Define Functions Parameters and Return Values

Define Functions Parameters and Return Values is not a checkbox topic. It changes how you build, inspect, or reason about a Python project. This lesson approaches it as documentation you can work from: first the behavior, then the mechanics, then a reproducible example, and finally the failure cases that matter when the example leaves a tutorial.

In this lesson

• Place Functions Parameters and Return Values in the context of the Functions and Program Structure module rather than treating it as an isolated feature.
• Build a mental model for what happens before, during, and after the operation.
• Work through a reproducible example connected to the scenario: build a small inventory/reporting utility that evolves as new language features are learned.
• Inspect the result and distinguish evidence from assumption.
• Recognize failure modes, misleading shortcuts, and production constraints.
• Leave with a verification checklist and a practical exercise rather than a memorized snippet.

Testing the behavior

For a Python developer, Functions Parameters and Return Values becomes useful when it changes a decision you can verify. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. For Functions Parameters and Return Values, apply this check in the context of the Functions and Program Structure workflow before carrying the assumption into later Python work.

The practical question behind define functions parameters and return values is not simply whether the feature exists, but what behavior it gives you control over. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. For Functions Parameters and Return Values, apply this check in the context of the Functions and Program Structure workflow before carrying the assumption into later Python work.

Maintainability and readability

Before adding more syntax, make the state of the system observable. That habit matters especially when working with Functions Parameters and Return Values. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. In this lesson's Functions Parameters and Return Values example, record the evidence you observed rather than treating the rule as a slogan; that note becomes useful when the next Functions and Program Structure exercise changes the conditions. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

There are usually several ways to accomplish the same visible result. The important skill is knowing which guarantees differ when you choose one form of Functions Parameters and Return Values over another. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. In this lesson's Functions Parameters and Return Values example, record the evidence you observed rather than treating the rule as a slogan; that note becomes useful when the next Functions and Program Structure exercise changes the conditions. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

Questions to answer about Functions Parameters and Return Values

1. What is the smallest input or state that makes Functions Parameters and Return Values observable?
2. What does success look like, and how can you prove it without relying on a vague UI message?
3. Which configuration, permissions, types, versions or environment details can change the result?
4. Which failure is most likely for a beginner, and what evidence distinguishes it from a different failure?
5. What should remain true after the example is repeated, automated or moved to another environment?

Performance or operational implications

In the Functions and Program Structure part of this learning path, Functions Parameters and Return Values is deliberately introduced now because later lessons depend on the boundary it establishes. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. Keep this point tied to Functions Parameters and Return Values. The same general engineering habit appears elsewhere, but the evidence and failure signals in this Functions and Program Structure lesson are specific to this mechanism. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

A production system rarely fails at the exact line shown in a beginner example, so this section connects Functions Parameters and Return Values to the surrounding runtime and operational context. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. The specific test here is about Functions Parameters and Return Values: change one relevant input, configuration value or boundary and make sure the result still matches the contract described above. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

Practice variation

For a Python developer, Functions Parameters and Return Values becomes useful when it changes a decision you can verify. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. In this lesson's Functions Parameters and Return Values example, record the evidence you observed rather than treating the rule as a slogan; that note becomes useful when the next Functions and Program Structure exercise changes the conditions. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

The practical question behind define functions parameters and return values is not simply whether the feature exists, but what behavior it gives you control over. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. In this lesson's Functions Parameters and Return Values example, record the evidence you observed rather than treating the rule as a slogan; that note becomes useful when the next Functions and Program Structure exercise changes the conditions. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

Evidence table

What you inspect	What it tells you	What it does not prove
Source/configuration for Functions Parameters and Return Values	What you asked the platform/runtime to do	That the request actually succeeded
Build/validation output	Whether static checks accepted the artifact	That production data and permissions behave correctly
Runtime/result output	What happened for this input	That every edge case is safe
Logs/diagnostics	Where the system spent time or failed	The root cause without interpretation
Repeat test	Whether behavior is reproducible	That the design is optimal

Review questions

Before adding more syntax, make the state of the system observable. That habit matters especially when working with Functions Parameters and Return Values. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. Keep this point tied to Functions Parameters and Return Values. The same general engineering habit appears elsewhere, but the evidence and failure signals in this Functions and Program Structure lesson are specific to this mechanism. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

There are usually several ways to accomplish the same visible result. The important skill is knowing which guarantees differ when you choose one form of Functions Parameters and Return Values over another. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. The specific test here is about Functions Parameters and Return Values: change one relevant input, configuration value or boundary and make sure the result still matches the contract described above.

