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conda env create -f environment.yml
conda env create -f environment.yml
</pre>
</pre>
== Conda environment create, activate, deactivate, info (see a list) ==
[https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-conda Getting started with conda]. More details are in [https://conda.io/projects/conda/en/latest/user-guide/tasks/index.html Tasks].
<syntaxhighlight lang='bash'>
conda --version
# Manage environment
conda info --envs  # see a list of environments.
                  # The active environment is the one with an asterisk (*)
# create a new environment
conda create --name myenv
# remove an environment
conda remove --name myenv --all
# Manage Python
conda create --name snakes python=3.5
conda activate snowflakes # activate
conda info --envs
python --version
conda activate  # Change your current environment back to the default (base)
conda deactivate # exit any python virtualenv
# Managing packages
conda search beautifulsoup4
conda install beautifulsoup4
conda list
# Updating Anaconda or Miniconda
conda update conda
</syntaxhighlight>


== Anaconda ==
== Anaconda ==

Revision as of 13:40, 7 May 2024

Basic

Resources

Python end of life

https://endoflife.date/python or https://devguide.python.org/. By default, the end-of-life is scheduled 5 years after the first release, but can be adjusted by the release manager of each branch.

Install, setup

Multiple python versions

Ubuntu

How to Install the Latest Python Version on Ubuntu Linux

Mac

# check pip version
python -m pip --version

# install
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
python get-pip.py

# Upgrading pip
python -m pip install -U pip
  • On my 2018 mac, the default python3 is at "/usr/local/bin/pyhton3". In "~/Library/Python" directory, it has "2.7", "3.8" and "3.9".
  • On my 2021 mac Ventura, the default python3 is at "/usr/bin". But when we try to run 'python3', it asked to install the command line developer tools. After the installation we can use python3. Still, there is no "~/Library/Python" directory.

Online compiler

IDE

  • PyCharm
  • Thonny
  • Spyder
  • RStudio
    • Create a file (xxx.py)
    • Click the terminal tab. Type 'python' (or ipython3).
    • Use Ctrl/CMD + Alt + Enter to run your python code line by line or a chunk.

Visual Studio Code

The ipynb file can contain figures.

This (Harmony Manuscript) has several notebook files where the code in ipynb files were written in R, not Python.

I can use vsc to open a ipynb file.

Conversion

nbdev

Emacs

Emacs Shell mode: how to send region to shell?

JupyterLab

  • What is the difference between Jupyter Notebook and JupyterLab?
  • Jupyter Notebook (classic) and JupyterLab are both web-based interactive computing environments for working with data and code, but they have some key differences in terms of their user interface, features, and capabilities.
  • JupyterLab is a more modern and powerful tool than Jupyter Notebook, and is recommended for users who want a more flexible and feature-rich interface for working with data and code. However, Jupyter Notebook remains a popular and widely used tool, particularly for working with Jupyter notebooks.
  • 7 Reasons Why You Should Use Jupyterlab for Data Science

Some resources

Different installation methods

JupyterLab Desktop

pip/pip3 Jupyter

  • https://jupyter.org/ 
    which python3
# /usr/bin/python3

pip3 install jupyterlab
jupyter-lab
# http://localhost:8888/lab
# The current directory will be available on the file browser panel in JupyterLab.

    On Mac, it shows the following when I run 'pip3 install jupyterlab' 

    Installing collected packages: pip
  WARNING: The scripts pip, pip3 and pip3.9 are installed in '/Users/XXX/Library/Python/3.9/bin' which is not on PATH.
  Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
Successfully installed pip-23.0
WARNING: You are using pip version 21.2.4; however, version 23.0 is available.
You should consider upgrading via the '/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip' command.

    That is, I need to use /Users/XXX/Library/Python/3.9/bin/jupyter-lab to launch jupyter-lab OR add the path to ".zshrc"; see jupyterlab doc.

conda + Jupyter

conda install --yes jupyterlab && conda clean --yes --all

IPython shell

Extract python code from Jupyter notebook

Execute Javascript in a Jupyter Notebook

How to Execute Javascript in a Jupyter Notebook on Linux

Google colab

R programming

Setup Jupyter Notebook for R or Using R on Jupyter Notebook

To use R in JupyterLab, you will first need to install the IRkernel package in your R environment using the following command: 

install.packages('IRkernel')

Once you have installed the IRkernel package, you can register it with JupyterLab using the following command in your R console: 

IRkernel::installspec()

After you have registered the kernel, you can start a new Jupyter notebook or JupyterLab session and select the "R" kernel from the kernel dropdown menu. This will allow you to run R code in JupyterLab, including data analysis, visualization, and other tasks.

Xeus-R: a future-proof Jupyter kernel for R

Meet Xeus-R: a future-proof Jupyter kernel for R

Run Jupyter Notebooks on an Apple M1 Mac

Cheat sheet

The Most Frequently Asked Questions About Python Programming

https://www.makeuseof.com/tag/python-programming-faq/

Running

Interactively

Use Ctrl+d to quit.

How to run a python script file

python mypython.py

Run python statements from a command line

Use -c (command) option. 

python -c "import psutil"

run python source code line by line

run python source code line by line 

python -m pdb <script.py>

Install a new module

  • See an example of installing HTSeq.

Module != Package

  • A Python module is a single file containing Python code, while a package is a collection of modules organized in a specific way.
  • A module has a filename with the suffix .py added.

PyPI/Python Package Index

pip

pip, use PyPI as the default source for packages and their dependencies.

As an example, motionEye can be installed by pip install or pip2 install; see its wiki and source code on Github. 

sudo apt-get install python-pip
pip --version
pip install SomePackage
pip show --files SomePackage
pip install --upgrade SomePackage
pip install --upgrade https://github.com/Lasagne/Lasagne/archive/master.zip 
pip install ‐‐upgrade pip  # Upgrade itself
pip uninstall SomePackage

sudo apt install python3-pip
pip3 --version

Upgrade packages

How to Upgrade Python Packages with Pip

List installed packages and their versions, location/directory

pip3 list -v

On my Ubuntu 20.04, the packages installed by pip3 is located in ~/.local/lib/python3.8/site-packages/. It does not matter where I issued the pip3 install command.

The danger of upgrading pip

Don't use sudo + pip

https://askubuntu.com/questions/802544/is-sudo-pip-install-still-a-broken-practice

"--user" option in pip

$ pip install Pygments
...
OSError: [Errno 13] Permission denied: '/usr/local/lib/python2.7/dist-packages/Pygments-2.2.0.dist-info'
/usr/local/lib/python2.7/dist-packages/pip-9.0.1-py2.7.egg/pip/_vendor/requests/packages/urllib3/util/ssl_.py:122: InsecurePlatformWarning: A true SSLContext object is not available. This prevents urllib3 from configuring SSL appropriately and may cause certain SSL connections to fail. You can upgrade to a newer version of Python to solve this. For more information, see https://urllib3.readthedocs.io/en/latest/security.html#insecureplatformwarning.
  InsecurePlatformWarning
$ pip install --user Pygments
Collecting Pygments
  Using cached Pygments-2.2.0-py2.py3-none-any.whl
Installing collected packages: Pygments
Successfully installed Pygments-2.2.0

pip -t option

We can force to install a package in user's directory (i.e. a package is already installed in the global directory /usr/lib/python3/dist-packages but some applications cannot find it). Pip install python package into a specific directory other than the default install location 

pip3 install -t ~/.local/bin/python3.10/site-packages pytz

virtualenv

Python “Virtual Environments” allows us to install a Python package in an isolated location, rather than installing it globally.

