Search Results for "p1-sec"
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Showing 174 open source projects for "p1-sec"
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The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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Comet Backup - Fast, Secure Backup Software for MSPsComet is a flexible backup platform, giving you total control over your backup environment and storage destinations.
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Sec-Context
AI Code Security Anti-Patterns distilled from 150+ sources
Sec-Context is a curated security research project that distills common code anti-patterns and vulnerabilities that generative AI tends to produce, presenting them as a comprehensive set of examples and secure alternatives that can be used to train or guide AI assistants and reviewers toward safer code generation. It compiles insights from over 150 industry and academic sources into structured reference documents that outline real-world security problems such as hardcoded secrets, SQL injection, cross-site scripting, command injection, weak password storage, and other frequent issues that occur when code is auto-generated without context of best practices. ... -
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Particle Firmware for the Electron, P1
Device OS (Firmware) for particle devices
The Photon uses an ARM Cortex M3 CPU based microcontroller. All of the code is built around the GNU GCC toolchain offered and maintained by ARM. The build requires version 5.3.1 20160307 or newer of ARM GCC and will print an error message if the version is older than this. In order to turn your source code into binaries, you will need a tool called make. Windows users need to explicitly install make on their machines. Make sure you can use it from the terminal window. The entire Particle... -
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Sealed Secrets for Kubernetes
A Kubernetes controller and tool for one-way encrypted Secrets
Sealed Secrets provides declarative Kubernetes Secret Management in a secure way. Since the Sealed Secrets are encrypted, they can be safely stored in a code repository. This enables an easy-to-implement GitOps flow that is very popular among the OSS community. Sealed Secrets offers a powerful CLI tool (kubeseal) to one-way encrypt your Kubernetes Secret easily. The Sealed Secrets controller will decrypt any Sealed Secret into its equivalent Kubernetes Secret. Sealed Secrets are safe to... -
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Colly
Elegant Scraper and Crawler Framework for Golang
...With Colly you can easily extract structured data from websites, which can be used for a wide range of applications, like data mining, data processing or archiving. Clean API. Fast (>1k request/sec on a single core) Manages request delays and maximum concurrency per domain. Automatic cookie and session handling. Sync/async/parallel scraping. Distributed scraping. Caching, automatic encoding of non-unicode responses. Robots.txt support. Google App Engine support. -
The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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Snappy
A fast compressor/decompressor
...For instance, compared to the fastest mode of zlib, Snappy is an order of magnitude faster for most inputs, but the resulting compressed files are anywhere from 20% to 100% bigger. Snappy is intended to be fast. On a single core of a Core i7 processor in 64-bit mode, it compresses at about 250 MB/sec or more and decompresses at about 500 MB/sec or more. (These numbers are for the slowest inputs in our benchmark suite; others are much faster.) In our tests, Snappy usually is faster than algorithms in the same class (e.g. LZO, LZF, QuickLZ, etc.) while achieving comparable compression ratios. -
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AWS Secrets Manager Python caching
Enables in-process caching of secrets for Python applications
The AWS Secrets Manager Python caching client enables in-process caching of secrets for Python applications. To use this client you must have Python 3.6 or newer. Use of Python versions 3.5 or older are not supported. An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager. To create an AWS account, go to Sign In or Create an AWS Account and then choose I am a new user. Follow the instructions to create an AWS account. To create a secret in AWS Secrets Manager,... -
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AWS Secrets Manager Java caching client
Enables in-process caching of secrets for Java applications
The AWS Secrets Manager Java caching client enables in-process caching of secrets for Java applications. To use this client you must have a Java 8 development environment. If you do not have one, go to Java SE Downloads on the Oracle website, then download and install the Java SE Development Kit (JDK). Java 8 or higher is recommended. An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager and use AWS SDK for Java. To create an AWS account, go to Sign In or... -
