1679593320
Reth: Modular, Contributor-friendly & Blazing-fast Implementation
reth 🏗️🚧
Modular, contributor-friendly and blazing-fast implementation of the Ethereum protocol
The project is still work in progress, see the disclaimer below.
What is Reth? What are its goals?
Reth (short for Rust Ethereum, pronunciation) is a new Ethereum full node implementation that is focused on being user-friendly, highly modular, as well as being fast and efficient. Reth is an Execution Layer (EL) and is compatible with all Ethereum Consensus Layer (CL) implementations that support the Engine API. It is originally built and driven forward by Paradigm, and is licensed under the Apache and MIT licenses.
As a full Ethereum node, Reth allows users to connect to the Ethereum network and interact with the Ethereum blockchain. This includes sending and receiving transactions/logs/traces, as well as accessing and interacting with smart contracts. Building a successful Ethereum node requires creating a high-quality implementation that is both secure and efficient, as well as being easy to use on consumer hardware. It also requires building a strong community of contributors who can help support and improve the software.
More concretely, our goals are:
- Modularity: Every component of Reth is built to be used as a library: well-tested, heavily documented and benchmarked. We envision that developers will import the node's crates, mix and match, and innovate on top of them. Examples of such usage include but are not limited to spinning up standalone P2P networks, talking directly to a node's database, or "unbundling" the node into the components you need. To achieve that, we are licensing Reth under the Apache/MIT permissive license. You can learn more about the project's components here.
- Performance: Reth aims to be fast, so we used Rust and the Erigon staged-sync node architecture. We also use our Ethereum libraries (including ethers-rs and revm) which we’ve battle-tested and optimized via Foundry.
- Free for anyone to use any way they want: Reth is free open source software, built for the community, by the community. By licensing the software under the Apache/MIT license, we want developers to use it without being bound by business licenses, or having to think about the implications of GPL-like licenses.
- Client Diversity: The Ethereum protocol becomes more antifragile when no node implementation dominates. This ensures that if there's a software bug, the network does not finalize a bad block. By building a new client, we hope to contribute to Ethereum's antifragility.
- Support as many EVM chains as possible: We aspire that Reth can full-sync not only Ethereum, but also other chains like Optimism, Polygon, BNB Smart Chain, and more. If you're working on any of these projects, please reach out.
- Configurability: We want to solve for node operators that care about fast historical queries, but also for hobbyists who cannot operate on large hardware. We also want to support teams and individuals who want both sync from genesis and via "fast sync". We envision that Reth will be configurable enough and provide configurable "profiles" for the tradeoffs that each team faces.
Status
The project is not ready for use. We hope to have full sync implemented sometime in Q1 2023, followed by optimizations. In the meantime, we're working on making sure every crate of the repository is well documented, abstracted and tested.
For Developers
Running Reth
See the Reth Book for instructions on how to run Reth.
Build & Test
Rust minimum required version to build this project is 1.65.0 published 02.11.2022
Prerequisites:
- Debian
libclanglibclang-dev
To fully test Reth, you will need to have Geth installed, but it is possible to run a subset of tests without Geth.
First, clone the repository:
git clone https://github.com/paradigmxyz/reth
cd reth
Next, run the tests:
# Without Geth
cargo test --all
# With Geth
cargo test --all --features geth-tests
We recommend using cargo nextest to speed up testing. With nextest installed, simply substitute cargo test with cargo nextest run.
Contributing
If you want to contribute, or follow along with contributor discussion, you can use our main telegram to chat with us about the development of Reth!
See our contributor docs for more information on the project.
A good starting point is Project Layout which gives an overview of the repository's structure, and descriptions for each package.
Our contributor guidelines can be found in CONTRIBUTING.md.
Getting Help
If you have any questions, first see if the answer to your question can be found in the book.
If the answer is not there:
- Join the Telegram to get help, or
- Open a discussion with your question, or
- Open an issue with the bug
Security
See SECURITY.md.
Acknowledgements
Reth is a new implementation of the Ethereum protocol. In the process of developing the node we investigated the design decisions other nodes have made to understand what is done well, what is not, and where we can improve the status quo.
None of this would have been possible without them, so big shoutout to the teams below:
- Geth: We would like to express our heartfelt gratitude to the go-ethereum team for their outstanding contributions to Ethereum over the years. Their tireless efforts and dedication have helped to shape the Ethereum ecosystem and make it the vibrant and innovative community it is today. Thank you for your hard work and commitment to the project.
