I tested the 6 Best AI for Python coding 

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February 5, 2025
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11 min read
6 Best AI for Python coding 

Let me tell you about the week I spent testing AI coding assistants because, honestly, debugging Python at 3 AM gets old real fast. After 15 years of coding Python (and consuming concerning amounts of coffee), I decided to put the top AI coding assistants through their paces.

See, here's the thing - we've all been there. You're staring at a stubborn bug, your Stack Overflow searches are coming up empty, and you're wondering if maybe you should've become a goat farmer instead. That's where these AI coding buddies come in clutch.

I tested six different AI assistants, putting them through everything from basic "Hello World" hand-holding to "Oh god, why is this recursive function eating all my RAM?" scenarios. Some impressed me, others... well, let's just say they might need a few more training epochs.

The best part? These AI tools aren't just glorified autocomplete - they're like having a senior developer looking over your shoulder, minus the judgmental sighs when you forget to close your parentheses.

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Ready to find out which ones actually delivered and which ones just made me reach for more coffee? Let's dive in..

Key takeaways 

  • An overview of 6 Best AI for Python coding, including their features, limitations, strengths and weaknesses, and pricing tiers.
  • Ways that AI has transformed how developers write, debug, and optimize Python code, making programming more efficient and less time-consuming.
  • The various AI tools available for Python coding range from free plans suitable for budget-conscious beginners to premium solutions designed for advanced developers and teams for specialized tasks.
  • AI tools offer features for different coding stages, such as error debugging, code generation, and code suggestions, allowing developers to choose what aligns with their specific challenges and goals.
  • Leveraging the best AI for Python coding helps developers focus more on creative problem-solving and innovation, as AI easily handles repetitive or demanding tasks.

6 best AI for python coding 

  1. GitHub Copilot
  2. Tabnine
  3. OpenAI Codex
  4. Deepcode AI  
  5. BitoAI
  6. Amazon CodeWhisperer 

GitHub Copilot

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Developed by GitHub and OpenAI, GitHub Copilot is an AI-powered coding assistant designed to enhance developer productivity by providing intelligent code suggestions and automating various coding tasks. 

Feature Description 
Code CompletionOffers real-time code suggestions, predicting you'd likely type next.
Contextual UnderstandingDraws context from the coding environment, including open tabs and project repositories, to provide relevant suggestions.
Multi-Language SupportSupports various programming languages, making it versatile for different coding tasks.
In-line Code SuggestionsProvides coding suggestions directly in the IDE, helping with boilerplate code and complex functions.
Copilot pull request summariesAI-generated summaries outline pull request changes, impacted files, and key review focus areas for reviewers.
Boilerplate Code GenerationGenerating boilerplate code, which can be tedious to do manually.
Integration Integrated into tools like Visual Studio, JetBrains IDEs, Azure Data Studio, Xcode, and Vim/Neovim). 
Copilot Chat A chat interface lets you ask coding-related questions and ask Copilot to provide command suggestions or explanations of commands.

Pricing Tier

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TierDescription Cost
Free Copilot Chat in GitHub2000 completions per month50 messages per month$0
ProBlock suggestions matching public code Copilot pull request summaries Copilot Chat skills in IDEs
Copilot Chat in Windows Terminal Copilot in the CLI
$10
Business Organization-wide policy management Audit logs Increased GitHub Models rate limits4$19 per user/month
Enterprise 2000 completions per month50 messages per monthFine-tuning a custom large language model
Audit logs Increased GitHub Models rate limits Copilot knowledge bases
Organization-wide policy management Audit logs Increased GitHub Models rate limits
$ 39 per user/month

Best For 

  • All levels of developers, particularly those who work with multiple programming languages

Limitations 

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  • Still requires thorough review and testing by developers
  • over-dependence on AI suggestions instead of manual brainstorming 

Pros

  • Integration with popular IDEs
  • Help with learning programming languages
  • Accessibility for solo developers
  • Efficiency in boilerplate code generation

Tabnine

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Tabnine is an AI-powered code completion tool that writes code more efficiently and accurately. It uses machine learning algorithms to predict and suggest the following line of code based on the context of the project, the programming language, and the developer's coding style.