  • How To Manage Python Packages Using Pip. First Create a new project folder and cd to the project folder in your terminal. 
    # Python 2
$ sudo pip install virtualenv
$ virtualenv <DIR_NAME>
$ source <DIR_NAME>/bin/activate
(<DIR_NAME>) ~$ which python
....
$ deactivate

# Python 3, https://docs.python.org/3/tutorial/venv.html
$ python3 -m venv <DIR_NAME>  # DIR_NAME is also called an environment
$ source <DIR_NAME>/bin/activate
(<DIR_NAME>) ~$ which python
....
$ deactivate

    Here is an example 

    ~/github/PUREE$ python3 -m venv myenv
The virtual environment was not created successfully because ensurepip is not
available.  On Debian/Ubuntu systems, you need to install the python3-venv
package using the following command.

    apt install python3.10-venv
...
~/github/PUREE$ sudo apt install python3.10-venv
~/github/PUREE$ python3 -m venv myenv

~/github/PUREE$ source myenv/bin/activate
(myenv) ~/github/PUREE$ which python
/home/brb/github/PUREE/myenv/bin/python
(myenv) ~/github/PUREE$ pip freeze > requirements.txt
(myenv) ~/github/PUREE$ deactivate
~/github/PUREE$

~/github/PUREE$ ls myenv/bin
activate      activate.fish  f2py   f2py3.10    pip   pip3.10  python3     wheel
activate.csh  Activate.ps1   f2py3  normalizer  pip3  python   python3.10
  • Python Tutorial: virtualenv and why you should use virtual environments. pip freeze. 
    pip list
pip freeze --local > requirements.txt
...
pip install -r requirements.txt
pip list

pipenv

  • Why Use Pipenv to Create a Python Environment?
  • Pipenv is a Python virtualenv management tool that supports a multitude of systems and nicely bridges the gaps between pip, pyenv and virtualenv. It automatically creates and manages a virtualenv for your projects, as well as adds/removes packages from your Pipfile as you install/uninstall packages. It also generates the ever-important Pipfile.lock, which is used to produce deterministic builds.
  • https://pipenv.pypa.io/en/latest/pipfile/

Poetry

  • https://python-poetry.org/
  • Poetry is a tool for dependency management and packaging in Python. It allows you to declare the libraries your project depends on and it will manage (install/update) them for you. Poetry offers a poetry.lock lockfile to ensure repeatable installs, and can build your project for distribution.

pipx (alternative to pip3)

  • Pipx is a tool that helps you install and run end-user applications written in Python. It is similar to macOS’s brew, JavaScript’s npx, and Linux’s apt.
    • Pipx is focused on installing and managing Python packages that can be run from the command line directly as applications.
    • pipx is made specifically for application installation, as it adds isolation yet still makes the apps available in your shell: pipx creates an isolated environment for each application and its associated packages.
    python3 -m pip install --user pipx
python3 -m pipx ensurepath
# OR sudo apt install pipx   
# Or pip3 install pipx

pipx install <package_name> # no sudo needed
pipx list
pipx uninstall <package_name>
  • I need to find an alternative to pip utility because of a problem when I used pip command. Error: externally-managed-environment
  • Official website [1] - Install and Run Python Applications in Isolated Environments, github
  • pipx vs pip
    • pipx is made specifically for application installation and adds isolation yet still makes the apps available in your shell. pipx creates an isolated environment for each application and its associated packages. On the other hand, pip is a general-purpose package installer for both libraries and apps with no environment isolation.
    • If you want to install an application that has dependencies that conflict with other applications or libraries on your system, you can use pipx to create an isolated environment for that application and its dependencies. This way, you can avoid conflicts between different versions of the same package.
    • On my Ubuntu, pip installs packages to /usr/local/lib/python3.8/dist-packages/.
  • Pipx – Install And Run Python Applications In Isolated Environments
  • Run Python applications in virtual environments

python setup.py

If a package has been bundled by its creator using the standard approach to bundling modules (with Python’s distutils tool), all you need to do is download the package, uncompress it and type: 

python setup.py build
sudo python setup.py install

For Python 2, the packages are installed under /usr/local/lib/python2.7/dist-packages/. 

$ ls -l /usr/local/lib/python2.7/dist-packages/
total 12
-rw-r--r-- 1 root staff  273 Jan 12 13:45 easy-install.pth
drwxr-sr-x 4 root staff 4096 Jan 12 13:45 HTSeq-0.6.1p1-py2.7-linux-x86_64.egg
drwxr-sr-x 4 root staff 4096 Jan 12 13:42 pysam-0.9.1.4-py2.7-linux-x86_64.egg

python setup.py bdist_wheel

Get a list of installed modules

http://stackoverflow.com/questions/739993/how-can-i-get-a-list-of-locally-installed-python-modules 

pydoc modules

Not helpful. See the pip list command.

Check installed packages' versions

If you install packages through pip, use 

$ pip list
...
pyOpenSSL (0.13.1)
pyparsing (2.0.1)
pysam (0.10.0)
python-dateutil (1.5)
pytz (2013.7)
rudix (2016.12.13)
scipy (0.13.0b1)
setuptools (1.1.6)
singledispatch (3.4.0.3)
six (1.4.1)
tornado (4.4.2)
vboxapi (1.0)
xattr (0.6.4)
zope.interface (4.1.1)

And more information about a package by using pip show PACKAGE. 

$ pip show pysam
Name: pysam
Version: 0.10.0
Summary: pysam
Home-page: https://github.com/pysam-developers/pysam
Author: Andreas Heger
Author-email: [email protected]
License: MIT
Location: /Users/XXX/Library/Python/2.7/lib/python/site-packages
Requires:

The following method works whether the package is installed by source or binary package 

>>> import pysam
>>> print(pysam.__version__)
0.10.0
>>> print pysam.__version__
0.10.0

See http://hammelllab.labsites.cshl.edu/tetoolkit-faq/

Install a specific version of package through pip

https://stackoverflow.com/questions/5226311/installing-specific-package-versions-with-pip

For example, pysam package was actively released. But the new release (0.11.2.2) may introduce some bugs. So I have to install an older version (0.10.0 works for me on Mac El Capitan and Sierra). 