- Erigon (fka Turbo-Geth): Erigon pioneered the "Staged Sync" architecture that Reth is using, as well as introduced MDBX as the database of choice. We thank Erigon for pushing the state of the art research on the performance limits of Ethereum nodes.
- Akula: Reth uses forks of the Apache versions of Akula's MDBX Bindings, FastRLP and ECIES . Given that these packages were already released under the Apache License, and they implement standardized solutions, we decided not to reimplement them to iterate faster. We thank the Akula team for their contributions to the Rust Ethereum ecosystem and for publishing these packages.
🚧 WARNING: UNDER CONSTRUCTION 🚧
This project is work in progress and subject to frequent changes as we are still working on wiring up each individual node component into a full syncing pipeline.
It has not been audited for security purposes and should not be used in production yet.
We will be updating the documentation with the completion status of each component, as well as include more contributing guidelines (design docs, architecture diagrams, repository layouts) and "good first issues". See the "Contributing and Getting Help" section above for more.
We appreciate your patience until we get there. Until then, we are happy to answer all questions in the Telegram link above.
Download Details:
Author: Paradigmxyz
Source Code: https://github.com/paradigmxyz/reth
License: Apache-2.0, MIT licenses found
#rust #system #modular #ethereum #blockchain
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1679593320
Reth: Modular, Contributor-friendly & Blazing-fast Implementation
reth 🏗️🚧
Modular, contributor-friendly and blazing-fast implementation of the Ethereum protocol
The project is still work in progress, see the disclaimer below.
What is Reth? What are its goals?
Reth (short for Rust Ethereum, pronunciation) is a new Ethereum full node implementation that is focused on being user-friendly, highly modular, as well as being fast and efficient. Reth is an Execution Layer (EL) and is compatible with all Ethereum Consensus Layer (CL) implementations that support the Engine API. It is originally built and driven forward by Paradigm, and is licensed under the Apache and MIT licenses.
As a full Ethereum node, Reth allows users to connect to the Ethereum network and interact with the Ethereum blockchain. This includes sending and receiving transactions/logs/traces, as well as accessing and interacting with smart contracts. Building a successful Ethereum node requires creating a high-quality implementation that is both secure and efficient, as well as being easy to use on consumer hardware. It also requires building a strong community of contributors who can help support and improve the software.
More concretely, our goals are:
- Modularity: Every component of Reth is built to be used as a library: well-tested, heavily documented and benchmarked. We envision that developers will import the node's crates, mix and match, and innovate on top of them. Examples of such usage include but are not limited to spinning up standalone P2P networks, talking directly to a node's database, or "unbundling" the node into the components you need. To achieve that, we are licensing Reth under the Apache/MIT permissive license. You can learn more about the project's components here.
- Performance: Reth aims to be fast, so we used Rust and the Erigon staged-sync node architecture. We also use our Ethereum libraries (including ethers-rs and revm) which we’ve battle-tested and optimized via Foundry.
- Free for anyone to use any way they want: Reth is free open source software, built for the community, by the community. By licensing the software under the Apache/MIT license, we want developers to use it without being bound by business licenses, or having to think about the implications of GPL-like licenses.
- Client Diversity: The Ethereum protocol becomes more antifragile when no node implementation dominates. This ensures that if there's a software bug, the network does not finalize a bad block. By building a new client, we hope to contribute to Ethereum's antifragility.
- Support as many EVM chains as possible: We aspire that Reth can full-sync not only Ethereum, but also other chains like Optimism, Polygon, BNB Smart Chain, and more. If you're working on any of these projects, please reach out.
- Configurability: We want to solve for node operators that care about fast historical queries, but also for hobbyists who cannot operate on large hardware. We also want to support teams and individuals who want both sync from genesis and via "fast sync". We envision that Reth will be configurable enough and provide configurable "profiles" for the tradeoffs that each team faces.
Status
The project is not ready for use. We hope to have full sync implemented sometime in Q1 2023, followed by optimizations. In the meantime, we're working on making sure every crate of the repository is well documented, abstracted and tested.
For Developers
Running Reth
See the Reth Book for instructions on how to run Reth.
Build & Test
Rust minimum required version to build this project is 1.65.0 published 02.11.2022
Prerequisites:
- Debian
libclanglibclang-dev
To fully test Reth, you will need to have Geth installed, but it is possible to run a subset of tests without Geth.
First, clone the repository:
git clone https://github.com/paradigmxyz/reth
cd reth
Next, run the tests:
# Without Geth
cargo test --all
# With Geth
cargo test --all --features geth-tests
We recommend using cargo nextest to speed up testing. With nextest installed, simply substitute cargo test with cargo nextest run.
