| #!/usr/bin/env python | |
| # -*- encoding: utf-8 -*- | |
| """xml2json.py Convert XML to JSON | |
| Relies on ElementTree for the XML parsing. This is based on | |
| pesterfish.py but uses a different XML->JSON mapping. | |
| The XML->JSON mapping is described at | |
| http://www.xml.com/pub/a/2006/05/31/converting-between-xml-and-json.html |
How to use sed, a special editor for modifying files automatically. If you want to write a program to make changes in a file, sed is the tool to use.
There are a few programs that are the real workhorse in the UNIX toolbox. These programs are simple to use for simple applications, yet have a rich set of commands for performing complex actions. Don't let the complex potential of
This guide helps to configure the hibernation on a default Fedora35 (also worked fine in previous Fedora34) installation by using a swap file. The Fedora35 installation comes with btrfs as default filesystem. Also, it comes with a zram swap device:
$ swapon
NAME TYPE SIZE USED PRIO
/dev/zram0 partition 8G 0B 100
Find the Discord channel in which you would like to send commits and other updates
In the settings for that channel, find the Webhooks option and create a new webhook. Note: Do NOT give this URL out to the public. Anyone or service can post messages to this channel, without even needing to be in the server. Keep it safe!
| import androidx.compose.animation.core.* | |
| import androidx.compose.foundation.background | |
| import androidx.compose.foundation.layout.* | |
| import androidx.compose.foundation.shape.CircleShape | |
| import androidx.compose.material.MaterialTheme | |
| import androidx.compose.material.Text | |
| import androidx.compose.runtime.Composable | |
| import androidx.compose.runtime.getValue | |
| import androidx.compose.ui.Alignment | |
| import androidx.compose.ui.Modifier |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| import seaborn as sns | |
| def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14): | |
| """Prints a confusion matrix, as returned by sklearn.metrics.confusion_matrix, as a heatmap. | |
| Note that due to returning the created figure object, when this funciton is called in a | |
| notebook the figure willl be printed twice. To prevent this, either append ; to your | |
| function call, or modify the function by commenting out the return expression. |
| <div x-data="googlePlacesAutocomplete" class="grid grid-cols-3 gap-2"> | |
| <input type="text" x-model="address.address1" x-ref="googleAutocomplete" autocomplete="chrome-off" class="col-span-3 sm:col-span-2 order-1" placeholder="Add‌ress"> | |
| <input type="text" x-model="address.address2" placeholder="Apt/Ste" class="col-span-3 sm:col-span-1 order-2"> | |
| <input type="text" x-model="address.city" placeholder="Ci‌ty" class="col-span-1" x-bind:class="`order-${order.locality}`"> | |
| <select x-model="address.state" placeholder="State" class="col-span-1 order-4" x-show="isUSA"> | |
| <option value="">State</option> | |
| <option value="AL">Alabama</option> | |
| <option value="AK">Alaska</option> | |
| <option value="AZ">Arizona</option> | |
| <option value="AR">Arkansas</option> |
Coredump contains stack information as well. If you can use this stack information along with the EBP and EIP register values in the coredump file, you can print the stack trace. I had written a program to do this. You can find the program in the following link.
https://gist.github.com/root42/c979b037f85dc4b2be1f3735afedeb1d
Usage: Compile the above program and give the corefile when you execute it.
$corestrace core
If you want symbols also to be printed, you do like this: Let's assume the program that generated the core is 'test'.
| // ==UserScript== | |
| // @name Weibo Huati Check-in | |
| // @description 超级话题集中签到 | |
| // @namespace https://greasyfork.org/users/10290 | |
| // @version 0.4.2018053114 | |
| // @author xyau | |
| // @match http*://*.weibo.com/* | |
| // @match http*://weibo.com/* | |
| // @icon https://n.sinaimg.cn/photo/5b5e52aa/20160628/supertopic_top_area_big_icon_default.png | |
| // @grant GM_getValue |
| from typing import Optional, Tuple | |
| import torch | |
| from torch.utils.data import Dataset, random_split | |
| def train_test_split( | |
| dataset: Dataset, | |
| test_ratio: float, | |
| seed: Optional[int] = None, |