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Input-Process-Output Model

Dave Braunschweig

The input–process–output (IPO) model  is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or another process. Many introductory programming and systems analysis texts introduce this as the most basic structure for describing a process. [1]

A computer program or any other sort of process using the input-process-output model receives inputs from a user or other source, does some computations on the inputs, and returns the results of the computations. The system divides the work into three categories: [2]

• A requirement from the environment (input)
• A computation based on the requirement (process)
• A provision for the environment (output)

For example, a program might be written to convert Fahrenheit temperatures into Celsius temperatures. Following the IPO model, the program must:

• Ask the user for the Fahrenheit temperature (input)
• Perform a calculation to convert the Fahrenheit temperature into the corresponding Celsius temperature (process)
• Display the Celsius temperature (output)
• Wikiversity: Computer Programming
• Flowgorithm – Flowchart Programming Language
• Wikipedia: IPO model ↵

Programming Fundamentals Copyright © 2018 by Dave Braunschweig is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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Input-Process-Output Model Analysis Essay

The input-process-output model of team effectiveness is used to understand how teams accomplish their tasks and maximize their performance. According to Conte and Landy (2019), inputs include “the organizational context, the team task, and team composition” and affect processes and outputs both directly and indirectly (p. 517). Moreover, inputs consist of individual-level factors, team-level factors, and environment-level factors (Jex & Britt, 2014, pp. 416-417). For example, the workers’ skills and attitudes, authority structure, or the task nature may influence team processes and, consequently, the outputs. Process variables, such as communication, decision making, coordination, cohesion, and norms, affect the innovation, as well as productivity and satisfaction of team members (Conte & Landy, 2019, p. 517). The model demonstrates that the constituents of a team are interrelated and interconnected, and the organizational outcomes will depend on the inputs and team processes.

In my career as an industrial and organizational (I/O) psychologist, the input-process-output model can be used to improve employee productivity and solve organizational problems. For example, if the workers’ productivity is low, I/O psychologist will study their working environment and relationships between team members. If the atmosphere is tense, the role of the I/O psychologist will be to understand why this tension exists and find the solution to this problem. The organizational context, such as the training system, managerial support, or technology, may also affect productivity. The role of the I/O psychologist is to study all these factors and help make them more stimulating. Finally, the input-process-output model can be used to examine the company’s morale and use this information to train and motivate the employees. I can use this model to help managers plan policies, carry out training sessions, and develop organizational success plans.

Conte, J. M. & Landy, F. J. (2019). Work in the 21st century: An introduction to industrial and organizational psychology (6th ed.). Wiley.

Jex, S. M. & Britt, T. W. (2014). Organizational psychology: A scientist-practitioner approach (3rd ed.). John Wiley & Sons.

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Learn how to use the input-process-output (IPO) model

You might have read that the input-process-output (IPO) model can be helpful in business and other organizations, but you’re not sure precisely what it means and how to apply it. That’s understandable — the phrase might sound like a complex computer system or an intimidating theory.

The reality is that the IPO model is very easy to understand. While it has roots in computer programming, it appears in many different industries and settings because it’s an effective way to plan, analyze, and improve how work gets done.

After reading this post, you’ll understand what the input-process-output model is all about and be ready to apply it to your business processes. You’ll learn:

• What the input-process-output (IPO) model is

How to use the IPO model

Benefits of the ipo model, examples of input-process-output in different industries, best practices when thinking about ipo, what is input-process-output (ipo).

Input-process-output (IPO) — also called an IPO model or IPO diagram — is a visual tool used to describe a workflow, the flow of information, or activities within a system. An IPO diagram helps you identify all the factors that influence a process and all the process’s outcomes, and it gives you a structured approach to analyzing and improving the system.

The IPO diagram consists of three columns listing inputs on the left, describing the process in the middle, and then tracking the outputs on the right. By diagramming a process in this way, almost any business — including computer science, systems analysis, and business analysis — can better identify the cause of a problem and improve a system’s performance.

As part of Six Sigma methodology , the IPO model fits within a more complex technique called DMAIC — which stands for Define, Measure, Analyze, Improve, and Control. The input-process-output model is an important part of the Define stage of DMAIC because it helps clarify and define a project’s goals, scope, and boundaries. This clarity helps to establish a solid foundation for the subsequent stages.

IPO assumes that if we control causal factors, we can also control their effects. Drawing the workflow using an IPO diagram can help visualize any system where it’s difficult to see how all the pieces connect. Although it’s primarily descriptive, teams can use IPO for analytical, quality control, or planning purposes. It’s useful in production, manufacturing, teamwork, and many other areas.

Creating your own initial IPO model is relatively easy. The IPO diagram gives you a simple framework for listing the inputs and outputs of any system. The details will depend on your industry and the specific process you want to explore.

Getting the details right — and knowing the difference between inputs, process steps, and outputs — can require careful thinking. Let’s examine each category:

• Input can include data, information, or resources that enter the system.
• Process can include activities, transformations, or operations performed on the inputs.
• Output can include results, products, or outcomes produced by the processes.

In manufacturing, a general, high-level IPO diagram might look something like this:

Although this diagram establishes a cause-and-effect pattern from left to right, you don’t necessarily need to start with inputs. If you’re planning a new process, try starting with the desired output and working back. The output should be thorough, specific, and measurable. Output is usually focused on four categories of standards that organizations are trying to achieve — quality, cost, time, and safety.

One drawback of the IPO method is it’s hard to account for random variables. To identify all possible inputs, consider people, environmental factors, methods, measurements, materials, and machines. As you define the process, break it down into clearly defined steps. Once the model is complete, you can analyze the process to determine relationships and identify areas for improvement.

There are many benefits to using the IPO model, such as:

• It’s easy to use . You don’t need to know how to use software or have specific expertise and training. Anyone can create an IPO diagram and spend time thinking about factors in a process.

• It’s versatile . It’s used in different industries and can be applied to almost any business process. You don’t have to follow a set of prescribed rules. You can apply this framework creatively, depending on your goals.

• It helps define key process input variables. Use the model to gain insights into how different factors contribute to the overall output and identify how to improve your input.

• It helps streamline operations . Identify bottlenecks, redundancies, or inefficiencies in operations. This understanding allows teams to reconfigure processes, allocate resources effectively, and streamline operations for better performance and productivity.

• It helps with problem-solving. Businesses can analyze the IPO diagram to identify potential causes and effects when an issue or challenge arises. They can pinpoint areas where disruptions may occur, allowing them to troubleshoot and rectify the problem more effectively.

• It can enable training and documentation. The model provides a visual representation of a business process, making it easier to convey information and train new employees. IPO can be a reference tool for documenting and preserving knowledge about processes within an organization.

• It helps clarify process steps and why. It can help eliminate what does not produce a good outcome.

• It’s a good communication tool. The model allows teams or stakeholders to visualize and discuss the flow of information within a system. It facilitates effective communication and collaboration by providing a common understanding of how inputs become outputs. This shared understanding enables teams to work together more efficiently and make informed decisions.

• It’s a good introduction to more complicated Six Sigma process mapping. The SIPOC (Supplier, Input, Process, Output, Customer) diagram adds the supplier to the start of the process chain and the customer to the end of it. This method can extend the IPO diagram beyond internal processes to map out a larger chain of cause and effect. IPO is also a helpful concept to master before exploring value stream mapping .

The input-process-output model emerged in the twentieth century as a fundamental model for describing complex computer systems. However, IPO quickly found applications outside of computer programming as a practical methodology in general systems theory and design. Many businesses found that by diagramming processes, they could improve quality and efficiency. IPO diagrams are now used in various industries. Some of the most common are:

• Manufacturing. The IPO model can show the most important factors influencing production outcomes. Companies can then identify bottlenecks, optimize resource allocation, improve quality, and enhance efficiency.
• Commerce. In online order processing, the input happens when a customer places an online order. The process happens when the order is received, the cost is calculated, and payment is processed. The output includes an order confirmation, an inventory check, shipping, and a confirmation email.
• Software development. A software development process could include gathering requirements, designing, coding, testing, and deployment. In software, it’s a good idea to start with output, break down the input variables, and determine the process of code needed to generate a fully functioning application as the output.

You might also encounter the use of IPO diagrams in the social sciences, food and hospitality, economics, finance planning, and other areas. The principles of the model are foundational enough that they can be applied almost anywhere.

While practices differ depending on the industry, if you are looking to improve the performance of a team or system, there are a few basic principles to follow when applying this model.

To avoid common pitfalls, plan ahead and check that your diagram is:

• Achievable. Define an attainable scope for your processes and make sure your processes are within that scope.
• Comprehensive. Consider all the possible outputs before capturing or changing your inputs. Likewise, check that you have anticipated all possible inputs, both those you add intentionally and others that might be harder to control.
• Inclusive. Make sure to involve the whole team to avoid bias on what should go into the inputs and outputs.

Get started with the input-process-output model

The IPO model is a simple but effective way to think carefully about cause and effect in small and large systems. Whether you want to improve teamwork, discover the cause of a problem, increase revenue, or design a more efficient system, this framework can help you achieve your business goals.

When you’re ready to get started, decide what business process you want to analyze and sketch it out with paper and pen using this method. Then explore Adobe Workfront , which can help you design a workflow using the input-process-output model and identify all the factors in your work processes that lead to success.

Adobe Workfront

Workfront is enterprise work management software that connects work to strategy and drives better collaboration to deliver measurable business outcomes. It integrates people, data, processes, and technology across an organization so you can manage the entire lifecycle of projects from start to finish. By optimizing and centralizing digital projects, cross-functional teams can connect, collaborate, and execute from anywhere to help them do their best work.

Take a product tour or watch the overview video to learn more.

https://business.adobe.com/blog/basics/dpu-dpmo-ppm-rty

https://business.adobe.com/blog/basics/what-is-workflow-automation

https://business.adobe.com/blog/basics/workplace-collaboration-tips

A Comprehensive Guide to Input-Process-Output Models

Updated: January 31, 2024 by Ken Feldman

Are you looking for a business improvement tool that is intuitive, simple to use, and visual in nature? Do you want to explore your internal business process and make sure you understand all of the inputs, outputs, and potential error states? 

If you are answering yes to these questions, then using input-process-output could be the perfect methodology for you. Let’s find out more. 

Overview: What is input-process-output (I-P-O)? 

Input-process-output (I-P-O) is a structured methodology for capturing and visualizing all of the inputs, outputs, and process steps that are required to transform inputs into outputs. It is often referred to, interchangeably, as an I-P-O model or an I-P-O diagram, both of which make reference to the intended visual nature of the method. 

A simple example is shown below from research in healthcare.

https://www.researchgate.net/figure/The-Input-Process-Output-diagram-of-the-proposed-system_fig2_323935725

As the methodology is incredibly versatile, it is used across many industries and sectors with (inevitably) some modifications and adaptations. These can include, for example, the addition of feedback loops from output to input, in doing so creating models analogous to closed-loop control theory.

Typically, we would use I-P-O in the “define” stage of a Six Sigma DMAIC project and follow a specific method for generating the model. The steps are:

• Decide upon the process steps that will be in scope of the I-P-O model. Try to ensure the the scope is manageable with, ideally, less than 10 process steps defined.
• List all of the possible outputs, including potential error states.
• List all of the inputs to your process steps, using clear descriptive language.
• Create a visual I-P-O model.
• Check that the inputs are transformed to the outputs via the process steps as shown in the model. 

