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Python

Environment

Qualified supports Python 2.7, 3.4, 3.6, 3.7, 3.8 and 3.11.

Timeout

The sandbox environment will timeout the code within 12 seconds.

Packages

The following Python packages are installed:

Python 2.7

  • numpy: 1.12.0
  • scipy: 0.13.3
  • scikit-learn: 0.18.1
  • gmpy2: 2.0.2
  • pandas: 0.13.1
  • six: 1.10.0
  • pymongo: 3.4.0
  • redis: 2.10.5
  • psycopg2: 2.7
  • beautifulsoup4: 4.2.1
  • requests: 2.7.0
  • pycrypto: 2.6.1

Python 3.4

  • numpy: 1.12.0
  • scipy: 0.13.3
  • scikit-learn: 0.18.1
  • gmpy2: 2.0.2
  • pandas: 0.13.1
  • six: 1.10.0
  • pymongo: 3.4.0
  • redis: 2.10.5
  • psycopg2: 2.7
  • beautifulsoup4: 4.2.1
  • requests: 2.7.0
  • pycrypto: 2.6.1

Python 3.6

  • numpy: 1.14.0
  • scipy: 1.0.0
  • scikit-learn: 0.19.1
  • gmpy2: 2.0.8
  • pandas: 0.22.0
  • six: 1.10.0
  • pymongo: 3.6.0
  • redis: 2.10.6
  • psycopg2: 2.7.4
  • beautifulsoup4: 4.6.0
  • requests: 2.7.0
  • pycrypto: 2.6.1

Python 3.7

Since Python 3.7, we have presets for different kinds of challenges. Use the Run Configuration menu in project code challenge mode to select a preset.

Default (no preset)

  • beautifulsoup4: 4.7.1
  • gmpy2: 2.0.8
  • numpy: 1.16.3
  • pandas: 0.24.2
  • pycrypto: 2.6.1
  • regex: 2019.04.14
  • requests: 2.21.0
  • scikit-learn: 0.20.3
  • scipy: 1.2.1
  • six: 1.12.0

Data Science (datascience preset)

  • beautifulsoup4: 4.9.0
  • numpy: 1.18.4
  • pandas: 1.0.3
  • requests: 2.23.0
  • seaborn: 0.10.1
  • scikit-learn: 0.22.2.post1
  • scipy: 1.4.1
  • matplotlib: 3.2.1
  • mpld3
  • jinja2: 2.11.2
  • six: 1.14.0
  • gensim: 3.8.3
  • keras: 2.3.1
  • networkx: 2.4
  • nltk: 3.5
  • spacy: 2.2.4
  • psycopg2: 2.8.5
  • sqlalchemy: 1.3.16
  • statsmodels: 0.11.1
  • scrapy: 2.1.0
  • wordcloud: 1.7.0

Django (django preset)

Only available in Project Code Challenges.

  • django: 2.2.1

Python 3.8

Default (no preset)

  • aiohttp: 3.8.1
  • beautifulsoup4: 4.9.1
  • flask: 1.1.2
  • gmpy2: 2.0.8
  • jinja2: 2.11.2
  • matplotlib: 3.3.0
  • mpld3: 0.3.1.dev1
  • numpy: 1.19.1
  • pandas: 1.0.5
  • pycrypto: 2.6.1
  • regex: 2020.7.14
  • requests: 2.24.0
  • scikit-learn: 0.23.1
  • scipy: 1.5.2
  • seaborn: 0.10.1
  • six: 1.15.0
  • sqlalchemy: 1.3.19

Data Science (datascience preset)

  • beautifulsoup4: 4.9.1
  • gensim: 3.8.3
  • graphviz: 0.14.1
  • jinja2: 2.11.2
  • keras: 2.4.3
  • koala2: 0.0.35
  • matplotlib: 3.3.0
  • mpld3: 0.3.1.dev1
  • networkx: 2.4
  • nltk: 3.5
  • numpy: 1.19.1
  • pandas: 1.1.0
  • psycopg2: 2.8.5
  • pydotplus: 2.0.2
  • requests: 2.24.0
  • scikit-learn: 0.23.1
  • scipy: 1.5.2
  • scrapy: 2.2.1
  • seaborn: 0.10.1
  • six: 1.15.0
  • spacy: 2.3.2
  • sqlalchemy: 1.3.18
  • statsmodels: 0.11.1
  • wordcloud: 1.7.0

Django (django preset)

Only available in Project Code Challenges.

  • django: 3.2
  • djangorestframework: 3.12.4
  • django-filter: 21.1
  • django-guardian: 2.4.0

Python 3.11

Default (no preset)

  • aiohttp: 3.8.3
  • beautifulsoup4: 4.11.2
  • cryptography: 39.0.1
  • Flask: 2.2.2
  • gmpy2: 2.1.5
  • Jinja2: 3.1.2
  • matplotlib: 3.6.3
  • moto: 4.1.5
  • mpld3: 0.5.9
  • networkx: 3.0
  • numpy: 1.24.2
  • pandas: 1.5.3
  • pysparkling: 0.6.2
  • regex: 2022.10.31
  • requests: 2.28.2
  • scikit-learn: 1.2.1
  • scipy: 1.10.0
  • seaborn: 0.12.2
  • six: 1.15.0
  • sqlalchemy: 2.0.2

Testing

Our Python environment supports the following testing frameworks: