front-EndCurrently learning React for full-stack application development

Professional Experience

Head of IT / Lead Solutions Architect Private Practice / Consulting | [Approximate years, e.g., 2008 - 2024]

Led IT strategy and project implementation for clients across various industries. Combined the responsibilities of a technical leader, consultant, and lead developer to create comprehensive turnkey solutions.

Key Achievements and Responsibilities:

  • Automation System Design: Designed and implemented custom automation systems that reduced manual operation time by an average of 40% and minimized human error.

  • IT Infrastructure Architecture: Responsible for the full lifecycle of creating IT infrastructure for businesses: from network design and hardware selection to server configuration (Windows/Linux), virtualization, and deployment of containerized applications (Docker).

  • Complex API Integrations: Integrated disparate systems (CRM, ERP, Ajax alarm systems, Dahua video surveillance) via APIs to create a unified information space, enabling automated workflows and real-time analytics.

  • Technical Consulting: Acted as the principal technical advisor for clients, translating their business requirements into clear technical specifications and architectural plans.

Project Examples

1. Integrated Business Automation Platform

  • Problem: A client was dealing with fragmented data across their CRM, accounting software, and inventory management system, leading to inefficiencies and errors.

  • Architectural Solution: Designed a central automation core using Python/Django, which unified data from all systems via REST APIs. The solution was deployed in Docker containers on a VPS server, ensuring scalability and reliability.

  • Technologies: Python, Django, REST API, Docker, PostgreSQL, Linux (VPS).

  • Result: Created a single dashboard for monitoring business metrics, automated 90% of data synchronization tasks, and virtually eliminated reporting errors.

2. Proactive IoT-Based Monitoring System

  • Problem: The client required an automated response to events from security systems (Ajax alarm) and video surveillance (Dahua).

  • Architectural Solution: Developed an intermediary service (middleware) in Python (FastAPI) that received events from both systems' APIs. The service analyzed and correlated events, triggering automated scenarios: sending notifications, archiving video fragments, and creating incident log entries.

  • Technologies: Python, FastAPI, WebSockets, API Integration.

  • Result: Incident response time was reduced by 75%, and all event information began to be automatically collected in a unified audit report.

Additional Information

  • Legal Status: Registered as a Private Entrepreneur (3rd Group), which allows for flexible collaboration with international clients (including experience with Spain, Hungary, etc.).

  • Languages: Ukrainian (Native), Russian (Fluent), English (Proficient in reading technical documentation, actively improving).

  • Personal Attributes: A passion for technology and automation. A commitment to continuous learning and professional growth. Team-oriented and open to new challenges.

Skills and abilities

Programming

Services

Administration


Writing

Portfolio


  • 519 USD

    Maestro CRM Bot — Telegram Integration with KeyCRM

    Python
    Maestro CRM Bot — Telegram Integration with KeyCRM — example of freelancer's portfolio work in category Python
    **Status:** Production-ready | **Type:** Backend + Bot + Web Panel | **Team:** Solo

    Full-featured web application implementing Telegram bot integration with KeyCRM order management system. Customers can check balance, view orders, and receive notifications directly in Telegram.

    … ## Core Features

    **Telegram Bot (Aiogram 3.22)**
    - Automatic authorization via phone number
    - Real-time balance checking
    - Order history with pagination
    - Smart status change notifications
    - Interactive menus via Telegram buttons

    **Web Admin Interface**
    - Django Admin Panel for user management
    - User activity analytics
    - Balance calculation configuration
    - KeyCRM synchronization monitoring

    **Automation (Celery + Redis)**
    - Periodic data synchronization (every 5 minutes)
    - Background notification processing
    - Celery Beat scheduler for schedule management

    **Security**
    - Two-step phone authentication
    - HTTPS/SSL for all requests
    - Webhook token protection
    - Environment-based configuration

    ## Technology Stack

    **Backend:** Django 5.1.14 | Python 3.13 | PostgreSQL 16 | Redis 7

    **Bot & Async:** Aiogram 3.22 | asyncio/uvloop | httpx/aiohttp

    **Task Queue:** Celery 5.5.3 | Celery Beat 2.8.1

    **DevOps:** Docker | Docker Compose | Nginx | Gunicorn/Uvicorn

    **Quality:** Black | Flake8 | mypy | pytest (104 dependencies)

    ## Architecture

    ```
    bot/ → Telegram event handlers
    keycrm/ → REST API KeyCRM integration
    webhook/ → Incoming event processing
    config/ → Django config (local/production)
    docker-compose → Orchestration (web, bot, celery, db, redis, nginx)
    ```