Feature Description 
AI-Powered Code CompletionOffers context-aware code suggestions as you type, improving coding speed and accuracy.
Code Refactoring Tabnine suggests improvements to the code, such as simplifying complex expressions or reducing duplication
Integration with IDEsSeamlessly integrates with popular IDEs such as Visual Studio Code, IntelliJ IDEA, and PyCharm.
Local Model OptionProvides a local AI model for offline use, enhancing security and privacy.
Customizable AI ModelsAllows users to create personalized AI models based on their coding style and preferences.
Error DetectionIdentifies potential errors in the code and suggests fixes to improve quality.
Multi-Language SupportCompatible with various programming languages, including Python, JavaScript, Java, and more.

Pricing Tier 

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TierDescription Cost
BasicAI code completions for current line and multiple lines for full-function implementationAI-powered chat using leading LLMs from Anthropic, OpenAI, and Tabnine  (some limits apply)Support for all major IDEs$0
Enterprise IP indemnificationIntegration with Atlassian Jira to inform AI responses and generationAdmin tools for tracking usage and user productivity$39 per user/month

Best For 

  • Developers looking for intelligent code completion

Limitations

  • Limited Free Plan
  • Dependence on the Internet for full features
  • Steep learning curve

Pros

  • Time management 
  • Strong privacy focus
  • Flexible Integration
  • Customizable coding pecks 

Cons

  • Expensive for advanced features
  • Dependence on user input for quality suggestions

OpenAI Codex

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OpenAI Codex is an advanced AI model developed by OpenAI, specifically designed to assist with coding tasks by generating code snippets, completing code, and even translating natural language into code. 

Feature Description 
Natural Language to CodeTranslates natural language queries into code snippets across various programming languages.
Code CompletionProvides intelligent suggestions for completing partial lines of code or entire functions.
Multi-Language SupportSupports multiple programming languages including Perl, Go, PHP, JavaScript, TypeScript, Ruby, and more.
Integration with ToolsCan be integrated into popular development environments and tools like GitHub Copilot.
Contextual UnderstandingAnalyzes existing code to provide relevant suggestions based on the project context.
Error DetectionIdentifies potential issues in the code and suggests fixes to improve code quality.

Pricing Tier 

Accept tokens as against currency denomination 

Best For

  • Developers interested in natural language processing capabilities

Limitations

  • Fluctuating token-based costs
  • Context limitation 
  • Dependency on Internet access

Pros

  • Enhanced productivity
  • Versatile functionality
  • Rich Integration options 
  • Continuous updates 

Cons

  • Variable quality of suggestions
  • Steep learning curve

DeepCode AI

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DeepCode is an AI-powered code review tool that enhances code quality and security by providing real-time analysis and suggestions. 

Feature Description 
Real-Time Code AnalysisScans code as it is written, flagging potential issues immediately.
AI-Powered SuggestionsProvides context-aware suggestions for fixing identified issues.
Security Vulnerability DetectionDetects security vulnerabilities such as SQL injection risks and buffer overflows.
Multi-Language SupportSupports languages including Java, Python, JavaScript, TypeScript, and C++.
Integration with ToolsSeamlessly integrates with platforms like GitHub, Bitbucket, and GitLab.
Continuous LearningLearn from new data to improve detection capabilities over time.
Free for Open Source ProjectsAvailable at no cost for open-source projects to encourage community use.

Pricing Tier 

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Price TierDescription Cost
FreeLimited tests per product$ 0
Team Minimum of 5 contributing developers, up to 10
Products priced separately
Open-source license compliance
Jira integration
$ 25
Enterprise Jira integration
Rich API
Reports
Custom user roles
Security policy management
Application asset discovery
$ Customized upon request 

Best For 

  • Software developers 
  • Companies focused on code quality
  • Open source contributors 

Limitations

  • May occasionally flag non-issues as problems
  • Lacks complete understanding of project-specific nuances; human reviewers are still necessary

Pros

  • Improved code quality
  • Enhanced security
  • Wide language support
  • Easy integration
  • Continuous improvement

Cons

  • Developers dependency on AI
  • Limited to suggested fixes

Bito AI

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Bito AI streamlines code review with AI-driven analysis, suggestions, and summaries, integrating with GitHub and GitLab to reduce review time by up to 45% and enhance code quality for engineering teams.

Feature Description 
Real-Time Code ReviewProvides immediate feedback on code changes within IDEs like VS Code and JetBrains.
AI-Powered SuggestionsOffers context-aware suggestions for code improvements and best practices.
IntegrationSeamlessly integrates with GitHub and GitLab.
Multi-language Support over 50 programming languages.
Security ChecksConducts security assessments without storing user code for model training.
Analytics DashboardTracks metrics related to code reviews, including the number of pull requests and issues found.