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ESP3D
FW for ESP8266/ESP8285/ESP32 used with 3D printer
...The web interface files are present in the data directory but UI has its own repository ESP3D-WEBUI. Use GPIO2 to the ground to reset all settings in a hard way, 2-6 sec after boot / not before!! Set GPIO2 to ground before boot change boot mode and go to special boot that do not reach FW. Currently, boot takes 10 sec - giving 8 seconds to connect GPIO2 to GND and do a hard recovery for settings. Complete configuration by web browser (Station or Access point) or by Serial/telnet commands. -
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AWS Secrets Manager Go Caching Client
Enables in-process caching of secrets for Go applications
The AWS Secrets Manager Go caching client enables in-process caching of secrets for Go applications. To use this client you must have a Go development environment. If you do not have one, go to Golang Getting Started on The Go Programming Language website, then download and install Go. An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager and use AWS SDK for Go. To create an AWS account, go to Sign In or Create an AWS Account and then choose I am a new user.... -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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AWS Secrets Manager Caching Client .NET
Enables in-process caching of secrets for C# applications
The AWS Secrets Manager .NET caching client enables in-process caching of secrets for C# applications. The AWS Secrets Manager caching client enables in-process caching of secrets for .NET applications. To use this client, you must have a .NET project with one of the following, .NET Framework 4.6.1 or higher, .NET Standard 2.0 or higher, and An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager and use AWS SDK for .NET. To create an AWS account, go to Sign In... -
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Dexmond.com is the official website of Dexmond Technologies, dedicated to CypherNight: MAX-SEC V3, a professional-grade, multi-platform data encryption suite designed for securing, digitally signing, and managing sensitive files with uncompromising security. The core tool combines military-strength cryptography — AES-256-GCM for symmetric encryption, RSA-4096 (with OAEP padding) for asymmetric operations, Ed25519 digital signatures, and Argon2id for secure passphrase-based key derivation — to protect data against brute-force, offline, and alteration attacks. ...
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Ligolo-ng
An advanced, yet simple, tunneling/pivoting tool
...You need to download the Wintun driver (used by WireGuard) and place the wintun.dll in the same folder as Ligolo. You can listen to ports on the agent and redirect connections to your control/proxy server. You can easily hit more than 100 Mbits/sec. Here is a test using iperf from a 200Mbits/s server to a 200Mbits/s connection. -
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git absorb
git commit --fixup, but automatic
This is a port of Facebook's hg absorb. Facebook demoed hg absorb which is probably the coolest workflow enhancement I've seen to version control in years. Essentially, when your working directory has uncommitted changes on top of draft changesets, you can run hg absorb and the uncommitted modifications are automagically folded ("absorbed") into the appropriate draft ancestor changesets. This is essentially doing hg histedit + "roll" actions without having to make a commit or manually make... -
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etcd
Distributed reliable key-value store for the most critical data
A distributed, reliable key-value store for the most critical data of a distributed system. etcd is a strongly consistent, distributed key-value store that provides a reliable way to store data that needs to be accessed by a distributed system or cluster of machines. It gracefully handles leader elections during network partitions and can tolerate machine failure, even in the leader node. etcd is a consistent distributed key-value store. Mainly used as a separate coordination service, in... -
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OpenBB
Investment Research for Everyone, Everywhere
Customize and speed up your analysis, bring your own data, and create instant reports to gain a competitive edge. Whether it’s a CSV file, a private endpoint, an RSS feed, or even embed an SEC filing directly. Chat with financial data using large language models. Don’t waste time reading, create summaries in seconds and ask how that impacts investments. Create your dashboard with your favorite widgets. Create charts directly from raw data in seconds. Create charts directly from raw data in seconds. Customize your dashboards to build your dream terminal, integrate with your private datasets and bring your own fine-tuned AI copilots. -
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Kraken
P2P Docker registry capable of distributing TBs of data in seconds