    ## Key Capabilities

    1. **Real-time Synchronization** — REST API + Webhooks + Redis caching
    2. **Scalability** — async/await + Celery workers + microservice architecture
    3. **Reliability** — Health checks + structured logging + error tracking
    4. **Production-ready** — Docker/Compose + Nginx + SSL + migrations + static files

    ## Deployment

    **Local:**
    ```bash
    source venv/bin/activate && pip install -r requirements.txt
    python manage.py migrate && ./run_local.sh
    ```

    **Production (Docker):**
    ```bash
    docker-compose up -d && docker-compose exec web python manage.py migrate
    docker-compose exec web python manage.py collectstatic
    ```

    **Services:** db (PostgreSQL 16), redis (Redis 7), web (Gunicorn), bot (Aiogram), celery, celery-beat, nginx

    ## Metrics

    | Metric | Value |
    |--------|-------|
    | Lines of Code | ~3000+ |
    | Django Apps | 3 (bot, keycrm, webhook) |
    | API Endpoints | 15+ |
    | Tests/Coverage | 20+ tests / 65%+ |
    | Active Users | 100+ |
    | Daily Sync | 50+ orders |
    | API Response | < 200ms |
    | Uptime | 99.9%+ |

    ## Design Patterns

    MVC architecture | Factory Pattern | Observer Pattern | Singleton | Repository Pattern | Middleware logging

    ## Skills Demonstrated

    **Backend:** Django 5, PostgreSQL, REST API, async/await, Celery, distributed systems

    **Bot:** Telegram Bot API, interactive UI, state management

    **DevOps:** Docker, Docker Compose, Nginx, SSL/TLS, health checks, production deployment

    **Engineering:** Architectural design, Clean Code, Unit/Integration tests, Git workflows

    ## Requirements

    - Docker & Docker Compose
    - Python 3.13+ (local development)
    - 2GB RAM, 5GB disk space

    **Variables:** TELEGRAM_TOKEN, KEYCRM_API_KEY, DB_PASSWORD, DJANGO_SECRET_KEY, DEBUG=False

    ## Results

    ✓ Production-ready application ✓ 100+ active users ✓ Automatic synchronization ✓ < 200ms API response ✓ 99.9%+ uptime ✓ Horizontal scaling
  • 564 USD

    AI Voice Assistant for Mobile Operator

    AI & Machine Learning
    AI Voice Assistant for Mobile Operator — example of freelancer's portfolio work in category AI & Machine Learning
    ## About the Project

    Intelligent voice and text assistant for Ucell mobile operator (Uzbekistan), capable of consulting clients on tariff plans, answering frequently asked questions, and providing personalized recommendations based on user needs.

    … ## Challenges Solved

    - **Consultation Automation**: Reducing call center load through automatic responses to common questions
    - **Personalization**: Smart tariff selection based on user needs analysis (internet, calls, SMS)
    - **Multilingualism**: Full support for Russian and Uzbek languages
    - **24/7 Availability**: Round-the-clock operation without downtime

    ## Key Features

    **Voice and Text Interface**
    - Speech recognition and synthesis via Yandex SpeechKit with native voices for RU/UZ
    - Support for WebM, Opus, MP3 formats
    - Text chat for written communication

    **Intelligent Recommendation System**
    - NLP analysis of user requirements
    - Vector search across 50+ tariff plans database
    - Personalized recommendations based on needs

    **FAQ with Semantic Search**
    - Knowledge base: 29 Q&A in 13 categories
    - Vector search with 87-98% accuracy
    - Automatic vectorization of new FAQ
    - View statistics for popularity analysis

    **Advanced Admin Panel**
    - Tariff and FAQ management through user-friendly interface
    - Inline editing, question similarity testing
    - Detailed dialogue logs with time metrics
    - Request statistics visualization

    ## Technology Stack

    **Backend**: Django 5.2 (async), Django Ninja (REST API), PostgreSQL 16 + pgvector, Redis

    **AI & ML**: OpenAI GPT-4, Yandex SpeechKit (STT/TTS), sentence-transformers (multilingual-e5-large), pgvector (vector search)

    **DevOps**: Docker & Docker Compose, Gunicorn + Uvicorn, Nginx, Systemd

    **Additional**: django-unfold, FFmpeg, cryptography, httpx

    ## Technical Features

    **Asynchronous Processing**: Parallel STT, vector search, AI generation, and TTS work to minimize response time

    **Vector Search**: Semantic comparison with 0.7 threshold for FAQ, vector caching for acceleration

    **Contextual Dialogues**: Storing last 10 messages history, continuous dialogues with session_id, adaptive prompts

    **Analytics**: Time metrics for each stage, token counting, full request logging

    ## Results

    - Request processing: < 2 seconds for full cycle (STT → AI → TTS)
    - FAQ accuracy: 87-98% semantic search relevance
    - Coverage: 29 FAQ in 13 categories, 50+ tariff plans
    - Security: API tokens, data encryption (Fernet), CORS/CSRF protection, rate limiting
    - Production-ready: Docker containers, automatic migrations, health checks, SSL/TLS

    ## Achievements

    The project demonstrates deep understanding of modern AI/ML technologies, experience with vector databases, skills in creating high-load async systems and integrating complex external APIs (Yandex, OpenAI), knowledge of DevOps practices.