Often, it can be helpful to have the team that’s generating the I-P-O model complete a Gemba walk. Visiting the actual place of work and viewing the process in action can tease out some of the less obvious inputs and outputs and contributes to continuous improvement of the existing process steps.

2 benefits and 1 drawback of I-P-O 

Used correctly, the I-P-O model offers a simple, practical, and efficient way to analyse and document a transformation process. Let’s explore some benefits and drawbacks of I-P-O.

1. It’s visual and easy to explain

It’s often said that the best business improvement tools are simple to use, intuitive, and visual, and I-P-O ticks all three of these boxes. A sheet of paper, marker pen, and an enthusiastic team willing to contribute will get you a long way. It’s also versatile, suitable for use with the executive management group as well as the wider business improvement team.

2. It’s easy to execute

There is a clear and simple methodology to generate I-P-O models, and this helps you recognise and document all of the possible inputs, outputs, and error states. As it’s visual, it’s easy to update and change as the team explores many potential inputs and outputs.

3. It’s internally focused without regard for external customers or suppliers   

Developing I-P-O models is usually all about internal business processes, and we often hear this called micro-process-mapping. This typically means we do not consider our external suppliers and customers in the analysis. However, don’t worry, we have complimentary models such as SIPOC and COPIS that help us make sense of the bigger (macro) picture.

Why is I-P-O important to understand? 

For such a relatively simple mapping tool, it provides a really powerful insight into our internal business processes. Let’s dig a little deeper.

It helps with defining your key process input variables

Once we’ve documented and visualised our inputs and outputs, we can turn our attention to determining and controlling which inputs provide a significant impact on the output variation — these are known as our key process input variables . 

It’s aligned with Six Sigma and Lean principles 

In a classic Six Sigma and Lean project approach, we strive to reduce process variation and remove defects and waste. With I-P-O, we identify inputs, outputs, and error states from our processes so we can begin to explore and understand the Y(output) = f ((X) input) equation.

It’s the perfect springboard to create full process maps 

Once we have created I-P-O models, we have the perfect starting place for generating complete process maps . This could be moving on to value stream mapping , spaghetti maps, or one of many other types of process maps that are available.

An industry example of I-P-O 

A government agency with multiple departments was embarking upon a business transformation project to improve customer service times and efficiency. As part of the transformation project, a Six Sigma Black Belt who was assigned to the activity was requested to explore and document existing processes and prepare the teams for process improvement.

The Black Belt chose to create I-P-O models due to the ease of use and versatility of the approach. Each of the business departments designated a team to work on the I-P-O models and, alongside the Black Belt, defined the process scope, ensuring this was of manageable size. 

With the teams in place and scope defined the process outputs were brainstormed and captured visually using whiteboards. The corresponding inputs were added, and the I-P-O models checked for completeness.

Generating the I-P-O models highlighted a number of potential output error states that were subsequently investigated as part of the business transformation project and contributed to improved customer service times. As the models were captured visually on whiteboards, they were easily updated during the project and used to inform staff of their contribution towards continuous improvement.

3 best practices when thinking about I-P-O 

Like many process-driven mapping activities, there are some key things for us to consider when creating I-P-O models. Let’s look at three of these.  

1. Remember: It’s a team sport; don’t go it alone 

Even relatively simple processes have multiple inputs and outputs. Often we find that different team members have detailed knowledge of specific process inputs and outputs, and we should make good use of this collective knowledge.

2. Make sure the scope is achievable

Don’t be overly ambitious with the scope and try to include too many process steps for your I-P-O model. If you find yourself listing 10 or more process steps, it’s probably time to stop and re-evaluate.

3. Consider all of the inputs and outputs 

Be diligent, get all the team involved, and make sure there is no bias — we don’t want to just list the things we think should be inputs and outputs in an ideal world. In addition, we should consider and document all of the possible output error states.

Frequently Asked Questions (FAQ) about I-P-O

Is i-p-o related to sipoc .

It can be a logical next step to create a SIPOC model from an I-P-O model. With SIPOC, we consider both suppliers (S) and customers (C) in the analysis, the so-called wider or bigger picture. With I-P-O, we concentrate more on the internal business process.

Where do I start with an I-P-O model? 

Start by defining the processes that are in scope, making sure the scope is manageable. Then consider and document all of the possible outputs from the process steps before moving on to capture the inputs.

Do I need a software program to generate I-P-O models? 

Definitely not. You can start with paper, pen, and a pack of sticky notes. However, there are a number of free templates available for download that can help you and your team as you start to populate the I-P-O model.

A final thought on I-P-O

Ease of use and versatility are just two of the major plus points of developing I-P-O models for your internal business processes. Add in their highly visual nature, and this means you can easily engage your team on a journey to continuous improvement.

About the Author

Ken Feldman

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The input–process–output (IPO) model is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or another process. Many introductory programming and systems analysis texts introduce this as the most basic structure for describing a process. [1]

A computer program or any other sort of process using the input-process-output model receives inputs from a user or other source, does some computations on the inputs, and returns the results of the computations. The system divides the work into three categories: [2]

• A requirement from the environment (input)
• A computation based on the requirement (process)
• A provision for the environment (output)

For example, a program might be written to convert Fahrenheit temperatures into Celsius temperatures. Following the IPO model, the program must:

• Ask the user for the Fahrenheit temperature (input)
• Perform a calculation to convert the Fahrenheit temperature into the corresponding Celsius temperature (process)
• Display the Celsius temperature (output)
• Wikiversity: Computer Programming
• Flowgorithm – Flowchart Programming Language
• Wikipedia: IPO model ↵

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IResearchNet

Input-Process-Output Model

Much of the work in organizations is accomplished through teams. It is therefore crucial to determine the factors that lead to effective as well as ineffective team processes and to better specify how, why, and when they contribute. Substantial research has been conducted on the variables that influence team effectiveness, yielding several models of team functioning. Although these models differ in a number of aspects, they share the commonality of being grounded in an input-process-output (IPO) framework. Inputs are the conditions that exist prior to group activity, whereas processes are the interactions among group members. Outputs are the results of group activity that are valued by the team or the organization.

The input-process-output model has historically been the dominant approach to understanding and explaining team performance and continues to exert a strong influence on group research today. The framework is based on classic systems theory, which states that the general structure of a system is as important in determining how effectively it will function as its individual components. Similarly, the IPO model has a causal structure, in that outputs are a function of various group processes, which are in turn influenced by numerous input variables. In its simplest form, the model is depicted as the following:

Input —> Process —> Output

Inputs reflect the resources that groups have at their disposal and are generally divided into three categories: individual-level factors, group-level factors, and environmental factors. Individual-level factors are what group members bring to the group, such as motivation, personality, abilities, experiences, and demographic attributes. Examples of group-level factors are work structure, team norms, and group size. Environmental factors capture the broader context in which groups operate, such as reward structure, stress level, task characteristics, and organizational culture.

Processes are the mediating mechanisms that convert inputs to outputs. A key aspect of the definition is that processes represent interactions that take place among team members. Many different taxonomies of teamwork behaviors have been proposed, but common examples include coordination, communication, conflict management, and motivation.

In comparison with inputs and outputs, group processes are often more difficult to measure, because a thorough understanding of what groups are doing and how they complete their work may require observing members while they actually perform a task. This may lead to a more accurate reflection of the true group processes, as opposed to relying on members to self-report their processes retrospectively. In addition, group processes evolve over time, which means that they cannot be adequately represented through a single observation. These difficult methodological issues have caused many studies to ignore processes and focus only on inputs and outputs. Empirical group research has therefore been criticized as treating processes as a “black box” (loosely specified and unmeasured), despite how prominently featured they are in the IPO model. Recently, however, a number of researchers have given renewed emphasis to the importance of capturing team member interactions, emphasizing the need to measure processes longitudinally and with more sophisticated measures.

Indicators of team effectiveness have generally been clustered into two general categories: group performance and member reactions. Group performance refers to the degree to which the group achieves the standard set by the users of its output. Examples include quality, quantity, timeliness, efficiency, and costs. In contrast, member reactions involve perceptions of satisfaction with group functioning, team viability, and personal development. For example, although the group may have been able to produce a high-quality product, mutual antagonism may be so high that members would prefer not to work with one another on future projects. In addition, some groups contribute to member well-being and growth, whereas others block individual development and hinder personal needs from being met.

Both categories of outcomes are clearly important, but performance outcomes are especially valued in the teams literature. This is because they can be measured more objectively (because they do not rely on team member self-reports) and make a strong case that inputs and processes affect the bottom line of group effectiveness.

Steiner’s Formula

Consistent with the IPO framework, Ivan Steiner derived the following formula to explain why teams starting off with a great deal of promise often end up being less than successful:

Actual productivity = potential productivity – process loss

Although potential productivity is the highest level of performance attainable, a group’s actual productivity often falls short of its potential because of the existence of process loss. Process loss refers to the suboptimal ways that groups operate, resulting in time and energy spent away from task performance. Examples of process losses include group conflict, communication breakdown, coordination difficulty, and social loafing (group members shirking responsibility and failing to exert adequate individual effort). Consistent with the assumptions of the IPO model, Steiner’s formula highlights the importance of group processes and reflects the notion that it is the processes and not the inputs (analogous to group potential) that create the group’s outputs. In other words, teams are a function of the interaction of team members and not simply the sum of individuals who perform tasks independently.

Limitations of the IPO Model

The major criticism that has been levied against the IPO model is the assumption that group functioning is static and follows a linear progression from inputs through outputs. To incorporate the reality of dynamic change, feedback loops were added to the original IPO model, emanating primarily from outputs and feeding back to inputs or processes. However, the single-cycle, linear IPO path has been emphasized in most of the empirical research. Nevertheless, in both theory and measurement, current team researchers are increasingly invoking the notion of cyclical causal feedback, as well as nonlinear or conditional relationships.

Although the IPO framework is the dominant way of thinking about group performance in the teams literature, relatively few empirical studies have been devoted to the validity of the model itself. In addition, research directly testing the input-process-output links has frequently been conducted in laboratory settings, an approach that restricts the number of relevant variables that would realistically occur in an organization. However, although the IPO model assumes that process fully mediates the association between inputs and outputs, some research has suggested that a purely mediated model may be too limited. Therefore, alternative models have suggested that inputs may directly affect both processes and outputs.

Without question, the IPO model reflects the dominant way of thinking about group performance in the groups literature. As such, it has played an important role in guiding research design and encouraging researchers to sample from the input, process, and output categories in variable selection. Recent research is increasingly moving beyond a strictly linear progression and incorporating the reality of dynamic change. In addition, alternatives to the traditional IPO model have been suggested in which processes are not purely mediated.

