Search Results for "python compile source code" - Page 10
Sort By:
Showing 2059 open source projects for "python compile source code"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
-
1
pep484 stubs for Django
PEP-484 stubs for Django
This package contains type stubs and a custom mypy plugin to provide more precise static types and type inference for Django framework. Django uses some Python "magic" that makes having precise types for some code patterns problematic. This is why we need this project. The final goal is to be able to get precise types for the most common patterns. We are independent from Django at the moment. There's a proposal to merge our project into the Django itself. You can show your support by liking... -
2
pipx
Install and run Python applications in isolated environments
pipx is a tool to help you install and run end-user applications written in Python. It's roughly similar to macOS's brew, JavaScript's npx, and Linux's apt. It's closely related to pip. In fact, it uses pip, but is focused on installing and managing Python packages that can be run from the command line directly as applications. pip is a general-purpose package installer for both libraries and apps with no environment isolation. pipx is made specifically for application installation, as it adds... -
3
Kedro
A Python framework for creating reproducible, maintainable code
Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together... -
4
Gleam
A friendly language for building type-safe, scalable systems!
Gleam's powerful static type system helps find and prevent bugs at compile time, long before it reaches your users. It also serves as a productive refactoring tool, enabling programmers to confidently make large changes to unfamiliar code, quickly and with low risk. For problems, the type system can't solve (such as your server being hit by a bolt of lightning) the Erlang virtual machine provides well-tested mechanisms for gracefully handling failure. Hunting down bugs can be stressful so... -
Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
-
5
JS-Beautify
Beautifier for javascript
js-beautify is a command-line and Python-based tool that beautifies and formats JavaScript, HTML, and CSS code. It helps improve code readability by enforcing consistent indentation and style rules. Widely used in development workflows and CI pipelines, it supports customization through config files and can process both single files and entire projects. -
6
Chainlit
Build Python LLM apps in minutes
Chainlit is an open-source Python package that makes it incredibly fast to build and share LLM apps. Integrate the Chainlit API in your existing code to spawn a ChatGPT-like interface in minutes! Integrate seamlessly with an existing code base or start from scratch in minutes. Understand the intermediary steps that produced an output at a glance. Deep dive into prompts in the Prompt Playground to understand where things went wrong and iterate. Invite your teammates, create annotated datasets... -
7
Semantic Router
Superfast AI decision making and processing of multi-modal data
Semantic Router is a superfast decision-making layer for your LLMs and agents. Rather than waiting for slow, unreliable LLM generations to make tool-use or safety decisions, we use the magic of semantic vector space — routing our requests using semantic meaning. Combining LLMs with deterministic rules means we can be confident that our AI systems behave as intended. Cramming agent tools into the limited context window is expensive, slow, and fundamentally limited. Semantic Router enables... -
8
PyCaret
An open-source, low-code machine learning library in Python
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the experiment cycle exponentially and makes you more productive. In comparison with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only. This makes experiments exponentially fast and efficient... -
9
PyJNIus
Access Java classes from Python
Pyjnius is a Python library for accessing Java classes. A Python module to access Java classes as Python classes using the Java Native Interface (JNI). Warning: the pypi name is now pyjnius instead of jnius. When you use autoclass, it will discover all the methods and fields of the class and resolve them. You can use the signatures method of JavaMethod and JavaMultipleMethod, to inspect the discovered signatures of a method of an object. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
Synthetic Data Vault (SDV)
Synthetic Data Generation for tabular, relational and time series data
The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent... -
11
OpenAssistant
Chat-based assistant that understands tasks
... the world interested in bringing this technology to everyone. The code and models are licensed under the Apache 2.0 license. Open Assistant will be free to use and modify. There will be versions which will be runnable on consumer hardware. You do not need to run the project locally unless you are contributing to the development process. The website link above will take you to the public website where you can use the data collection app. -
12
vyper
Pythonic Smart Contract Language for the EVM
