Exemples de la Bibliothèque de Trading de Cryptomonnaies CCXT

Exemples · Citations · Tutoriels

Exemples

Pour exécuter les exemples ccxt depuis n'importe quel dossier, tapez l'une des commandes suivantes dans la console.

Typescript

Exemples Typescript

JavaScript

Exemples JavaScript

node path/to/example.js # substitute for actual filename here

Ces exemples peuvent nécessiter les modules Node.js super-utiles et de haute qualité par xpl :

• ololog: Journalisation multiplateforme avec blackjack et hookers (ololog @ npm)
• ansicolor: Une bibliothèque JavaScript de qualité pour la gestion des couleurs/styles ANSI (ansicolor @ npm)
• as-table: Une simple fonction qui imprime des objets sous forme de tableaux ASCII (as-table @ npm)

Tous les modules ci-dessus sont installés automatiquement par npm avec les dépendances de développement de la bibliothèque ccxt.

PHP

Exemples PHP

php -f path/to/example.php # substitute for actual filename here

Python

Exemples Python

python path/to/example.py # substitute for actual filename here

Citations CCXT Dans Des Articles Et Thèses

• Evaluating machine learning models for predictive
  2025, Shavez Mushtaq Qureshi, Asad Rehman Khattak, Muhammad Shah Rukh (Qarshi University), Atif Saeed, Farooq Ahmad (COMSATS University Islamabad), Sultan H. Almotiri, Mohammed A. Al Ghamdi (Umm Al-Qura University)
• Machine Learning-Based Detection of Pump-and-Dump Schemes in Real-Time
  2024, Manuel Bolz, Kevin Bründler, Liam Kane, Panagiotis Patsias, Liam Tessendorf, Krzysztof M. Gogol, Taehoon Kim, Claudio J. Tessone (University of Zurich)
• Forecasting cryptocurrency's buy signal with a bagged tree learning approach to enhance purchase decisions
  2024, Raed Alsini, Abdulaziz A Alsulami, Abdulaziz A Alqurashi, Nawaf Alhebaishi, Badraddin Alturki, Mouhamad D Mashat (King Abdulaziz University), Qasem Abu Al-Haija (Jordan University of Science and Technology), Ali Alqahtani, (Najran University)
• A Hybrid COMTE-LEFTIST Time-Series Explanation Method For a Time-series Classification Bitcoin Recommendation System
  2024, Lucas Rabelo de Araujo Morais, Teresa Bernarda Ludermir (Universidade Federal de Pernambuco)
• Deep Complex Networks: Applications in Financial Systems Modeling
  2024, Antonio Briola (University College London)
• FTX's downfall and Binance's consolidation: the fragility of Centralized Digital Finance
  2023, David Vidal-Tom´as, Antonio Briola, Tomaso Astea (University College London)
• Detecting Pump-and-Dumps with Crypto-Assets
  2023, Dean Fantazzini, Yufeng Xiao (Moscow State University)
• Detecting Depegs: Towards Safer Passive Liquidity Provision on Curve Finance
  2023, Thomas Cintra, Max Holloway (Xenophon Labs)
• Development Of A Cryptocurrency Bot
  2023, José Manuel Rodríguez Lomeña (Universitat Polit`ecnica de Catalunya)
• Dependency Structures in Cryptocurrency Market from High to Low Frequency
  2022, Antonio Briola (University College London), Tomaso Astea (London School Of Economics)
• Anatomy of a Stablecoin's failure: the Terra-Luna case
  2022, Antonio Briola, David Vidal-Tom´as, Yuanrong Wanga (University College London), Tomaso Astea (London School Of Economics)
• FreqAI: generalizing adaptive modeling for chaotic time-series forecasting
  2022, Robert A. Caulk, Elin Törnquist, Matthias Voppichler, Andrew R. Lawless, Ryan McMullan, Wagner Costa Santos, Timothy C. Pogue, Johan van der Vlugt, Stefan P. Gehring, Pascal Schmidt (Freqtrade)
• Analysis and Implementation of Arbitrage Bots in Centralized and Decentralized Finance
  2022, Claudio Gebbia (University of Zurich)
• Hybrid Cryptocurrency Pump and Dump Detection
  2020, Hadi Mansourifar, Weidong Shi (University of Houston), Lin Chen (Texas Tech University)
• Cryptocurrency Trading: A Comprehensive Survey
  2020, Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, David Martinez-Rego, Fan Wu, Lingbo Li (King's College London)
• Algorithm for cryptocurrency price discrepancy detection
  2020, Imre Lendak, Marta Patiño Martínez, Gergely Tyukodi, Daniel Minguez Camacho (Universidad Politécnica de Madrid)
• An Empirical Analysis of the Python Package Index (PyPI)
  2019, Ethan Bommarito, Michael J Bommarito II (University of Michigan)
• To the moon: defining and detecting cryptocurrency pump-and-dumps
  2018, Josh Kamps (VU University Amsterdam), Bennett Kleinberg (University College London)