References:

• Hackman, J. R. (1987). The design of work teams. In J. Lorsch (Ed.), Handbook of organizational behavior (pp. 315-342). New York: Prentice Hall.
• Ilgen, D. R., Hollenbeck, J. R., Johnson, M., & Jundt, D. (2005). Teams in organizations: From input-process-output models to IMOI models. Annual Review of Psychology, 56, 517-543.
• Steiner, I. D. (1972). Group process and productivity. New York: Academic Press.
• Group Dynamics
• Industrial-Organizational Psychology

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How to Use Input Process Output Model For Business Success

March 18th, 2024

Teams are the backbone of modern organizations, driving innovation, problem-solving, and organizational success. 

However, building and sustaining high-performing teams is a complex endeavor that requires a deep understanding of the underlying dynamics and processes.

This is where the Input-Process-Output (IPO) model comes into play, providing a framework for analyzing and optimizing team effectiveness .

Key Highlights

• The Input Process Output Model (IPO model) is a fundamental framework for understanding and analyzing group dynamics and team effectiveness.
• It provides a systematic approach to examining the factors that influence group performance, including inputs, processes, and outputs.
• Input factors include team composition, resources, and environmental conditions that shape group interactions.
• Group processes refer to the interactions, communication patterns, and decision-making approaches within the team.
• Outputs are the tangible and intangible results of group efforts, such as productivity, quality, and satisfaction.
• Understanding the IPO model can help organizations optimize team performance, foster collaboration, and achieve desired outcomes.

More About Input Process Output Model

The Input-Process-Output (IPO) model provides a comprehensive framework for analyzing and optimizing team effectiveness. 

Developed by researchers in the field of organizational behavior, this model offers a systematic approach to examining the factors that influence group performance. 

From the initial inputs that shape team interactions to the processes that unfold within the group, ultimately leading to specific outputs or outcomes.

By breaking down the complexities of group dynamics into these three distinct components, the IPO model empowers organizations to identify areas for improvement , implement targeted interventions, and foster an environment conducive to high-performing teams. 

Whether you’re a team leader, a project manager, or a member of a collaborative group, understanding the IPO model can unlock valuable insights and strategies for maximizing team potential and achieving desired results.

What is the Input Process Output Model (IPO Model)?

The Input Process Output Model (IPO model) is a widely used framework for understanding and analyzing team effectiveness and group performance. 

Developed by organizational psychologists, the IPO model provides a structured approach to examining the various factors that influence how teams function and achieve their goals.

Definition and Overview of the Input Process Output Model

The IPO model proposes that team effectiveness is a result of the interplay between three key components: 

Inputs refer to the individual characteristics, group-level factors, and environmental conditions that exist before the team begins its work,

Processes encompass the interactions, behaviors, and dynamics that occur within the team as it undertakes its tasks. 

Outputs represent the results or outcomes achieved by the team, such as productivity, quality, and member satisfaction.

Importance of the IPO Model in Understanding Team Effectiveness

The IPO model is valuable for several reasons. First, it offers a comprehensive framework for analyzing team performance by considering a wide range of factors that can impact team functioning. 

By examining inputs, processes, and outputs, researchers and practitioners can identify strengths, weaknesses, and areas for improvement within teams.

Second, the IPO model highlights the interdependence between inputs, processes, and outputs. 

It recognizes that team effectiveness is not solely determined by any single factor but rather by the complex interplay among various elements. 

For example, a team with highly skilled members (input) may still struggle if they lack effective communication processes or face environmental constraints.

Furthermore, the IPO model emphasizes the importance of team processes, which are often overlooked or underestimated. 

It underscores that team interactions, such as communication, coordination, and conflict management , are crucial in shaping team outcomes.

By focusing on processes, the model provides insights into how teams can optimize their functioning and improve their performance.

Overall, the Input Process Output model offers a systematic and holistic approach to understanding team effectiveness, making it a valuable tool for researchers, managers, and team leaders.

Inputs in the Input Process Output Model

The input stage of the Input Process Output model refers to the various factors that influence a team’s functioning and performance. 

These inputs can be categorized into three levels: individual, group, and environmental.

Individual-level input factors encompass the unique characteristics, skills, and experiences that each team member brings to the table. 

These include:

• Skills: The knowledge, abilities, and competencies that individuals possess, such as technical expertise, problem-solving skills, communication skills, and creativity.
• Personalities: Individual traits, values, and behavioral tendencies that shape how team members interact and contribute to the group dynamic.
• Experiences: Prior experiences, backgrounds, and perspectives that shape an individual’s approach to teamwork and problem-solving.

Group-level input factors refer to the characteristics and dynamics of the team itself. 

• Group size: The number of members in a team can significantly impact group processes, communication, and coordination.
• Team norms: The shared expectations, values, and standards that govern a team’s behavior, decision-making processes, and interactions.
• Work structure: The way tasks are divided, roles are assigned, and responsibilities are distributed among team members.

Environmental input factors are external factors that can influence a team’s functioning and performance. 

• Organizational culture: The values, beliefs, and practices that shape the overall work environment and expectations within an organization .
• Reward systems: The incentives, recognition, and compensation structures in place that can motivate or demotivate team members.
• Physical environment: The physical workspace, tools, and resources available to the team, can impact productivity and collaboration.

By understanding and optimizing these input factors, teams can increase their chances of success by ensuring they have the right mix of skills, personalities, and resources to tackle the tasks at hand effectively. 

Effective team composition, clear norms, and a supportive organizational environment can lay the foundation for productive team processes and desirable outputs.

Processes in the Input Process Output Model

The processes in the IPO model refer to the interactions, mechanisms, and dynamics that occur within a team as they work towards their goals. 

These group processes act as the critical link between the inputs (individual characteristics, team composition, resources, etc.) and the eventual outputs or outcomes.

Team Interactions and Group Processes

At the heart of team processes are the interactions and exchanges that take place among team members. 

This includes critical processes like communication, coordination, conflict management, and decision-making. 

Effective communication ensures that information, ideas, and feedback flow smoothly within the team. 

Coordination involves orchestrating the sequence and integration of team activities. Conflict management refers to strategies for resolving disagreements and tensions productively. 

Group decision-making encompasses the methods and procedures teams use to analyze problems, evaluate alternatives, and reach consensus.

Other key group processes include:

• Team motivation and effort norms
• Emotional support and interpersonal cohesion 
• Performance monitoring and feedback loops
• Problem-solving approaches and creativity
• Task assignment and role negotiation

The quality and patterns of these group processes can significantly impact team effectiveness and productivity.

Challenges in Measuring Group Processes

While the importance of group processes is widely acknowledged, measuring and quantifying them presents challenges. 

Many group processes are inherently dynamic, fluid, and context-dependent, making them difficult to capture with static measures. 

Processes like communication and conflict resolution often involve subtle cues, tones, and unspoken behaviors that are hard to assess objectively. 

Researchers have employed techniques like direct observation, video coding, self-report surveys , and social network analysis to study group processes. 

However, these methods have their limitations and can be time-consuming, subjective, or disruptive to the team’s natural functioning.

Dynamic Nature of Team Processes Over Time  

Team processes are not static; they evolve and change as the team progresses through different phases of development and task cycles. 

The patterns of interaction, the intensity of certain processes, and the team’s foci can shift substantially from the initial formation stage to periods of high task execution and ultimately to project completion.

For instance, in the early stages, teams may emphasize processes like getting to know each other, establishing norms, and clarifying roles. 

During midpoint task work, the emphasis may shift to coordination, motivation, and monitoring. As deadlines approach, decision-making, and conflict-resolution processes may become more pronounced.

The dynamic nature of team processes poses challenges for managers and researchers alike. 

It requires ongoing assessment, adjustment of interventions, and a recognition that different processes may need to be prioritized at various points in the team’s journey. 

Capturing these temporal dynamics is crucial for a comprehensive understanding of how inputs get transformed into outputs through team processes.

Outputs in the Input Process Output Model

The outputs in the IPO model refer to the results or outcomes that emerge from the team processes. 

These outputs can be evaluated at the team and individual member levels.

Team Performance Outcomes

One of the primary outputs of interest is the team’s performance, which can be measured in terms of productivity, quality, and efficiency. 

Productivity refers to the quantity of work accomplished or outputs generated by the team within a given timeframe. 

Quality, on the other hand, focuses on the excellence and accuracy of the team’s deliverables, ensuring they meet or exceed established standards. 

Efficiency considers the ratio of inputs (resources, time, effort) to outputs, aiming to maximize productivity while minimizing waste .

Individual Member Reactions

In addition to team-level outcomes, the IPO model also considers individual member reactions as important outputs. 

These include job satisfaction, which reflects how content and fulfilled team members feel about their roles and experiences within the team. 

Team viability refers to the likelihood that the team will continue to work together effectively in the future, based on factors such as cohesion, commitment, and perceived success. 

Personal growth represents the extent to which individual team members have developed new skills, knowledge, or abilities through their participation in the team.

Steiner’s Formula: Actual Productivity vs. Potential Productivity

One way to evaluate team performance is to compare the team’s actual productivity to its potential productivity, as described by Steiner’s formula. 

Steiner’s formula suggests that a team’s actual productivity is equal to its potential productivity minus the losses due to faulty processes.

These process losses can stem from various factors, such as poor coordination, communication breakdowns, motivation issues, or interpersonal conflicts within the team.

By understanding the gap between actual and potential productivity, teams can identify areas for improvement in their processes and inputs to minimize process losses and enhance overall team effectiveness.

The IPO model provides a framework for analyzing and addressing these discrepancies, ultimately leading to better team performance and individual member outcomes.

Limitations and Extensions of the IPO Model

While the Input Process Output Model provides a useful framework for understanding group dynamics and team effectiveness, it is important to recognize its limitations. 

One key assumption of the IPO model is its linearity and static nature. The model presents a simplified, linear sequence where inputs lead to processes, which then lead to outputs. 

However, in reality, group interactions are often more complex, dynamic, and cyclical.

The IPO model does not fully account for the feedback loops and reciprocal relationships that exist between inputs, processes, and outputs. 

For example, the outputs achieved by a team can influence the motivation levels (an input factor) and group processes in subsequent tasks or projects. 

Additionally, the model assumes a relatively static set of inputs and processes, whereas, in practice, these elements can change and evolve as the team progresses through different stages of development.

To address these limitations, researchers have proposed extensions and alternative models that incorporate feedback loops and dynamic change. 

One such extension is the Input-Mediator-Output-Input (IMOI) model , which recognizes the cyclical nature of team interactions by including an additional feedback loop from outputs back to inputs. 

This model acknowledges that the outcomes achieved by a team can shape future inputs, such as team composition, resources, or environmental factors.

Another alternative is the direct input-output links model, which suggests that certain input factors can directly influence outputs without necessarily going through group processes. 

For example, the expertise or experience levels of team members (input factors) may have a direct impact on the quality of the team’s output, regardless of the specific group processes involved.

These extensions and alternative models highlight the importance of considering the dynamic and non-linear nature of team interactions. 

While the IPO model provides a useful starting point, it is essential to recognize its simplifications and limitations. 

By incorporating feedback loops, dynamic change , and direct input-output links, researchers and practitioners can develop a more comprehensive understanding of group dynamics and team effectiveness.

Applications and Best Practices

The input-process-output (IPO) model provides a valuable framework for understanding and optimizing team effectiveness. 

By breaking down team dynamics into distinct components, the model offers practical applications for team building and performance improvement efforts.

