vdropbox 0.2.7

Utilities to read/write python objects to/from dropbox

vdropbox

Utilities to read/write objects to/from dropbox

Usage

The first thing to do is to declare the Vdropbox object using a token with:

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

Unlike the official dropbox python package it is not needed to have a leading / in all names.

Basic functions

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

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

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

Reading and writting 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")

Internally it is using oyaml so all yamls are ordered.

Reading and writting yamls

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")

Internally it is using oyaml so all yamls are ordered.

Reading and writting excels with pandas

import pandas as pd
# Dummy dataframe
df = pd.DataFrame(list("ABCDE"), columns=["col"])

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

# Read a parquet file
vdp.read_excel("df.parquet")

It is possible to pass keyworded arguments to the internal pd.read_excel or df.to_excel function. For example:

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

Reading and writting parquets with pandas

import pandas as pd
# Dummy dataframe
df = pd.DataFrame(list("ABCDE"), columns=["col"])

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

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

It is possible to pass keyworded arguments to the internal pd.read_parquet or df.to_parquet function.

Authors

• Arnau Villoro

License

The content of this repository is licensed under a MIT.