Performance – Would a long article representing SVG rendered letters (and not a font) be performant (usable and scrollable)?

I would like to know if there are any websites Each character / character is an SVG pathinstead of using a font.

I look at places like here that discuss icon fonts and their relationship to accessibility and some issues they solve. But I'm wondering if you could do without a font like OTF / TTF / WOFF and instead use SVG paths everywhere.

It looks as though you would lose the SEO benefit if you did not mirror your SVG path-controlled text content with regular font content among the scenes, but I definitely want to make sure of a performance Perspective, if it were technically possible to have a huge long 100-page article and quickly leaf through it with 12-16px writing, with no flickering or performance issues. That would be an interesting check.

SQL Server – Draw values ​​with letters and numbers, but remove all letters

This error occurs whenever I run my query.
Enter the image description here

I believe that to fix this, I need to format the column that contains these values ​​into a separate number. I've already tried the Format () and Replace () functions, but they did not work for me. Any other suggestions?

CHOOSE
e.Accounting code AS [Vehicle],
Concat (e.year + & # 39 ;, e.make + & # 39 ;, e.model + & # 39 ;, cast (e.)[Description] AS VARCHAR (80))) AS NAME,
Iif (cff.stringtype = & # 39 ;, cff1.stringtype, cff.stringtype) AS & # 39; operator & # 39 ;,
fta.fluid,
so.odometer,
CASE
WHEN
COALESCE (Lag (e.accountingcode) OVER (partition after e.accountingcode)
SORT BY
e.accountingcode, so.odometer), 0) <> e.accountingcode
THEN
0
OTHERWISE
Lag (so.odometer) OVER (partition by e.accountingcode)
SORT BY
e.accountingcode, so.odometer)
THE END
AS & # 39; Previous Odometer & # 39 ;, so.odometer - Iif ((
CASE
WHEN
COALESCE (Lag (e.accountingcode) OVER (partition after e.accountingcode)
SORT BY
e.accountingcode, so.odometer), 0) <> e.accountingcode
THEN
0
OTHERWISE
Lag (so.odometer) OVER (partition by e.accountingcode)
SORT BY
e.accountingcode, so.odometer)
THE END
) = 0, so.
CASE
WHEN
COALESCE (Lag (e.accountingcode) OVER (partition after e.accountingcode)
SORT BY
e.accountingcode, so.odometer), 0) <> e.accountingcode
THEN
0
OTHERWISE
Lag (so.odometer) OVER (partition by e.accountingcode)
SORT BY
e.accountingcode, so.odometer)
THE END
) AS "Miles Traveled", sh.hour,
CASE
WHEN
COALESCE (Lag (e.accountingcode) OVER (partition after e.accountingcode)
SORT BY
e.accountingcode, sh.hour), 0) <> e.accountingcode
THEN
0
OTHERWISE
Lag (sh.hour) OVER (Partition BY e.accountingcode
SORT BY
e.accountingcode, sh.hour)
THE END
AS "Earlier Hours", sh.hour - Iif ((
CASE
WHEN
COALESCE (Lag (e.accountingcode) OVER (partition after e.accountingcode)
SORT BY
e.accountingcode, sh.hour), 0) <> e.accountingcode
THEN
0
OTHERWISE
Lag (sh.hour) OVER (Partition BY e.accountingcode
SORT BY
e.accountingcode, sh.hour)
THE END
) = 0, sh.hour,
CASE
WHEN
COALESCE (Lag (e.accountingcode) OVER (partition after e.accountingcode)
SORT BY
e.accountingcode, sh.hour), 0) <> e.accountingcode
THEN
0
OTHERWISE
Lag (sh.hour) OVER (Partition BY e.accountingcode
SORT BY
e.accountingcode, sh.hour)
THE END
) AS & # 39; used hours & # 39; fta.fifototalcost / fta.totalgallons AS [Avg Price], fta.totalgallons AS [Total Gallons], fta.fifototalcost AS [Total Cost]

The e.AccountingCode column contains the incorrect value.

python – My code displays a set of letters for letters including spaces

Can I make it easier anyway?

My code shows it correctly:

v = lambda x: [x[0:i+1] for i within reach (len (x))]+[x[0:-i-1] for i within reach (len (x))]print (* v (input ("Enter a sentence:")), sep = " n")

That works too:

Text = input ("Enter a sentence:")
v = [text[:i] for i in the range (1, len (text) +1)]print (* (v + v[::-1]), sep = & # 39; n & # 39;

The following will be printed:

Enter something: test
t
th
tes
exam
tes
th
t

EDIT: Answered

forms – Webform check Allow only lowercase letters

I have an e-mail field in a web form that triggers a rule that compares the field with a user's e-mail. The problem is that the rules are case-sensitive. If the Web Form field has uppercase letters and the user's e-mail address is not, they do not match as they should.