Using the IPO Model for Team Building and Performance Improvement

One of the primary applications of the IPO model is in the realm of team building and development initiatives. 

The model can serve as a diagnostic tool to identify potential areas of improvement within a team. 

For instance, if a team is consistently underperforming (output), the IPO model can help pinpoint whether the root cause lies in the input factors (e.g., lack of necessary skills or resources) or the team processes (e.g., poor communication or coordination).

Once the areas for improvement have been identified, targeted interventions can be designed and implemented. 

These interventions may include training programs to enhance individual skills (input optimization), facilitated workshops to improve group processes ( process optimization ), or structural changes to the team’s composition or environment (input reconfiguration).

Strategies for Optimizing Inputs, Processes, and Outputs

The IPO model provides a structured approach to optimizing team effectiveness by addressing each component systematically:

Input Optimization

• Conduct thorough job analyses and person-job fit assessments during team member selection.
• Provide training and development opportunities to enhance individual skills and competencies.
• Ensure that team members have access to necessary resources and information.
• Align team composition with task requirements (e.g., diversity, size, expertise).

Process Optimization

• Implement team-building activities to foster cohesion, trust, and shared norms.
• Establish clear communication channels and protocols for effective information sharing.
• Encourage constructive conflict resolution and decision-making processes.
• Promote accountability and feedback mechanisms for continuous improvement .

Output Monitoring and Adjustment

• Establish clear performance metrics and regularly measure team outputs.
• Identify and address process losses that hinder team productivity.
• Celebrate and reinforce positive team behaviors and outcomes.
• Adapt and reconfigure inputs or processes as needed based on feedback and changing circumstances.

Case Studies

The IPO model has been successfully applied across various organizational settings. 

Software Development Teams

Agile methodologies like Scrum heavily rely on the IPO model principles. 

Input factors like cross-functional team composition and co-location are emphasized, while iterative processes like daily stand-ups and retrospectives facilitate continuous improvement.

Healthcare Teams

Interprofessional healthcare teams often face challenges in coordinating their diverse expertise and backgrounds (inputs). 

Interventions focused on improving team processes, such as structured communication protocols (e.g., SBAR) and shared decision-making, have been shown to enhance patient outcomes (outputs).

Virtual Teams

With the rise of remote work and global teams, optimizing virtual team inputs (e.g., communication tools, cultural awareness) and processes (e.g., establishing team norms, and managing time zone differences) becomes crucial for achieving desired outputs.

Cross-functional Project Teams

Organizations frequently assemble cross-functional teams to tackle complex projects. 

Applying the Input Process Output model principles can help manage the diverse inputs (functional expertise, goals) and optimize processes like conflict resolution and decision-making to deliver successful project outcomes.

By leveraging the Input Process Output model’s principles and strategies, organizations can proactively address team dynamics, foster collaboration, and drive sustained high performance.

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Software Design and Development - Input Process Output

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Input Process Output!

• Introduction

A comprehensive introduction to Input Process Output tables. Learn how to effectively model the important processing going on in your system.

One of the first things we need to do in software development is understand the problem. We can't begin to plan the most effective solution until we properly understand what it is we are trying to solve. Input Process Output tables, or IPO tables for short, are an effective way to model the important processing going on in your system.

Let's consider the three parts of the table:

• Output - A piece of information which we want.
• Input - Data which is required in order to create the required outputs.
• Process - The steps involved in creating the outputs from the inputs.

An Input Process Output table then is a table listing what inputs are required to create a set of desired outputs and the processing required to make that transformation occur. Here is a simple example for calculating an average of a set of numbers:

Notice there are many things missing here. We say nothing about how the output is displayed or what is done with it. We don't mention where the inputs came from. Actions are largely ignored. With an IPO table we are interested in data and little else. This helps us to be very specific and not get distracted by other details.

On the rest of this page I will explain my take on how Input Process Output tables should be used in software design and development. There is no official way they are to be used or implemented however so you will come across other ways of implementing them and you are more than welcome to deviate from what I have explained here if you feel it better helps you achieve your goals.

There are several examples of IPO tables on this page. Some of them are examples of what not to do. Those are listed with a red heading. Correctly implemented tables are listed with a blue heading.

Laying out your IPO tables

There are several different methods for displaying IPO tables. Some people prefer to list the items vertically instead of horizontally for instance. However you choose to display them is fine, the underlying principle of what they convey will still be the same. The layout described here is one which I find particularly easy to read.

This layout makes it easy to follow the flow of data from Input, through the processing to the final Output. Items are listed in chronological order. Inputs line up with the top of the processing. The output lines up with the final bit of processing which leads to it's creation. There should also be a descriptive heading on the table to label what the IPO table actually represents.

The language used for describing the processing is also important. It should be non technical. IPO tables are intended to help us define and understand the problem. They will be created by the developer and shown to the client or key actors to verify that the developers understanding of the problem is accurate and whole. Often these people do not have a software development background. It is essential that the processing is written in a way that they can fully understand what is going on. Avoid pseudocode in describing your processing.

This would make perfect sense to someone with programming experience but could be quite confusing to others. It is ok to have decisions and repetition in your processing but they should be described in general terms rather than algorithmically. Here is a better way to do it:

• Two types of processes

When thinking about software development we can divide processes into two types. Those which are part of the problem, and those which are part of the implementation of the solution. Let's look at an example to illustrate what is meant by this.

If we are going to make a simple calculator then the processes of addition, subtraction, multiplication and division would be processes which are part of the problem. They are defined before we even start considering the solution.

How we decide to manage a history of calculations performed, eg. as an array of records, is an implementation process however. It is something we think about when planning how we are going to build the calculator.

What do we model with an IPO table?

Any process may be explored through an IPO table but if we say that it's purpose is to help us better understand and define the problem then this gives us guidance as to which processes would be better to model. Ideally we want to model processes representing the problem. Processes which are part of implementing the solution are generally better explained using algorithms.

If we are modelling a problem for which a computerised solution is to be created then major processes and things involving calculations should be modelled. Other aspects of the problem may be modelled considering how important they are to understanding the underlying principle of the problem.

If we are modelling an existing system from which to create a new or improved system then we probably want to model more processes within the system (virtually all processing is part of the problem) but still take into account the comments in the previous paragraph.

Deciding if a process is part of the problem or solution can sometimes be tricky, especially for certain types of things such as games. An easy way to help you decide is to think about what would happen if you were to implement a paper based solution instead of a computerised one. If the process would still be done with pen and paper it is probably something valuable to express in an IPO table.

As an example of this, lets consider a game of Tic Tac Toe. Even if playing the game on paper the process of determining if someone has won the game is still required. This is something we should therefore model.

Other processes however such as how the players will input where their pieces are to go or how we go about rendering the board on the screen are processes which we wouldn't consider when playing with pen and paper so they are not part of the problem.

Don't worry that you are not modelling all of the system. You will probably only model a small and fragmented aspect of the system through the IPO diagrams. This is ok. Each diagram, table or chart, IPO's included, is only intended to model a certain aspect of the problem or solution.

• Information not actions

A common mistake when creating IPO tables is to specify actions as either your Inputs or Outputs. For example an input may be listed as player wins game . This is incorrect as it is not an input but an event that occurs which triggers the processing. In an IPO we are not concerned with what triggers the processing (that will be looked at in other diagrams). We are only concerned with what information is to be created and what data is required in order to do this. Maybe the processing involves calculating a final score once the player has finished the game. The inputs then will be whatever details are required in order to calculate this high score. This may be for instance, player health, time taken, bonuses collected etc. Instead of:

Which is incorrect. The input is an action. The output does have data within it but it is more about how the data is displayed. We only want the data listed in an IPO table. How it is to be displayed is something which should be modelled using prototypes or screen designs. The processing also involves actions which will be performed but are not actually part of producing the output. A more correct IPO would be:

Your inputs and outputs should be categorised as either a data type (integer, float, string, boolean) or data structure (arrays or records) or a file with data in it.

• The big picture

So how do Input Process Output tables fit into the big picture of software design and development?

IPO tables are a valuable tool to help you define and understand the problem. This may be one for which a computerised solution is to be created. Alternatively it may be an existing system which is to be replaced or improved. IPO tables will help you identify and understand the major processes that exist or need to exist. IPO tables look at these processes in isolation. These processes can then be linked together, by looking for matches between the inputs of a process and the corresponding outputs of other processes which will be represented by way of Data Flow Diagrams. The details of these tables will also help when creating algorithms for the final solution.

Pick a sport and create a set of IPO tables that would be required if you were going to develop a piece of software to manage scoring for a game.

• Section Breakdown
• Layout out IPO tables
• What do we model?
• Next Section

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Input, Process, Output Model

Introduction, introduction to input, process, output model.

The Input, Process, Output (IPO) model is a conceptual framework used to understand and describe the flow of data within a system or process. It breaks down the system into three key components:

Here optional storage component has been added for clarity.

Input Stage

• user keystrokes
• mouse clicks
• file / database contents
• input from other programs
• network packets.

Process Stage

• perform calculations
• make decisions
• store data in memory
• call functions or subroutines,
• execute various operations to transform the input into a desired output.

Output Phase

Output Stage

Outputs are the results, outcomes, or responses generated by the system after processing the input data. They represent the transformed or processed information that is produced by the system. Outputs can be in soft copy or hard copy form and can take various forms, such as:

• notifications
• actions triggered by the system.

Example – Ecommerce Website

Consider an e-commerce website that follows the IPO model.

Input: A customer visits the website and provides their order details, including the items to purchase, quantity, and shipping address.

Process: The website’s backend system processes the order by validating the inputs, checking product availability, calculating the total cost, applying any discounts or promotions, and updating inventory records.

Output: The system generates an order confirmation page for the customer, displaying the total cost, estimated delivery date, and order reference number. Simultaneously, the system generates an order notification for the seller and updates the inventory database to reflect the reduced stock.

In this example, the inputs are the customer’s order details, the process involves validating and calculating the order, and the outputs include the confirmation page for the customer and the order notification for the seller.

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How To Make Conceptual Framework (With Examples and Templates)

We all know that a research paper has plenty of concepts involved. However, a great deal of concepts makes your study confusing.

A conceptual framework ensures that the concepts of your study are organized and presented comprehensively. Let this article guide you on how to make the conceptual framework of your study.

Related: How to Write a Concept Paper for Academic Research

Table of Contents

At a glance: free conceptual framework templates.

Too busy to create a conceptual framework from scratch? No problem. We’ve created templates for each conceptual framework so you can start on the right foot. All you need to do is enter the details of the variables. Feel free to modify the design according to your needs. Please read the main article below to learn more about the conceptual framework.

Conceptual Framework Template #1: Independent-Dependent Variable Model

Conceptual framework template #2: input-process-output (ipo) model, conceptual framework template #3: concept map, what is a conceptual framework.

A conceptual framework shows the relationship between the variables of your study.  It includes a visual diagram or a model that summarizes the concepts of your study and a narrative explanation of the model presented.

Why Should Research Be Given a Conceptual Framework?

Imagine your study as a long journey with the research result as the destination. You don’t want to get lost in your journey because of the complicated concepts. This is why you need to have a guide. The conceptual framework keeps you on track by presenting and simplifying the relationship between the variables. This is usually done through the use of illustrations that are supported by a written interpretation.