See Installing Vyper to install vyper. See Tools and Resources for an additional list of framework and tools with vyper support. See Documentation for the documentation and overall design goals of the Vyper language. See Learn.Vyperlang.org for learning Vyper by building a Pokémon game. See try.vyperlang.org to use Vyper in a hosted jupyter environment! There is also an online compiler available you can use to experiment with the language and compile to bytecode and/or IR. While the vyper... -
13
Thinc
A refreshing functional take on deep learning
..., configure and deploy custom models built with their favorite framework. Switch between PyTorch, TensorFlow and MXNet models without changing your application, or even create mutant hybrids using zero-copy array interchange. Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers. -
14
BentoML
Unified Model Serving Framework
BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads... -
15
PML
The easiest way to use deep metric learning in your application
This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you... -
16
FastMCP
The fast, Pythonic way to build Model Context Protocol servers
FastMCP is a Pythonic framework designed to simplify the creation of MCP servers. It allows developers to build servers that provide context and tools to Large Language Models (LLMs) using clean and intuitive Python code, streamlining the integration process between AI models and external resources. -
17
FastHTML
The fastest way to create an HTML app
Built on solid web foundations, not the latest fads - with FastHTML you can get started on anything from simple dashboards to scalable web applications in minutes. -
18
pmd
An extensible multilanguage static code analyzer
PMD is a source code analyzer. It finds common programming flaws like unused variables, empty catch blocks, unnecessary object creation, and so forth. It supports Java, JavaScript, Salesforce.com Apex and Visualforce, PLSQL, Apache Velocity, XML, and XSL. Additionally, it includes CPD, the copy-paste-detector. CPD finds duplicated code in Java, C, C++, C#, Groovy, PHP, Ruby, Fortran, JavaScript, PLSQL, Apache Velocity, Scala, Objective C, Matlab, Python, Go, Swift and Salesforce.com Apex... -
19
Jupyter Notebook Tools for Sphinx
Sphinx source parser for Jupyter notebooks
nbsphinx is a Sphinx extension that provides a source parser for *.ipynb files. Custom Sphinx directives are used to show Jupyter Notebook code cells (and of course their results) in both HTML and LaTeX output. Un-evaluated notebooks – i.e. notebooks without stored output cells – will be automatically executed during the Sphinx build process. -
20
Capstone
Capstone disassembly/disassembler framework
... architecture-neutral API. Provide details on disassembled instruction (called “decomposer” by others). Provide semantics of the disassembled instruction, such as list of implicit registers read & written. Implemented in pure C language, with lightweight bindings for D, Clojure, F#, Common Lisp, Visual Basic, PHP, PowerShell, Emacs, Haskell, Perl, Python, Ruby, C#, NodeJS, Java, GO, C++, OCaml, Lua, Rust, Delphi, Free Pascal & Vala (ready either in main code, or provided externally by the community). -
21
SST
Build serverless apps. Set breakpoints and test your functions locally
SST is an open-source serverless application platform that deploys to your AWS account, helping you go from idea to IPO. Work on your local Lambda functions lives, without mocking or redeploying your app. Higher-level CDK constructs are made specifically for building serverless apps. Manage the resources in your application with the SST Console. Traditionally, we’ve built and deployed web applications where we have some degree of control over the HTTP requests that are made to our server. Our... -
22
Hypothesis
The property-based testing library for Python
Hypothesis is a powerful library for property-based testing in Python. Instead of writing specific test cases, users define properties and Hypothesis generates random inputs to uncover edge cases and bugs. It integrates with unittest and pytest, shrinking failing examples to minimal reproducible cases. Widely adopted in production systems, Hypothesis boosts code reliability by exploring input spaces far beyond manually crafted tests. -
23
TPOT
A Python Automated Machine Learning tool that optimizes ML
Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. -
24
Tribuo
Tribuo - A Java machine learning library
Tribuo* is a machine learning library written in Java. It provides tools for classification, regression, clustering, model development, and more. It provides a unified interface to many popular third-party ML libraries like xgboost and liblinear. With interfaces to native code, Tribuo also makes it possible to deploy models trained by Python libraries (e.g. scikit-learn, and pytorch) in a Java program. Tribuo is licensed under Apache 2.0. Remove the uncertainty around exactly which artifacts... -
25
deepfakes_faceswap
Deepfakes Software For All
Faceswap is the leading free and open source multi-platform deepfakes software. When faceswapping was first developed and published, the technology was groundbreaking, it was a huge step in AI development. It was also completely ignored outside of academia because the code was confusing and fragmentary. It required a thorough understanding of complicated AI techniques and took a lot of effort to figure it out. Until one individual brought it together into a single, cohesive collection.