Pricing Tier 

Pricing Tier Description Cost
Free20 AI Chat requests per day50 AI Code Completions per month25+ spoken languages and 50+ programming languages Programmable AI in your CLISecure, encrypted code and AI requestsGPT-4o mini and similar models$ 0
10X Developer PlanGPT-4o, Claude Sonnet 3.5, and best-in-class AI modelsUnlimited AI Chat and AI Code Completion requests
AI summaries in GitHub and GitLab PRs with line-level suggestions
600 GPT-4o requests per month included ($0.03 per additional request)
$19
TeamOn-prem AI Code Review Agent
AI Code Review Agent integrated into CI/CD pipeline
Custom rules for a pull request
Dedicated customer and technical support
SSO, SCIM, and SAML 
Audit log
Custom pricing 

Best For 

  • Intermediate to advanced Python developers

Limitations

  •  Some users report that the tool does not significantly improve existing processes, with issues in code completion and unit test generation noted
  • May encounter inaccuracies in suggestions, necessitating human review
  • Concerns about pricing transparency

Pros

  • Automate tedious tasks
  • Saves time
  • User-friendly Interface
  •  Enhances collaboration

Cons

  • Mixed reviews on effectiveness
  • Over-reliance on AI suggestions may lead to diminished coding skills over time

Amazon CodeWhisperer

Amazon CodeWhisperer is an AI-powered coding assistant developed by Amazon Web Services (AWS) designed to enhance developer productivity through intelligent code suggestions and real-time assistance.

Feature Description 
Multi-IDE SupportIntegrates with popular IDEs such as VS Code, JetBrains, AWS Cloud9, and others.
Documentation GenerationAutomatically generates documentation for your code to maintain clarity.
Security ScanningIntegrates with Amazon CodeGuru to perform security scans, detecting vulnerabilities like exposed credentials and log injection.
Code RefactoringSuggests improvements for existing code, aiding in refactoring efforts.
Code SuggestionsProvides intelligent code suggestions based on the context of your code and comments, helping to write code faster and more accurately.
Real-Time Code CompletionOffers real-time completion suggestions for lines of code and entire functions.
Error DetectionIdentifies potential errors in the code before they become issues, enhancing code quality.
Collaboration ToolsFacilitates teamwork through shared coding experiences and instant feedback.

Pricing Tier 

Pricing Tier Description Cost
FreeCode faster with code suggestions in the IDE and CLIFree for public CLI completionsLimited monthly access of advanced featuresGet answers about your AWS account resources (limit 25 queries per month)Diagnose common errors in the console Use where you work: your IDE, CLI, the AWS Management Console, Slack, and more$0
ProIncludes features of Free Tier plan, plus
Manage users and policies with enterprise access controls
Chat, debug code, add tests, and more in your integrated developer environment (IDE
Customize Amazon Q to your code base to get even better suggestions) 
High limits of advanced features
Accelerate tasks with the Amazon Q Developer agents for software development
Get answers about your AWS account resources 
Simplify query authoring with generative SQL (limit 1000 queries per month)
$19

Best For 

  • Developers Working with AWS Services
  • Cross-Platform Developers
  • Small to Medium-Sized Teams

Limitations

  • May not fully understand project-specific nuances or complex scenarios
  • Dependency on the AWS Ecosystem
  • There may be concerns regarding data privacy and security as a cloud-based tool.

Pros

  • Excellent code quality
  • Comprehensive security features
  • Seamless Integration

Cons

  • Steep learning curve
  •  Variable performance

Comparative table

AI toolsFeature Compatible programming languages Best For 
GitHub CopilotCopilot pull request summaries
Code Completion
VS Code, Visual Studio, JetBrains IDEsAll levels of developers, specifically those keen on multiple programming languages 
TabnineAI-Powered Code CompletionVS Code, IntelliJ IDEADevelopers looking for smart code completion

OpenAI Codex
Natural Language to Code
Code Completion
GitHub Copilot; accessible via APIDevelopers interested in natural language processing
DeepCode AIReal-Time Code AnalysisSecurity Vulnerability DetectionIntelliJ IDEA, VS Code, GitHubDevelopers/companies focused on code quality
Bito AIAI-Powered Suggestions
GitHub and GitLab
Intermediate to advanced Python developers
Amazon CodeWhispererCode SuggestionsCode Refactoring Real-Time Code CompletionAWS Cloud9, JetBrains IDEs, VS CodeDevelopers Working with AWS Services