Also, people who will read your research must have a clear guide to the variables in your study and where the research is heading. By looking at the conceptual framework, the readers can get the gist of the research concepts without reading the entire study. 

Related: How to Write Significance of the Study (with Examples)

What Is the Difference Between Conceptual Framework and Theoretical Framework?

Both of them show concepts and ideas of your study. The theoretical framework presents the theories, rules, and principles that serve as the basis of the research. Thus, the theoretical framework presents broad concepts related to your study. On the other hand, the conceptual framework shows a specific approach derived from the theoretical framework. It provides particular variables and shows how these variables are related.

Let’s say your research is about the Effects of Social Media on the Political Literacy of College Students. You may include some theories related to political literacy, such as this paper, in your theoretical framework. Based on this paper, political participation and awareness determine political literacy.

For the conceptual framework, you may state that the specific form of political participation and awareness you will use for the study is the engagement of college students on political issues on social media. Then, through a diagram and narrative explanation, you can show that using social media affects the political literacy of college students.

What Are the Different Types of Conceptual Frameworks?

The conceptual framework has different types based on how the research concepts are organized 1 .

1. Taxonomy

In this type of conceptual framework, the phenomena of your study are grouped into categories without presenting the relationship among them. The point of this conceptual framework is to distinguish the categories from one another.

2. Visual Presentation

In this conceptual framework, the relationship between the phenomena and variables of your study is presented. Using this conceptual framework implies that your research provides empirical evidence to prove the relationship between variables. This is the type of conceptual framework that is usually used in research studies.

3. Mathematical Description

In this conceptual framework, the relationship between phenomena and variables of your study is described using mathematical formulas. Also, the extent of the relationship between these variables is presented with specific quantities.

How To Make Conceptual Framework: 4 Steps

1. identify the important variables of your study.

There are two essential variables that you must identify in your study: the independent and the dependent variables.

An independent variable is a variable that you can manipulate. It can affect the dependent variable. Meanwhile, the dependent variable is the resulting variable that you are measuring.

You may refer to your research question to determine your research’s independent and dependent variables.

Suppose your research question is: “Is There a Significant Relationship Between the Quantity of Organic Fertilizer Used and the Plant’s Growth Rate?” The independent variable of this study is the quantity of organic fertilizer used, while the dependent variable is the plant’s growth rate.

2. Think About How the Variables Are Related

Usually, the variables of a study have a direct relationship. If a change in one of your variables leads to a corresponding change in another, they might have this kind of relationship.

However, note that having a direct relationship between variables does not mean they already have a cause-and-effect relationship 2 . It takes statistical analysis to prove causation between variables.

Using our example earlier, the quantity of organic fertilizer may directly relate to the plant’s growth rate. However, we are not sure that the quantity of organic fertilizer is the sole reason for the plant’s growth rate changes.

3. Analyze and Determine Other Influencing Variables

Consider analyzing if other variables can affect the relationship between your independent and dependent variables 3 .

4. Create a Visual Diagram or a Model

Now that you’ve identified the variables and their relationship, you may create a visual diagram summarizing them.

Usually, shapes such as rectangles, circles, and arrows are used for the model. You may create a visual diagram or model for your conceptual framework in different ways. The three most common models are the independent-dependent variable model, the input-process-output (IPO) model, and concept maps.

a. Using the Independent-Dependent Variable Model

You may create this model by writing the independent and dependent variables inside rectangles. Then, insert a line segment between them, connecting the rectangles. This line segment indicates the direct relationship between these variables. 

Below is a visual diagram based on our example about the relationship between organic fertilizer and a plant’s growth rate. 

b. Using the Input-Process-Output (IPO) Model

If you want to emphasize your research process, the input-process-output model is the appropriate visual diagram for your conceptual framework.

To create your visual diagram using the IPO model, follow these steps:

• Determine the inputs of your study . Inputs are the variables you will use to arrive at your research result. Usually, your independent variables are also the inputs of your research. Let’s say your research is about the Level of Satisfaction of College Students Using Google Classroom as an Online Learning Platform. You may include in your inputs the profile of your respondents and the curriculum used in the online learning platform.
• Outline your research process. Using our example above, the research process should be like this: Data collection of student profiles → Administering questionnaires → Tabulation of students’ responses → Statistical data analysis.
• State the research output . Indicate what you are expecting after you conduct the research. In our example above, the research output is the assessed level of satisfaction of college students with the use of Google Classroom as an online learning platform.
• Create the model using the research’s determined input, process, and output.

Presented below is the IPO model for our example above.

c. Using Concept Maps

If you think the two models presented previously are insufficient to summarize your study’s concepts, you may use a concept map for your visual diagram.

A concept map is a helpful visual diagram if multiple variables affect one another. Let’s say your research is about Coping with the Remote Learning System: Anxiety Levels of College Students. Presented below is the concept map for the research’s conceptual framework:

5. Explain Your Conceptual Framework in Narrative Form

Provide a brief explanation of your conceptual framework. State the essential variables, their relationship, and the research outcome.

Using the same example about the relationship between organic fertilizer and the growth rate of the plant, we can come up with the following explanation to accompany the conceptual framework:

Figure 1 shows the Conceptual Framework of the study. The quantity of the organic fertilizer used is the independent variable, while the plant’s growth is the research’s dependent variable. These two variables are directly related based on the research’s empirical evidence.

Conceptual Framework in Quantitative Research

You can create your conceptual framework by following the steps discussed in the previous section. Note, however, that quantitative research has statistical analysis. Thus, you may use arrows to indicate a cause-and-effect relationship in your model. An arrow implies that your independent variable caused the changes in your dependent variable.

Usually, for quantitative research, the Input-Process-Output model is used as a visual diagram. Here is an example of a conceptual framework in quantitative research:

Research Topic : Level of Effectiveness of Corn (Zea mays) Silk Ethanol Extract as an Antioxidant

Conceptual Framework in Qualitative Research

Again, you can follow the same step-by-step guide discussed previously to create a conceptual framework for qualitative research. However, note that you should avoid using one-way arrows as they may indicate causation . Qualitative research cannot prove causation since it uses only descriptive and narrative analysis to relate variables.

Here is an example of a conceptual framework in qualitative research:

Research Topic : Lived Experiences of Medical Health Workers During Community Quarantine

Conceptual Framework Examples

Presented below are some examples of conceptual frameworks.

Research Topic : Hypoglycemic Ability of Gabi (Colocasia esculenta) Leaf Extract in the Blood Glucose Level of Swiss Mice (Mus musculus)

Figure 1 presents the Conceptual Framework of the study. The quantity of gabi leaf extract is the independent variable, while the Swiss mice’s blood glucose level is the study’s dependent variable. This study establishes a direct relationship between these variables through empirical evidence and statistical analysis . 

Research Topic : Level of Effectiveness of Using Social Media in the Political Literacy of College Students

Figure 1 shows the Conceptual Framework of the study. The input is the profile of the college students according to sex, year level, and the social media platform being used. The research process includes administering the questionnaires, tabulating students’ responses, and statistical data analysis and interpretation. The output is the effectiveness of using social media in the political literacy of college students.

Research Topic: Factors Affecting the Satisfaction Level of Community Inhabitants

Figure 1 presents a visual illustration of the factors that affect the satisfaction level of community inhabitants. As presented, environmental, societal, and economic factors influence the satisfaction level of community inhabitants. Each factor has its indicators which are considered in this study.

Tips and Warnings

• Please keep it simple. Avoid using fancy illustrations or designs when creating your conceptual framework. 
• Allot a lot of space for feedback. This is to show that your research variables or methodology might be revised based on the input from the research panel. Below is an example of a conceptual framework with a spot allotted for feedback.

Frequently Asked Questions

1. how can i create a conceptual framework in microsoft word.

First, click the Insert tab and select Shapes . You’ll see a wide range of shapes to choose from. Usually, rectangles, circles, and arrows are the shapes used for the conceptual framework. 

Next, draw your selected shape in the document.

Insert the name of the variable inside the shape. You can do this by pointing your cursor to the shape, right-clicking your mouse, selecting Add Text , and typing in the text.

Repeat the same process for the remaining variables of your study. If you need arrows to connect the different variables, you can insert one by going to the Insert tab, then Shape, and finally, Lines or Block Arrows, depending on your preferred arrow style.

2. How to explain my conceptual framework in defense?

If you have used the Independent-Dependent Variable Model in creating your conceptual framework, start by telling your research’s variables. Afterward, explain the relationship between these variables. Example: “Using statistical/descriptive analysis of the data we have collected, we are going to show how the <state your independent variable> exhibits a significant relationship to <state your dependent variable>.”

On the other hand, if you have used an Input-Process-Output Model, start by explaining the inputs of your research. Then, tell them about your research process. You may refer to the Research Methodology in Chapter 3 to accurately present your research process. Lastly, explain what your research outcome is.

Meanwhile, if you have used a concept map, ensure you understand the idea behind the illustration. Discuss how the concepts are related and highlight the research outcome.

3. In what stage of research is the conceptual framework written?

The research study’s conceptual framework is in Chapter 2, following the Review of Related Literature.

4. What is the difference between a Conceptual Framework and Literature Review?

The Conceptual Framework is a summary of the concepts of your study where the relationship of the variables is presented. On the other hand, Literature Review is a collection of published studies and literature related to your study. 

Suppose your research concerns the Hypoglycemic Ability of Gabi (Colocasia esculenta) Leaf Extract on Swiss Mice (Mus musculus). In your conceptual framework, you will create a visual diagram and a narrative explanation presenting the quantity of gabi leaf extract and the mice’s blood glucose level as your research variables. On the other hand, for the literature review, you may include this study and explain how this is related to your research topic.

5. When do I use a two-way arrow for my conceptual framework?

You will use a two-way arrow in your conceptual framework if the variables of your study are interdependent. If variable A affects variable B and variable B also affects variable A, you may use a two-way arrow to show that A and B affect each other.

Suppose your research concerns the Relationship Between Students’ Satisfaction Levels and Online Learning Platforms. Since students’ satisfaction level determines the online learning platform the school uses and vice versa, these variables have a direct relationship. Thus, you may use two-way arrows to indicate that the variables directly affect each other.

• Conceptual Framework – Meaning, Importance and How to Write it. (2020). Retrieved 27 April 2021, from https://afribary.com/knowledge/conceptual-framework/
• Correlation vs Causation. Retrieved 27 April 2021, from https://www.jmp.com/en_ph/statistics-knowledge-portal/what-is-correlation/correlation-vs-causation.html
• Swaen, B., & George, T. (2022, August 22). What is a conceptual framework? Tips & Examples. Retrieved December 5, 2022, from https://www.scribbr.com/methodology/conceptual-framework/

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

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• Python »
• 3.14.0a0 Documentation »
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• subprocess — Subprocess management
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subprocess — Subprocess management ¶

Source code: Lib/subprocess.py

The subprocess module allows you to spawn new processes, connect to their input/output/error pipes, and obtain their return codes. This module intends to replace several older modules and functions:

Information about how the subprocess module can be used to replace these modules and functions can be found in the following sections.

PEP 324 – PEP proposing the subprocess module

Availability : not WASI, not iOS.