Where to go next

In the Functions and Program Structure part of this learning path, Functions Parameters and Return Values is deliberately introduced now because later lessons depend on the boundary it establishes. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. For Functions Parameters and Return Values, apply this check in the context of the Functions and Program Structure workflow before carrying the assumption into later Python work. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

A production system rarely fails at the exact line shown in a beginner example, so this section connects Functions Parameters and Return Values to the surrounding runtime and operational context. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. Keep this point tied to Functions Parameters and Return Values. The same general engineering habit appears elsewhere, but the evidence and failure signals in this Functions and Program Structure lesson are specific to this mechanism. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

Worked example: Functions Parameters and Return Values

The following python example is written specifically for this lesson. Read the requirement first, then predict the important result before running or reproducing it.

# Functions Parameters and Return Values
values = [12, 18, 25, 31]
threshold = 20
selected = [value for value in values if value >= threshold]
print("selected:", selected)
print("count:", len(selected))

Expected observation

selected: [25, 31]\ncount: 2

Read the example deliberately

• Line/construct 1: values = [12, 18, 25, 31] — identify what state or contract this introduces, then trace where that state is consumed.
• Line/construct 2: threshold = 20 — identify what state or contract this introduces, then trace where that state is consumed.
• Line/construct 3: selected = [value for value in values if value >= threshold] — identify what state or contract this introduces, then trace where that state is consumed.
• Line/construct 4: print("selected:", selected) — identify what state or contract this introduces, then trace where that state is consumed.
• Line/construct 5: print("count:", len(selected)) — identify what state or contract this introduces, then trace where that state is consumed.

Do not stop at “it ran.” Change one meaningful value related to Functions Parameters and Return Values, predict the new result, run/reproduce the example again, and explain why the output changed. That mutation test is a stronger check of understanding than copying the original result.

The idea behind Functions Parameters and Return Values

For this part of Define Functions Parameters and Return Values, move beyond the earlier mental model and ask how the behavior survives repetition. Run or reproduce the step twice, change the ordering or boundary case where safe, and verify that the same invariant still holds. A reliable Functions and Program Structure workflow is one that produces evidence you can compare, not one that succeeds only when the exact tutorial sequence is copied.

The practical question behind define functions parameters and return values is not simply whether the feature exists, but what behavior it gives you control over. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. The specific test here is about Functions Parameters and Return Values: change one relevant input, configuration value or boundary and make sure the result still matches the contract described above. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

Mental model before syntax

Before adding more syntax, make the state of the system observable. That habit matters especially when working with Functions Parameters and Return Values. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. For Functions Parameters and Return Values, apply this check in the context of the Functions and Program Structure workflow before carrying the assumption into later Python work.

There are usually several ways to accomplish the same visible result. The important skill is knowing which guarantees differ when you choose one form of Functions Parameters and Return Values over another. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. Keep this point tied to Functions Parameters and Return Values. The same general engineering habit appears elsewhere, but the evidence and failure signals in this Functions and Program Structure lesson are specific to this mechanism. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

Failure-mode matrix

Symptom	Likely category	First evidence to collect
The Functions Parameters and Return Values behavior never occurs	configuration / control flow	verify the relevant code/configuration is actually reached
Build or validation fails	syntax / type / unsupported option	read the first meaningful diagnostic, not the last cascade message
Works locally but not elsewhere	environment / version / permission	compare runtime versions, identity, configuration and data
Result is valid but wrong	assumption / data shape / business rule	inspect intermediate values and boundary conditions
Intermittent behavior	concurrency / timing / external dependency	add timestamps, correlation IDs or deterministic reproduction

Terminology and boundaries

In the Functions and Program Structure part of this learning path, Functions Parameters and Return Values is deliberately introduced now because later lessons depend on the boundary it establishes. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. In this lesson's Functions Parameters and Return Values example, record the evidence you observed rather than treating the rule as a slogan; that note becomes useful when the next Functions and Program Structure exercise changes the conditions.

How the mechanism behaves step by step

For the How the mechanism behaves step by step part of Define Functions Parameters and Return Values, use a separate verification pass rather than repeating the earlier explanation. Focus on Functions Parameters and Return Values under one changed condition and write down the before/after evidence. This is verification pass 2 for Python lesson 26: the useful outcome is a concrete observation—output, state, diagnostic, generated artifact, query result or test result—that another learner can reproduce in the Functions and Program Structure workflow.

Now apply Functions Parameters and Return Values to the current How the mechanism behaves step by step concern. Start from the smallest state that demonstrates the behavior, vary one input or configuration choice, and explain the result in terms of the Python runtime or platform. If two outcomes look similar in the UI, use logs, return values, generated artifacts, query results, tests or another concrete signal to distinguish them.

