Platform tools
This page is a collection of methods used to save and retrieve custom user data inside the SigTech platform.
The following command imports the Python module:
from sigtech import platform_tools
Pandas DataFrames and series can be saved to a file in a user's designated AWS S3 bucket and accessed later using the same workspace.
The following code block demonstrates how to save a Pandas DataFrame into a .csv file and store it in the AWS S3 bucket:
from sigtech import platform_tools as pt
import pandas as pd
hist = pd.DataFrame({'data': [1, 2, 3, 4]})
pt.save_raw(hist, 'signal_data.csv')
Once saved, the following code loads the file.
from sigtech import platform_tools as pt
hist = pt.get_raw('signal_data.csv')
Other file types can be saved to S3 using the
save_file function and retrieved using the open_file function within Platform Tools. Example: a NumPy series can be saved in bytes to a file-like object and parsed with the
save_file function:import io
import numpy as np
from sigtech import platform_tools as pt
results = np.array([])
file_obj = io.BytesIO()
np.save(file_obj, results, allow_pickle = True)
# We place the pointer back at the beginning of the file-like object
file_obj.seek(0)
pt.save_file(file_obj, f'results')
The file can later be retrieved with the
open_file function, which works similarly to Python's built-in open function:import numpy as np
from sigtech import platform_tools as pt
with pt.open_file(f'results') as f:
results = np.load(f, allow_pickle=True)
Data can also be uploaded in the Custom Data pathway in your workspace.
To upload a file, click Custom Data in the workspace-and-collaboration menu:
Upload your own custom data via the workspace
The Custom Data screen is displayed. Follow the onscreen instructions to upload your file.
Once uploaded, the
open_file function can also be used to access this data. In the following example, the file name "dummy_data.csv" is adopted. Amend this file name to match the name of the file you have uploaded to run the code block:
from sigtech import platform_tools
import pandas as pd
# assuming the file name is dummy_data.csv
df = pd.read_csv(platform_tools.open_file("dummy_data.csv"))
The functions
get_dataset and get_dataset_file can be used to retrieve datasets and individual files previously uploaded using the data ingestion API. Results are returned as a Pandas DataFrame. In the following example
'<id>' is used as a shorthand for explanatory purposes. from sigtech import platform_tools as pt
dataset_id = '<id>'
file_id = '<id>'
full_dataset = pt.get_dataset(dataset_id)
individual_file_df = pt.get_dataset_file(dataset_id, file_id)
Last modified 1yr ago