Does ruamel.yaml have a function to do the process with all files in one directory?
Something like this:
data = yaml.load(Path("*.*"))
No, it does not, but you can do it one line (assuming you have the imports and the YAML() instance):
from pathlib import Path
import ruamel.yaml
yaml = ruamel.yaml.YAML()
data = [yaml.load(p) for p in Path('.').glob('*.yaml')]
Recently, I installed pandas_profiling for the purpose of a particular project I created in the PyCharm IDE. It worked after having updated 'External tools' in Settings. Realising a similar need in another project context I did the installation of pandas_profiling in …\venv\Scripts path for that particular project as well. Did similar update of External tools in the new project. Yet the console keeps telling me that it cannot detect the module. Both projects have the pandas_profiling package files in the 'site packages' and 'venv' directories when I check. Any ideas out there? Thx, for your kind support.
from pathlib import Path
import pandas as pd
import numpy as np
import requests
import pandas_profiling
if __name__ == "__main__":
file_name = Path("C:\\Users\…..csv")
if not file_name.exists():
data = requests.get(
"C:\\Users\…..csv"
)
file_name.write_bytes(data.content)
df = pd.read_csv(file_name)
df["Feature_1"] = pd.to_datetime(df["Feature_1"], errors="coerce")
# Example: Constant variable
# df["source"] = "name of org"
# Example: Boolean variable
df["boolean"] = np.random.choice([True, False], df.shape[0])
# Example: Mixed with base types
df["mixed"] = np.random.choice([1, "A"], df.shape[0])
# Example: Highly correlated variables
df["Feature_2"] = df["Feature_2"] + np.random.normal(scale=5, size=(len(df)))
# Example: Duplicate observations
duplicates_to_add = pd.DataFrame(df.iloc[0:10])
duplicates_to_add[u"Feature_1"] = duplicates_to_add[u"Feature_1"]
df = df.append(duplicates_to_add, ignore_index=True)
profile = df.profile_report(
title="Report", correlation_overrides=["recclass"]
)
profile.to_file(output_file=Path("C:\\Users.....html"))
Response from console in new project (while working in existing project):
Traceback (most recent call last):
File "C:/Users/.../PycharmProjects/.../Pandas_Profiling_2.py", line 8, in <module>
import pandas_profiling
ModuleNotFoundError: No module named 'pandas_profiling'
Process finished with exit code 1
I got above error when I try to run the next code
from odoo import models, fields, api
from odoo.exceptions import ValidationError
from odoo.addons.base.res.res_request import referenceable_models
Because there is no res name module present in base module thats why it is giving an error
I want to simplify code. so i make a utils.py , but Google Colaboratory directory is "/content" I read other questions. but this is not my solution
In Google's Colab notebook, How do I call a function from a Python file?
%%writefile example.py
def f():
print 'This is a function defined in a Python source file.'
# Bring the file into the local Python environment.
execfile('example.py')
f()
This is a function defined in a Python source file.
It look likes just using def().
using this, i always write the code in cell.
but i want to this code
import example.py
example.f()
A sample maybe you want:
!wget https://raw.githubusercontent.com/tensorflow/models/master/samples/core/get_started/iris_data.py -P local_modules -nc
import sys
sys.path.append('local_modules')
import iris_data
iris_data.load_data()
I have also had this problem recently.
I addressed the issue by the following steps, though it's not a perfect solution.
src = list(files.upload().values())[0]
open('util.py','wb').write(src)
import util
This code should work with Python 3:
from google.colab import drive
import importlib.util
# Mount your drive. It will be at this path: "/content/gdrive/My Drive/"
drive.mount('/content/gdrive')
# Load your module
spec = importlib.util.spec_from_file_location("YOUR_MODULE_NAME", "/content/gdrive/My Drive/utils.py")
your_module_name = importlib.util.module_from_spec(spec)
spec.loader.exec_module(your_module_name)
import importlib.util
import sys
from google.colab import drive
drive.mount('/content/gdrive')
# To add a directory with your code into a list of directories
# which will be searched for packages
sys.path.append('/content/gdrive/My Drive/Colab Notebooks')
import example.py
This works for me.
Use this if you are out of content folder! hope this help!
import sys
sys.path.insert(0,'/content/my_project')
from example import*
STEP 1. I have just created a folder 'common_module' like shown in the image :
STEP 2 called the required Class from my "colab" code cell,
sys.path.append('/content/common_module/')
from DataPreProcessHelper import DataPreProcessHelper as DPPHelper
My class file 'DataPreProcessHelper.py' looks like this
Add path of 'sample.py' file to system paths as:
import sys
sys.path.append('drive/codes/')
import sample
In my ember-cli app i have installed an addon called 'ember-cli-selectize'. Looking at the directory structure i can see that its files are located at /node_modules/ember-cli-selectize'. Now i want to create a custom component that extends this addon. How do i import/require it? I've tried these and none seems to work:
var EmberSelectize = require('/ember-cli-selectize/app/components/ember-selectize');
import EmberSelectize from 'components/ember-selectize';
import EmberSelectize from 'node_modules/ember-cli-selectize/addon/components/ember-selectize';
import EmberSelectize from 'ember-cli-selectize/addon/components/ember-selectize';
i always get this 'Could not find module' error no matter what. I need to somehow import/require it to do something like
import EmberSelectize from 'wherever/it/is';
export default EmberSelectize.extend({
//my own customizations
})
You were close with:
import EmberSelectize from 'components/ember-selectize';
Addons namespace themselves - in this case, ember-cli-selectize. So, just add the namespace to your import:
import EmberSelectizeComponent from 'ember-cli-selectize/components/ember-selectize';
then you can extend:
export default EmberSelectizeComponent.extend({ });