See Introduction to Conda for more details.
I first installed Anaconda on my ubuntu at
~/anaconda, when I was trying to update my anaconda, according to the documentation from Continuum Analytics, I should use the following commands:
conda update conda conda update anaconda
Then I realized that I did not have conda installed, so I installed it using the documentation from here.
After conda is installed, when I run
conda update anaconda, I got the following error:
Error: package ‘anaconda’ is not installed in /home/xiang/miniconda
It appears conda is assuming my anaconda is installed under
/home/xiang/miniconda which is NOT true.
conda is the package manager. Anaconda is a set of about a hundred packages including conda, numpy, scipy, ipython notebook, and so on.
You installed Miniconda, which is a smaller alternative to Anaconda that is just conda and its dependencies, not those listed above.
Once you have Miniconda, you can easily install Anaconda into it with
conda install anaconda.
conda is both a command line tool, and a python package.
Miniconda installer = Python +
Anaconda installer = Python +
conda + meta package
meta Python pkg
anaconda = about 160 other Python packages for daily use in data science
Anaconda installer = Miniconda installer +
conda install anaconda
conda is an environment manager and a package manager. It means the tool itself.
conda makes it possible to
conda install flake8
conda create -n myenv python=3.6
conda is not a binary command, is a Python package. To make
conda work, you have to create a Python environment and install package
conda into it. This is where Anaconda installer and Miniconda installer comes in.
Installer Minoconda installs a Python and the package
conda. Installer Anaconda not only does what Miniconda does, it also install a meta Python package named
anaconda for you.
Meta packages, are packages that do NOT contain actual softwares and simply depend on other packages to be installed.
The actual 160+ python packages included in pkg
anaconda are listed in
info/recipe/meta.yaml in its source file.
package: name: anaconda version: '2019.07' build: ignore_run_exports: - '*' number: '0' pin_depends: strict string: py36_0 requirements: build: - python 3.6.8 haf84260_0 is_meta_pkg: - true run: - alabaster 0.7.12 py36_0 - anaconda-client 1.7.2 py36_0 - anaconda-project 0.8.3 py_0 # ... - beautifulsoup4 4.7.1 py36_1 # ... - curl 7.65.2 ha441bb4_0 # ... - hdf5 1.10.4 hfa1e0ec_0 # ... - ipykernel 5.1.1 py36h39e3cac_0 - ipython 7.6.1 py36h39e3cac_0 - ipython_genutils 0.2.0 py36h241746c_0 - ipywidgets 7.5.0 py_0 # ... - jupyter 1.0.0 py36_7 - jupyter_client 5.3.1 py_0 - jupyter_console 6.0.0 py36_0 - jupyter_core 4.5.0 py_0 - jupyterlab 1.0.2 py36hf63ae98_0 - jupyterlab_server 1.0.0 py_0 # ... - matplotlib 3.1.0 py36h54f8f79_0 # ... - mkl 2019.4 233 - mkl-service 2.0.2 py36h1de35cc_0 - mkl_fft 1.0.12 py36h5e564d8_0 - mkl_random 1.0.2 py36h27c97d8_0 # ... - nltk 3.4.4 py36_0 # ... - numpy 1.16.4 py36hacdab7b_0 - numpy-base 1.16.4 py36h6575580_0 - numpydoc 0.9.1 py_0 # ... - pandas 0.24.2 py36h0a44026_0 - pandoc 126.96.36.199 0 # ... - pillow 6.1.0 py36hb68e598_0 # ... - pyqt 5.9.2 py36h655552a_2 # ... - qt 5.9.7 h468cd18_1 - qtawesome 0.5.7 py36_1 - qtconsole 4.5.1 py_0 - qtpy 1.8.0 py_0 # ... - requests 2.22.0 py36_0 # ... - sphinx 2.1.2 py_0 - sphinxcontrib 1.0 py36_1 - sphinxcontrib-applehelp 1.0.1 py_0 - sphinxcontrib-devhelp 1.0.1 py_0 - sphinxcontrib-htmlhelp 1.0.2 py_0 - sphinxcontrib-jsmath 1.0.1 py_0 - sphinxcontrib-qthelp 1.0.2 py_0 - sphinxcontrib-serializinghtml 1.1.3 py_0 - sphinxcontrib-websupport 1.1.2 py_0 - spyder 3.3.6 py36_0 - spyder-kernels 0.5.1 py36_0 # ...
Seeing from the above info, pre-installed packages from meta pkg
anaconda are mainly for web scraping and data science. Like
If you have a Miniconda installed,
conda install anaconda will make it same as an Anaconda installation, except that the installation folder names are different.