finagg
async-profiler
finagg | async-profiler | |
---|---|---|
17 | 10 | |
387 | 7,175 | |
- | 1.9% | |
8.1 | 8.7 | |
6 days ago | 8 days ago | |
Python | C++ | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
finagg
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This Week In Python
finagg – A Python package for aggregating and normalizing historical data from popular and free financial APIs
- FLaNK Stack 29 Jan 2024
- Show HN: Finagg – free and nearly unlimited financial data
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[D] Website to get historical price for agriculture commodities?
This is certainly a weird place to ask this question. That being said, you should explore the FRED API. Here's my project that implements most of it in Python: https://github.com/theOGognf/finagg The walkthrough shows you how to find what you're looking for
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Fundamental Data Sources
I created a Python package exactly for this. https://github.com/theOGognf/finagg. It aggregates historical fundamental data for whatever tickers you specify or from a subset of tickers. Let me know what you think
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Is accurate quarterly earnings data availible?
This package https://github.com/theOGognf/finagg already implements the complete SEC EDGAR REST API (disclaimer: I'm the author), and the archive-based API is in the works. I suggest you give it a go using the latest version off GitHub
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Sunday Daily Thread: What's everyone working on this week?
I've got some time set aside to implement a (file based) SEC EDGAR API described in this issue https://github.com/theOGognf/finagg/issues/43
- finagg: NEW Data - star count:107.0
async-profiler
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JVM Profiling in Action
We'll use async-profiler and flame graphs for profiling. To simplify the process, we'll run the code using JBang.
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The Return of the Frame Pointers
JIT'ed code is sadly poorly supported, but LLVM has had great hooks for noting each method that is produced and its address. So you can build a simple mixed-mode unwinder, pretty easily, but mostly in process.
I think Intel's DNN things dump their info out to some common file that perf can read instead, but because the *kernels* themselves reuse rbp throughout oneDNN, it's totally useless.
Finally, can any JVM folks explain this claim about DWARF info from the article:
> Doesn't exist for JIT'd runtimes like the Java JVM
that just sounds surprising to me. Is it off by default or literally not available? (Google searches have mostly pointed to people wanting to include the JNI/C side of a JVM stack, like https://github.com/async-profiler/async-profiler/issues/215).
- FLaNK Stack 29 Jan 2024
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Tracking Java Native Memory with JDK Flight Recorder
debugging native calls in itself is also painful. I have switched to using async-profiler (https://github.com/async-profiler/async-profiler) instead of JFR for most of my usecases.
A. it tracks native calls by default
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Show HN: Javaflame – Simple Flamegraph for your Java application
https://github.com/async-profiler/async-profiler#flame-graph...
Ok, Windows is not supported. But IntelliJ made a fork which works on Windows.
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Lettuce (Redis) + Mybatis (MySQL) take up most of the CPU in production - Is it normal? Did you observe that in your environment? Any ways to optimize it?
Hi, today I used async-profiler to check the CPU usage of my Spring Boot app (just a normal backend) in production. Surprisingly, Lettuce (Redis) + Mybatis (MySQL) take up most of the CPU time. I am not talking about wall time here, but CPU time, since I know database requests need to wait for milliseconds and thus wall time will be very long. Therefore, I wonder:
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A question about Http4s new major version
You can use async-profiler to see what is happening under the hood.
- Reducing code size in (Rust) librsvg by removing an unnecessary generic struct
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what is your favorite programming trick/tool that not many People know about?
I have used visual vm quite a bit. https://github.com/async-profiler/async-profiler is also amazing... Throw the binary on the system and fire it up. It also profiles down into native code as well if you do that kind of thing.
What are some alternatives?
pyautoenv - Automatically activate and deactivate Python environments as you move around the file system.
jmh - https://openjdk.org/projects/code-tools/jmh
sql-to-kml - Format SQL query results into a KML file.
container-jfr - Secure JDK Flight Recorder management for containerized JVMs
plombery - Python task scheduler with a user-friendly web UI
jfr-libraries - a list of libraries that generate JFR events
usepython - Run Python scripts in a Pyodide service worker
Arthas - Alibaba Java Diagnostic Tool Arthas/Alibaba Java诊断利器Arthas
bytewax - Python Stream Processing
opentelemetry-java-instrumentation - OpenTelemetry auto-instrumentation and instrumentation libraries for Java
java-snapshot-testing - Facebook style snapshot testing for JAVA Tests
junit-jfr - a JUnit 5 extension that generates JFR events