    ---

    **Technologies**: Python, Django 5.2, PostgreSQL, pgvector, Redis, Docker, OpenAI GPT-4, Yandex SpeechKit, NLP, Vector Search, REST API, Async/Await

    **Development Time**: 3 weeks | **Status**: Production-ready, actively used
  • 350 USD

    Intelligent Control System Development for Industrial Batteries

    AI & Machine Learning
    Intelligent Control System Development for Industrial Batteries — example of freelancer's portfolio work in category AI & Machine Learning
    Goal: Maximizing profit from electricity arbitrage on the "Day-Ahead Market" (DAM).

    Business Challenge

    … The client operated a SmartLogger 3000C01 industrial battery with a 400 kWh capacity but managed it manually. The objective was to create an automated system capable of:

    Analyzing hourly electricity prices on the DAM (Day-Ahead Market).

    Accounting for the facility's real-time power consumption.

    Creating an optimal charge/discharge schedule.

    Maximizing revenue from electricity sales.

    Technical Implementation

    Tech Stack:

    Core: Python 3.x (Flask, SQLite)

    AI: Google Gemini AI API (gemini-2.0-flash-exp)

    Integrations: SOAP API (SmartLogger), REST API (OREE - Energy Market), Excel Parsing

    Automation: Cron

    System Architecture:

    1. Data Collection Module:

    Integration with OREE API to fetch DAM prices for the next day.

    Parsing historical consumption data from Excel (KWT.xls).

    Reading current battery status via SmartLogger SOAP API.

    2. AI Optimizer (System Core):

    Development of a specialized prompt for Gemini with a step-by-step algorithm.

    Analysis of a 24-hour window considering:

    Hourly prices (UAH/kWh).

    Forecasted facility consumption.

    Technical constraints (charge/discharge rates).

    ROI threshold (minimum margin of 3 UAH/kWh).

    Support for multi-cycle optimization (morning + evening peaks).

    Adaptive discharge based on actual consumption.

    3. Execution Module:

    Automatic schedule execution via SOAP API.

    Hourly monitoring and adjustment.

    Operation logging and Telegram status notifications.

    4. Web Interface (Flask):

    Dashboard with performance visualization.

    Operation history, profit stats, system configuration, and access control.

    Results

    Technical Achievements:

    Increased Discharge Hours: From 2 to 10 hours per day.

    Profit Growth: 11% increase (from 2,874 to 3,198 UAH/day).

    Automation: 100% of routine operations automated.

    Forecast Accuracy: 95%+.

    Economic Impact:

    Projected Monthly Profit: ~96,000 UAH.

    System ROI: Payback period of 2–3 months.

    Time Savings: 2–3 hours saved for the client daily.

    Key Technical Solutions

    AI Integration: Custom prompt engineering, JSON Mode for guaranteed response structure, and fallback mechanisms for AI unavailability.

    Consumption Optimization: Analysis of historical data from the previous week and consideration of the facility's daily work schedule.

    Reliability: Retry mechanisms for API requests (up to 10 attempts) and backup scenarios for connection failures.

    Automation: Cron jobs for daily forecasting (00:00) and 24/7 continuous operation.

    Implementation Complexity: SOAP/REST integrations, dynamic programming algorithms, production deployment (SSH, Linux). Uniqueness: Hybrid approach (AI + Business Logic), adaptability to real-time consumption rather than theoretical maximums, production-ready autonomy.

    Skills Applied: Python, AI/ML Integration, Google Gemini API, SOAP/REST API, Flask, SQLite, Cron, Automation, Excel Parsing, Production Deployment, Linux Administration, Algorithm Optimization, Data Analysis, Industrial IoT.

    Duration: 2 weeks | Role: Full-stack Developer + AI Integration | Status: Live in production, autonomous
  • 500 USD

    Time Tracker for Mac OS

    Python
    Time Tracker for Mac OS — example of freelancer's portfolio work in category Python
    # MTimer — Native Time Tracker for macOS

    ## About the Project

    … A fully functional native application for time tracking on macOS. Developed using PyObjC (AppKit) and SQLite, it demonstrates a deep understanding of the Apple ecosystem and the creation of professional desktop applications in Python.

