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<p>EOS User Story provides an interface to the users to share how they are using the product and relate to other users’ stories and vote them up. It helps users tell developers how they are using the products and request new features, report bugs, etc. The project aims to enhance the user experience by introducing new features and improve on the existing ones. These features include providing users the functionality of sharing stories with a single click, providing request templates for products, personalized email notifications, priority labels for stories, priority based sorting of stories, and a feature for users to mention other users in the comments section.</p>

<p>The current Python's development process is very complicated for core developers. When an external contributor uploads a patch for a certain issue, the core developer needs to download the patch and then apply the patch and run the tests manually to make sure it works properly. Also, the core developers review the code on the forked version of Rietveld code review tool which is not being maintained. Once the patch is correct, the changes are committed manually. This is a manual and burdensome process for core developers. On <a href="https://mail.python.org/pipermail/core-workflow/2016-January/000345.html" target="_blank">1st January 2016</a>, Brett Cannon decided to migrate from Mercurial on hg.python.org to Git on GitHub.</p> <p>So, my project is about migrating to Git/Github. I will be working on creating pull requests on Github whenever a patch is submitted on the issue tracker (<a href="https://bugs.python.org" target="_blank">https://bugs.python.org</a>) and integrating various bots to maintain linear history of commits, auto-close of issues, enforce CLA, etc. Towards the end of the GSoC period, I will work on patch-related improvements.</p>

Milvus currently lacks a Debezium source connector, meaning data can flow into Milvus (via sink connectors) but not out of it into the broader data ecosystem. This critical gap forces users into manual workarounds for data replication, auditing, and prevents the creation of hybrid pipelines that join vector search results with relational data. The plan is to implement a Hybrid strategy focused exclusively on the future-proof Milvus 2.6+ StreamingNode architecture. This approach will leverage two separate sources to guarantee a complete and ordered change stream: Woodpecker Streaming Service (WAL): Used as the only source for all Data Manipulation Language (DML) events (inserts and deletes). Etcd Watch: Used as the cleanest source for all Data Definition Language (DDL) events (schema changes), which simplifies parsing and aligns with Debezium's schema history mechanism.

Kubernetes has recently moved its forensic container checkpointing feature into beta. This feature allows checkpointing containers within Kubernetes pods, and, with some additional steps, restoring them on a different node. This approach preserves active TCP connections of the container. However, workloads (e.g., web servers) with established TCP connections to the migrated container cannot make use of this feature, as the container IP changes after migrating to another node. This project implements a P4-based load balancer on the data plane that dynamically reroutes packets to the correct IP address after container migration. The goal is to make the migration invisible to the client, causing only a period of service unavailability, after which communication can be resumed without re-establishing the TCP connection. Deliverables of this project include a P4-based load balancer, control plane code for P4 runtime interaction, a minimal CNI plugin for Kubernetes integration, and performance benchmarks to demonstrate the system's effectiveness.

<p>The GTK client (Tryton) already has CSV Import/Export feature. This project would implement the same feature in web client (SAO) keeping the behavior similar.</p>

<p>The goal of this project is to design and implement a visualization module in PySAL, the <code>splot</code> package. This will meet the growing demand for a simple to use, lightweight interface that connects PySAL to different popular visualization toolkits. The <code>splot</code> package will ultimately provide the users with both static plots ready for publication and interactive visualizations that allow for quick iteration and data exploration. In a first phase we will therefore create different visualizations in both a static version with Matplotlib and an interactive version with Bokeh. We will then create a common API for easy access to both versions. After adding documentation we will be able to provide a complete and user friendly package. Finally, we will explore how alternative visualization packages, like Vega, could be integrated into the <code>splot</code> package in future.</p>

<p>JyNI is a compatibility layer with the goal to enable Jython to use native CPython extensions like NumPy or SciPy. So far it was developed on Linux and some additional effort was spent to let the core part work properly on OSX. In principle the current version of JyNI is workable on POSIX platforms. I propose to create a proper Windows version of JyNI. A fully accurate implementation of this proposal includes to establish workability of all extensions and features that are currently supported on POSIX platforms.</p>

<p>Enable full application of Time-Frequency Analysis tools on Source Estimate M/EEG neurophysiological data by integrating <code>mne.SourceEstimate</code> objects with <code>mne.time_frequency.tfr</code> functions.</p>

<p>The project aims to parse numbers written in natural language. This needs to be done while keeping incorporation with dateparser and price-parser in mind. We also need to provide support for multiple languages.</p>