$ sudo -H pip uninstall pysam
Uninstalling pysam-0.11.2.2:
......
$ sudo -H pip install pysam==0.10.0
Collecting pysam==0.10.0
  Downloading pysam-0.10.0.tar.gz (2.3MB)
    100% |████████████████████████████████| 2.3MB 418kB/s 
Installing collected packages: pysam
  Running setup.py install for pysam ... done
Successfully installed pysam-0.10.0

warning: Please check the permissions and owner of that directory

I got this message when I use root to run the 'sudo pip install PACKAGE' command.

See

python3-pip installed but pip3 command not found?

sudo apt-get remove python3-pip; sudo apt-get install python3-pip

DeepSurv example

https://github.com/jaredleekatzman/DeepSurv 

git clone https://github.com/jaredleekatzman/DeepSurv.git
sudo cp /usr/bin/pip /usr/bin/pip.bak
sudo nano /usr/bin/pip # See https://stackoverflow.com/a/50187211 more detail

# Method 1 for Theano
sudo pip install theano
# Method 2 for Theano
pip install --user --upgrade https://github.com/Theano/Theano/archive/master.zip 

pip install --user --upgrade https://github.com/Lasagne/Lasagne/archive/master.zip
cd DeepSurv/
pip install . --user
sudo apt install python-pytest
pip install h5py --user
sudo pip uninstall protobuf # https://stackoverflow.com/a/33623372
pip install protobuf --user
sudo apt install python-tk
py.test
============ test session starts ===========
platform linux2 -- Python 2.7.12, pytest-2.8.7, py-1.4.31, pluggy-0.3.1
rootdir: /home/brb/github/DeepSurv, inifile:
collected 7 items

tests/test_deepsurv.py .......

========== 7 passed in 5.77 seconds ========

How to list all installed modules

help('modules')  # the output is not pretty

Comment

  1. Use the comment symbol # for a single line
  2. Use a delimiter “”” on each end of the comment. Attention: Don't use triple-quotes

Python Comments from zentut.com.

Docstring

Try / Except

Try and Except in Python 

try:
    number = int(input("Enter a number: "))
    print(number)
except:
    print("Invalid Input")

if __name__ == "__main__":

How to Get the Current Directory in Python

How to Get the Current Directory in Python

Import a compiled C module

string and string operators

Reference:

  1. Python for Genomic Data Science from coursera.
  2. Python Hello World and String Manipulation
dna[0]='g' 
dna[-1]='c' (start counting from the right)
dna[-2]='g'
dna[0:3]='gat' (the end always excluded)
dna[:3]='gat'
dna[2:]='tgc'
len(dna)=6
type(dna)
print(dna)
dna.count('c')
dna.upper()
dna.find('ag')=3  (only the first occurrence of 'ag' is reported)
dna.find('17', 2) (start looking from pos 17)
dna.rfind('ag')   ( search backwards in string)
dna.islower()    (True)
dna.isupper()    (False)
dna.replace('a', 'A')
print(dna.upper().isupper())

Format

Format Specification Mini-Language

Regular expression

The Beginner’s Guide to Regular Expressions With Python

User's input

dna=raw_input("Enter a DNA sequence: ")  # python 2
dna=input("Enter a DNA sequence: ")      # python 3

To convert a user's input (a string) to others 

int(x, [, base])
flaot(x)
str(x) #converts x to a string
str(65) # '65'

chr(x)  # converts an integer to a character
chr(65) # 'A'

Print

Why is parenthesis in print voluntary in Python 2.7?

Fancy Output

print("THE DNA's GC content is ", gc, "%") # gives too many digits following the dot
print("THE DNA's GC content is %5.3f %%" % " % gc) 
# the percent operator separating the formatting string and the value to
# replace the format placeholder
print("%d" % 10.6)  # 10
print("%e" % 10.6)  # 10.060000e+01
print("%s" % dna)   # gatagc

Type

Built-in Functions, How to check type of variable (object) in Python 

type(object)

List

A list is an ordered set of values 

gene_expr=['gene', 5.16e-08, 0.001385, 7.33e-08]
print(gene_expr[2]
gene_expr[0]='Lif'

Slice a list (it will create a new list) 

gene_expr[-3:]  # [5.16e-08, 0.001385, 7.33e-08]
gene_expr[1:3] = [6.09e-07]

Clear the list 

gene_expr[]=[]

List functions

Size of the list 

len(gene_expr)

Delete an element 

del gene_expr[1]

Extend/append to a list 

gene_expr).extend([5.16e-08, 0.00123])

Count the number of times an element appears in a list 

print(gene_expr.count('Lif'), gene_expr.count('gene'))

Reverse all elements in a list 

gene_expr.reverse()
print(gene_expr)
help(list)

Lists as Stacks 

stack=['a', 'b', 'c', 'd']
stack.append('e')

Sorting lists 

mylist=[3, 31, 123, 1, 5]
sorted(mylist)
mylist  # not changed
mylist.sort()

mylist=['c', 'g', 'T', 'a', 'A']
mylist.sort()

Don't change an element in a string! 


motif = 'nacggggtc'
motif[0] = 'a'    # ERROR

Tuples

A tuple consists of a number of values separated by commas, and is another standard sequence data type, like strings and lists. 

t=1,2,3
t
t=(1,2,3)  # we may input tuples with or without surrounding parentheses

Sets

A set is an unordered collection with no duplicate elements. 

brca1={'DNA repair', 'zine ion binding'}
brca2={protein binding', 'H4 histone'}
brca1 | brca2
brca1 & brca2
brca1 - brca2

Dictionaries

A dictionary is an unordered set of key and value pairs, with the requirement that the keys are unique (within on dictionary). 

TF_motif = {'SP1' : 'gggcgg', 
            'C/EBP' : 'attgcgcaat',
            'ATF' : 'tgacgtca',
            'c-Myc' : 'cacgtg',
            'Oct-1' : 'atgcaaat'}
# Access
print("The recognition sequence for the ATF transcription is %s." % TF_motif['ATF']) 
# Update
TF_motif['AP-1'] = 'tgagtca'
# Delete
del TF_motif['SP1']
# Size of a list
len(TF_motif)
# Get a list of all the 'keys' in a dictionary
list(TF_motif.keys())
# Get a list of all the 'values'
list(TF_motif.values())
# sort
sorted(TF_motif.keys())
sorted(TF_motif.values())

We can retrieve data from dictionaries using the items() method. 

for name,seq in seqs.item():
    print(name, seq)

In summary, strings, lists and dictionaries are most useful data types for bioinformatics.

if statement

dna=input('Enter DNA sequence: ')
if 'n' in dna :
  nbases=dna.count('n')
  print("dna sequence has %d undefined bases " % nbases)

if condtion 1:
  do action 1
elif condition 2:
  do action 2
else:
  do action 3

Logical operators

Use and, or, not. 

dna=input('Enter DNA sequence: ')
if 'n' in dna or 'N' in dna:
    nbases=dna.count('n')+dna.count('N')
    print("dna sequence has %d undefined bases " % nbases)
else:
    print("dna sequence has no undefined bases)

