Environment management with conda and pip in MLOps - Step-by-Step Execution

Process Flow - Environment management with conda and pip

Start: Need new environment

↓

Create conda env

↓

Activate env

↓

Install packages with conda

↓

If package missing

Yes↓

Install package with pip

↓

Use environment

↓

Deactivate env

↓

Delete env if needed

↓

End

This flow shows how to create and manage a Python environment using conda, install packages with conda or pip, then use and clean up the environment.

Execution Sample

MLOps

conda create -n myenv python=3.12
conda activate myenv
conda install numpy
pip install requests
conda deactivate

Create a conda environment, activate it, install numpy with conda, install requests with pip, then deactivate the environment.

Process Table

Step	Command	Action	Result/Output
1	conda create -n myenv python=3.12	Create environment named myenv with Python 3.12	Environment 'myenv' created with Python 3.12
2	conda activate myenv	Activate the environment myenv	Prompt changes to (myenv), environment active
3	conda install numpy	Install numpy package using conda	numpy installed successfully
4	pip install requests	Install requests package using pip inside conda env	requests installed successfully
5	conda deactivate	Deactivate the current environment	Prompt returns to base, environment deactivated
6	conda env list	List all conda environments	Shows 'myenv' and 'base' environments
7	conda remove -n myenv --all	Delete the environment myenv	Environment 'myenv' deleted successfully

💡 Environment deleted or deactivated, no active conda environment

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	After Step 7
Active Environment	base	base	myenv	myenv	myenv	base	base
Installed Packages	base packages	base packages	base packages	base + numpy	base + numpy + requests	base packages	base packages

Key Moments - 3 Insights

Why do we sometimes use pip inside a conda environment instead of conda?

Some packages are not available in conda repositories, so pip is used inside the active conda environment to install those packages, as shown in step 4 of the execution_table.

What happens if you try to install packages without activating the conda environment?

Packages will install in the base environment or system Python, not the intended environment. Step 2 shows activation is needed before installing packages in 'myenv'.

Why do we deactivate the environment after use?

Deactivating returns you to the base environment or system Python, preventing accidental package installs or runs in the wrong environment, as shown in step 5.

Visual Quiz - 3 Questions

Look at the execution_table, what is the active environment after step 3?

A None

B base

C myenv

D root

💡 Hint

Check the 'Active Environment' row in variable_tracker after step 3

At which step does the environment become inactive?

A Step 4

B Step 5

C Step 6

D Step 7

💡 Hint

Look at the 'Active Environment' variable in variable_tracker and the command in execution_table

If you skip step 2 and run 'conda install numpy', where will numpy be installed?

A In the base environment

B In the 'myenv' environment

C Nowhere, command fails

D In a new environment

💡 Hint

Refer to key_moments about activating environment before installing packages

Concept Snapshot

conda create -n envname python=3.12  # create env
conda activate envname                # activate env
conda install package                  # install with conda
pip install package                    # install with pip if missing
conda deactivate                      # leave env
conda remove -n envname --all         # delete env
Use conda envs to isolate projects and avoid conflicts.

Full Transcript

This lesson shows how to manage Python environments using conda and pip. First, you create a new environment with a specific Python version using 'conda create'. Then you activate it with 'conda activate' to work inside it. You install packages preferably with 'conda install', but if a package is missing, you use 'pip install' inside the active environment. After finishing work, you deactivate the environment with 'conda deactivate' to return to the base system. You can list environments with 'conda env list' and delete an environment with 'conda remove -n envname --all'. Activating the environment before installing packages ensures they go to the right place. Deactivating prevents accidental installs in the wrong environment. This process helps keep projects clean and dependencies separate.

Practice

1. What is the main purpose of using conda create -n myenv python=3.8?

easy

A. To delete the environment named 'myenv' and install Python 3.8 globally

B. To update Python to version 3.8 in the current environment

C. To create a new isolated environment named 'myenv' with Python 3.8 installed

D. To install all packages listed in a file named 'myenv' with Python 3.8

Solution

1. Step 1: Understand the conda create command

   This command is used to create a new environment in conda, isolating packages and Python versions.

2. Step 2: Analyze the flags and arguments

   The -n myenv specifies the environment name, and python=3.8 sets the Python version inside it.