Syntax or configuration anatomy

There are usually several ways to accomplish the same visible result. The important skill is knowing which guarantees differ when you choose one form of Functions Parameters and Return Values over another. At the intermediate stage, the goal is not to cover every advanced option. It is to establish the correct mental model and the verification habit that later pages can extend. Where the platform has version-specific behavior, prefer the current official documentation and check the version shown by your own tools before assuming an older screenshot or blog post is authoritative. For Functions Parameters and Return Values, apply this check in the context of the Functions and Program Structure workflow before carrying the assumption into later Python work.

Worked example built from a real requirement

This section needs a different question from the earlier explanation: what would make Functions Parameters and Return Values fail specifically while working through Worked example built from a real requirement? Choose one realistic boundary, reproduce it deliberately, and inspect the first useful diagnostic or intermediate value. The aim in Define Functions Parameters and Return Values is to recognize the mechanism under changed conditions, not to repeat the same successful path with different wording.

For the Worked example built from a real requirement part of Define Functions Parameters and Return Values, use a separate verification pass rather than repeating the earlier explanation. Focus on Functions Parameters and Return Values under one changed condition and write down the before/after evidence. This is verification pass 3 for Python lesson 26: the useful outcome is a concrete observation—output, state, diagnostic, generated artifact, query result or test result—that another learner can reproduce in the Functions and Program Structure workflow.

Trace the example line by line

Now apply Functions Parameters and Return Values to the current Trace the example line by line concern. Start from the smallest state that demonstrates the behavior, vary one input or configuration choice, and explain the result in terms of the Python runtime or platform. If two outcomes look similar in the UI, use logs, return values, generated artifacts, query results, tests or another concrete signal to distinguish them.

For the Trace the example line by line part of Define Functions Parameters and Return Values, use a separate verification pass rather than repeating the earlier explanation. Focus on Functions Parameters and Return Values under one changed condition and write down the before/after evidence. This is verification pass 4 for Python lesson 26: the useful outcome is a concrete observation—output, state, diagnostic, generated artifact, query result or test result—that another learner can reproduce in the Functions and Program Structure workflow.

Variants you will meet in real code

Before adding more syntax, make the state of the system observable. That habit matters especially when working with Functions Parameters and Return Values. Documentation often presents the API or syntax first because reference pages are written for lookup. A tutorial has a different job. Here the explanation begins with intent, then shows the smallest concrete implementation, then adds constraints. That order lets you understand why a setting or line exists before you are asked to remember its spelling. The specific test here is about Functions Parameters and Return Values: change one relevant input, configuration value or boundary and make sure the result still matches the contract described above.

Now apply Functions Parameters and Return Values to the current Variants you will meet in real code concern. Start from the smallest state that demonstrates the behavior, vary one input or configuration choice, and explain the result in terms of the Python runtime or platform. If two outcomes look similar in the UI, use logs, return values, generated artifacts, query results, tests or another concrete signal to distinguish them.

Interactions with neighboring concepts

This section needs a different question from the earlier explanation: what would make Functions Parameters and Return Values fail specifically while working through Interactions with neighboring concepts? Choose one realistic boundary, reproduce it deliberately, and inspect the first useful diagnostic or intermediate value. The aim in Define Functions Parameters and Return Values is to recognize the mechanism under changed conditions, not to repeat the same successful path with different wording.

Now apply Functions Parameters and Return Values to the current Interactions with neighboring concepts concern. Start from the smallest state that demonstrates the behavior, vary one input or configuration choice, and explain the result in terms of the Python runtime or platform. If two outcomes look similar in the UI, use logs, return values, generated artifacts, query results, tests or another concrete signal to distinguish them.

Failure modes that reveal misunderstanding

This section needs a different question from the earlier explanation: what would make Functions Parameters and Return Values fail specifically while working through Failure modes that reveal misunderstanding? Choose one realistic boundary, reproduce it deliberately, and inspect the first useful diagnostic or intermediate value. The aim in Define Functions Parameters and Return Values is to recognize the mechanism under changed conditions, not to repeat the same successful path with different wording.

For the Failure modes that reveal misunderstanding part of Define Functions Parameters and Return Values, use a separate verification pass rather than repeating the earlier explanation. Focus on Functions Parameters and Return Values under one changed condition and write down the before/after evidence. This is verification pass 5 for Python lesson 26: the useful outcome is a concrete observation—output, state, diagnostic, generated artifact, query result or test result—that another learner can reproduce in the Functions and Program Structure workflow.

Choosing between common alternatives

For the Choosing between common alternatives part of Define Functions Parameters and Return Values, use a separate verification pass rather than repeating the earlier explanation. Focus on Functions Parameters and Return Values under one changed condition and write down the before/after evidence. This is verification pass 6 for Python lesson 26: the useful outcome is a concrete observation—output, state, diagnostic, generated artifact, query result or test result—that another learner can reproduce in the Functions and Program Structure workflow.