Contributing
If you want to contribute, or follow along with contributor discussion, you can use our main telegram to chat with us about the development of Reth!
See our contributor docs for more information on the project.
A good starting point is Project Layout which gives an overview of the repository's structure, and descriptions for each package.
Our contributor guidelines can be found in CONTRIBUTING.md.
Getting Help
If you have any questions, first see if the answer to your question can be found in the book.
If the answer is not there:
- Join the Telegram to get help, or
- Open a discussion with your question, or
- Open an issue with the bug
Security
See SECURITY.md.
Acknowledgements
Reth is a new implementation of the Ethereum protocol. In the process of developing the node we investigated the design decisions other nodes have made to understand what is done well, what is not, and where we can improve the status quo.
None of this would have been possible without them, so big shoutout to the teams below:
- Geth: We would like to express our heartfelt gratitude to the go-ethereum team for their outstanding contributions to Ethereum over the years. Their tireless efforts and dedication have helped to shape the Ethereum ecosystem and make it the vibrant and innovative community it is today. Thank you for your hard work and commitment to the project.
- Erigon (fka Turbo-Geth): Erigon pioneered the "Staged Sync" architecture that Reth is using, as well as introduced MDBX as the database of choice. We thank Erigon for pushing the state of the art research on the performance limits of Ethereum nodes.
- Akula: Reth uses forks of the Apache versions of Akula's MDBX Bindings, FastRLP and ECIES . Given that these packages were already released under the Apache License, and they implement standardized solutions, we decided not to reimplement them to iterate faster. We thank the Akula team for their contributions to the Rust Ethereum ecosystem and for publishing these packages.
🚧 WARNING: UNDER CONSTRUCTION 🚧
This project is work in progress and subject to frequent changes as we are still working on wiring up each individual node component into a full syncing pipeline.
It has not been audited for security purposes and should not be used in production yet.
We will be updating the documentation with the completion status of each component, as well as include more contributing guidelines (design docs, architecture diagrams, repository layouts) and "good first issues". See the "Contributing and Getting Help" section above for more.
We appreciate your patience until we get there. Until then, we are happy to answer all questions in the Telegram link above.
Download Details:
Author: Paradigmxyz
Source Code: https://github.com/paradigmxyz/reth
License: Apache-2.0, MIT licenses found
1612595276
Fast Fit Keto - {Update 2021} Review,Price & Read More!
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What is FastSwap (FAST) | What is FAST token
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1660370580
Ranger: A Fast Implementation Of Random forests
ranger: A Fast Implementation of Random Forests
Marvin N. Wright
Introduction
ranger is a fast implementation of random forests (Breiman 2001) or recursive partitioning, particularly suited for high dimensional data. Classification, regression, and survival forests are supported. Classification and regression forests are implemented as in the original Random Forest (Breiman 2001), survival forests as in Random Survival Forests (Ishwaran et al. 2008). Includes implementations of extremely randomized trees (Geurts et al. 2006) and quantile regression forests (Meinshausen 2006).
ranger is written in C++, but a version for R is available, too. We recommend to use the R version. It is easy to install and use and the results are readily available for further analysis. The R version is as fast as the standalone C++ version.
Installation
R version
To install the ranger R package from CRAN, just run
install.packages("ranger")
R version >= 3.1 is required. With recent R versions, multithreading on Windows platforms should just work. If you compile yourself, the new RTools toolchain is required.
To install the development version from GitHub using devtools, run
devtools::install_github("imbs-hl/ranger")
Standalone C++ version
To install the C++ version of ranger in Linux or Mac OS X you will need a compiler supporting C++11 (i.e. gcc >= 4.7 or Clang >= 3.0) and Cmake. To build start a terminal from the ranger main directory and run the following commands
cd cpp_version
mkdir build
cd build
cmake ..
make
After compilation there should be an executable called "ranger" in the build directory.
To run the C++ version in Microsoft Windows please cross compile or ask for a binary.
Usage
R version
For usage of the R version see ?ranger in R. Most importantly, see the Examples section. As a first example you could try
ranger(Species ~ ., data = iris)
Standalone C++ version
In the C++ version type
./ranger --help
for a list of commands. First you need a training dataset in a file. This file should contain one header line with variable names and one line with variable values per sample (numeric only). Variable names must not contain any whitespace, comma or semicolon. Values can be seperated by whitespace, comma or semicolon but can not be mixed in one file. A typical call of ranger would be for example
./ranger --verbose --file data.dat --depvarname Species --treetype 1 --ntree 1000 --nthreads 4
If you find any bugs, or if you experience any crashes, please report to us. If you have any questions just ask, we won't bite.