Loops

while 

dna=input('Enter DNA sequence:')
pos=dna.find('gt', 0)

while pos>-1 :
    print("Donar splice site candidate at position %d" %pos)
    pos=dna.find('gt', pos+1)

for 

motifs=["attccgt", "aggggggttttttcg", "gtagc"]
for m in motifs:
    print(m, len(m))

range 

for i in range(4):
    print(i)
for i in range(1,10,2):
    print(i)

Problem: find all characters in a given protein sequence are valid amino acids. 

protein='SDVIHRYKUUPAKSHGWYVCJRSRFTWMVWWRFRSCRA'
for i in range(len(protein)):
    if protein[i] not in 'ABCDEFGHIKLMNPQRSTVWXYZ': 
        print("this is not a valid protein sequence!")
        break

continue 

protein='SDVIHRYKUUPAKSHGWYVCJRSRFTWMVWWRFRSCRA'
corrected_protein=''
for i in range(len(protein)):
    if protein[i] not in 'ABCDEFGHIKLMNPQRSTVWXYZ': 
        continue
    corrected_protein=corrected_protein+protein[i]
print("COrrected protein seq is %s" % corrected_protein)

else Statement used with loops

  • If used with a for loop, the else statement is executed when the loop has exhausted iterating the list
  • If used with a while loop, the else statement is executed when the condition becomes false
# Find all prime numbers smaller than a given integer
N=10
for y in range(2, N):
    for x in range(2, y):
        if y %x == 0:
            print(y, 'equals', x, '*', y//x)
            break
        else:
            // loop fell through without finding a factor
            print(y, 'is a prime number')

The pass statement is a placeholder 

if motif not in dna:
    pass
else:
    some_function_here()

Functions

Get modular with Python function 

def function_name(arguments) :
    function_code_block
    return output

For example, 

def gc(dna) :
    "this function computes the gc perc of a dna seq"
    nbases=dna.count('n')+dna.count('n')
    gcpercent=float(dna.count('c')+dna.count('C')+dna.count('g)
+dna.count('G'))*100.0/(len(dna)-nbases)
    return gcpercent
gc('AAAAGTNNAGTCC')
help(gc)

SyntaxError: invalid syntax

https://stackoverflow.com/a/11890194

On the Python shell add an empty line at the end of function definition. Eg 

>>> def fun(a):
...     return a+1
... 
>>> fun(9)
10
>>> exit()

On a python script 

def fun(a):
    return a+1
print fun(9)

Debug functions

https://stackoverflow.com/a/4929267

You can launch a Python program through pdb by using pdb myscript.py or python -m pdb myscript.py 

$ cat debug.py
def fun(a):
    a= a*2
    a= a*3
    return a+1
print fun(5)

$ python -m pdb debug.py
> /home/pi/Downloads/debug.py(1)<module>()
-> def fun(a):
(Pdb) b fun
Breakpoint 1 at /home/pi/Downloads/debug.py:1
(Pdb) c
> /home/pi/Downloads/debug.py(2)fun()
-> a= a*2
(Pdb) n
> /home/pi/Downloads/debug.py(3)fun()
-> a= a*3
(Pdb) 
> /home/pi/Downloads/debug.py(4)fun()
-> return a+1
(Pdb) p a
30
(Pdb) n
--Return--
> /home/pi/Downloads/debug.py(4)fun()->31
-> return a+1
(Pdb) exit

Boolean functions

Problem: checks if a given dna seq contains an in-frame stop condon 

dna=input("Enter a dna seq: ")
if (has_stop_codon(dna)) :
    print("input seq has an in frame stop codon.")
else :
    print("input seq has no in frame stop codon.")

def has_stop_codon(dna) :
    "This function checks if given dna seq has in frame stop codons."
    stop_codon_found=False
    stop_codons=['tga', 'tag', 'taa']
    for i in range(0, len(dna), 3) :
        codon=dna[i:i+3].lower()
        if codon in stop_codons : 
            stop_codon_found=True
            break
    return stop_codon_found

Function default parameter values

Suppose the has_stop_codon function also accepts a frame argument (equal to 0, 1, or 2) which specifies in what frame we want to look for stop codons. 

def has_stop_codon(dna, frame=0) :
    "This function checks if given dna seq has in frame stop codons."
    stop_codon_found=False
    stop_codons=['tga', 'tag', 'taa']
    for i in range(frame, len(dna), 3) :
        codon=dna[i:i+3].lower()
        if codon in stop_codons : 
            stop_codon_found=True
            break
    return stop_codon_found

dna="atgagcggccggct"
has_stop_codon(dna)    # False
has_stop_codon(dna, 0) # False
has_stop_codon(dna, 1) # True
has_stop_codon(frame=0, dna=dna)

More examples

Reverse complement of a dna sequence 

def reversecomplement(seq):
    """Return the reverse complement of the dna string."""
    seq = reverse_string(seq)
    seq = complement(seq)
    return seq

reversecomplement('CCGGAAGAGCTTACTTAG')

To reverse a string 

def reverse_string(seq):
    return seq[::-1]

reverse_string(dna)

Complement a DNA Sequence 

def complement(dna):
    """Return the complementary sequence string."""
    basecomplement = {'A':'T', 'C':'G', 'G':'C', 'T':'A', 
                      'N':'N', 'a':t', 'c':'g', 'g':'c', 't':'a', 'n':'n'} # dictionary
    letters = list(dna) # list comprehensions
    letters = [basecomplement[base] for base in letters]
    return ''.join(letters)

Split and Join functions

sentence="enzymes and other proteins come in many shapes"
sentence.split()  # split on all whitespaces
sentence.split('and') # use 'and' as the separator

'-'.join(['enzymes', 'and', 'other', 'proteins', 'come', 'in', 'many', 'shapes'])

Variable number of function arguments

def newfunction(fi, se, th, *rest):
  print("First: %s" % fi)
  print("Second: %s" % se)
  print("Third: %s" % th)
  print("Rest... %s" % rest)
  return

Modules and packages

Packages group multiple modules under on name, by using "dotted module names". For example, the module name A.B designates a submodule named B in a package named A. See What's the difference between a Python module and a Python package?

<dnautil.py> 

#!/usr/bin/python
"""
dnautil module contains a few useful functions for dna seq
"""
def gc(dna) :
    blah
    blah
    return gcpercent

When a module is imported, Python first searches for a built-in module with that name.

If built-in module is not found, Python then searches for a file obtained by adding the extension .py to the name of the module that it's imported:

  • in your current directory,
  • the directory where Python has been installed
  • in a path, i.e., a colon(':') separated list of file paths, stored in the environment variable PYTHONPATH.

