1 - access https://www.linkedin.com/feed/following
2 - Scroll a little
3 - Open developer console;
4 - place the code in this gist
credits/ref: https://mighil.com/mass-unfollow-people-on-linkedin/
#!/usr/bin/env bash | |
set -o errexit | |
set -o nounset | |
set -o pipefail | |
if [[ "${TRACE-0}" == "1" ]]; then | |
set -o xtrace | |
fi | |
# Check for upgradable packages |
#!/usr/bin/env bash | |
set -o errexit | |
set -o nounset | |
set -o pipefail | |
if [[ "${TRACE-0}" == "1" ]]; then | |
set -o xtrace | |
fi | |
# Function to send a message to Slack |
alt_map = {'ins':'0'} | |
complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'} | |
def reverse_complement(seq): | |
for k,v in alt_map.iteritems(): | |
seq = seq.replace(k,v) | |
bases = list(seq) | |
bases = reversed([complement.get(base,base) for base in bases]) | |
bases = ''.join(bases) | |
for k,v in alt_map.iteritems(): |
1 - access https://www.linkedin.com/feed/following
2 - Scroll a little
3 - Open developer console;
4 - place the code in this gist
credits/ref: https://mighil.com/mass-unfollow-people-on-linkedin/
# convert any kB lines to MB: | |
awk '$3=="kB"{$2=$2/1024;$3="MB"} 1' /proc/meminfo | |
# converts to gigabytes: | |
awk '$3=="kB"{$2=$2/1024^2;$3="GB";} 1' /proc/meminfo | |
# convert to MB or GB as appropriate: | |
awk '$3=="kB"{if ($2>1024^2){$2=$2/1024^2;$3="GB";} else if ($2>1024){$2=$2/1024;$3="MB";}} 1' /proc/meminfo |
sudo apt-get update && sudo apt-get install -yqq daemonize dbus-user-session fontconfig | |
sudo daemonize /usr/bin/unshare --fork --pid --mount-proc /lib/systemd/systemd --system-unit=basic.target | |
exec sudo nsenter -t $(pidof systemd) -a su - $LOGNAME | |
snap version |
class Solution { | |
public: | |
vector<vector<string>> partition(string s) { | |
vector<vector<string>> result; | |
vector<string> part; | |
dfs(0, s, part, result); | |
return result; | |
} | |
void dfs(int i, string& s, vector<string>& part, vector<vector<string>>& result){ | |
if(i>=s.size()){ |
# Copy your updated FrequentWords function (along with all required subroutines) below this line | |
def FrequentWords(Text, k): | |
FrequentPatterns = [] # output variable | |
# your code here | |
Count = CountDict(Text, k) | |
m = max(Count.values()) | |
for i in Count: | |
if Count[i] == m: | |
FrequentPatterns.append(Text[i:i+k]) |