Please cite our paper if you use ranger.
References
- Wright, M. N. & Ziegler, A. (2017). ranger: A fast implementation of random forests for high dimensional data in C++ and R. J Stat Softw 77:1-17. https://doi.org/10.18637/jss.v077.i01.
- Schmid, M., Wright, M. N. & Ziegler, A. (2016). On the use of Harrell's C for clinical risk prediction via random survival forests. Expert Syst Appl 63:450-459. https://doi.org/10.1016/j.eswa.2016.07.018.
- Wright, M. N., Dankowski, T. & Ziegler, A. (2017). Unbiased split variable selection for random survival forests using maximally selected rank statistics. Stat Med 36:1272-1284. https://doi.org/10.1002/sim.7212.
- Nembrini, S., König, I. R. & Wright, M. N. (2018). The revival of the Gini Importance? Bioinformatics. https://doi.org/10.1093/bioinformatics/bty373.
- Breiman, L. (2001). Random forests. Mach Learn, 45:5-32. https://doi.org/10.1023/A:1010933404324.
- Ishwaran, H., Kogalur, U. B., Blackstone, E. H., & Lauer, M. S. (2008). Random survival forests. Ann Appl Stat 2:841-860. https://doi.org/10.1097/JTO.0b013e318233d835.
- Malley, J. D., Kruppa, J., Dasgupta, A., Malley, K. G., & Ziegler, A. (2012). Probability machines: consistent probability estimation using nonparametric learning machines. Methods Inf Med 51:74-81. https://doi.org/10.3414/ME00-01-0052.
- Hastie, T., Tibshirani, R., Friedman, J. (2009). The Elements of Statistical Learning. Springer, New York. 2nd edition.
- Geurts, P., Ernst, D., Wehenkel, L. (2006). Extremely randomized trees. Mach Learn 63:3-42. https://doi.org/10.1007/s10994-006-6226-1.
- Meinshausen (2006). Quantile Regression Forests. J Mach Learn Res 7:983-999. http://www.jmlr.org/papers/v7/meinshausen06a.html.
- Sandri, M. & Zuccolotto, P. (2008). A bias correction algorithm for the Gini variable importance measure in classification trees. J Comput Graph Stat, 17:611-628. https://doi.org/10.1198/106186008X344522.
- Coppersmith D., Hong S. J., Hosking J. R. (1999). Partitioning nominal attributes in decision trees. Data Min Knowl Discov 3:197-217. https://doi.org/10.1023/A:1009869804967.
Download Details:
Author: imbs-hl
Source Code: https://github.com/imbs-hl/ranger
1624682160
Chatbots In Mental Health. Friendly But Not Too Friendly.
Mental health is the proverbial elephant in the room that no one wants to address. India is on the verge of a mental health epidemic, yet one would hardly find a public discourse on ways to prevent it or treat it. There are hardly any steps being taken at the scale required to manage this the increasing number of people with mental health issues. Corona is to blame for this massive spike in the number of cases. The isolation because of lockdown, fear and uncertainty due to job cuts and general discomfort due to the inability to control several aspects of life has triggered severe mental trauma in people across the country. The issue is even more complicated by the fact that no one has any idea when things will ever return to normal, if at all.
There is a huge gap in the treatment that should be available and of the help available at hand, easily and cost-effectively. Even in developed countries, the ratio of psychiatrists, psychologists, psychiatric social workers, and mental health nurses to patients is 1: 10,000. The lacuna in the system ensures that most people suffering from mental health issues are never able to get the help they need.
Many digital interfaces are emerging as viable complementary services to fulfil some Artificial intelligence-based solutions are developed by working closely with healthcare professionals to provide a person with assistance, and often, some sort of companionship. This can also bring down the cost of psychiatric diagnosis and treatment. Most people have faced stigma prevalent in our society when it comes to its psychiatric disorders, which often hampers with effective treatment.
Chatbots are Natural Language Processing(NLP) based frameworks that interact with human users using spoken, written, and visual languages. Built specifically to communicate with people struggling with mental problems, Chatbots have the potential to be useful tools. According to experts, “suicide prediction and prevention, identification of predictors for a response, and identifying which particular drug is best suited for a particular patient are some of the areas where AI has been found to be useful in psychiatry.”
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