Nov 052021While posting our game Walled Garden on reddit, we had a few people approach us regarding the games marketability. One of them being a guest poster for the website https://gameskeys.net/.
So, check them out! They are a great resource for purchasing super cheap games. The sites is also loaded with game reviews and guides.
Nov 032019Can't install security updates:
sudo apt-get update && sudo apt-get dist-upgrade
first enter the following command in the terminal
sudo rm /var/lib/apt/lists/* -vf
then update your system by entering the following command in the terminal
sudo apt-get update && sudo apt-get upgrade
after this there should be no errors and everything should work fine.
The key(s) in the keyring /etc/apt/trusted.gpg.d/*** are ignored as the file has an unsupported filetype.
Sep 242019//Scoreboard and netgraph combined
alias +scores "net_graph 3; +showscores"
alias -scores "net_graph 0; -showscores"
bind tab +scores
//radar
cl_radar_scale 0.3
cl_hud_radar_scale 1.15
cl_radar_icon_scale_min 1
cl_radar_always_centered 1
cl_drawhud_force_radar 1
cl_hud_bomb_under_radar 1
//player damage
developer 1
con_filter_enable 2
con_filter_text_out "Player:"
con_filter_text "damage Given"
//misc
cl_hud_healthammo_style "1" // show HP and ammo without bars and bullet icons
hud_showtargetid "1" // 1 to enable the red playername target text
+cl_show_team_equipment
cl_forcepreload "1"
mat_queue_mode "2"
r_dynamic "1"
r_drawparticles "0"
r_drawtracers_firstperson "0"
// Jumpthrow
bind mouse1 +attack
bind mouse2 +attack2
bind "SPACE" "+jump"
alias "+jumpthrow" "+jump;-attack;-attack2"
alias "-jumpthrow" "-jump"
bind "mouse4" "+jumpthrow"
Jun 222019Obviously not every pacakge on github is going to be available via pip, but downloading and installing manually clutters up your project directory. That kind of defeats the purpose of using pipenv in the first place. However, installing a package by using the git uri with pipenv is possible just like it is with pip. Here's what you type:
pipenv install -e git+git://github.com/user/project.git#egg=<project>
Pretty simple right? Here's an example of one that I've used recently just in case:
pipenv install -e git+git://github.com/miso-belica/sumy.git#egg=sumy
Which is the command to install this package: https://github.com/miso-belica/sumy
If you have pipenv command not found use this to fix it:
sudo -H pip install -U pipenv
for scrapy with Python 3, you'll need
sudo apt-get install python3 python-dev python3-dev \
build-essential libssl-dev libffi-dev \
libxml2-dev libxslt1-dev zlib1g-dev \
python-pip
with Python 2, you'll need
sudo apt-get install python-dev \
build-essential libssl-dev libffi-dev \
libxml2-dev libxslt1-dev zlib1g-dev \
python-pip
Jun 192019I had some smoked salmon from Walmart in the fridge and decided to dip it in some wasabi and soy sauce to imitate sashimi. It was pretty tasty and I thought I would put together a bootleg sushi guide here.
I figure using smoked salmon and imitation crab meat with a variety of ingredients will give me a much better understanding of which types of sushi I enjoy the most. I don’t need to make rice every time and I don’t ever need to roll it up if I’m just snacking at home.
My first experiment will be smoke salmon and artificial crab meat paired with cream cheese, sprouts, and avocado.
Ingredients
- Cucumber
- Avocado
- Asparagus
- Jalapenos
- green onion
- carrots
- sprouts
- bell peppers
- pineapple
- mango
- apple
- pear
- cream cheese
- tempura [cooked] shrimp
- imitation crabmeat [cooked]
- raw sashimi grade salmon
- smoked salmon
- raw sashimi grade tuna
- Black Nori (seaweed wrap)
Toppings
- sesame seeds
- thin slices of fish
- shrimp or crab salad
- seaweed salad
- sliced almonds
- sprouts
- thinly sliced avocado
- volcano topping
Links
https://www.allaboutsushiguide.com/Sushi-Ingredients.html
Jun 142019Import CSV as Dict
- Creates ordered dict
- You can increase file size limit
- Using next() can bypass the header row
import csv
# Dict reader creates an ordered dict (first row will be headers)
with open('./data/file.csv', newline='') as file:
# Huge csv files might give you a size limit error
csv.field_size_limit(100000000)
results = csv.DictReader(file, delimiter=';', quotechar='*', quoting=csv.QUOTE_ALL)
# next() can help in iterations sometimes
next(results)
for row in results:
# prints each item in the column with header 'key'
print(row['key'])
Import CSV with No Header (nested lists)
- newline='' prevents blank lines
- csv.reader uses indexes [0], [1]
# newline='' prevents blank lines
with open('./data/file.csv', newline='') as file:
results = csv.reader(file, delimiter=':', quoting=csv.QUOTE_NONE)
for row in results:
# csv reader uses indexes
print(row[0])
Writing and Creating Headers
- Create a csv.writer object
- Create header manually before loop
- Nested lists are better than tuples inside lists
- writer.writerow and writer.writerows
# Creates a csv writer object
writer = csv.writer(
file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
# Write header first if you would like
writer.writerow(['title', 'price', 'shipping'])
''' Tuples inside list (list inside lists are usually better though).
If you're using tuples and they are variable size, note that a single tuple
will convert to string type in a loop so indexing it [0] won't work. '''
products = [['slinky', '$5', 'Free'],
['pogo', '$12', '$6'],
['Yoyo', '$7', '$2']]
# write each row normal
for item in products:
writer.writerow(map(str, item))
# Writes all items into a single row
writer.writerow(sum(products, []))
# Writes all 3 rows
writer.writerows(products)
Using DictWriter for Headers
- fieldnames indicates header to object
- writer.writeheader() writes those fields
# DictWriter field names will add the headers for you when you call writeheader()
with open("./data/file.csv", "w") as file:
writer = csv.DictWriter(
file, fieldnames=['title', 'price', 'shipping'],
quoting=csv.QUOTE_NONNUMERIC)
writer.writeheader()
writer.writerows([['slinky', '$5', 'Free'],
['pogo', '$12', '$6'],
['Yoyo', '$7', '$2']])
Bonus - Flatten any List
- Function will flatten any level of nested lists
- or type == tuple() to catch tuples too
# -- Bonus (Off Topic) --
# You can flatten any list with type checking and recursion
l = [1, 2, [3, 4, [5, 6]], 7, 8, [9, [10]]]
output = []
def flatten_list(l):
for i in l:
if type(i) == list:
flatten_list(i)
else:
output.append(i)
reemovNestings(l)