You can use the sys.path variable from the sys built-in module to check the list of all directories where Python look for files 

import sys
sys.path

If the sys.path variable does not contains the directory where you put your module you can extend it: 

sys.path.append("/home/$USER/python")
sys.path

Using modules (from PACKAGE/DIRNAME/FILENAME import CLASS)

from math import *
print(floor(3.7))

import dnautil
dna="atgagggctaggt"
gc(dna)          # gc is not defined
dnautil.gc(dna)  # Good

Import Names from a Module 

from dnautil import *
gc(dna)          # OK

from dnautil import gc, has_stop_codon

Get modular with Python functions & Learn object-oriented programming with Python from opensource.com.

from...import vs import vs import...as

  • Difference between 'import' and 'from...import' in Python
  • Import, From and As Keywords in Python
  • `from … import` vs `import .`
  • Difference between import and from in Python. Python's import loads a Python module into its own namespace, so that you have to add the module name followed by a dot in front of references to any names from the imported module that you refer to: 
    import feathers
duster = feathers.ostrich("South Africa")

    from loads a Python module into the current namespace, so that you can refer to it without the need to mention the module name again: 

    from feathers import *
duster = ostrich("South Africa")
    • Question: Why are both import and from provided? Can't I always use from? Answer: If you were to load a lot of modules using from, you would find sooner or later that there was a conflict of names; from is fine for a small program but if it was used throughout a big program, you would hit problems from time to time
    • Question: Should I always use import then? Answer: No ... use import most of the time, but use from is you want to refer to the members of a module many, many times in the calling code; that way, you save yourself having to write "feather." (in our example) time after time, but yet you don't end up with a cluttered namespace. You could describe this approach as being the best of both worlds.
  • from … import OR import … as for modules
  • Some examples: 
    from numpy import array   # Run file; load specific 'attribute'
arr = array([1,2,3])    # Use name directly: no need to qualify
print(arr) # print [1 2 3]

from math import pi
pi # 3.141592653589793
math.pi  # NameError: name 'math' is not defined

    VS 

    import numpy   # Run file; load module as a whole
arr = numpy.array([1,2,3])  # Use its attribute names: '.' to qualify
print(arr) # print [1 2 3]

import math
math.pi # 3.141592653589793
dir(math)

    VS 

    import numpy as np
dir(np)

import math as m
m.pi # 3.141592653589793
  • scRNA_cell_deconv_benchmark example.

help

from AAA import BBB
help(BBB)
help(BBB.FunctionName)

import BBB as CCC
help(CCC)

Packages & __init__.py

Each package in Python is a directory which MUST contain a special file __init__.py. This file can be empty and it indicates that the directory it contains is a Python package, so it can be imported the same way a module can be imported. https://docs.python.org/2/tutorial/modules.html

Example: suppose you have several modules dnautil.py, rnautil.py , and proteinutil.py. You want to group them in a package called "bioseq" which processes all types of biological sequences. The structure of the package: 

bioseq/
  __init__.py
  dnautil.py
  rnautil.py
  proteinutil.py
  fasta/
    __init__.py
    fastautil.py
  fastq/
    __init__.py
    fastqutil.py

Loading from packages: 

import bioseq.dnautil
bioseq.dnautil.gc(dna)

from bioseq import dnautil
dnautil.gc(dna)

from bioseq.fasta.fastautil import fastqseqread

Example

Building a Multiple Choice Quiz by freeCodeCamp.org

QuestionFile.py 

class Question:
    def __init__(self, prompt, answer):
        self.prompt = prompt
        self.answer = answer

app.py 

from QuestionFile import Question

question_prompts = [
    "What color are apples?\n(a) Red/Green\n(b) Purple\n(c) Orange\n\n",
    "What color are Bananas?\n(a) Teal\n(b) Magenta\n(c) Yellow\n\n",
    "What color are strawberries?\n(a) Yellow\n(b) Red\n(c) Blue\n\n"
]

questions = [
    Question(question_prompts[0], "a"),
    Question(question_prompts[1], "c"),
    Question(question_prompts[2], "b")
]

def run_test(question):
    score = 0
    for question in questions:
        answer = input(question.prompt)
        if answer == question.answer:
            score += 1
    print("You got " + str(score) + " /" + str(len(questions))+ " correct")

run_test(questions)

Run the program by python3 app.py

Files - Communicate with the outside

f=open('myfile', 'r') # read
f=open('myfile')
f=open('myfile', 'w') # write
f=open('myfile', 'a') # append

Take care if a file does not exists

try:
    f = open('myfile')
except IOError:
    print("the file myfile does not exist!!")

Reading

for line in f:
    print(line)

Change positions within a file object 

f.seek(0)  # go to the beginning of the file
f.read()

Read a single line 

f.seek(0)
f.readline()

Write into a file 

f=open("/home/$USER/myfile, 'a)
f.write("this is a new line")
f.close()

>>> with open("file.txt", "w") as f:
...   f.write(str(object))
...

Importing large tab-delimited .txt file into Python 

# R
write.table(iris[1:10,], file="iris.txt", sep="\t", quote=F, row.names=F)

# Python
import csv
with open('iris.txt') as f:
    reader = csv.reader(f, delimiter="\t")
    d = list(reader)
print(d[0][2])
print(d[1][2])

# Shell
$ python test_csv.py
Petal.Length
1.4

If the data are all numerical, we can use the numpy package. 

# R
write.table(iris[1:10, 1:4], 
            file="~/Downloads/iris2.txt", 
            sep="\t", quote=F, row.names=F, col.names=F)

# Python
import numpy as np
d = np.loadtxt('iris2.txt', delimiter="\t")
print(d[0][2])
print(d[1][2])

# Shell
$ python test_csv2.py
1.4
1.4

Read text file from a URL

import urllib.request

url = "http://textfiles.com/adventure/aencounter.txt"
file = urllib.request.urlopen(url)

for line in file:
   print(line.decode('utf-8'))

Command line arguments

Suppose we run 'python processfasta.py myfile.fa' in the command line, then 

import sys
print(sys.argv)  #  ['processfasta.py', 'myfile.fa']

More completely 

#!/usr/bin/python
"""
processfasta.py builds a dictionary with all sequences from a FASTA file.
"""

import sys
filename=sys.argv[1]

try:
  f = open(filename)
except IOError:
    print("File %s does not exist!" % filename)

Parsing command line arguments with getopt. Suppose we want to store in the dictionary the sequences bigger than a given length provided in the command line: 'processfasta.py -l 250 myfile.fa' 

#!/usr/bin/python
import sys
import getopt

def usage():
    print """
processfasta.py: reads a FASTA file and builds a 
dictionary with all sequence bigger than a given length

processfasta.py [-h] [-l <length>] <filename>

 -h           print this message
 -l <length>  filter all sequences with a length
              smaller than <length>
              (default <length>=0)
 <filename>   the file has to be in FASTA format

o, a = getopt.getopt(sys.argv[1:], '1:h')
opts = {} # empty dictionary
seqlen=0;

for k,v in o:
    opts[k] = v
if 'h' in opts.keys():  # he means the user wants help
    usage(); sys.exit()
if len(a) < 1:
    usage(); sys.exit("input fasta file is missing")
if 'l' in opts.keys():
    if opts['l'] <0 :
        print("length of seq should be positive!"); sys.exit(0);
    seqlen=opts['l']

stdin and stdout

sys.stdin.read()

sys.stdout.write("Some useful ouput.\n")

sys.stderr.write("Warning: input file was not found\n")

