vdropbox 1.1.2

Utilities to read/write python objects to/from dropbox

vdropbox

Utilities to read/write objects to/from Dropbox.

🚀 Usage

The first step is to declare the Vdropbox object using a token:

from vdropbox import Vdropbox
vdp = Vdropbox("my_secret")

Unlike the official dropbox Python package, it is not required to have a leading / in all file names.

[!NOTE] Ensure your Dropbox token has the necessary permissions.

🛠 Custom Logger

You can pass a custom logger to Vdropbox if you want to control logging behavior:

import logging
from vdropbox import Vdropbox

logger = logging.getLogger("my_logger")
vdp = Vdropbox("my_secret", logger=logger)

[!TIP] Using a custom logger allows you to integrate Vdropbox logs into your existing logging setup.

📁 Basic Functions

# Check if a file exists
vdp.file_exists("my_file.txt")
vdp.file_exists("folder/my_file.txt")

# Check contents of a folder
vdp.ls("my_folder")

# Delete a file
vdp.delete("my_file.txt")

[!WARNING] Deleting a file is irreversible!

📝 Reading and Writing Text Files

data = "Hello world"

# Write a text file
vdp.write_file(data, "my_file.txt")

# Read a text file
vdp.read_file("my_file.txt")

[!NOTE] The default encoding is UTF-8.

📜 Reading and Writing YAML Files

data = {"a": 4, "b": 2}

# Write a YAML file
vdp.write_yaml(data, "my_file.yaml")

# Read a YAML file
vdp.read_yaml("my_file.yaml")

[!TIP] Internally, it uses oyaml, so all YAML files maintain their order.

📊 Reading and Writing Excel Files with Pandas

import pandas as pd
# Create a dummy DataFrame
df = pd.DataFrame(list("ABCDE"), columns=["col"])

# Write an Excel file
vdp.write_excel(df, "df.xlsx")

# Read an Excel file
df = vdp.read_excel("df.xlsx")

[!TIP] You can pass keyword arguments to pd.read_excel or df.to_excel.

Example:

vdp.write_excel(df, "test.xlsx", index=False)

🔹 Reading and Writing Parquet Files with Pandas

import pandas as pd
# Create a dummy DataFrame
df = pd.DataFrame(list("ABCDE"), columns=["col"])

# Write a Parquet file
vdp.write_parquet(df, "df.parquet")

# Read a Parquet file
df = vdp.read_parquet("df.parquet")

[!TIP] You can pass keyword arguments to pd.read_parquet or df.to_parquet.

👥 Authors

• Arnau Villoro

📜 License

The content of this repository is licensed under MIT.