There are two options for webform validation that allow me to force the email to contain only lowercase letters.

Regular expression, upper and lower case is considered
Checks the user-entered text with a regular case-sensitive expression. Works with: Email, hidden, number, text box, text box.
Regular expression, uppercase and lowercase is not considered
Checks the user-entered text with a regular expression that is case-insensitive. Works with: Email, hidden, number, text box, text box.

Which one should I use, and what is the regular expression so that uppercase letters are not allowed?

Many Thanks!

c – Allows the user to enter letters only when registering.

Condition to receive only letters in this

scanf ("% s", & name);

int check (struct reg list)[]char name[128]) {

int i;
for (i = 0; i <reg_size; i ++) {
if (! strncmp (list[i].name, name, 128))
Return 1;
}
Return 0;
}

Data record invalid (structure list)[5]) {
int i;
for (i = 0; i <5; ++ i)
char name[128];
printf ("enter name:  n");
scanf ("% s", & name);
if (strcmp[i] < '0' || nome[i] >    & # 39; # 9 & 39);
printf ("Enter a valid name");
}
otherwise if (check (list, name)) {
reg_size ++;
list[reg_size-1].id = reg_size;
strcpy[reg_size-1]name, name);
list[reg_size-1].cred = 0.0;
printf (" nuser% s created with id% d  n  n", list[reg_size-1].name, reg_size);
}
otherwise
{
printf (" nName not available  n  n");
}
}

python – Counting lower case and non-lower case letters for multi-condition token text

Assuming that the text is tagged with blanks for a natural language processing task, the goal is to check the number of words (case insensitive) and check them under certain conditions.

The current code works as expected, but is there a way to optimize the conditions for an optimum to make it cleaner or more direct?

First, the function must determine if:

  • Token is an XML tagIf so, ignore it and switch to the next token
  • Token is predefined in a list delayed sentence startIf so, ignore it and switch to the next token
Skip # XML tags.
if re.search (r "(]*>) ", token):
continue
# Skip when sentence symbols begin.
elif-token in self.DELAYED_SENT_START:
continue

Then it is checked if the option should be switched is_first_word Condition if the token is the first word of the sentence; Note that each line can contain many sentences.

  • if the token is in a list of predefined sentence ends and the is_first_word Condition is False, then set is_first_word to True and then on to the next token

  • If nothing is to be noted, since none of the characters falls under the letters regex, then put is_first_word False and on to the next token

# Reset the `is_first_word` after sending end symbols.
if not is_first_word and token in self.SENT_END:
is_first_word = true
continue

# Skips words that have nothing to keep in mind.
if not re.search (r "[{}]".format (ll_lu_lt), tokens):
is_first_word = false
continue

Then finally after checking for non-weightable words, and the feature finally continues to update the weight.

First, all weights are set to 0 and then 1, if they are not is_first_word,

Then if the möglicherweise_use_first_token If the option is set, check if the token is written in lower case. In this case, use the word. Otherwise, assign it a weight of 0.1. This is better than setting the weight to 0.

Finally, update the weights if it is not zero. And set that is_first_word switch to false

current_word_weight = 0
if not is_first_word:
current_word_weight = 1
elif maybe_use_first_token:
# Gated special treatment of the first sentence word.
# Check if the first character set of the token is lowercase.
if token[0].is deeper ():
current_word_weight = 1
elif i == 1:
current_word_weight = 0.1

if current_word_weight> 0:
casing[token.lower()][token]    + = current word weight

is_first_word = false

The full code is in Train() Function below:

#! / usr / bin / env python3
# - * - Coding: utf-8 - * -

import re

import from collections defaultdict, Counter
from six import text_type

of sacremoses.corpus import Perluniprops
import nonbreaking prefixes from sacremoses.corpus

perluniprops = Perluniprops ()


Class MosesTruecaser (Object):
"" "
This is a python port of the Moses Truecaser
https://github.com/moses-smt/mosesdecoder/blob/master/scripts/recaser/train-truecaser.perl
https://github.com/moses-smt/mosesdecoder/blob/master/scripts/recaser/truecase.perl
"" "
# Perl Unicode Properties fonts.
Lowercase_Letter = text_type (& # 39;. Join (perluniprops.chars (& # 39; Lowercase_Letter & # 39;)))
Uppercase_Letter = text_type (& # 39;. Join (perluniprops.chars (& # 39; Uppercase_Letter & # 39;)))
Titlecase_Letter = text_type (& # 39;. Join (perluniprops.chars (& # 39; Uppercase_Letter & # 39;)))