...In our busiest cluster, Kraken distributes more than 1 million blobs per day, including 100k 1G+ blobs. At its peak production load, Kraken distributes 20K 100MB-1G blobs in under 30 sec. Kraken is capable of distributing Docker images at > 50% of max download the speed limit on every host. Cluster size and image size do not have a significant impact on download speed. Support uploader authentication and data integrity protection through TLS. Other than pluggable storage, Kraken only has an optional dependency on DNS. -
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proxy.py
Utilize all available CPU cores for accepting new client connections
proxy.py is made with performance in mind. By default, proxy.py will try to utilize all available CPU cores to it for accepting new client connections. This is achieved by starting AcceptorPool which listens on configured server port. Then, AcceptorPool starts Acceptor processes (--num-acceptors) to accept incoming client connections. Alongside, if --threadless is enabled, ThreadlessPool is setup which starts Threadless processes (--num-workers) to handle the incoming client connections.... -
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Akka
Build concurrent, distributed, and resilient message-driven apps
...Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to 50 million msg/sec on a single machine. Small memory footprint; ~2.5 million actors per GB of heap. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. -
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formidable
The most used, flexible, fast and streaming parser
The most used, flexible, fast and streaming parser for multipart form data. Supports uploading to serverless environments, AWS S3, Azure, GCP or the filesystem. Used in production. This project is semantically versioned and available as part of the Tidelift Subscription for professional-grade assurances, enhanced support and security. The maintainers of formidable and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the Open Source... -
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HTTP Kit
Clojure HTTP server/client library with WebSocket support
...So you can use it with all your current libraries (e.g. Compojure) and middleware. Using an event-driven architecture like Nginx, HTTP-kit is very, very fast. It comfortably handles tens of thousands of requests/sec on even midrange hardware. Here is another test about how it stacks up with others. It's not only fast, but efficient! Each connection costs nothing but a few kB of memory. RAM usage grows O(n) with connections. Written from the ground-up to be lean, the entire client/server is available as a single ~90kB JAR with zero dependencies and ~3k lines of (mostly Java) code. ... -
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Ring
Ring is a reasoning MoE LLM provided and open-sourced by InclusionAI
Ring is a reasoning Mixture-of-Experts (MoE) large language model (LLM) developed by inclusionAI. It is built from or derived from Ling. Its design emphasizes reasoning, efficiency, and modular expert activation. In its “flash” variant (Ring-flash-2.0), it optimizes inference by activating only a subset of experts. It applies reinforcement learning/reasoning optimization techniques. Its architectures and training approaches are tuned to enable efficient and capable reasoning performance.... -
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Gorilla WebSocket
Fast, well-tested and widely used WebSocket implementation for Go
Gorilla WebSocket is a Go implementation of the WebSocket protocol. The Gorilla WebSocket package provides a complete and tested implementation of the WebSocket protocol. The package API is stable. An application can also send and receive messages using the io.WriteCloser and io.Reader interfaces. To send a message, call the connection NextWriter method to get an io.WriteCloser, write the message to the writer and close the writer when done. To receive a message, call the connection... -
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Prime number ( primenumbers )
Benchmark for 50 000 000 prime numbers as single and multicore
...(PS: C++ multicore 6 second). Added C files for gcc compiler in Windows 10 and for Xcode C command line project in MacOS ( tested on Mac mini M2 with single core 16 to 25 sec and multicore 2,3 to 5 second by compiler -O switch). Surprise, same code in JavaScript for M2 chip in Safari: 12,5 sec single core and 3,3 sec multi core. Python version with numba and numpy on MacOS with M2: 3,78 sec, Intel Ultra 5 225F Linux Fedora 43 GNOME(*Intel): 3,64 sec., W11Intel: 3,73; Faster style in python, MacOS M2: 1,81 sec, *Intel & W11Intel: 2,02 sec.; Ultra faster style in python, MacOS M2: 1,24 s - 1,26 s - 1,34 s, *Intel: 1,48 s - 1,50 s, W11Intel: 1,53 - 1,63. -
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inoscope
Arduino & STM32 Nucleo-based oscilloscope
Arduino & STM32 Nucleo-based dual-trace oscilloscope (200 ksamp/sec on Arduino Uno/ATmega328P and 2 Msamp/sec on Nucleo-F411RE)
