Skip to main content

A python package for providing fintech indicators

Project description

Install JupyterHub

curl -L https://tljh.jupyter.org/bootstrap.py | sudo -E python3 - --admin tljhadmin --version 1.0.0b1

Edit ~/.profile, add the following to the end

export PATH=/opt/tljh/user/bin/:$PATH

curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.3/install.sh | bash

nvm install 20.17.0

nvm alias default 20.17.0

sudo -E /opt/tljh/user/bin/python3 -m pip install backtrader matplotlib dash pandas netifaces psutil ffquant numpy

sudo -E /opt/tljh/user/bin/jupyter lab build

sudo systemctl restart jupyterhub jupyter-tljhadmin

Visit http://192.168.25.144 in your browser

Log in as tljhadmin and set your password

Let new user register with username and password

sudo tljh-config set auth.type nativeauthenticator.NativeAuthenticator

sudo tljh-config reload

BE CAREFULL!!! When this feature is enabled, the admin user has to go through the sign-up process. Username must be the same with the one used in the installation command.

Admin user authorizes user registration at http://192.168.25.144/hub/authorize

Compile ffquant and upload to PyPi

python -m pip install setuptools wheel twine

Increase version number in setup.py

python setup.py sdist bdist_wheel

python -m twine upload dist/*

Ask Joanthan for PyPi API token.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ffquant-1.4.2-py3-none-any.whl (25.4 kB view details)

Uploaded Python 3

File details

Details for the file ffquant-1.4.2-py3-none-any.whl.

File metadata

  • Download URL: ffquant-1.4.2-py3-none-any.whl
  • Upload date:
  • Size: 25.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.1

File hashes

Hashes for ffquant-1.4.2-py3-none-any.whl
Algorithm Hash digest
SHA256 5d352346b626565e400825593c44ab8bf0e675da9d603bcb251121fb094ec257
MD5 9b257c76dac93d719e86cdc0dde1f4fe
BLAKE2b-256 ec38352db3a39419a89ae6b6ba60a231f4d90a7eff14253603d04cff67c47fd1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page