The ENIGMA project uses a hierarchy of objects to represent entities. These objects are serialized and deserialized using (de)serialization routines implemented for them. However, the current implementation is not very clean as it checks the type of each argument against an if-else ladder, making it difficult to read and extend. This project aims to make the serialization framework easier to use and extend by changing the way the serialize, serialize_into and deserialize functions work to dispatch to supported types implicitly without the need for an if-else ladder. And the project also aims to implement support for additional data types like generic routines for map, vector and complex numbers. This would enable more easily serializing ENIGMA's internal state for use in sending state either across a network or into a file. Additionally, the project aims to introduce support for the JSON format within the serialization system, offering it as a new option alongside the existing bytes format. This addition enhances the readability and debugging capability of the serialized data.

Effective connectivity analyses are a staple of many neurophysiological research projects, providing key insights into the healthy functioning of the brain and pathological alterations with disease. MNE-Connectivity leverages the API of the highly-popular MNE-Python signal processing package to provide tools for computing such connectivity. However, given the complexities associated with studying interactions in the brain, it is critical that the metrics for estimating connectivity are robust, and the estimates themselves statistically significant. Naturally, it is essential that such tools are available in open-source toolboxes, something we will address in this project. First, building on recent work in the MNE-Connectivity toolbox, we will implement further support for advanced multivariate connectivity metrics in the form of a dedicated decoding module. This module will provide flexible tools for the data-driven analysis of connectivity that is critical for robust characterisations of network activity in multi-channel recordings. The only comparable implementations of such methods are in toolboxes for the proprietary language MATLAB, limiting the availability of these tools to the wider research community. Second, we will expand the existing set of statistical features available in MNE-Python to include tools for assessing the statistical significance of estimated connectivity, crucial for distinguishing genuine interactions from background noise. In all cases, new features will be complemented with detailed examples and tutorials in the MNE-Connectivity documentation. Altogether, the project will expand the repertoire and quality of open-source tools available for studying connectivity in the brain, a cornerstone of modern neurophysiological research.

<p>CVE Binary Tool is running on Linux systems now by taking advantages of bash commands like file and string. Since file and string have already been naively implemented, it is ideal to extend the tool to other operating systems like Windows.</p>

This proposal aims to develop an information theoretic approach to filter out artificial information from real information in geospatial datasets. The project will use the bitinformation framework to distinguish between real and false information, where real information is defined as the mutual information between adjacent bits. The proposed algorithm will filter out artificial information, which is a consequence of prior compression, from real information, which reflects the underlying signal. The project will involve a theoretical review, test case generation, algorithm development, evaluation, and integration into xbitinfo, a software package that implements the bitinformation framework. The resulting artificial information filter will provide a valuable tool for users who may not have access to high-precision/uncompressed data, and it will enhance the accuracy and reliability of geospatial data analysis. As a participant in the Google Summer of Code, I am excited about the opportunity to work on this project and contribute to the development of an open-source software tool that will benefit the scientific community.

<p>A Linear Algebra Library and a plotting Library are the basic requirements for scientific software to be built on. With this project, we aim to create a language-independent plotting library inspired by Matplotlib, that can be easily bridged to any language</p>

<p>Currently, EOS delivers icons via a set of well-documented methods, which chiefly include EOS-Icons Package, CDN, or direct download of icons in SVG/PNG formats. This project will be based on developing an npm package that can deliver EOS Icons to its users as an independent component library and create a unified central system that will enable EOS to deliver its icons to various frameworks (e.g. React, Vue and Angular) independently. This npm package will be as lightweight as possible in order to reduce the load put on the browser (using the tree shaking approach), which will result in providing a much smoother workflow to the users. Creating a package of EOS Icons for React, Vue, and Angular frameworks will go a long way in having a more consistent user experience as well as boost capability to accommodate users who migrate from one framework to another.</p>

The EOS User Story project is a project that supports the development and testing of other projects. I will be working on improving and adding features to the platform. I will be working on both the frontend and backend of the project. The frontend uses react.js and the backend is made in Strapi. During the program, I will migrate the services to newer versions and add some interesting features in the comment section, notification section, labels , etc. After this program user story will be ready to use by EOS and other organizations. The main objectives of my proposal are- 1. Migration to typescript 2. Migration to Strapi V4 3. Revamping the notification section 4. Making the comment section user friendly 5. Adding more UI/UX solutions 6. Removing existing bugs.