This module does not work or is not available on WebAssembly platforms, or on iOS. See WebAssembly platforms for more information on WASM availability; see iOS for more information on iOS availability.

Using the subprocess Module ¶

The recommended approach to invoking subprocesses is to use the run() function for all use cases it can handle. For more advanced use cases, the underlying Popen interface can be used directly.

Run the command described by args . Wait for command to complete, then return a CompletedProcess instance.

The arguments shown above are merely the most common ones, described below in Frequently Used Arguments (hence the use of keyword-only notation in the abbreviated signature). The full function signature is largely the same as that of the Popen constructor - most of the arguments to this function are passed through to that interface. ( timeout , input , check , and capture_output are not.)

If capture_output is true, stdout and stderr will be captured. When used, the internal Popen object is automatically created with stdout and stdin both set to PIPE . The stdout and stderr arguments may not be supplied at the same time as capture_output . If you wish to capture and combine both streams into one, set stdout to PIPE and stderr to STDOUT , instead of using capture_output .

A timeout may be specified in seconds, it is internally passed on to Popen.communicate() . If the timeout expires, the child process will be killed and waited for. The TimeoutExpired exception will be re-raised after the child process has terminated. The initial process creation itself cannot be interrupted on many platform APIs so you are not guaranteed to see a timeout exception until at least after however long process creation takes.

The input argument is passed to Popen.communicate() and thus to the subprocess’s stdin. If used it must be a byte sequence, or a string if encoding or errors is specified or text is true. When used, the internal Popen object is automatically created with stdin set to PIPE , and the stdin argument may not be used as well.

If check is true, and the process exits with a non-zero exit code, a CalledProcessError exception will be raised. Attributes of that exception hold the arguments, the exit code, and stdout and stderr if they were captured.

If encoding or errors are specified, or text is true, file objects for stdin, stdout and stderr are opened in text mode using the specified encoding and errors or the io.TextIOWrapper default. The universal_newlines argument is equivalent to text and is provided for backwards compatibility. By default, file objects are opened in binary mode.

If env is not None , it must be a mapping that defines the environment variables for the new process; these are used instead of the default behavior of inheriting the current process’ environment. It is passed directly to Popen . This mapping can be str to str on any platform or bytes to bytes on POSIX platforms much like os.environ or os.environb .

Added in version 3.5.

Changed in version 3.6: Added encoding and errors parameters

Changed in version 3.7: Added the text parameter, as a more understandable alias of universal_newlines . Added the capture_output parameter.

Changed in version 3.12: Changed Windows shell search order for shell=True . The current directory and %PATH% are replaced with %COMSPEC% and %SystemRoot%\System32\cmd.exe . As a result, dropping a malicious program named cmd.exe into a current directory no longer works.

The return value from run() , representing a process that has finished.

The arguments used to launch the process. This may be a list or a string.

Exit status of the child process. Typically, an exit status of 0 indicates that it ran successfully.

A negative value -N indicates that the child was terminated by signal N (POSIX only).

Captured stdout from the child process. A bytes sequence, or a string if run() was called with an encoding, errors, or text=True. None if stdout was not captured.

If you ran the process with stderr=subprocess.STDOUT , stdout and stderr will be combined in this attribute, and stderr will be None .

Captured stderr from the child process. A bytes sequence, or a string if run() was called with an encoding, errors, or text=True. None if stderr was not captured.

If returncode is non-zero, raise a CalledProcessError .

Special value that can be used as the stdin , stdout or stderr argument to Popen and indicates that the special file os.devnull will be used.

Added in version 3.3.

Special value that can be used as the stdin , stdout or stderr argument to Popen and indicates that a pipe to the standard stream should be opened. Most useful with Popen.communicate() .

Special value that can be used as the stderr argument to Popen and indicates that standard error should go into the same handle as standard output.

Base class for all other exceptions from this module.

Subclass of SubprocessError , raised when a timeout expires while waiting for a child process.

Command that was used to spawn the child process.

Timeout in seconds.

Output of the child process if it was captured by run() or check_output() . Otherwise, None . This is always bytes when any output was captured regardless of the text=True setting. It may remain None instead of b'' when no output was observed.

Alias for output, for symmetry with stderr .

Stderr output of the child process if it was captured by run() . Otherwise, None . This is always bytes when stderr output was captured regardless of the text=True setting. It may remain None instead of b'' when no stderr output was observed.

Changed in version 3.5: stdout and stderr attributes added

Subclass of SubprocessError , raised when a process run by check_call() , check_output() , or run() (with check=True ) returns a non-zero exit status.

Exit status of the child process. If the process exited due to a signal, this will be the negative signal number.

Output of the child process if it was captured by run() or check_output() . Otherwise, None .

Stderr output of the child process if it was captured by run() . Otherwise, None .

Frequently Used Arguments ¶

To support a wide variety of use cases, the Popen constructor (and the convenience functions) accept a large number of optional arguments. For most typical use cases, many of these arguments can be safely left at their default values. The arguments that are most commonly needed are:

args is required for all calls and should be a string, or a sequence of program arguments. Providing a sequence of arguments is generally preferred, as it allows the module to take care of any required escaping and quoting of arguments (e.g. to permit spaces in file names). If passing a single string, either shell must be True (see below) or else the string must simply name the program to be executed without specifying any arguments. stdin , stdout and stderr specify the executed program’s standard input, standard output and standard error file handles, respectively. Valid values are None , PIPE , DEVNULL , an existing file descriptor (a positive integer), and an existing file object with a valid file descriptor. With the default settings of None , no redirection will occur. PIPE indicates that a new pipe to the child should be created. DEVNULL indicates that the special file os.devnull will be used. Additionally, stderr can be STDOUT , which indicates that the stderr data from the child process should be captured into the same file handle as for stdout . If encoding or errors are specified, or text (also known as universal_newlines ) is true, the file objects stdin , stdout and stderr will be opened in text mode using the encoding and errors specified in the call or the defaults for io.TextIOWrapper . For stdin , line ending characters '\n' in the input will be converted to the default line separator os.linesep . For stdout and stderr , all line endings in the output will be converted to '\n' . For more information see the documentation of the io.TextIOWrapper class when the newline argument to its constructor is None . If text mode is not used, stdin , stdout and stderr will be opened as binary streams. No encoding or line ending conversion is performed. Changed in version 3.6: Added the encoding and errors parameters. Changed in version 3.7: Added the text parameter as an alias for universal_newlines . Note The newlines attribute of the file objects Popen.stdin , Popen.stdout and Popen.stderr are not updated by the Popen.communicate() method. If shell is True , the specified command will be executed through the shell. This can be useful if you are using Python primarily for the enhanced control flow it offers over most system shells and still want convenient access to other shell features such as shell pipes, filename wildcards, environment variable expansion, and expansion of ~ to a user’s home directory. However, note that Python itself offers implementations of many shell-like features (in particular, glob , fnmatch , os.walk() , os.path.expandvars() , os.path.expanduser() , and shutil ). Changed in version 3.3: When universal_newlines is True , the class uses the encoding locale.getpreferredencoding(False) instead of locale.getpreferredencoding() . See the io.TextIOWrapper class for more information on this change. Note Read the Security Considerations section before using shell=True .

These options, along with all of the other options, are described in more detail in the Popen constructor documentation.

Popen Constructor ¶

The underlying process creation and management in this module is handled by the Popen class. It offers a lot of flexibility so that developers are able to handle the less common cases not covered by the convenience functions.

Execute a child program in a new process. On POSIX, the class uses os.execvpe() -like behavior to execute the child program. On Windows, the class uses the Windows CreateProcess() function. The arguments to Popen are as follows.

args should be a sequence of program arguments or else a single string or path-like object . By default, the program to execute is the first item in args if args is a sequence. If args is a string, the interpretation is platform-dependent and described below. See the shell and executable arguments for additional differences from the default behavior. Unless otherwise stated, it is recommended to pass args as a sequence.

For maximum reliability, use a fully qualified path for the executable. To search for an unqualified name on PATH , use shutil.which() . On all platforms, passing sys.executable is the recommended way to launch the current Python interpreter again, and use the -m command-line format to launch an installed module.

Resolving the path of executable (or the first item of args ) is platform dependent. For POSIX, see os.execvpe() , and note that when resolving or searching for the executable path, cwd overrides the current working directory and env can override the PATH environment variable. For Windows, see the documentation of the lpApplicationName and lpCommandLine parameters of WinAPI CreateProcess , and note that when resolving or searching for the executable path with shell=False , cwd does not override the current working directory and env cannot override the PATH environment variable. Using a full path avoids all of these variations.

An example of passing some arguments to an external program as a sequence is:

On POSIX, if args is a string, the string is interpreted as the name or path of the program to execute. However, this can only be done if not passing arguments to the program.

It may not be obvious how to break a shell command into a sequence of arguments, especially in complex cases. shlex.split() can illustrate how to determine the correct tokenization for args :

Note in particular that options (such as -input ) and arguments (such as eggs.txt ) that are separated by whitespace in the shell go in separate list elements, while arguments that need quoting or backslash escaping when used in the shell (such as filenames containing spaces or the echo command shown above) are single list elements.

On Windows, if args is a sequence, it will be converted to a string in a manner described in Converting an argument sequence to a string on Windows . This is because the underlying CreateProcess() operates on strings.

Changed in version 3.6: args parameter accepts a path-like object if shell is False and a sequence containing path-like objects on POSIX.

Changed in version 3.8: args parameter accepts a path-like object if shell is False and a sequence containing bytes and path-like objects on Windows.

The shell argument (which defaults to False ) specifies whether to use the shell as the program to execute. If shell is True , it is recommended to pass args as a string rather than as a sequence.

On POSIX with shell=True , the shell defaults to /bin/sh . If args is a string, the string specifies the command to execute through the shell. This means that the string must be formatted exactly as it would be when typed at the shell prompt. This includes, for example, quoting or backslash escaping filenames with spaces in them. If args is a sequence, the first item specifies the command string, and any additional items will be treated as additional arguments to the shell itself. That is to say, Popen does the equivalent of:

On Windows with shell=True , the COMSPEC environment variable specifies the default shell. The only time you need to specify shell=True on Windows is when the command you wish to execute is built into the shell (e.g. dir or copy ). You do not need shell=True to run a batch file or console-based executable.

Read the Security Considerations section before using shell=True .

bufsize will be supplied as the corresponding argument to the open() function when creating the stdin/stdout/stderr pipe file objects:

0 means unbuffered (read and write are one system call and can return short)

1 means line buffered (only usable if text=True or universal_newlines=True )

any other positive value means use a buffer of approximately that size

negative bufsize (the default) means the system default of io.DEFAULT_BUFFER_SIZE will be used.

Changed in version 3.3.1: bufsize now defaults to -1 to enable buffering by default to match the behavior that most code expects. In versions prior to Python 3.2.4 and 3.3.1 it incorrectly defaulted to 0 which was unbuffered and allowed short reads. This was unintentional and did not match the behavior of Python 2 as most code expected.

