Change Details

# Outreachy Proposal – Lusophone Wishlist Project ## About me Hi, I’m Sania. I’m currently an undergraduate student and have been exploring software development through projects and coursework. Through Outreachy, I started understanding how open source projects work and how real user needs shape features. ## Wishlist I am applying for I am most interested in working on Wishlist #3 (duplicate reference detection). From what I understand, editors often add the same reference multiple times without realizing it, especially in long articles. Fixing this later takes extra effort. I find this problem interesting because it is simple in idea but requires careful handling of real-world data like URLs, DOIs, and ISBNs. It also directly improves the editing experience. ## Approach I plan to work step by step and keep things practical: - Start with simple duplicate detection using URLs - Extend support to DOI and ISBN - Handle edge cases and different formats - Focus on making the feature reliable and useful for editors ## Timeline **Weeks 1–2** - Set up development environment - Explore Visual Editor and how references are handled - Understand APIs and data flow - Discuss approach with mentors **Weeks 3–5** - Implement basic duplicate detection using URL matching - Test on simple cases **Weeks 6–8** - Extend detection to DOI and ISBN - Handle edge cases and improve accuracy **Weeks 9–10** - Integrate feature into the editor workflow - Improve usability and behavior **Weeks 11–12** - Testing, bug fixing, and cleanup - Improve based on mentor feedback - Add documentation ## What I learned from microtasks The microtasks helped me understand how to work with real data. - In Task 1, I worked with structured JSON and focused on formatting and display - In Task 2, I handled URLs, including broken links and timeouts This helped me think more about edge cases and real-world behavior instead of ideal inputs. ## Why me I am still early in open source, but I am consistent and willing to learn. I try to understand how things work instead of just completing tasks. I am comfortable working with Python, JavaScript, and APIs, and I am interested in building something that is actually useful for users. ## Impact This feature can help editors avoid duplicate references while editing instead of fixing them later. It saves time and improves workflow. Since Visual Editor is widely used, this can benefit many users beyond one community. ## After the internship I would like to continue improving the feature and contribute more to Wikimedia projects if possible. ## Availability I will be fully available from May 20 to the end of July and can dedicate around 40 hours per week. I am also flexible and open to adjusting my plan based on mentor feedback.

# Outreachy Proposal: Addressing the lusophone technological wishlist proposals - Visual Editor / Wikidata ## About me Hi, I’m Sania. I’m currently an undergraduate student and have been exploring software development through projects and coursework. Through Outreachy, I started understanding how open source projects work and how real user needs shape features. ## Wishlist I am applying for I am most interested in working on Wishlist #3 (duplicate reference detection). From what I understand, editors often add the same reference multiple times without realizing it, especially in long articles. Fixing this later takes extra effort. I find this problem interesting because it is simple in idea but requires careful handling of real-world data like URLs, DOIs, and ISBNs. It also directly improves the editing experience. ## Approach I plan to work step by step and keep things practical: - Start with simple duplicate detection using URLs - Extend support to DOI and ISBN - Handle edge cases and different formats - Focus on making the feature reliable and useful for editors ## Timeline **Weeks 1–2** - Set up development environment - Explore Visual Editor and how references are handled - Understand APIs and data flow - Discuss approach with mentors **Weeks 3–5** - Implement basic duplicate detection using URL matching - Test on simple cases **Weeks 6–8** - Extend detection to DOI and ISBN - Handle edge cases and improve accuracy **Weeks 9–10** - Integrate feature into the editor workflow - Improve usability and behavior **Weeks 11–12** - Testing, bug fixing, and cleanup - Improve based on mentor feedback - Add documentation ## What I learned from microtasks The microtasks helped me understand how to work with real data. - In Task 1, I worked with structured JSON and focused on formatting and display - In Task 2, I handled URLs, including broken links and timeouts This helped me think more about edge cases and real-world behavior instead of ideal inputs. ## Why me I am still early in open source, but I am consistent and willing to learn. I try to understand how things work instead of just completing tasks. I am comfortable working with Python, JavaScript, and APIs, and I am interested in building something that is actually useful for users. ## Impact This feature can help editors avoid duplicate references while editing instead of fixing them later. It saves time and improves workflow. Since Visual Editor is widely used, this can benefit many users beyond one community. ## After the internship I would like to continue improving the feature and contribute more to Wikimedia projects if possible. ## Availability I will be fully available from May 20 to the end of July and can dedicate around 40 hours per week. I am also flexible and open to adjusting my plan based on mentor feedback.

# Outreachy Proposal – L: Addressing the lusophone We technological wishlist Projectproposals - Visual Editor / Wikidata ## About me Hi, I’m Sania. I’m currently an undergraduate student and have been exploring software development through projects and coursework. Through Outreachy, I started understanding how open source projects work and how real user needs shape features. ## Wishlist I am applying for I am most interested in working on Wishlist #3 (duplicate reference detection). From what I understand, editors often add the same reference multiple times without realizing it, especially in long articles. Fixing this later takes extra effort. I find this problem interesting because it is simple in idea but requires careful handling of real-world data like URLs, DOIs, and ISBNs. It also directly improves the editing experience. ## Approach I plan to work step by step and keep things practical: - Start with simple duplicate detection using URLs - Extend support to DOI and ISBN - Handle edge cases and different formats - Focus on making the feature reliable and useful for editors ## Timeline **Weeks 1–2** - Set up development environment - Explore Visual Editor and how references are handled - Understand APIs and data flow - Discuss approach with mentors **Weeks 3–5** - Implement basic duplicate detection using URL matching - Test on simple cases **Weeks 6–8** - Extend detection to DOI and ISBN - Handle edge cases and improve accuracy **Weeks 9–10** - Integrate feature into the editor workflow - Improve usability and behavior **Weeks 11–12** - Testing, bug fixing, and cleanup - Improve based on mentor feedback - Add documentation ## What I learned from microtasks The microtasks helped me understand how to work with real data. - In Task 1, I worked with structured JSON and focused on formatting and display - In Task 2, I handled URLs, including broken links and timeouts This helped me think more about edge cases and real-world behavior instead of ideal inputs. ## Why me I am still early in open source, but I am consistent and willing to learn. I try to understand how things work instead of just completing tasks. I am comfortable working with Python, JavaScript, and APIs, and I am interested in building something that is actually useful for users. ## Impact This feature can help editors avoid duplicate references while editing instead of fixing them later. It saves time and improves workflow. Since Visual Editor is widely used, this can benefit many users beyond one community. ## After the internship I would like to continue improving the feature and contribute more to Wikimedia projects if possible. ## Availability I will be fully available from May 20 to the end of July and can dedicate around 40 hours per week. I am also flexible and open to adjusting my plan based on mentor feedback.