TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #15056 · Aug 13

#kotlin#android#android_app#android_application#android_firewall#anti_censorship#anti_surveillance#censorship_circumvention#censorship_resistance#dns#dns_over_https#dnscrypt#firewall#internet_freedom#open_source#privacy_enhancing_technologies#wireguard Rethink DNS + Firewall + VPN for Android is an app that helps you control your internet privacy and security easily without needing root access. It combines a VPN using WireGuard, a firewall that blocks internet access for apps based on your preferences (like when apps run in the background or by category), and a DNS-over-HTTPS client that hides your DNS requests from ISPs and censors. You can route different apps through different VPN tunnels, block ads and malware sites, and monitor which apps connect to the internet. This gives you more control over your data, reduces tracking, and helps bypass censorship on your Android device. https://github.com/celzero/rethink-app

Results

1 similar post found

Search: #parallelism

当前筛选 #parallelism清除筛选
djangoproject

@djangoproject · Post #118 · 08/08/2016, 11:44 AM

https://docs.python.org/3/library/multiprocessing.html multiprocessing is a package that supports spawning processes using an API similar to the threading module. The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows. The #multiprocessing module also introduces #APIs which do not have analogs in the #threading#module. A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data #parallelism). The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module. This basic example of data parallelism using Pool,