Call external programs

import subprocess
subprocess.call('["ls", "-l"]) # return code indicates the success or failure of the execution

subprocess.call('["tophat", "genome_mouse_idx", "PE_reads_1.fq.gz", "PE_reads_2.fq.gz"])

Exceptions

5 Python Examples to Handle Exceptions using try, except and finally

Debugging

How to Debug Your Python Code

Biopython & Pubmed

  • Parsers for various bioinformatics file formats (FASTA, Genbank)
  • Access to online services like NCBI Entrez or Pubmed databases
  • Interfaces to common bioinformatics programs such as BLAST, Clustalw and others.
import Bio
print(Bio.__version__)

Running BLAST over the internet 

from Bio.Blast import NCBIWWW
fasta_string = open("myseq.fa").read()
result_handle = NCBIWWW.qblast("blastn":, "nt", fasta_string)
# blastn is the program to use
# nt is the database to search against
# default output is xml
help(NCBIWWW.qblast)

The BLAST record 

from Bio.Blast import NCBIXML
blast_record = NCBIXML.read(result_handle)

Parse BLAST output 

len(blast_record.alignments)

E_VALUE_THRESH = 0.01
for alignment in blas_record.alignments:
  for hsp in alignment.hsps:
    if hsp.expect < E_VALUE_THRESH:
      print('***Alignment***')
      print('sequence:', alignment.title)
      print('length:', alignment.length)
      print('e value:', hsp.expect)
      print(hsp.query)
      print(hsp.match)
      print(hsp.sbjct)

More help with Biopython

pubmed_parser

Parser for Pubmed Open-Access XML Subset and MEDLINE XML Dataset

pyTest

pyc file

What is the difference between .py and .pyc files? [duplicate]. I observe it can cause a problem when I want to modify a python file but it keeps using the old pyc file so my change is not used (Raspbery Pi e-ink example).

Shutdown or restart OS

Below is tested on Raspbian 

import os
os.system('sudo shutdown -h now')

Popular python libraries

20 Python libraries you can’t live without

psutil

# pip install psutil --user
for x in range(10):
    psutil.cpu_percent(interval=1)

numpy

pandas

30 pandas Commands for Manipulating DataFrames

Write a pandas dataframe to a text file using to.csv(). https://stackoverflow.com/a/41514539 

a.to_csv('xgboost.txt', header=True, index=True, sep='\t')

scipy

seaborn

matplotlib

Installation. 

python -m pip install -U pip
python -m pip install -U matplotlib

# https://stackoverflow.com/a/50328517
sudo apt-get install python3.5-tk

Example. 

from sklearn import datasets
iris = datasets.load_iris()
import matplotlib.pyplot as plt
iris = iris.data

# Scatterplot
plt.scatter(iris[:,1], iris[:,2])
plt.show()

# Boxplot
plot.boxplot(iris[:,1])
plt.show()

# Histogram
plt.hist(iris[:,1])
plt.show()

scikit-learn

scikit-learn: Machine Learning in Python

Installation. 

pip install -U scikit-learn

Example. 

$ python
>>> from sklearn import datasets
>>> iris = datasets.load_iris()
>>> digits = datasets.load_digits()

PyTorch

feedparser

Never miss a Magazine article — build your own RSS notification system

Boto

A Python interface to Amazon Web Services

PIL, Pillow

plotnine

Python and R – Part 2: Visualizing Data with Plotnine

nltk: Natural Language Toolkit

https://www.nltk.org/

pygame

Learn Python by creating a video game

scanpy

Trouble shooting

ImportError: cannot import name main when running pip

https://stackoverflow.com/a/50187211

Error: externally-managed-environment

See pipx

TypeError: ‘module’ object is not callable

I was trying to run "bbknn.py" from here.

Solve “TypeError: ‘module’ object is not callable” in Python, TypeError: 'module' object is not callable

The problem is I have a file called "bbknn.py" and I have "import bbknn" in the code. It will confuse python. The solution is to rename my script file "bbknn.py" (avoid MODULE.py) to other name like "bbknnDemo.py".

When I import my module in python, it automatically runs all of the defined functions inside of it. How do I prevent it from auto executing my functions, but still allow me to call them in my main script?

Illegal instruction

I got this error after I called python3 -c 'import scanpy'. Python on Biowulf. 

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
TMPDIR=/tmp bash Miniconda3-latest-Linux-x86_64.sh -p ~/conda -b

source ~/conda/etc/profile.d/conda.sh # ~/conda/condabin is added to PATH

conda activate base
python -V # Python 3.9.4

conda create -n project1 pandas numpy scipy -y
conda activate project1
pip3 install scanpy bbknn
ls ~/conda/envs/project1/lib/python3.9/site-packages
# bbknn and scanpy are there  
python3 -c 'import scanpy'
# Illegal instruction

conda info --env
conda deactivate
conda remove --all -n project1 -y
conda deactivate

No matching distribution found for XXX

Got an error No matching distribution found for lasagne==0.2.dev1 when I ran 'pip install .' on DeepSurv.

https://github.com/imatge-upc/saliency-salgan-2017/issues/29

Python AttributeError: 'module' object has no attribute 'SSL_ST_INIT'

See https://stackoverflow.com/a/52398193. I got this message after I ran sudo pip install --upgrade cryptography and pip show cryptography. The reason I try to upgrade cryptography is the following message 

$ pip show protobuf
/home/brb/.local/lib/python2.7/site-packages/pip/_vendor/requests/__init__.py:83: 
  RequestsDependencyWarning: Old version of cryptography ([1, 2, 3]) may cause slowdown.
  warnings.warn(warning, RequestsDependencyWarning)
Name: protobuf
...

And OpenSSL & pyOpenSSL-0.15.1.egg-inf are under /usr/lib/python2.7/dist-packages directory on my Ubuntu 16.04.

Note the following solutions do not work 

$ sudo pip uninstall pyopenssl
$ sudo pip install pyOpenSSL==16.2.0

I always get an error message 

...
  File "/usr/lib/python2.7/dist-packages/OpenSSL/SSL.py", line 118, in <module>
    SSL_ST_INIT = _lib.SSL_ST_INIT
AttributeError: 'module' object has no attribute 'SSL_ST_INIT'

And a quick solution is to do sudo rm -r /usr/local/lib/python2.7/dist-packages/OpenSSL. I also did sudo pip install pyopenssl but I did not follow this answer (sudo apt install --reinstall python-openssl).

/usr/bin/env: ‘python’: No such file or directory

On Ubuntu 20.04, 

sudo apt-get install python-is-python3

This solved an error when I used youtube-dl.

