Utilities to read/write python objects to/from dropbox
Project description
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
License
The content of this repository is licensed under a MIT.
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