    **Key Achievements:**
    - 100% native UI through AppKit without web technologies
    - Universal binary (x86_64 + arm64) ready for distribution
    - Multilingual support with automatic detection of system language (UK/EN/RU)
    - Production-ready architecture with clean separation of logic

    ## Technical Stack

    **Base:** PyObjC (AppKit), SQLite, py2app
    **Patterns:** MVC, Singleton, Observer, State Management
    **UI:** NSTableView, NSStatusBar, NSAlert, NSUserNotificationCenter

    ## Core Functionality

    **Time Management**
    - Smart Timer with automatic session splitting at midnight
    - Period filters (Today/Week/Month) with real-time aggregation
    - Dynamic cost calculation based on hourly rates
    - Automatic recovery of active session after restart

    **User Experience**
    - Adaptive design with support for light/dark theme
    - Keyboard shortcuts (⌘ for Settings, Delete for removal)
    - Native notifications when starting/stopping tracking
    - Menu Bar App with live timer and quick task switching

    **Data Management**
    - CRUD operations with projects and hourly rates
    - Editing through a separate Settings window
    - Safe deletion with NSAlert confirmation
    - Real-time sync UI and menu bar upon data changes

    ## Technical Challenges

    **1. Keyboard Handling in NSTableView**
    Created `DeletableTableView` subclass with overridden `keyDown_` for Delete key, using `objc.super()` for proper interaction with Objective-C runtime.

    **2. UI Synchronization After Editing**
    Implemented a callback system preserving selection through project_id, refreshing all components (table, status bar, filters) simultaneously.

    **3. Localization in Compiled App**
    Used `NSLocale.preferredLanguages()` instead of locale module with fallback chain for maximum compatibility.

    **4. Application Lifecycle**
    Overrode `windowShouldClose_` with `orderOut_`, `setReleasedWhenClosed_(False)` and `applicationShouldHandleReopen_` for correct hide/show behavior.

    ## Results

    ✓ Stable production-ready application without crashes
    ✓ Support for Intel Mac and Apple Silicon
    ✓ Minimal footprint (~50MB standalone)
    ✓ Instant UI response
    ✓ Fully documented code

    ## Skills Acquired

    - **macOS Development:** AppKit framework, NSStatusBar/NSMenu/NSTableView, system events handling, multi-window coordination
    - **Python Advanced:** PyObjC bridging, Objective-C runtime interaction, py2app packaging, code signing
    - **Database:** SQLite optimization, aggregate queries, transaction management
    - **Software Engineering:** i18n best practices, UX design for desktop, error handling, version control

    ---

    **GitHub:** https://github.com/maciborka/MTimer
    **Stack:** Python 3.12, PyObjC (AppKit), SQLite, py2app
    **Platform:** macOS 12+ Universal (x86_64 + arm64)
    **License:** MIT
  • 2000 USD

    Mini-CRM

    Python
    Mini-CRM — example of freelancer's portfolio work in category Python
    Mini-CRM: A Custom System for Automating Record-Keeping and Deal Management
    This project is a fully custom CRM system, built from scratch for the effective management of personal business processes. The main goal was to create a unified, flexible, and high-performance tool for managing a client base, tracking deal stages, controlling financial flows, and automating routine document workflow.

    Key Capabilities and Features
    …
    The system combines several powerful modules that cover the full client work cycle:

    Financial Dashboard: The main screen provides a clear summary of key business indicators: Income, Expenses, Taxes, and Balance for the selected period. An interactive "Annual Trend" graph and an "Expense Distribution" chart (as seen in the screenshot) allow for an immediate assessment of the financial status.

    Deal Management (Sales Pipeline): A full-fledged sales pipeline is implemented, where each deal progresses through customizable stages (e.g., "Inquiry / Signed," "Act / Signed," "Received / Paid"). This provides a clear visual representation of the current state of all projects.

    Bank Integration (PrivatBank): The CRM automatically fetches and recognizes transactions from Privat24. This eliminates the need for manual data entry and allows linking a real payment to a specific invoice or deal in one click.

    Document Workflow Automation: The system allows for the generation of invoices (Рахунки) and acceptance acts (Акти) based on deal data and the service catalog. Most importantly, the document can be instantly sent to the client's e-mail directly from the CRM interface, which radically saves time.

    AI and Telegram Integrations: A built-in Telegram bot is used for real-time notifications about new deals, payments, or status changes. AI modules assist with analytics and automation (e.g., in classifying expenses or forecasting).

