>Easy Environment is a Python tool that provides easy-to-use functionality for managing files and data in different environments. It offers a class that simplifies file operations on the local disk and cloud services such as Google Cloud (Google Cloud Storage and Big Query) or SharePoint.
- Multi-format loading and saving: Load and save files in various formats with one command line
- Default supported formats: csv, docx, jpg, json, md, parquet, pdf, pickle, png, pptx, sql, toml, txt, xlsx, xml, yaml, yml
- Unsupported formats: Customisable. See Customise supported formats.
- Multi-environment management:
- Local disk: Loading/saving and management.
- Google Cloud Storage: Loading/saving and management.
- Big Query: Append, write, and run queries on Big Query tables.
- SharePoint: Download, upload, and manage files on SharePoint.
Start by installing easyenvi :
pip install easyenviLoad or save a large variety of format : csv, docx, jpg, json, md, parquet, pdf, pickle, png, pptx, sql, toml, txt, xlsx, xml, yaml, yml
from easyenvi import file
secrets = file.load('my_path/secrets.toml')
config = file.load('my_path/config.json')
query = file.load('my_path/titanic.sql')
file.save(df, 'my_path/titanic.csv')
file.save(df, 'my_path/my_dict.parquet')
file.save(my_dict, 'my_path/my_dict.pickle')To use Easy Environment, create an instance of the EasyEnvironment class. All the parameters in the EasyEnvironment class are optional: it depends on which environment you need to access.
from easyenvi import EasyEnvironment
envi = EasyEnvironment(
local_path="", # Optional
gcloud_project_id="your-project-id", # Optional
gcloud_credential_path="path/to/credentials.json", # Optional
GCS_path="gs:https://your-bucket-name/", # Optional
sharepoint_site_url="https://{tenant}.sharepoint.com/sites/{site}", # Optional
sharepoint_username="your-username", # Optional
sharepoint_user_password="your-password" # Optional
)Specifying certain parameters means certain dependencies:
- For using local operation,
local_pathis the path from which local operations should be executed - specify an empty string if you want to use the current directory. - For using Google Cloud, it is necessary to specify the project ID, the path to a credential .json file, and, in case of interaction with Google Cloud Storage, the path to the GCS folder (see Google Cloud Initialisation).
- For using SharePoint, it is necessary to specify the SharePoint site to interact with, as well as authentication credentials: either the client_id/client_secret pair or the username/user_password pair (see SharePoint Initialisation).
# Load any file format
my_dict = envi.local.load(path='inputs/my_dictionnary.pickle')
my_logo = envi.local.load(path='inputs/my_logo.png')
dataset = envi.local.load(path='inputs/dataset.csv')
# Save any file format
envi.local.save(obj=my_dict, path='outputs/my_dictionnary.pickle')
envi.local.save(obj=my_logo, path='outputs/my_logo.png')
envi.local.save(obj=dataset, path='outputs/dataset.csv')# Load any file format
my_dict = envi.gcloud.GCS.load(path='inputs/my_dictionnary.pickle')
my_logo = envi.gcloud.GCS.load(path='inputs/my_logo.png')
dataset = envi.gcloud.GCS.load(path='inputs/dataset.csv')
# Save any file format
envi.gcloud.GCS.save(obj=my_dict, path='outputs/my_dictionnary.pickle')
envi.gcloud.GCS.save(obj=my_logo, path='outputs/my_logo.png')
envi.gcloud.GCS.save(obj=dataset, path='outputs/dataset.csv')df = pd.DataFrame(data={'age': [21, 52, 30], 'wage': [12, 17, 11]})
# Create a new table
envi.gcloud.BQ.write(dataset, 'mydata.mytable')
# Append an existing table
envi.gcloud.BQ.append(dataset, 'mydata.mytable')
# Run queries
query = """
SELECT *
FROM mydata.mytable
WHERE age < 40
"""
new_dataset = envi.gcloud.BQ.query(query).to_dataframe()# Download a file
envi.sharepoint.download(
input_path="/Document partages/sharepoint_folder/my_file.txt",
output_path="local_folder/my_file.txt"
)
# Upload a file
envi.sharepoint.upload(
input_path="local_folder/my_file.txt",
output_path="Document partages/folder/my_file.txt"
)
# List files
envi.sharepoint.list_files(folder="local_folder")The documentation is available here : Easy Environment - Documentation
Future releases of Easy Environment will include support for additional cloud storage providers, including Amazon Web Services (AWS) and Microsoft Azure.