Projects based on python

  • pithos Pandora on linux
  • Many Raspberry Pi GPIO projects
  • GeneScissors It also requires pip and scikit-learn packages.
  • KeepNote It depends on Python 2.X, sqlite and PyGTK.
  • Zim It depends on Python, Gtk and the python-gtk bindings.
  • Cherrytree It depends on Python2, Python-gtk2, Python-gtksourceview2, p7zip-full, python-enchant and python-dbus.

Send emails

  • Less secure apps & your Google Account. To help keep your account secure, from May 30, 2022, ​​Google no longer supports the use of third-party apps or devices which ask you to sign in to your Google Account using only your username and password.
    • Send Email via Gmail and SMTP Use an App Password 2022/9. Click on Security -> 2-Step Verification (You may need to enter your PW first). Scroll to the bottom of the page, and you'll see the "App passwords" section. You can delete/create app passwords but you can't view any existing passwords.
  • How to Send Automated Email Messages in Python 3 2021/3

GUI programming

New book: Create Graphical User Interfaces with Python

Qt for GUI development

Python 3

pip3

Use pip3 instead of pip for Python 3. For example, 

pip3 install --upgrade pip

pip3 install -U scikit-learn

pip3 install -U matplotlib

http.server

Edit Files With Workspaces. The 'http.server' module is contained in python3. 

cd ~/website
python3 -m http.server

C vs Python

C vs. Python: The Key Differences

R and Python: reticulate package

  • Installing and Configuring Python with RStudio
    • The instruction is based on virtualenv. But I'm following Biowulf's Python miniconda instruction to create a new project/environment. One caveat is I need to run source ~/$USER/conda/etc/profile.d/conda.sh each time before I start R in order to make conda available OR I need to set the RETICULATE_MINICONDA_PATH variable (see below).
    • The conda-related reticulate functions include conda_create(), use_condaenv(), conda_install(), conda_list(), conda_remove()
    • Use py_config() to check the current python path and other python versions found.
    • My example 
      library(reticulate)
# Assume I followed Biowulf's instruction to create 'project1'
Sys.setenv(RETICULATE_MINICONDA_PATH = "~/conda") 
conda_list()
use_condaenv("project1", required=T)
py_config()
  • Python Version Configuration. Suppose I have installed miniconda and create a new environment called 'project1'. Then after calling source ~/conda/etc/profile.d/conda.sh I can start in R 
    library(reticulate)
use_condaenv("project1", required = TRUE)
  • Test python and markdown files 
    def add_three(x):
    z = x + 3
    return z

    ---
title: "R Notebook"
output: html_notebook
---

```{r}
library(reticulate)
py_discover_config()
x <- 5
source_python("test.py")
y <- add_three(x)
print(y)
```

Pass R variables to Python. Works
```{python}
a = 7
print(r.x)
```

Pass python variables to R. Works.
```{r}
py$a
py_run_string("y = 10"); py$y
```

How to quit python

Type exit and hit Enter. See https://rstudio.github.io/reticulate/.

R vs Python

Call R from Python

  • rwrap Seamlessly integrate R packages into Python.
  • rpy2

Conda, Anaconda, miniconda

Private environment

Conda on Biowulf & mambaforge

Transfer a conda environment to another computer: YAML files

Managing environments 

# computer 1
conda env export > environment.yml

# computer 2
conda env create -f environment.yml

Conda environment create, activate, deactivate, info (see a list)

Getting started with conda. More details are in Tasks. 

conda --version

# Manage environment
conda info --envs  # see a list of environments. 
                   # The active environment is the one with an asterisk (*)
# create a new environment
conda create --name myenv
# remove an environment
conda remove --name myenv --all

# Manage Python
conda create --name snakes python=3.5
conda activate snowflakes # activate
conda info --envs
python --version
conda activate  # Change your current environment back to the default (base)
conda deactivate # exit any python virtualenv

# Managing packages
conda search beautifulsoup4
conda install beautifulsoup4
conda list

# Updating Anaconda or Miniconda
conda update conda

Anaconda

  • Introduction to Anaconda. Simplifies installation of Python packages
    • Platform-independent package manager
    • Doesn’t require administrative privileges
    • Installs non-Python library dependencies (MKL, HDF5, Boost)
    • Provides ”virtual environment” capabilities
    • Many channels exist that support additional packages
  • Install Anaconda on macOS. Better to use the command line method in order to install it to the user's directory. The new python can be manually loaded into the shell by using source ~/.bash_profile. Like Ubuntu, ananconda3 is installed under ~/ directory. In addition, Anaconda-Navigator is available under Finder -> Applications.
  • How To Install the Anaconda Python Distribution on Ubuntu 16.04. As we can see Anaconda3 will be installed under /home/$USER/anaconda3.
    • Download Anaconda3-2018.12-Linux-x86_64.sh from https://www.anaconda.com/distribution/#download-section
    • bash Anaconda3-2018.12-Linux-x86_64.sh
    • There is a question: Do you wish the installer to initialize Anaconda3. If you answer Yes, it will run conda init & modify ~/.bashrc file. # This will overwrite system's Python. So the default python/python3 will now be in /home/$USER/anaconda3/bin/. 
      Do you wish the installer to initialize Anaconda3
by running conda init? [yes|no]
[no] >>> yes
no change     /home/brb/anaconda3/condabin/conda
no change     /home/brb/anaconda3/bin/conda
no change     /home/brb/anaconda3/bin/conda-env
no change     /home/brb/anaconda3/bin/activate
no change     /home/brb/anaconda3/bin/deactivate
no change     /home/brb/anaconda3/etc/profile.d/conda.sh
no change     /home/brb/anaconda3/etc/fish/conf.d/conda.fish
no change     /home/brb/anaconda3/shell/condabin/Conda.psm1
no change     /home/brb/anaconda3/shell/condabin/conda-hook.ps1
no change     /home/brb/anaconda3/lib/python3.8/site-packages/xontrib/conda.xsh
no change     /home/brb/anaconda3/etc/profile.d/conda.csh
modified      /home/brb/.bashrc

==> For changes to take effect, close and re-open your current shell. <==

If you'd prefer that conda's base environment not be activated on startup, 
   set the auto_activate_base parameter to false: 

conda config --set auto_activate_base false

      If I choose not to modify .bashrc file, 

      Do you wish the installer to initialize Anaconda3
by running conda init? [yes|no]
[no] >>> no

You have chosen to not have conda modify your shell scripts at all.
To activate conda's base environment in your current shell session:

eval "$(/home/brb/anaconda3/bin/conda shell.YOUR_SHELL_NAME hook)" 

To install conda's shell functions for easier access, first activate, then:

conda init

If you'd prefer that conda's base environment not be activated on startup, 
   set the auto_activate_base parameter to false: 

conda config --set auto_activate_base false

Thank you for installing Anaconda3!
    • Anaconda-Navigator (including jupyter notebook, Spyder IDE, ...) can be launched by typing anaconda-navigator in a terminal