def __init __ (self):
# Initialize object.
super (MosesTruecaser, itself) .__ init__ ()
# Initialize the language-specific, break-through prefixes.
self.SKIP_LETTERS_REGEX = r "[{}{}{}]".format (self.Lowercase_Letter,
self.Uppercase_Letter, self.Titlecase_Letter)

self.SENT_END = [".", ":", "?", "!"]
        self.DELAYED_SENT_START =["(""["""""'""&"""["(""["""""'""'""""," & # 91; "," & # 93; "]def train (self, filename, possibly_use_first_token = false):
housing = defaultdict (counter)
with open (filename) as fin:
for line in fin:
# Follow the first words in the sentences of the line.
is_first_word = true
for i, token in enumeration (line.split ()):
Skip # XML tags.
if re.search (r "(]*>) ", token):
continue
# Skip when sentence symbols begin.
elif-token in self.DELAYED_SENT_START:
continue

# Reset the `is_first_word` after sending end symbols.
if not is_first_word and token in self.SENT_END:
is_first_word = true
continue

# Skips words that have nothing to handle.
If not, re.search (self.SKIP_LETTERS_REGEX, tokens):
is_first_word = false
continue

current_word_weight = 0
if not is_first_word:
current_word_weight = 1
elif maybe_use_first_token:
# Gated special treatment of the first sentence word.
# Check if the first character set of the token is lowercase.
if token[0].is deeper ():
current_word_weight = 1
elif i == 1:
current_word_weight = 0.1

if current_word_weight> 0:
casing[token.lower()][token]    + = current word weight

is_first_word = false
Return housing

Sample input: https://gist.github.com/alvations/33799dedc4bab20dd24fb64970451e49

Expected issue of Train(): https://gist.github.com/alvations/d6d2363bca9a4a9a16e8076f8e8c1e60

Windows 7 – Remove drive letters from the first primary active boot partition or delete and still boot

I have created an image backup and restored it to a VHD file. The original drive has three primary partitions. It also has two CD-ROM drives that appear as the first two volumes. How diskpart lists the volumes of the original disk:

DISCARD> list vol

Volume ### Ltr Label Fs Type Size Status Info
---------- --- ----------- ----- ---------- ------- ---- ----- --------
Volume 0 E Jun 06 2018 UDF-DVD-ROM 125 MB Free of errors
Volume 1 L DVD-ROM 0 B No media
Volume 2 SYSTEM NTFS partition 100 MB Error free system
Volume 3 C operating system NTFS partition 1384 GB Healthy start
Volume 4 D HP_RECOVERY NTFS partition 12 GB error free

I do not know where the "info" column values ​​come from. Note that Volume 2 (the first primary partition on the drive, which in my opinion is also the active partition with the MBR information) is NOT assigned a drive letter.

You can see here that the NoDefaultDriveLetter attribute is set and that the second and third primary partitions on the drive DO NOT contain this attribute:

DISCOUNT> sel vol 2

Volume 2 is the selected volume.

DISKPART> Attributes Volume
Read only: no
Hidden: No.
No Default drive letter: Yes
Shadow Copy: No.

DISKPART> Select volume 3

Volume 3 is the selected volume.

DISKPART> Attributes Volume
Read only: no
Hidden: No.
No Default drive letter: No.
Shadow Copy: No.

DISKPART> Select volume 4

Volume 4 is the selected volume.

DISKPART> Attributes Volume
Read only: no
Hidden: No.
No Default drive letter: No.
Shadow Copy: No.

Now I've tried to set the NoDefaultDriveLetter attribute for Volume 2. However, this affects ALL partitions on the hard disk. Therefore, NONE of the partitions gets a drive letter. The DiskPart documentation clearly states that while the attribute is set for the volume, it executes at the volume level and affects all volumes on the same volume. It sounds like they are not working properly, they just document that they affect the entire hard drive.

Well, somehow my Dell computer was partitioned so that only the very first partition had the NoDefaultDriveLetter attribute. So I would think that there must be some software for that? My first question would be: Does anyone know how that works?

I have a follow-up question if the answer to the first question is that it is by no means possible.

This system partition contains the hidden Boot folder and the BCD file. There is not much else there. Is one of these options possible?

1) Since this is a VM (for Hyper-V), I can simply create a new VHD, move the system partition to that drive, delete it from the original, and set the NoDefaultDriveLetter attribute to the new VHD. Then use the BootRec utility to make sure it finds and references the operating system on drive C.

2) Can I just delete the entire partition and put the MBR / BCD on the C drive with the BootRec program? Or you can not put this on the same partition where the operating system is located?

Any advice appreciated!