The executable argument specifies a replacement program to execute. It is very seldom needed. When shell=False , executable replaces the program to execute specified by args . However, the original args is still passed to the program. Most programs treat the program specified by args as the command name, which can then be different from the program actually executed. On POSIX, the args name becomes the display name for the executable in utilities such as ps . If shell=True , on POSIX the executable argument specifies a replacement shell for the default /bin/sh .

Changed in version 3.6: executable parameter accepts a path-like object on POSIX.

Changed in version 3.8: executable parameter accepts a bytes and path-like object on Windows.

stdin , stdout and stderr specify the executed program’s standard input, standard output and standard error file handles, respectively. Valid values are None , PIPE , DEVNULL , an existing file descriptor (a positive integer), and an existing file object with a valid file descriptor. With the default settings of None , no redirection will occur. PIPE indicates that a new pipe to the child should be created. DEVNULL indicates that the special file os.devnull will be used. Additionally, stderr can be STDOUT , which indicates that the stderr data from the applications should be captured into the same file handle as for stdout .

If preexec_fn is set to a callable object, this object will be called in the child process just before the child is executed. (POSIX only)

The preexec_fn parameter is NOT SAFE to use in the presence of threads in your application. The child process could deadlock before exec is called.

If you need to modify the environment for the child use the env parameter rather than doing it in a preexec_fn . The start_new_session and process_group parameters should take the place of code using preexec_fn to call os.setsid() or os.setpgid() in the child.

Changed in version 3.8: The preexec_fn parameter is no longer supported in subinterpreters. The use of the parameter in a subinterpreter raises RuntimeError . The new restriction may affect applications that are deployed in mod_wsgi, uWSGI, and other embedded environments.

If close_fds is true, all file descriptors except 0 , 1 and 2 will be closed before the child process is executed. Otherwise when close_fds is false, file descriptors obey their inheritable flag as described in Inheritance of File Descriptors .

On Windows, if close_fds is true then no handles will be inherited by the child process unless explicitly passed in the handle_list element of STARTUPINFO.lpAttributeList , or by standard handle redirection.

Changed in version 3.2: The default for close_fds was changed from False to what is described above.

Changed in version 3.7: On Windows the default for close_fds was changed from False to True when redirecting the standard handles. It’s now possible to set close_fds to True when redirecting the standard handles.

pass_fds is an optional sequence of file descriptors to keep open between the parent and child. Providing any pass_fds forces close_fds to be True . (POSIX only)

Changed in version 3.2: The pass_fds parameter was added.

If cwd is not None , the function changes the working directory to cwd before executing the child. cwd can be a string, bytes or path-like object. On POSIX, the function looks for executable (or for the first item in args ) relative to cwd if the executable path is a relative path.

Changed in version 3.6: cwd parameter accepts a path-like object on POSIX.

Changed in version 3.7: cwd parameter accepts a path-like object on Windows.

Changed in version 3.8: cwd parameter accepts a bytes object on Windows.

If restore_signals is true (the default) all signals that Python has set to SIG_IGN are restored to SIG_DFL in the child process before the exec. Currently this includes the SIGPIPE, SIGXFZ and SIGXFSZ signals. (POSIX only)

Changed in version 3.2: restore_signals was added.

If start_new_session is true the setsid() system call will be made in the child process prior to the execution of the subprocess.

Availability : POSIX

Changed in version 3.2: start_new_session was added.

If process_group is a non-negative integer, the setpgid(0, value) system call will be made in the child process prior to the execution of the subprocess.

Changed in version 3.11: process_group was added.

If group is not None , the setregid() system call will be made in the child process prior to the execution of the subprocess. If the provided value is a string, it will be looked up via grp.getgrnam() and the value in gr_gid will be used. If the value is an integer, it will be passed verbatim. (POSIX only)

Added in version 3.9.

If extra_groups is not None , the setgroups() system call will be made in the child process prior to the execution of the subprocess. Strings provided in extra_groups will be looked up via grp.getgrnam() and the values in gr_gid will be used. Integer values will be passed verbatim. (POSIX only)

If user is not None , the setreuid() system call will be made in the child process prior to the execution of the subprocess. If the provided value is a string, it will be looked up via pwd.getpwnam() and the value in pw_uid will be used. If the value is an integer, it will be passed verbatim. (POSIX only)

If umask is not negative, the umask() system call will be made in the child process prior to the execution of the subprocess.

If env is not None , it must be a mapping that defines the environment variables for the new process; these are used instead of the default behavior of inheriting the current process’ environment. This mapping can be str to str on any platform or bytes to bytes on POSIX platforms much like os.environ or os.environb .

If specified, env must provide any variables required for the program to execute. On Windows, in order to run a side-by-side assembly the specified env must include a valid SystemRoot .

If encoding or errors are specified, or text is true, the file objects stdin , stdout and stderr are opened in text mode with the specified encoding and errors , as described above in Frequently Used Arguments . The universal_newlines argument is equivalent to text and is provided for backwards compatibility. By default, file objects are opened in binary mode.

Added in version 3.6: encoding and errors were added.

Added in version 3.7: text was added as a more readable alias for universal_newlines .

If given, startupinfo will be a STARTUPINFO object, which is passed to the underlying CreateProcess function.

If given, creationflags , can be one or more of the following flags:

CREATE_NEW_CONSOLE

CREATE_NEW_PROCESS_GROUP

ABOVE_NORMAL_PRIORITY_CLASS

BELOW_NORMAL_PRIORITY_CLASS

HIGH_PRIORITY_CLASS

IDLE_PRIORITY_CLASS

NORMAL_PRIORITY_CLASS

REALTIME_PRIORITY_CLASS

CREATE_NO_WINDOW

DETACHED_PROCESS

CREATE_DEFAULT_ERROR_MODE

CREATE_BREAKAWAY_FROM_JOB

pipesize can be used to change the size of the pipe when PIPE is used for stdin , stdout or stderr . The size of the pipe is only changed on platforms that support this (only Linux at this time of writing). Other platforms will ignore this parameter.

Changed in version 3.10: Added the pipesize parameter.

Popen objects are supported as context managers via the with statement: on exit, standard file descriptors are closed, and the process is waited for.

Popen and the other functions in this module that use it raise an auditing event subprocess.Popen with arguments executable , args , cwd , and env . The value for args may be a single string or a list of strings, depending on platform.

Changed in version 3.2: Added context manager support.

Changed in version 3.6: Popen destructor now emits a ResourceWarning warning if the child process is still running.

Changed in version 3.8: Popen can use os.posix_spawn() in some cases for better performance. On Windows Subsystem for Linux and QEMU User Emulation, Popen constructor using os.posix_spawn() no longer raise an exception on errors like missing program, but the child process fails with a non-zero returncode .

Exceptions ¶

Exceptions raised in the child process, before the new program has started to execute, will be re-raised in the parent.

The most common exception raised is OSError . This occurs, for example, when trying to execute a non-existent file. Applications should prepare for OSError exceptions. Note that, when shell=True , OSError will be raised by the child only if the selected shell itself was not found. To determine if the shell failed to find the requested application, it is necessary to check the return code or output from the subprocess.

A ValueError will be raised if Popen is called with invalid arguments.

check_call() and check_output() will raise CalledProcessError if the called process returns a non-zero return code.

All of the functions and methods that accept a timeout parameter, such as run() and Popen.communicate() will raise TimeoutExpired if the timeout expires before the process exits.

Exceptions defined in this module all inherit from SubprocessError .

Added in version 3.3: The SubprocessError base class was added.

Security Considerations ¶

Unlike some other popen functions, this library will not implicitly choose to call a system shell. This means that all characters, including shell metacharacters, can safely be passed to child processes. If the shell is invoked explicitly, via shell=True , it is the application’s responsibility to ensure that all whitespace and metacharacters are quoted appropriately to avoid shell injection vulnerabilities. On some platforms , it is possible to use shlex.quote() for this escaping.

On Windows, batch files ( *.bat or *.cmd ) may be launched by the operating system in a system shell regardless of the arguments passed to this library. This could result in arguments being parsed according to shell rules, but without any escaping added by Python. If you are intentionally launching a batch file with arguments from untrusted sources, consider passing shell=True to allow Python to escape special characters. See gh-114539 for additional discussion.

Popen Objects ¶

Instances of the Popen class have the following methods:

Check if child process has terminated. Set and return returncode attribute. Otherwise, returns None .

Wait for child process to terminate. Set and return returncode attribute.

If the process does not terminate after timeout seconds, raise a TimeoutExpired exception. It is safe to catch this exception and retry the wait.

This will deadlock when using stdout=PIPE or stderr=PIPE and the child process generates enough output to a pipe such that it blocks waiting for the OS pipe buffer to accept more data. Use Popen.communicate() when using pipes to avoid that.

When the timeout parameter is not None , then (on POSIX) the function is implemented using a busy loop (non-blocking call and short sleeps). Use the asyncio module for an asynchronous wait: see asyncio.create_subprocess_exec .

Changed in version 3.3: timeout was added.

Interact with process: Send data to stdin. Read data from stdout and stderr, until end-of-file is reached. Wait for process to terminate and set the returncode attribute. The optional input argument should be data to be sent to the child process, or None , if no data should be sent to the child. If streams were opened in text mode, input must be a string. Otherwise, it must be bytes.

communicate() returns a tuple (stdout_data, stderr_data) . The data will be strings if streams were opened in text mode; otherwise, bytes.

Note that if you want to send data to the process’s stdin, you need to create the Popen object with stdin=PIPE . Similarly, to get anything other than None in the result tuple, you need to give stdout=PIPE and/or stderr=PIPE too.

If the process does not terminate after timeout seconds, a TimeoutExpired exception will be raised. Catching this exception and retrying communication will not lose any output.

The child process is not killed if the timeout expires, so in order to cleanup properly a well-behaved application should kill the child process and finish communication:

The data read is buffered in memory, so do not use this method if the data size is large or unlimited.

Sends the signal signal to the child.

Do nothing if the process completed.

On Windows, SIGTERM is an alias for terminate() . CTRL_C_EVENT and CTRL_BREAK_EVENT can be sent to processes started with a creationflags parameter which includes CREATE_NEW_PROCESS_GROUP .

Stop the child. On POSIX OSs the method sends SIGTERM to the child. On Windows the Win32 API function TerminateProcess() is called to stop the child.

Kills the child. On POSIX OSs the function sends SIGKILL to the child. On Windows kill() is an alias for terminate() .

The following attributes are also set by the class for you to access. Reassigning them to new values is unsupported:

The args argument as it was passed to Popen – a sequence of program arguments or else a single string.

If the stdin argument was PIPE , this attribute is a writeable stream object as returned by open() . If the encoding or errors arguments were specified or the text or universal_newlines argument was True , the stream is a text stream, otherwise it is a byte stream. If the stdin argument was not PIPE , this attribute is None .

If the stdout argument was PIPE , this attribute is a readable stream object as returned by open() . Reading from the stream provides output from the child process. If the encoding or errors arguments were specified or the text or universal_newlines argument was True , the stream is a text stream, otherwise it is a byte stream. If the stdout argument was not PIPE , this attribute is None .

If the stderr argument was PIPE , this attribute is a readable stream object as returned by open() . Reading from the stream provides error output from the child process. If the encoding or errors arguments were specified or the text or universal_newlines argument was True , the stream is a text stream, otherwise it is a byte stream. If the stderr argument was not PIPE , this attribute is None .