Miniconda

  • https://docs.conda.io/en/latest/miniconda.html As you can see miniconda installers were separated by the Python version.
  • How To Install Miniconda In Linux 2021. It includes Install Miniconda interactively, unattended installation, Update Miniconda, and Uninstall Miniconda. If you've chosen the default location, the installer will display “PREFIX=/var/home/<user>/miniconda3”. To manually activate conda's base environment, do /home/<user>/miniconda3/etc/profile.d/conda.sh where we assume miniconda is installed under /home/<user>/miniconda3 directory.
  • Miniconda Installation for macOS users 2019. At the end of installation, we see if we don't want conda's base environment to be activated on start up, we can do conda config --set auto_activate_base false
  • See also Python on Biowulf about how to specify prefix.
  • We can add/install a module to an existing environment. See Miniconda: Python(s) in a convenient setup.
conda install -n <env_name> <package>
conda create -n myenv python=3 # create a new environment named “myenv” with Python 3 installed
   # after that, use "conda activate myenv" and use "conda install numpy" to install the numpy

Install and "conda init"

  • Windows: screenshots are included Setting up Python on Windows with Miniconda by Anaconda & Anaconda documentation. The default is not to add Anaconda to my PATH environment variable.
  • Ubuntu: How to Install Miniconda on Ubuntu 20.04. After installation, PATH variable will prepend ~/miniconda3/condabin which contains only 1 file: conda.
  • conda init
    • Running conda init initializes conda for shell interaction by writing some shell code in the relevant startup scripts of your shell (e.g~/.bashrc) 1. This allows the conda command to interact more closely with the shell context and provides a cleaner PATH manipulation and snappier responses in some conda commands. The main advantage of running conda init is that it enables the use of the conda activate and conda deactivate commands, which are used to activate and deactivate conda environments.
    • We only need to call "conda init" once no matter after we install conda how many conda environments we will work.
    • One disadvantage of running conda init is that it can sometimes cause issues if the initialization is not done correctly or if there are conflicts with other configurations in your shell startup scripts. However, these issues can usually be resolved by troubleshooting and making the necessary changes to your configurat

conda environment

A conda environment is a directory that contains a specific collection of conda packages that you have installed.

You need to create an environment first before you can activate it. The conda activate command does not create an environment for you, it only activates an existing one. 

conda create --name myenv

conda activate myenv

Q: Where are the environments located? A: Conda environments are typically stored in the envs subdirectory of your Anaconda installation directory. For example, if you have an environment named myenv, it would be located in a directory like ~/anaconda3/envs/myenv. The exact path can be found by using conda env list command.

Q: How do I list all existing environments? A: To list all existing conda environments, you can use the conda env list or conda info --envs command. Here’s how you do it: 

conda env list
#
base       * /opt/conda
DrivR-Base   /opt/conda/envs/DrivR-Base

Q: How to quit a conda environment? 

conda deactivate  # Return to base
conda deactivate  # Exit base

Q: Check the disk space used by a specific conda environment. 

du -sh /path/to/conda/envs/your_enviornment_name

Q: How to delete a conda environemnt, 

conda deactivate
conda env remove --name your_environment_name
# OR
conda remove --name your_environment_name --all

Install all anaconda packages

Uninstall miniconda

  1. rm -rf ~/miniconda3
  2. nano ~/.bash_profile and delete conda initialize block

What's the purpose of the “base” (for best practices) in Anaconda?

https://stackoverflow.com/a/56504279

Does Conda replace the need for virtualenv?

Yes. Conda is not limited to Python but can be used for other languages too.

GCC/gFortran

  • conda install gcc
  • Using conda-forge channel - conda install -c conda-forge gfortran

Using R language with Anaconda

  • Using R language with Anaconda 
    conda create -n r_env r-essentials r-base
conda activate r_env
  • Difference of install a package using install.packages() function in R and using the conda install command?
    • The install.packages() function in R and the conda install command are two different ways to install R packages. The install.packages() function is used to install packages from the Comprehensive R Archive Network (CRAN), while the conda install command is used to install packages from the Anaconda repository.
    • One key difference between the two methods is that conda can manage dependencies across multiple programming languages, while install.packages() only manages dependencies within R.
    • Another difference is that conda allows you to create and manage multiple isolated environments, each with its own set of packages. This can be useful if you want to have different versions of packages available for different projects. With install.packages(), all packages are installed in the same global library, which can make it more difficult to manage dependencies and avoid conflicts.
  • The Definitive Guide to Conda Environments, Using R language with Anaconda. Environments created with conda create live by default in the envs/ folder of your Conda directory, whose path will look something like /Users/user-name/miniconda3/envs or /Users/user-name/anaconda3/envs. 
    Activate conda base                  Create a new env    Activate a new env           Deactivate an env
----------------------------> (base) ----------------->  -------------------> (r-env) -----------------> (base)
eval $(conda shell.bash hook)"       conda create r-env  conda activate r-env         conda deactivate

    $ eval "$(/home/brb/anaconda3/bin/conda shell.bash hook)"
(base) $ mkdir mypythonproj; cd mypythonproj  # This step seems not necessary
(base) $ conda create -n r-env r-base
...
#
# To activate this environment, use
#
#     $ conda activate r-env
#
# To deactivate an active environment, use
#
#     $ conda deactivate
(base) $ conda activate r-env
(r-env) $ ls anaconda3/envs
r-env
(r-env) $ conda install r-essentials
(r-env) $ which R
/home/brb/anaconda3/envs/r-env/bin/R
(r-env) $ ls -la   # Still Empty
(r-env) $ R --version
R version 3.4.3 (2017-11-30) -- "Kite-Eating Tree"
# Note that the current R version should be 4.0.3
(r-env) $ conda env list
base                     /home/brb/anaconda3
r-env                 *  /home/brb/anaconda3/envs/r-env
(r-env) $ conda deactivate
(base)  $

    It seems to be better to save the environment inside a project directory. So using python -m venv /path/to/new/environment method is preferred. You can also use conda create --prefix /path/to/new/environment. Placing environments outside of the default env/ folder comes with some drawbacks. Read the document of 'The Definitive Guide to Conda Environments'.

  • conda-forge channel, A brief introduction, https://anaconda.org/conda-forge/r-base. Following the instruction seems to mess things up though the conda-forge says the latest version is 4.0.3 (3 years late). 
    $ eval "$(/home/brb/anaconda3/bin/conda shell.bash hook)"
(base) $ conda install -c conda-forge r-base
...
## Package Plan ##

  environment location: /home/brb/anaconda3

  added / updated specs:
    - r-base
...
Downloading and Extracting Packages
r-base-3.2.2    ...
(base) $ R --version
/home/brb/anaconda3/lib/R/bin/exec/R: error while loading shared libraries: libreadline.so.6: cannot open shared object file: No such file or directory
(base) $ which R
/home/brb/anaconda3/bin/R

Run R with Jupyter notebook

Example 1: GEO2RNAseq

GEO2RNAseq

Example 2: p-NET

Biologically informed deep neural network for prostate cancer classification and discovery and the paper 2021.

Mamba

Web framework

Flask

Django

Games

Simulate gravity in your Python game

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