How to choose the right AI tool for Python coding

  1. Project Complexity: Projects have three sides to them, and they are simple, intermediate, and complex. Carefully think this through before choosing and operating a tool. 
  1. Budget: Almost every AI Python code generator comes with a free plan, but even that has feature restrictions that are open to paid plans. So, although you may start using them for free, you will eventually have to pay for services in the future. Look up the paid plan costs of your chosen tool to help you save for that future payment.
  1. Required Features: The simple way to know if an AI tool has the features necessary to better your development project is by looking at its Unique Selling Points (USPs), aka “What sets it apart?” When you do, you'll find out if it has the functionality to enhance your coding quality and development goals.

Benefits of using AI for Python coding

  1. Faster Debugging: AI tools analyze code as it is written, providing immediate feedback on potential errors or inefficiencies. This allows developers to identify and fix issues on the go, significantly reducing the time spent on debugging.
  1. Refactoring Support: AI can assist in refactoring code by identifying areas that require improvement or simplification, ultimately leading to a more organized and efficient code structure.
  1. Task Automation: AI tools automate repetitive coding tasks such as generating boilerplate code or performing routine data manipulations, allowing developers to focus on more complex and creative aspects of their projects.
  1. Integration with Development Environments (IDEs): Many AI tools integrate seamlessly with popular IDEs, enabling automation features directly within the development environment. This integration streamlines workflows and enhances productivity by reducing manual effort.

FAQs

What is the best AI tool for Python coding?

  • Eventually, it depends on what coding challenge you aim to solve. OpenAI Codex is great for generating code snippets, completing code, and even translating natural language into code. At the same time, Amazon CodeWhisperer can help with providing more real-time programming assistance and intelligent code suggestions.

What features should I look for in an AI coding assistant?

  • Look for features such as code suggestions and autocompletion, error detection and debugging, and code refactoring capabilities. Additionally, ensure the tool generates documentation and integrates with your preferred IDE for a seamless workflow.

Can AI tools handle large Python projects efficiently?

  • Yes, AI tools can efficiently manage large Python projects by providing real-time code suggestions, automating documentation, and detecting errors early, which helps maintain code quality and reduces technical debt.

Are AI tools reliable for production-level Python coding?

  • AI tools are increasingly reliable for production-level Python coding, as they utilize advanced algorithms to suggest context-aware code, detect potential issues, and enhance overall code quality. However, human oversight is still recommended for critical decisions.

Conclusion

Now that you're at the end of this article, you know the 6 Best AI for Python coding, their benefits, and factors to help you understand which AI tool will align with your coding programming.

Apply these findings diligently in your search, and you'll be on your way to achieving your coding goals.

DISCLAIMER!

“This publication, review, or article ("Content") is based on our independent evaluation and is subjective, reflecting our opinions, which may differ from others' perspectives or experiences. We do not guarantee the accuracy or completeness of the Content and disclaim responsibility for any errors or omissions it may contain.

The information provided is not investment advice and should not be treated as such, as products or services may change after publication. By engaging with our Content, you acknowledge its subjective nature and agree not to hold us liable for any losses or damages arising from your reliance on the information provided.

Always conduct your own research and consult professionals where necessary.”

I’m Fredrick Eghosa, a lifelong learner and tech enthusiast with a deep passion for AI, SEO, and digital innovation. I thrive on curiosity, constantly exploring how artificial intelligence is reshaping industries, from content creation to business automation. My true excitement comes from uncovering new ideas, experimenting with emerging technologies, and sharing insights that push boundaries. I love diving deep, asking big questions, and discovering what’s next. 🚀
I’m Fredrick Eghosa, a lifelong learner and tech enthusiast with a deep passion for AI, SEO, and digital innovation. I thrive on curiosity, constantly exploring how artificial intelligence is reshaping industries, from content creation to business automation. My true excitement comes from uncovering new ideas, experimenting with emerging technologies, and sharing insights that push boundaries. I love diving deep, asking big questions, and discovering what’s next. 🚀
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I’m Fredrick Eghosa, a lifelong learner and tech enthusiast with a deep passion for AI, SEO, and digital innovation. I thrive on curiosity, constantly exploring how artificial intelligence is reshaping industries, from content creation to business automation. My true excitement comes from uncovering new ideas, experimenting with emerging technologies, and sharing insights that push boundaries. I love diving deep, asking big questions, and discovering what’s next. 🚀
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