Use communicate() rather than .stdin.write , .stdout.read or .stderr.read to avoid deadlocks due to any of the other OS pipe buffers filling up and blocking the child process.

The process ID of the child process.

Note that if you set the shell argument to True , this is the process ID of the spawned shell.

The child return code. Initially None , returncode is set by a call to the poll() , wait() , or communicate() methods if they detect that the process has terminated.

A None value indicates that the process hadn’t yet terminated at the time of the last method call.

Windows Popen Helpers ¶

The STARTUPINFO class and following constants are only available on Windows.

Partial support of the Windows STARTUPINFO structure is used for Popen creation. The following attributes can be set by passing them as keyword-only arguments.

Changed in version 3.7: Keyword-only argument support was added.

A bit field that determines whether certain STARTUPINFO attributes are used when the process creates a window.

If dwFlags specifies STARTF_USESTDHANDLES , this attribute is the standard input handle for the process. If STARTF_USESTDHANDLES is not specified, the default for standard input is the keyboard buffer.

If dwFlags specifies STARTF_USESTDHANDLES , this attribute is the standard output handle for the process. Otherwise, this attribute is ignored and the default for standard output is the console window’s buffer.

If dwFlags specifies STARTF_USESTDHANDLES , this attribute is the standard error handle for the process. Otherwise, this attribute is ignored and the default for standard error is the console window’s buffer.

If dwFlags specifies STARTF_USESHOWWINDOW , this attribute can be any of the values that can be specified in the nCmdShow parameter for the ShowWindow function, except for SW_SHOWDEFAULT . Otherwise, this attribute is ignored.

SW_HIDE is provided for this attribute. It is used when Popen is called with shell=True .

A dictionary of additional attributes for process creation as given in STARTUPINFOEX , see UpdateProcThreadAttribute .

Supported attributes:

Sequence of handles that will be inherited. close_fds must be true if non-empty.

The handles must be temporarily made inheritable by os.set_handle_inheritable() when passed to the Popen constructor, else OSError will be raised with Windows error ERROR_INVALID_PARAMETER (87).

In a multithreaded process, use caution to avoid leaking handles that are marked inheritable when combining this feature with concurrent calls to other process creation functions that inherit all handles such as os.system() . This also applies to standard handle redirection, which temporarily creates inheritable handles.

Added in version 3.7.

Windows Constants ¶

The subprocess module exposes the following constants.

The standard input device. Initially, this is the console input buffer, CONIN$ .

The standard output device. Initially, this is the active console screen buffer, CONOUT$ .

The standard error device. Initially, this is the active console screen buffer, CONOUT$ .

Hides the window. Another window will be activated.

Specifies that the STARTUPINFO.hStdInput , STARTUPINFO.hStdOutput , and STARTUPINFO.hStdError attributes contain additional information.

Specifies that the STARTUPINFO.wShowWindow attribute contains additional information.

A STARTUPINFO.dwFlags parameter to specify that the Working in Background mouse cursor will be displayed while a process is launching. This is the default behavior for GUI processes.

Added in version 3.13.

A STARTUPINFO.dwFlags parameter to specify that the mouse cursor will not be changed when launching a process.

The new process has a new console, instead of inheriting its parent’s console (the default).

A Popen creationflags parameter to specify that a new process group will be created. This flag is necessary for using os.kill() on the subprocess.

This flag is ignored if CREATE_NEW_CONSOLE is specified.

A Popen creationflags parameter to specify that a new process will have an above average priority.

A Popen creationflags parameter to specify that a new process will have a below average priority.

A Popen creationflags parameter to specify that a new process will have a high priority.

A Popen creationflags parameter to specify that a new process will have an idle (lowest) priority.

A Popen creationflags parameter to specify that a new process will have an normal priority. (default)

A Popen creationflags parameter to specify that a new process will have realtime priority. You should almost never use REALTIME_PRIORITY_CLASS, because this interrupts system threads that manage mouse input, keyboard input, and background disk flushing. This class can be appropriate for applications that “talk” directly to hardware or that perform brief tasks that should have limited interruptions.

A Popen creationflags parameter to specify that a new process will not create a window.

A Popen creationflags parameter to specify that a new process will not inherit its parent’s console. This value cannot be used with CREATE_NEW_CONSOLE.

A Popen creationflags parameter to specify that a new process does not inherit the error mode of the calling process. Instead, the new process gets the default error mode. This feature is particularly useful for multithreaded shell applications that run with hard errors disabled.

A Popen creationflags parameter to specify that a new process is not associated with the job.

Older high-level API ¶

Prior to Python 3.5, these three functions comprised the high level API to subprocess. You can now use run() in many cases, but lots of existing code calls these functions.

Run the command described by args . Wait for command to complete, then return the returncode attribute.

Code needing to capture stdout or stderr should use run() instead:

To suppress stdout or stderr, supply a value of DEVNULL .

The arguments shown above are merely some common ones. The full function signature is the same as that of the Popen constructor - this function passes all supplied arguments other than timeout directly through to that interface.

Do not use stdout=PIPE or stderr=PIPE with this function. The child process will block if it generates enough output to a pipe to fill up the OS pipe buffer as the pipes are not being read from.

Run command with arguments. Wait for command to complete. If the return code was zero then return, otherwise raise CalledProcessError . The CalledProcessError object will have the return code in the returncode attribute. If check_call() was unable to start the process it will propagate the exception that was raised.

Run command with arguments and return its output.

If the return code was non-zero it raises a CalledProcessError . The CalledProcessError object will have the return code in the returncode attribute and any output in the output attribute.

This is equivalent to:

The arguments shown above are merely some common ones. The full function signature is largely the same as that of run() - most arguments are passed directly through to that interface. One API deviation from run() behavior exists: passing input=None will behave the same as input=b'' (or input='' , depending on other arguments) rather than using the parent’s standard input file handle.

By default, this function will return the data as encoded bytes. The actual encoding of the output data may depend on the command being invoked, so the decoding to text will often need to be handled at the application level.

This behaviour may be overridden by setting text , encoding , errors , or universal_newlines to True as described in Frequently Used Arguments and run() .

To also capture standard error in the result, use stderr=subprocess.STDOUT :

Added in version 3.1.

Changed in version 3.4: Support for the input keyword argument was added.

Changed in version 3.6: encoding and errors were added. See run() for details.

Replacing Older Functions with the subprocess Module ¶

In this section, “a becomes b” means that b can be used as a replacement for a.

All “a” functions in this section fail (more or less) silently if the executed program cannot be found; the “b” replacements raise OSError instead.

In addition, the replacements using check_output() will fail with a CalledProcessError if the requested operation produces a non-zero return code. The output is still available as the output attribute of the raised exception.

In the following examples, we assume that the relevant functions have already been imported from the subprocess module.

Replacing /bin/sh shell command substitution ¶

Replacing shell pipeline ¶.

The p1.stdout.close() call after starting the p2 is important in order for p1 to receive a SIGPIPE if p2 exits before p1.

Alternatively, for trusted input, the shell’s own pipeline support may still be used directly:

Replacing os.system() ¶

Calling the program through the shell is usually not required.

The call() return value is encoded differently to that of os.system() .

The os.system() function ignores SIGINT and SIGQUIT signals while the command is running, but the caller must do this separately when using the subprocess module.

A more realistic example would look like this:

Replacing the os.spawn family ¶

P_NOWAIT example:

P_WAIT example:

Vector example:

Environment example:

Replacing os.popen() , os.popen2() , os.popen3() ¶

Return code handling translates as follows:

Replacing functions from the popen2 module ¶

If the cmd argument to popen2 functions is a string, the command is executed through /bin/sh. If it is a list, the command is directly executed.

popen2.Popen3 and popen2.Popen4 basically work as subprocess.Popen , except that:

Popen raises an exception if the execution fails.

The capturestderr argument is replaced with the stderr argument.

stdin=PIPE and stdout=PIPE must be specified.

popen2 closes all file descriptors by default, but you have to specify close_fds=True with Popen to guarantee this behavior on all platforms or past Python versions.

Legacy Shell Invocation Functions ¶

This module also provides the following legacy functions from the 2.x commands module. These operations implicitly invoke the system shell and none of the guarantees described above regarding security and exception handling consistency are valid for these functions.

Return (exitcode, output) of executing cmd in a shell.

Execute the string cmd in a shell with Popen.check_output() and return a 2-tuple (exitcode, output) . encoding and errors are used to decode output; see the notes on Frequently Used Arguments for more details.

A trailing newline is stripped from the output. The exit code for the command can be interpreted as the return code of subprocess. Example:

Availability : Unix, Windows.

Changed in version 3.3.4: Windows support was added.

The function now returns (exitcode, output) instead of (status, output) as it did in Python 3.3.3 and earlier. exitcode has the same value as returncode .

Changed in version 3.11: Added the encoding and errors parameters.

Return output (stdout and stderr) of executing cmd in a shell.

Like getstatusoutput() , except the exit code is ignored and the return value is a string containing the command’s output. Example:

Changed in version 3.3.4: Windows support added

Converting an argument sequence to a string on Windows ¶

On Windows, an args sequence is converted to a string that can be parsed using the following rules (which correspond to the rules used by the MS C runtime):

Arguments are delimited by white space, which is either a space or a tab.

A string surrounded by double quotation marks is interpreted as a single argument, regardless of white space contained within. A quoted string can be embedded in an argument.

A double quotation mark preceded by a backslash is interpreted as a literal double quotation mark.

Backslashes are interpreted literally, unless they immediately precede a double quotation mark.

If backslashes immediately precede a double quotation mark, every pair of backslashes is interpreted as a literal backslash. If the number of backslashes is odd, the last backslash escapes the next double quotation mark as described in rule 3.

Module which provides function to parse and escape command lines.

Disabling use of vfork() or posix_spawn() ¶

On Linux, subprocess defaults to using the vfork() system call internally when it is safe to do so rather than fork() . This greatly improves performance.

If you ever encounter a presumed highly unusual situation where you need to prevent vfork() from being used by Python, you can set the subprocess._USE_VFORK attribute to a false value.

Setting this has no impact on use of posix_spawn() which could use vfork() internally within its libc implementation. There is a similar subprocess._USE_POSIX_SPAWN attribute if you need to prevent use of that.

It is safe to set these to false on any Python version. They will have no effect on older versions when unsupported. Do not assume the attributes are available to read. Despite their names, a true value does not indicate that the corresponding function will be used, only that it may be.

Please file issues any time you have to use these private knobs with a way to reproduce the issue you were seeing. Link to that issue from a comment in your code.

Added in version 3.8: _USE_POSIX_SPAWN

Added in version 3.11: _USE_VFORK

Table of Contents

• Frequently Used Arguments
• Popen Constructor
• Security Considerations
• Popen Objects
• Windows Constants
• Older high-level API
• Replacing /bin/sh shell command substitution
• Replacing shell pipeline
• Replacing os.system()
• Replacing the os.spawn family
• Replacing os.popen() , os.popen2() , os.popen3()
• Replacing functions from the popen2 module
• Legacy Shell Invocation Functions
• Converting an argument sequence to a string on Windows
• Disabling use of vfork() or posix_spawn()

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