Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.
![Screenshot 2023-12-18 at 10 40 27 PM](https://private-user-images.githubusercontent.com/3837836/291468646-4c30ad72-76ee-4939-a5fb-16b570d38cf2.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.V6ELDVU6dvXNFDVBwHrZXy4wQYpg6K6wUAjkBjUHRVM)
A dynamic DNS. DNS stands for Domain Name Server, which, in other words, is basically the server that answer your queries when you search for a hostname on the internet.
Example: If you search for "google.com" there will always (probably) a server that points out to that hostname and tells you the information the computer needs; the IP address.
If you want to give it a test, you only have to open your terminal and type "ping google.com" and you will see the real IP address appear! In my case it's 216.58.201.174 .
Anyways.. A DDNS is useful if you want to link or put a hostname to an IP that is not STATIC.
python main.py data.json
from torchtext import data | |
class DataFrameDataset(data.Dataset): | |
def __init__(self, df, text_field, label_field, is_test=False, **kwargs): | |
fields = [('text', text_field), ('label', label_field)] | |
examples = [] | |
for i, row in df.iterrows(): | |
label = row.sentiment if not is_test else None | |
text = row.text |
204.15.20.0/22 | |
69.63.176.0/20 | |
66.220.144.0/20 | |
66.220.144.0/21 | |
69.63.184.0/21 | |
69.63.176.0/21 | |
74.119.76.0/22 | |
69.171.255.0/24 | |
173.252.64.0/18 | |
69.171.224.0/19 |
#!/bin/env python | |
from time import sleep | |
import signal | |
from jpype import * | |
startJVM(getDefaultJVMPath()) | |
def handler(signum, frame): | |
raise KeyboardInterrupt |
# start GremlinServer | |
# bin/gremlin-server.sh -i org.apache.tinkerpop gremlin-python 3.2.2-SNAPSHOT | |
# bin/gremlin-server.sh conf/gremlin-server-modern-py.yaml | |
from gremlin_python.process.graph_traversal import GraphTraversal | |
from gremlin_python.process.graph_traversal import GraphTraversalSource | |
from gremlin_python.process.graph_traversal import __ | |
from gremlin_python.process.traversal import Operator | |
from gremlin_python.structure.io.graphson import GraphSONReader |
"""Global LRU caching utility. For that little bit of extra speed. | |
The caching utility provides a single wrapper function that can be used to | |
provide a bit of extra speed for some often used function. The cache is an LRU | |
cache including a key timeout. | |
Usage:: | |
import cache | |
@cache.memoize |
Tested on Ubuntu 14.04.
Install desired version of python 3 (e.g. 3.5.1). Make sure to use the --enable-shared
flag to generate python shared libraries, which will later be linked to.
env PYTHON_CONFIGURE_OPTS="--enable-shared" pyenv install 3.5.1