<p>DaRu (Data Analysis in RUby) is a library for storage, analysis, manipulation and visualisation of data. Currently it is doing good job for scientific usage(in IRuby notebook), but if user want to visualize some data for integration into existing web application, then Daru methods have to output result/chart/graph/datatable such a way that output is directly usable into web application (in html file). Also Daru must have better import/export technique so that new importers/exporters can be defined easily. Mostly modern web application will use NoSql database, that is easy to scale. It will be very useful if Daru can connect with relational or non-relational database and make query operations easy. This project aims to make Daru more powerful for web application to use it as data analysis and visualisation tool, by working on above issues.</p>

d-SEAMS currently uses an embedded Lua interpreter to provide user interactivity in tandem with YAML inputs for selecting workflows. The project seeks to replace this interface with a Python interface. This is expected to take place in two stages: - Replacing the Lua Interpreter with Python - Binding to C++ classes and functions directly With both of these milestones completed, feature parity will be kept with the existing code while also providing much more flexibility due to the Python library formed in the second deliverable.

My project aims to enhance the PyAfipWs project under the Python Argentina (PyAr) organization, focusing on two main objectives: significantly improving test coverage, followed by implementing documentation using Sphinx and refining GitHub Actions workflows. Additionally, if time permits, I aim to build a simulator for key AFIP web services using Python and Flask. Problem Statement: PyAfipWs currently faces dependency conflicts, lacks extensive test coverage, comprehensive documentation, and efficient GitHub Actions workflows. These issues hinder development, reliability, and collaboration within the project. Proposed Solution: Dependency Conflict Resolution: I'll address conflicts with pysimplesoap to ensure seamless integration and operation. Test Coverage Enhancement: Will add comprehensive unit tests for key modules such as wsfev1.py, utils.py, padron.py, and others, aiming for close to 100% coverage. Documentation Implementation: Utilizing Sphinx, I will create detailed usage guides, API references, and contribution guidelines, ensuring clarity and accessibility for developers. GitHub Actions Workflow Improvement: l will also work to enhance workflows by adding linting, type checking, and test automation, along with implementing PR automation for reviewer assignment and auto-merging. Simulator Development (if time permits): A Flask-based simulator mimicking AFIP web service endpoints will be built, facilitating controlled testing environments and streamlining development. Deliverables: Resolve dependency conflicts and initial Pull Requests addressing the issue. Implementing Extensive unit tests for key modules, along with Pull Requests showcasing high test coverage. Completing Sphinx documentation framework integrated with GitHub Actions for automated updates. Enhancing GitHub Actions workflows covering linting, testing, and PR automation, reflected in Pull Requests.

This project aims to implement a Near-to-Far Field Transformation (NFFT) feature in gprMax. This will enable users to compute the far-field radiation patterns and radar crosssections(RCS) from the near-field data. It will expand gprMax’s capabilities for antenna design, scattering analysis, etc. I propose to implement the Near-to-Far Field Transformation (NFFT) module and its integration at several key points in the existing workflow: - Adding the NFFT command - Module for Field Sampling during FDTD - Post-Processing & Far-Field Calculation - Integration with the API - Validation and Testing - Documentation and Review

This project aims to expand support for serious games within the Cormas platform, enabling easier interaction between players and environment, and autonomous agents. By extending Cormas with “playable” components the project will contribute to the development of a generic solution for designing, playing, and analyzing serious games. The planned development includes three phases, covering initial implementation, testing, and system optimization, with the ultimate goal of creating a first working prototype with a user interface accessible via a smartphone.

<p>All electromagnetic phenomena are governed by the Maxwell's equations, which describing how electric and magnetic fields are distributed due to charges and currents, and how they are changing in time. gprMax is open source software that simulates electromagnetic wave propagation by using Yee's algorithm to solve (3+1)D Maxwell’s equations with Finite-Difference Time-Domain (FDTD) method. The behavior of the electromagnetic wave is closely dependent on the material in which it propagates. Some dispersive media have quite complex electromagnetic properties depending on the wavelength. This, for example, means that for different frequencies the wave can propagate with a different speed in different materials. This significantly affects the solver’s output. The main goal of the project is to enhance series of scripts, which modelled electromagnetic properties of the variety range of materials. Initial series of scripts have been prepared, however, their technical improvement and coupling with main software gprMax is required.</p>

The function of the list configuration tool is to export the list and configuration of the administrator and generate a JSON file to store them. At the same time, you can also use these JSON files to import the list and configuration in the file into other users. This is a process of converting the server's online data into files for storage, backup and data migration.