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dict.sh Key Features
dict.sh Examples and Code Snippets
Lines of Code : 6License : Permissive (MIT)
Copystatic const char *dictcmd[] = { "d", "$(xsel -o)", NULL };
static Key keys[] = {
....
{ MODKEY, XK_d, spawn, {.v = dictcmd} },
...
d hello world
export D_SELECTOR='fzf --reverse --height=30%%'
d hello world
export D_SELECTOR='plainsel'
d hello world
git clone --depth 1 https://github.com/klesh/dict.sh.git
cd dict.sh
sudo make install
Community Discussions
Trending Discussions on dict.sh
QUESTION
In Python 3.7, Numpy: I saved and loaded a dict, using numpy (like I already asked here: Saving a sequence of 3rd-order Tensors and reading it back without losing array format ).
Loading it merges it to one big thing where i cannot get the single values anymore.
I used np.save('filename', dict) to save a dictionary like {(1, 0): 1, (1, 1): 2, (2, 0): 3, (2, 1): 4} and loaded_dict = np.load('filename.npy', allow_pickle=True) to load an object what I need to be a dictionary.
Now just trying to do loaded_dict[(1, 0)] does not work. In fact:
print(loaded_dict.shape) outputs ().
Working example code:
...ANSWER
Answered 2019-Jun-17 at 14:32loaded_dict is a numpy.ndarray not a dictionary. You can access the dictionary using .item() method,
QUESTION
I am trying to convert the following Python dict into PySpark DataFrame but I am not getting expected output.
ANSWER
Answered 2018-Jul-27 at 10:07Try this out :
QUESTION
I need to take 100 000 images from a directory, put them all in one big dictionary where the keys are the ids of the pictures and the values are the numpy arrays of the pixels of the images. Creating this dict takes 19 GB of my RAM and I have 24GB in total. Then I need to order the dictionary with respect to the key and at the end take only the values of this ordered dictionary and save it as one big numpy array. I need this big numpy array because I want to sent it to train_test_split sklearn function and split the whole data to train and test sets with respect to their label. I found this question where they have the same problem with running out of RAM in the step where after creating the dictionary of 19GB I try to sort the dict: How to sort a LARGE dictionary and people suggest using database.
...ANSWER
Answered 2019-Jan-04 at 10:06The reason using a DB helps is because the DB library stores data on the hard-disk rather than in memory. If you look at the documentation for the library the linked answer suggests then you'll see that the first argument is filename, demonstrating that the hard-disk is used.
https://docs.python.org/2/library/bsddb.html#bsddb.hashopen
However, the linked question is talking about sorting by value, not key. Sorting by key will be much less memory intensive although you'll likely still have memory issues when training your model. I'd suggest trying something along the lines of
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