    Product and Service Catalog: A hierarchical "Product and Service" directory allows for inventory management, recording both purchase and selling prices, which simplifies invoice creation and profitability calculation.

    Tech Stack

    One of the key features of the project is its modern and lightweight technology stack, ensuring high interface speed:

    Backend: Python (Django) for all business logic, APIs, and integrations.

    Frontend: htmx for creating a dynamic and "reactive" interface without full page reloads, making work in the CRM fast and smooth.

    Deployment: Docker for application containerization, ensuring easy deployment, scaling, and environment isolation.

    Integrations: PrivatBank API, Telegram Bot API, AI services.

    Result
    The result is a powerful personal tool, fully adapted to specific business processes. It automates routine tasks, provides full control over finances and deals, and consolidates all key data in one place.
  • 100 USD

    Domain-Gem

    Python
    Domain-Gem — example of freelancer's portfolio work in category Python
    Smart utility for automatic search and verification of domain name availability using Google Gemini AI.

    Capabilities

    … AI-generated domains: Uses Google Gemini to create creative domain names.
    Availability check: WHOIS real-time domain availability check.
    Automatic logging: Saves results to available.txt and taken.txt files.
    Duplicate filtering: Automatically excludes already checked domains.
    Interactive mode: Chat interface for creating domains based on arbitrary queries.
    Flexible authorization: Supports API keys and Service Account.
    Statistics: Detailed reporting on checked domains.
    ProcessSniper: Proper management of processes and threads (safety when pressing Ctrl+C).
    Customizable requirements: Full customization of domain requirements through config.py.
    Prompt viewing: Ability to see the exact prompt sent to Gemini AI.
  • 451 USD

    Cloudflare-Firebase Sync — Subdomain Automation System

    Python
    Cloudflare-Firebase Sync — Subdomain Automation System — example of freelancer's portfolio work in category Python
    Production-ready system for automatic creation and management of subdomains with Cloudflare DNS and Firebase Remote Config integration. Solves issues of fault tolerance, scalability, and infrastructure automation.

    Key Features

    … Function Description Technologies
    Batch Creation Simultaneous creation of multiple subdomains Python, Cloudflare API
    Auto-Rotation Automatic rotation and cleanup on schedule Cron, SQLite
    Multi-Firebase Publishing to multiple Firebase projects Firebase Admin SDK
    Round-Robin Fair distribution among domains Custom Algorithm
    Monitoring Detailed logging and metrics Python Logging
    Technical Stack

    Backend: Python 3.12, SQLite

    APIs: Cloudflare API, Firebase Admin SDK

    DevOps: Cron, Shell Scripting, Git

    Testing: Unit Tests, Integration Tests

    Patterns: Batch Processing, Multi-tenant, Modular Architecture

    Performance Metrics

    Creation of 1 subdomain: 8 seconds

    Batch (3 subdomains): 15 seconds

    Process acceleration: 10x compared to manual creation

    Uptime: 99.9% due to failover

    Cost reduction: 60% on operations

    Architectural Innovations

    Batch Processing:

    Python
    # Simultaneous creation of N subdomains
    SUBDOMAINS_BATCH_SIZE = 3
    subdomains = ["abc.domain1.com", "def.domain2.com", "xyz.domain3.com"]
    Multi-Firebase Publication:

    JSON
    {
    "reserve_urls": [
    "https://abc.domain1.com/api/",
    "https://def.domain2.com/api/"
    ]
    }
    Smart Round-Robin:

    Python
    # Intelligent load balancing
    domain = domains[index % len(domains)]
    Quality and Testing

    100% test coverage of critical functionality

    Complete documentation and API reference

    PEP 8 compliance and type hints

    CI/CD readiness with automated scripts

    Business Applications

    Addresses issues:

    Failover for high-load systems

    A/B testing and canary deployments

    Geographical load distribution

    Automatic scaling of infrastructure

    Results:

    Zero-downtime during failures

    3x increase in throughput in batch mode

    60% savings on operational costs

    Seconds instead of hours for deployment

    Demonstrated Skills

    Field Skills
    Backend REST API integration, Database design, Error handling
    DevOps Process automation, Configuration management, Monitoring
    Architecture Modular design, Scalability, Multi-tenant systems
    Quality Unit testing, Documentation, Code standards
    Value for Portfolio

    Production-ready solution with real-world application

    Modern technologies and cloud services

    Scalable architecture for enterprise-level

    Full automation with performance metrics

    Comprehensive testing and documentation

    Project Structure

    cloudflare-firebase-sync/
    ├── modules/ # Modular architecture
    │ ├── cloudflare_api.py # Integration with Cloudflare
    │ ├── firebase_api.py # Firebase Remote Config
    │ └── database.py # SQLite operations
    ├── test/ # Comprehensive testing
    │ ├── test_batch_workflow.py
    │ └── test_integration.py
    ├── main.py # Main workflow
    ├── config.py # Configuration system
    └── docs/ # Technical documentation

    Key feature: Batch mode for creating subdomains with publishing to multiple Firebase.
    Result: Fully automated system with 99.9% uptime.

