Open a Terminal window.
Open your zsh config file:
code ~/.zshrc
REQUIRED=('pytest' 'pylint' 'ipdb' 'PyYAML' 'nbresult' 'autopep8' 'flake8' 'yapf' 'lxml' 'requests' 'bs4' 'jupyterlab' 'pandas' 'matplotlib' 'seaborn' 'plotly' 'scikit-learn' 'tensorflow' 'nbconvert' 'xgboost' 'statsmodels' 'pandas-profiling' 'jupyter-resource-usage' 'dtale') | |
PACKAGES=$(pip freeze) | |
PACKS=() | |
while read -r line; do | |
PACKS+=("$line") | |
done <<< "$PACKAGES" | |
missing=() | |
for r in ${REQUIRED[@]}; do | |
present=0 | |
for p in ${PACKS[@]}; do |
print('Loading pandas...') | |
import pandas as pd | |
df = pd.DataFrame({'pandas':['OK']}) | |
df.shape | |
print('✅ pandas OK') | |
print('Loading Scikit-learn...') | |
from sklearn.decomposition import PCA | |
pca = PCA() | |
print('✅ Scikit-learn OK') | |
print('Loading TensorFlow...') |
REQUIRED=('pytest' 'pylint' 'ipdb' 'PyYAML' 'nbresult' 'autopep8' 'flake8' 'yapf' 'lxml' 'requests' 'bs4' 'jupyterlab' 'pandas' 'matplotlib' 'seaborn' 'plotly' 'scikit-learn' 'tensorflow' 'nbconvert' 'xgboost' 'statsmodels' 'pandas-profiling' 'jupyter-resource-usage' 'dtale') | |
PACKAGES=$(pip freeze) | |
PACKS=() | |
while read -r line; do | |
PACKS+=("$line") | |
done <<< "$PACKAGES" | |
missing=() | |
arch_name="$(uname -m)" | |
if [ "${arch_name}" = "x86_64" ]; then | |
if [ "$(sysctl -in sysctl.proc_translated)" = "1" ]; then |
import os | |
import pandas as pd | |
class Olist: | |
def get_data(self): | |
""" | |
This function returns a Python dict. | |
Its keys should be 'sellers', 'orders', 'order_items' etc... |
from time import sleep | |
class Trainer: | |
def run(self): | |
print("Training launched.") | |
print("Training running...") | |
sleep(2) | |
print("Taining finished.") | |
if __name__ == '__main__': |
pytest | |
pylint | |
ipdb | |
jupyterlab | |
numpy | |
pandas | |
matplotlib | |
seaborn | |
scikit-learn | |
packgenlite @ git+https://github.com/krokrob/packgenlite.git@master |
import os | |
import pandas as pd | |
class Olist: | |
def get_data(self): | |
""" | |
01-01 > This function returns all Olist datasets | |
as DataFrames within a Python dict. |