3. Final Answer:

   To create a new isolated environment named 'myenv' with Python 3.8 installed -> Option C

4. Quick Check:

   conda create -n myenv python=3.8 = D [OK]

Hint: Remember: 'conda create -n' makes new isolated envs [OK]

Common Mistakes:

• Confusing 'create' with 'install' or 'update'
• Thinking it affects the global Python installation
• Misunderstanding the '-n' flag as package name

2. Which of the following commands correctly activates a conda environment named dataenv?

easy

A. activate conda dataenv

B. conda activate dataenv

C. conda start dataenv

D. source deactivate dataenv

Solution

1. Step 1: Recall the syntax to activate conda environments

   The correct command to activate an environment is conda activate <env_name>.

2. Step 2: Check each option

   conda activate dataenv matches the correct syntax. Options B, C, and D use incorrect command order or wrong commands.

3. Final Answer:

   conda activate dataenv -> Option B

4. Quick Check:

   Activate env = conda activate env_name [OK]

Hint: Use 'conda activate env_name' to switch environments [OK]

Common Mistakes:

• Using 'activate conda' instead of 'conda activate'
• Confusing 'source deactivate' with activation
• Trying 'conda start' which is invalid

3. Given the following commands run in order:

conda create -n testenv python=3.9 -y
conda activate testenv
pip install numpy
pip list | grep numpy

What will be the output of the last command?

medium

A. numpy with its installed version number

B. No output because pip list does not work inside conda

C. Error: 'pip' command not found

D. List of all packages except numpy

Solution

1. Step 1: Understand environment creation and activation

   The environment 'testenv' is created with Python 3.9 and then activated, so all commands run inside it.

2. Step 2: Installing numpy with pip inside the active environment

   Running pip install numpy installs numpy in 'testenv'. The pip list | grep numpy command will show numpy and its version.

3. Final Answer:

   numpy with its installed version number -> Option A

4. Quick Check:

   pip install inside active env = numpy listed [OK]

Hint: pip installs packages in active conda env, visible with pip list [OK]

Common Mistakes:

• Thinking pip installs globally ignoring conda env
• Assuming pip commands fail inside conda
• Expecting no output from pip list

4. You run conda activate myenv but get the error: CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'. What is the most likely fix?

medium

A. Reinstall Python globally on your system

B. Deactivate any active environment before activating 'myenv'

C. Use pip install conda to fix the error

D. Run conda init to configure your shell, then restart the terminal

Solution

1. Step 1: Understand the error cause

   This error means the shell does not know how to run conda activate because it lacks proper initialization.

2. Step 2: Apply the fix by initializing conda for the shell

   Running conda init sets up the shell scripts needed. Restarting the terminal applies changes.

3. Final Answer:

   Run conda init to configure your shell, then restart the terminal -> Option D

4. Quick Check:

   Shell config for conda = conda init + restart [OK]

Hint: Run 'conda init' once after install, then restart terminal [OK]

Common Mistakes:

• Trying to reinstall Python instead of fixing shell config
• Using pip to install conda which is incorrect
• Ignoring the need to restart terminal after init

5. You want to create a reproducible environment for a project using conda and pip. Which sequence of commands correctly creates an environment, installs packages from a requirements.txt file using pip, and exports the environment including pip packages?

hard

A. conda create -n projenv python=3.10 -y && conda activate projenv && pip install -r requirements.txt && conda env export > environment.yml

B. conda create -n projenv python=3.10 -y && pip install -r requirements.txt && conda activate projenv && conda env export > environment.yml

C. conda create -n projenv python=3.10 -y && conda activate projenv && pip install -r requirements.txt && conda env export --from-history > environment.yml

D. conda activate projenv && conda create -n projenv python=3.10 -y && pip install -r requirements.txt && conda env export > environment.yml

Solution

1. Step 1: Create and activate the environment before installing packages

   You must first create the environment, then activate it to install packages inside it.

2. Step 2: Install pip packages and export full environment

   After activation, install packages from requirements.txt using pip. Then export the full environment including pip packages with conda env export.

3. Final Answer:

   conda create -n projenv python=3.10 -y && conda activate projenv && pip install -r requirements.txt && conda env export > environment.yml -> Option A

4. Quick Check:

   Create, activate, pip install, export full env = C [OK]

Hint: Activate env before pip install; export full env to include pip packages [OK]

Common Mistakes:

• Installing pip packages before activating environment
• Using --from-history which excludes pip packages
• Activating environment after installing packages