    The project demonstrates the ability to create enterprise-grade solutions for automating cloud infrastructure.
  • 451 USD

    Integration of KeyCRM with BigQuery for e-commerce

    Python
    Integration of KeyCRM with BigQuery for e-commerce — example of freelancer's portfolio work in category Python
    Automated system for importing, processing, and analyzing orders from an online store with integration of KeyCRM and Google BigQuery.
    Full synchronization of orders, products, payments, custom fields, and marketing data has been implemented.
    Data from KeyCRM undergoes cleansing, normalization, linking with additional entities, and is exported to BigQuery for report generation, analytics, and BI.

    … Key features:

    Import of orders, products, customers, managers, payments, and marketing data from KeyCRM via OpenAPI.

    Processing of custom fields of orders (custom_fields) with support for values for each order.

    Storage and updating of data in MySQL (Django ORM) with support for migrations and idempotent logic.

    Export of orders to Google BigQuery with automatic creation and updating of the table schema.

    MERGE operations for UPSERT in BigQuery: new and updated orders are synchronized without duplication.

    Local mirror of orders for quick analytics and data reconciliation.

    Support for complex relationships: products in an order, custom reasons for cancellation/exchange/return, manager comments.

    Django admin panel with convenient viewing and editing of all entities.

    Technologies:

    Python 3.12, Django 5.x, MySQL, Google BigQuery, REST API (KeyCRM), Celery, Docker.

    Full support for migrations, idempotent updates, transactions.

    Logging, error handling, automated tests.

    Result:

    The system allows the business to obtain up-to-date, clean, and structured data about orders for analytics, reporting, and BI, automate export to the cloud, track reasons for returns/cancellations, and generate reports based on custom fields and marketing channels.
  • 250 USD

    Vanity Crypto Address Generator

    Python
    Vanity Crypto Address Generator — example of freelancer's portfolio work in category Python
    High-performance generator of personalized crypto addresses
    Project Description
    Developed an advanced generator of beautiful (vanity) addresses for cryptocurrencies with maximum performance optimization. The system allows creating personalized crypto addresses with specified prefixes or suffixes for major blockchain networks.

    … Technical Specifications
    Supported blockchains:

    Bitcoin (BTC) - P2PKH addresses
    Ethereum (ETH) - standard addresses
    TRON (TRX) - native addresses
    Litecoin (LTC) - P2PKH addresses
    Dogecoin (DOGE) - P2PKH addresses
    Architecture and technologies:

    Python 3.8+ with multiprocessing architecture
    Maximum CPU usage - up to 100% load of all cores
    Optimized cryptographic libraries: secp256k1, web3.py, eth-account
    Performance: 100,000+ addresses per second on modern hardware
    Key Features
    Dual-mode operation:

    Single search for quick tasks
    Batch mode with CSV configuration files
    Intelligent system:

    Automatic assessment of complexity and search time
    Priority system for batch execution
    Warnings for long-term tasks
    Usability:

    Automatic saving of results in CSV
    Organized file structure
    CLI interface with detailed help
    Security:

    Cryptographically secure key generation
    Local processing without network requests
    Secure storage of private keys
    Technical Implementation
    Performance optimizations:

    Multiprocessing instead of threading (bypassing Python's GIL)
    Lock-free architecture with local counters
    Caching of cryptographic operations
    JIT compilation of critical sections
    Code structure:

    Modular architecture with separate network modules
    Abstract base class for extensibility
    Optimized dependencies (only necessary libraries)
    Comprehensive error handling and logging
    Results and Metrics
    Performance: Up to 100,000+ addresses/sec on multi-core systems
    Support: 5 major cryptocurrencies
    Operating modes: Single and batch search
    Automation: Configuration files for bulk tasks
    Reliability: Complete error handling and graceful termination
    Technologies Used
    Languages: Python 3.8+
    Cryptography: secp256k1, hashlib, secrets
    Blockchain: web3.py, eth-account, base58
    Architecture: multiprocessing, concurrent.futures
    CLI: argparse, rich formatting
    Data: CSV, JSON, structured logging
    Application
    The project is in demand for:

    Creating branded crypto addresses for companies
    Generating memorable addresses for personal use
    Mass creation of themed addresses
    Research tasks in the field of cryptography
    Project Achievements
    Maximum optimization: Utilizing all available CPU cores
    Scalability: From single tasks to batch processing of hundreds of jobs
    Production readiness: Complete error handling and security
    Documentation: Detailed technical description and usage examples
    This project demonstrates deep knowledge of cryptography, performance optimization in Python, and the creation of production-ready tools for blockchain development.
  • 147 USD

    Deploy a terminal Windows Server

    System & Network Administration
    Technical Specification:
    Deploy a terminal Windows Server with a VPN server for access.

