Implementing a basic plugin architecture shouldn't be a complicated task. The solution described here is working but you still have to import every plugin (inheriting from the base class).
This is my solution:
$ tree
Implementing a basic plugin architecture shouldn't be a complicated task. The solution described here is working but you still have to import every plugin (inheriting from the base class).
This is my solution:
$ tree
https://www.nerdfonts.com/font-downloads
The following solution thanks to @hackerzgz & @snacky101 will install all nerd fonts;
brew tap homebrew/cask-fonts
brew search '/font-.*-nerd-font/' | awk '{ print $1 }' | xargs -I{} brew install --cask {} || true
// ***************************************************************************************** | |
// ***************************************************************************************** | |
// ***************************************************************************************** | |
// ****************************************PC SA Main Script******************************** | |
// ***************************************************************************************** | |
// ***************************************************************************************** | |
// ***************************************************************************************** | |
SCRIPT_NAME MAIN //NEW MAIN |
Ошибка: | |
.\venv\Scripts\activate : Невозможно загрузить файл C:\path\venv\Scripts\activate.ps1, так как выполнение сценариев отключено в этой системе. | |
Для получения дополнительных сведений см. about_Execution_Policies по адресу http://go.microsoft.com/fwlink/?LinkID=135170. | |
строка:1 знак:1 | |
.\venv\Scripts\activate | |
~~~~~~~~~~~~~~~~~~~~~~~ | |
CategoryInfo : Ошибка безопасности: (:) [], PSSecurityException | |
FullyQualifiedErrorId : UnauthorizedAccess | |
Решение проблемы: |
#!/usr/bin/env bash | |
set -ex | |
export TEST_CLUSTER_NAME=quick-test | |
export CERT_MANAGER_VERSION=v1.3.1 | |
export KIND_IMAGE=kindest/node:v1.20.2 | |
# Create test cluster | |
echo "Creating test cluster..." | |
kind create cluster --name="$TEST_CLUSTER_NAME" --image="$KIND_IMAGE" | |
until kubectl --timeout=120s wait --for=condition=Ready pods --all --namespace kube-system; do sleep 1; done |
Service | SSL | status | Response Type | Allowed methods | Allowed headers |
---|
""" | |
This Python script provides a utility to compute the cosine similarity between two text sentences using the TF-IDF | |
(Term Frequency-Inverse Document Frequency) vectorization approach. | |
Key Components: | |
1. Import Statements: The script begins by importing necessary modules: | |
- TfidfVectorizer from sklearn.feature_extraction.text for converting text data into a matrix of TF-IDF features. | |
- cosine_similarity from sklearn.metrics.pairwise to compute the similarity between two vectors in the TF-IDF space. | |
- sys for accessing command-line arguments. |