Install Dask ============ You can install dask with ``conda``, with ``pip``, or by installing from source. Conda ----- Dask is installed by default in `Anaconda `_. You can update Dask using the `conda `_ command:: conda install dask This installs Dask and **all** common dependencies, including Pandas and NumPy. Dask packages are maintained both on the default channel and on `conda-forge `_. Optionally, you can obtain a minimal Dask installation using the following command:: conda install dask-core This will install a minimal set of dependencies required to run Dask similar to (but not exactly the same as) ``python -m pip install dask`` below. Pip --- You can install everything required for most common uses of Dask (arrays, dataframes, ...) This installs both Dask and dependencies like NumPy, Pandas, and so on that are necessary for different workloads. This is often the right choice for Dask users:: python -m pip install "dask[complete]" # Install everything You can also install only the Dask library. Modules like ``dask.array``, ``dask.dataframe``, ``dask.delayed``, or ``dask.distributed`` won't work until you also install NumPy, Pandas, Toolz, or Tornado, respectively. This is common for downstream library maintainers:: python -m pip install dask # Install only core parts of dask We also maintain other dependency sets for different subsets of functionality:: python -m pip install "dask[array]" # Install requirements for dask array python -m pip install "dask[bag]" # Install requirements for dask bag python -m pip install "dask[dataframe]" # Install requirements for dask dataframe python -m pip install "dask[delayed]" # Install requirements for dask delayed python -m pip install "dask[distributed]" # Install requirements for distributed dask We have these options so that users of the lightweight core Dask scheduler aren't required to download the more exotic dependencies of the collections (Numpy, Pandas, Tornado, etc.). Install from Source ------------------- To install Dask from source, clone the repository from `github `_:: git clone https://github.com/dask/dask.git cd dask python -m pip install . You can also install all dependencies as well:: python -m pip install ".[complete]" You can view the list of all dependencies within the ``extras_require`` field of ``setup.py``. Or do a developer install by using the ``-e`` flag:: python -m pip install -e . Anaconda -------- Dask is included by default in the `Anaconda distribution `_. Optional dependencies --------------------- Specific functionality in Dask may require additional optional dependencies. For example, reading from Amazon S3 requires ``s3fs``. These optional dependencies and their minimum supported versions are listed below. +---------------+----------+--------------------------------------------------------------+ | Dependency | Version | Description | +===============+==========+==============================================================+ | bokeh | >=1.0.0 | Visualizing dask diagnostics | +---------------+----------+--------------------------------------------------------------+ | cloudpickle | >=0.2.2 | Pickling support for Python objects | +---------------+----------+--------------------------------------------------------------+ | cityhash | | Faster hashing of arrays | +---------------+----------+--------------------------------------------------------------+ | distributed | >=2.0 | Distributed computing in Python | +---------------+----------+--------------------------------------------------------------+ | fastparquet | | Storing and reading data from parquet files | +---------------+----------+--------------------------------------------------------------+ | fsspec | >=0.6.0 | Used for local, cluster and remote data IO | +---------------+----------+--------------------------------------------------------------+ | gcsfs | >=0.4.0 | File-system interface to Google Cloud Storage | +---------------+----------+--------------------------------------------------------------+ | murmurhash | | Faster hashing of arrays | +---------------+----------+--------------------------------------------------------------+ | numpy | >=1.13.0 | Required for dask.array | +---------------+----------+--------------------------------------------------------------+ | pandas | >=0.23.0 | Required for dask.dataframe | +---------------+----------+--------------------------------------------------------------+ | partd | >=0.3.10 | Concurrent appendable key-value storage | +---------------+----------+--------------------------------------------------------------+ | psutil | | Enables a more accurate CPU count | +---------------+----------+--------------------------------------------------------------+ | pyarrow | >=0.14.0 | Python library for Apache Arrow | +---------------+----------+--------------------------------------------------------------+ | s3fs | >=0.4.0 | Reading from Amazon S3 | +---------------+----------+--------------------------------------------------------------+ | sqlalchemy | | Writing and reading from SQL databases | +---------------+----------+--------------------------------------------------------------+ | cytoolz/toolz | >=0.8.2 | Utility functions for iterators, functions, and dictionaries | +---------------+----------+--------------------------------------------------------------+ | xxhash | | Faster hashing of arrays | +---------------+----------+--------------------------------------------------------------+ Test ---- Test Dask with ``py.test``:: cd dask py.test dask Please be aware that installing Dask naively may not install all requirements by default. Please read the ``pip`` section above which discusses requirements. You may choose to install the ``dask[complete]`` version which includes all dependencies for all collections. Alternatively, you may choose to test only certain submodules depending on the libraries within your environment. For example, to test only Dask core and Dask array we would run tests as follows:: py.test dask/tests dask/array/tests