    It was decided to use the cloud provider Gigacloud. Based on their technology, an infrastructure with a virtual machine Windows Server 2016 and MikroTik was deployed. In MikroTik, an L2TP VPN was created and a network infrastructure was built. This protected the Windows Server from external threats.
    … A daily backup was also configured.
  • 451 USD

    Backend system.

    Python
    Backend system. — example of freelancer's portfolio work in category Python
    The client tasked us with creating a system that would extract data from the KeyCRM system via API. All data must be stored in a database and, after processing, sent to Google Sheets using an API.

    Python, combined with the Django framework, was proposed for the project implementation. Celery and Redis were used to automate the data sending process. Restrictions on the frequency of requests to KeyCRM and Google were considered, ensuring the system does not exceed set limits and avoids blockages. The frequency of server queries can be adjusted via the administrative panel. This phase of the work was completed in the shortest possible time.

    … Despite the rapid development, the project was designed to allow for scalability and enhanced functionality.

    The client suggested moving to a permanent collaboration, which prompted the modernization of the product and the expansion of its functionality beyond the initial technical specifications. It was proposed to create a unified order receiving system with the ability to accumulate client information and protect against fraud. A user verification system through reCAPTCHA was integrated. Thanks to a unified data processing system across all landings, the implementation of new sales points takes minimal time.

    The system continues to function and is maintained. The implementation of new functionalities occurs within a matter of hours.

    Currently, a system for accumulating client geo-data using external services has been implemented. This information is sent in real-time to KeyCRM, the database, and email with each new order.

    There are currently more than 30 landings.
  • 113 USD

    An example of a bot

    Python
    An example of a bot that conducts a survey of a job candidate. The bot asks questions and receives answers from the user. All data is stored in a database. The owner of the bot has the ability to add or delete questions and answer options!
  • 466 USD

    Bot Development

    Python
    Bot Development — example of freelancer's portfolio work in category Python
    Bot Development for a Major Company: A unique bot was developed to inform employees at an enterprise. The program is integrated with various information sources and is capable of sending notifications to employees automatically, either on a schedule or upon request. Features of the bot include alerts about unauthorized vehicle entry onto the premises, sending reports on employees' arrival at work, and the ability to search information by vehicle number and employee surname. Technologies used in this project include Python, Celery, Redis.
  • 113 USD

    The online shop.

    Web Programming
    The online shop. — example of freelancer's portfolio work in category Web Programming
    Services for the optimization and configuration of the website for electronic commerce:

    Correction of errors on the site: Fast and efficient removal of technical and functional faults to ensure the stable operation of the site.
    Including online sales possibilities: Activation and setting all the necessary functions to carry out sales through the internet.
    … Re-set the catalogue of goods: Full creation and configuration of the list of goods, including detailed description, values and photos.
    E-commerce settings: Full integration and configuration of the e-commerce system, including the shopping cart, methods of payment and delivery.
    Activation notified to customers and employees: Set up automatic notifications about the status of orders for customers and notified to employees about new orders and changes.
    Consultations on the site: Training and providing recommendations to customers on the use and management of the site, including content management, order processing and analytics.
  • 291 USD

    Charitable Fund

    Web Programming
    Charitable Fund — example of freelancer's portfolio work in category Web Programming
    Website based on wix
Show more 13 jobs

Reviews and compliments on completed projects 15

  • Real expert
  • Craft master
  • Quick answers
  • First-class quality
  • Nice communication
  • High responsibility
  • Great price
  • Lightning fast

18 May 34 USD
Set up a fiscalization trigger in KeyCRM

Quality
Professionalism
Cost
Contactability
Deadlines

As always, everything is clear, fast, and somewhat proactive. I recommend Vitaliy for collaboration.

Dmitro Fedorenko | Personal | Response review

22 January 34 USD
Set up post-payment control triggers and fiscalization in KeyCRM

Quality
Professionalism
Cost
Contactability
Deadlines

The task was completed with quality, understanding, and consultation. I recommend this specialist for involvement in projects with payment system integrations, CRM, and fiscalization services.

