This is a collection of basic "recipes", many using twurl (the Swiss Army Knife for the Twitter API!) and jq to query the Twitter API and format the results. Also, some scripts to test or automate common actions.
Spawning multiple ffmpeg processes with xargs:
On standard NVIDIA GPUs (Not the Quadros and Tesla lines), NVENC encodes are limited to two simultaneous sessions. The sample below illustrates how to pass a list of AVI files to ffmpeg and encode them to HEVC on two encode sessions:
$ find Videos/ -type f -name \*.avi -print | sed 's/.avi$//' |\
xargs -n 1 -I@ -P 2 ffmpeg -i "@.avi" -c:a aac -c:v hevc_nvenc "@.mp4"
This will find all files with the ending .avi
in the directory Videos/
and transcode them into HEVC/H265+AAC files with the ending .mp4. The noteworthy part here is the -P 2
to xargs, which starts up to two processes in parallel.
The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.
The correct way of creating a private frok by duplicating the repo is documented here.
For this assignment the commands are:
- Create a bare clone of the repository.
(This is temporary and will be removed so just do it wherever.)
git clone --bare git@github.com:usi-systems/easytrace.git
Using perf:
$ perf record -g binary
$ perf script | stackcollapse-perf.pl | rust-unmangle | flamegraph.pl > flame.svg
NOTE: See @GabrielMajeri's comments below about the
-g
option.
I work as a full-stack developer at work. We are a Windows & Azure shop, so we are using Windows as our development platform, hence this customization.
For my console needs, I am using Cmder which is based on ConEmu with PowerShell as my shell of choice.
Yes, yes, I know nowadays you can use the Linux subsystem on Windows 10 which allow you to run Ubuntu on Windows. If you are looking for customization of the Ubuntu bash shell, check out this article by Scott Hanselman.
import pandas as pd | |
import pandas.io.sql as sqlio | |
import psycopg2 | |
conn = psycopg2.connect("host='{}' port={} dbname='{}' user={} password={}".format(host, port, dbname, username, pwd)) | |
sql = "select count(*) from table;" | |
dat = sqlio.read_sql_query(sql, conn) | |
conn = None |
# An example to get the remaining rate limit using the Github GraphQL API. | |
import requests | |
headers = {"Authorization": "Bearer YOUR API KEY"} | |
def run_query(query): # A simple function to use requests.post to make the API call. Note the json= section. | |
request = requests.post('https://api.github.com/graphql', json={'query': query}, headers=headers) | |
if request.status_code == 200: |
For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.
After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft
{ | |
"workbench.colorCustomizations": { | |
"terminal.foreground": "#839496", | |
"terminal.background": "#002833", | |
"terminal.ansiBlack": "#003541", | |
"terminal.ansiBlue": "#268bd2", | |
"terminal.ansiCyan": "#2aa198", | |
"terminal.ansiGreen": "#859901", | |
"terminal.ansiMagenta": "#d33682", | |
"terminal.ansiRed": "#dc322f", |
:80 { | |
root /serve | |
} |