Dmitro Fedorenko | Safe Safe | Response review

26 November 2025 16 USD
Project consultation

Quality
Professionalism
Cost
Contactability
Deadlines

Andrey consulted very professionally on all the questions that interested us. He explained the complex points in detail and gave recommendations for further work on our project. I can only recommend him as a competent programmer. I look forward to further cooperation.

Natalya Shurdukova | Safe Safe | Response review

16 November 2025 19 USD
Consultation on the 1C project analyst

Quality
Professionalism
Cost
Contactability
Deadlines

The tasks within the project were completed in full. The specialist knows their business.

Pavel Zinchenko | Personal | Response review

15 November 2025 16 USD
Consultation

Quality
Professionalism
Cost
Contactability
Deadlines

Everything is great, professionally explained some points. Let's keep working.

Vlas Zubenko | Personal | Response review

12 November 2025 338 USD
Integration of TouchDesigner with automatic parsing of physiological data and transmission via OSC

Quality
Professionalism
Cost
Contactability
Deadlines

Competence and full immersion in the task with a quick resolution.

Dmitriy Kotelenets | Safe Safe | Response review

25 October 2025 29 USD
Need an experienced PHP programmer who can understand someone else's code for long-term collaboration.

Quality
Professionalism
Cost
Contactability
Deadlines

All done in the best possible way

Yury Romanovsky | Safe Safe | Response review

7 October 2025 226 USD
Setting up order export from CMS Wezom (Laravel) to CRM SalesDrive

Quality
Professionalism
Cost
Contactability
Deadlines

Maximum positive feedback and sincere recommendation for collaboration with Vitaliy!

The project was completed on time (three times faster than stated), within the agreed budget (there was a "risk" of price increase due to "difficulties" discovered during the project execution, but in the end, this did not happen, for which a special thank you).
Communication - instant, structured.
Action plan - written down, discussed (even the existence of a Plan B in case of failure with A is outlined).
Plan A worked - everything is done, everything works - bliss 🙂

Such work is very well described by the phrase "on spec, on time, on budget."
It is a pleasure to work with a specialist of this level - top class.

If needed, we will definitely reach out again.
Thank you.

Oleksii Oleksii | Safe Safe | Response review

23 September 2025 68 USD
Set up automatic invoicing of receipts in salesdrive via checkbox upon receiving cash on delivery.

Quality
Professionalism
Cost
Contactability
Deadlines

The work was done quickly and efficiently. There were some nuances on our side, the contractor thoroughly understood and explained everything. I recommend for collaboration!

Yury Kovalchuk | Safe Safe | Response review

17 September 2025 451 USD
Script for working with Cloudflare DNS API and Firebase Remote Config API

Quality
Professionalism
Cost
Contactability
Deadlines

Excellent task completed on time and in accordance with all details of the technical assignment.

Ilya Sv | Safe Safe | Response review

6 September 2025 79 USD
Set up AI to improve texts, headlines, and images for ads

Quality
Professionalism
Cost
Contactability
Deadlines

Everything is quite good. Thank you!

Andrey Vernidub | Safe Safe | Response review

16 July 2025 45 USD
Publication of Laravel + Reverb on hosting.

Quality
Professionalism
Cost
Contactability
Deadlines

Excellent performer. I recommend working with him, the person not only completed the task but also explained how and what works. So 10/10.

Andriy R | Safe Safe | Response review

22 February 2024 14 USD
Help identify real IP in POST API queries

Quality
Professionalism
Cost
Contactability
Deadlines

The task is done quickly. The result is satisfied.

Kostyantin Pivnenko | Safe Safe | Response review

26 December 2023 34 USD
Make-up on the WIX website

Quality
Professionalism
Cost
Contactability
Deadlines

I am very grateful to Vitaly for the work done. It was worked so that the goods came into the basket, as it was necessary in the task. The work was done quality and mainly fast, which was very important for me.

Yuliia Ivaniuta | Safe Safe | Response review

16 December 2023 45 USD
Исправить ошибку в скрипте или на сервере

Quality
Professionalism
Cost
Contactability
Deadlines

Everything is done clearly and quickly, I recommend the work.

Artem Grishin | Safe Safe | Response review

Activity

  Latest proposals 10
Freelance project
Freelance project
Report in Telegram on the crossing of lines by DAhua video surveillance cameras Personal project
194 USD
Development of an MVP AI service for preparing scientific texts Personal project
Development of an MVP AI service for preparing scientific texts
25 USD
Backend Developer
170 USD
Set up a fiscalization trigger in KeyCRM Personal project
34 USD
Scrape and upload calculators Personal project
226 USD
Freelance project
90 USD
Freelance project