Now apply Functions Parameters and Return Values to the current Choosing between common alternatives concern. Start from the smallest state that demonstrates the behavior, vary one input or configuration choice, and explain the result in terms of the Python runtime or platform. If two outcomes look similar in the UI, use logs, return values, generated artifacts, query results, tests or another concrete signal to distinguish them.

A production-oriented walkthrough for Functions Parameters and Return Values

1. Establish the Functions Parameters and Return Values behavior

2. Inspect the Functions Parameters and Return Values behavior

3. Implement the Functions Parameters and Return Values behavior

A useful variation is to introduce one boundary case that is plausible for Functions Parameters and Return Values: an empty value, a missing permission, an unexpected type, a repeated operation, an unavailable dependency, or a larger-than-normal input. The exact case depends on the technology, but the reasoning is the same—state the invariant you expect to remain true, then verify it explicitly. The specific test here is about Functions Parameters and Return Values: change one relevant input, configuration value or boundary and make sure the result still matches the contract described above. In Python lesson 26 — Define Functions Parameters and Return Values, use that observation as the checkpoint for this exact Functions and Program Structure topic rather than generalizing it beyond the evidence.

4. Exercise the Functions Parameters and Return Values behavior

5. Challenge the Functions Parameters and Return Values behavior

For the A production-oriented walkthrough for Functions Parameters and Return Values part of Define Functions Parameters and Return Values, use a separate verification pass rather than repeating the earlier explanation. Focus on Functions Parameters and Return Values under one changed condition and write down the before/after evidence. This is verification pass 7 for Python lesson 26: the useful outcome is a concrete observation—output, state, diagnostic, generated artifact, query result or test result—that another learner can reproduce in the Functions and Program Structure workflow.

6. Verify the Functions Parameters and Return Values behavior

7. Harden the Functions Parameters and Return Values behavior

A useful variation is to introduce one boundary case that is plausible for Functions Parameters and Return Values: an empty value, a missing permission, an unexpected type, a repeated operation, an unavailable dependency, or a larger-than-normal input. The exact case depends on the technology, but the reasoning is the same—state the invariant you expect to remain true, then verify it explicitly. Keep this point tied to Functions Parameters and Return Values. The same general engineering habit appears elsewhere, but the evidence and failure signals in this Functions and Program Structure lesson are specific to this mechanism.

8. Document the Functions Parameters and Return Values behavior

Document this step in the context of build a small inventory/reporting utility that evolves as new language features are learned. Keep the change small enough that you can state the expected result before executing it. Capture the relevant input, configuration or code, then record the observable result. If the result differs from the prediction, do not add more changes yet; narrow the mismatch using diagnostics appropriate to Python, a virtual environment and an editor. The specific test here is about Functions Parameters and Return Values: change one relevant input, configuration value or boundary and make sure the result still matches the contract described above.

Failure patterns worth recognizing early

Treating Functions Parameters and Return Values as syntax instead of behavior

If you can reproduce the syntax but cannot predict the state after it runs, the lesson is not finished. Rewrite the example in your own words and name the input, operation and observable result.

Copying a configuration from a different version

Python tooling evolves. Compare the documentation version, runtime/tool version and project settings before assuming that a screenshot or command from another environment applies unchanged.

Verifying only the happy path

A successful first run proves one path. Add at least one negative or boundary case relevant to Functions Parameters and Return Values. The failure should be intentional and the diagnostic should make sense.

Hiding the important state behind too much abstraction

Abstraction is useful after the behavior is understood. During the first implementation of Functions Parameters and Return Values, keep the decisive state and control flow visible enough to debug.

Recovering from common Functions Parameters and Return Values failures

Use this order when Functions Parameters and Return Values does not behave as expected:

1. Reproduce the smallest failing case.
2. Confirm the actual version/toolchain/environment.
3. Capture the first meaningful diagnostic or unexpected value.
4. Verify identity, permissions and configuration if the operation crosses a service boundary.
5. Inspect intermediate state rather than only the final UI.
6. Change one variable and rerun.
7. Compare the corrected behavior with a negative case.
8. Record the final cause so the same failure is faster to diagnose next time.

Practice: change the constraint

Extend the worked scenario so that Functions Parameters and Return Values must handle one additional real constraint. Choose one: a second data shape, a failed dependency, an invalid input, a permission difference, a repeat operation, or a larger workload. Before implementing the change, write down the behavior you expect and the evidence that will prove it.

Your result is complete when another learner can reproduce the change from your notes, observe the expected behavior, and intentionally trigger at least one documented failure without damaging their environment. In this lesson's Functions Parameters and Return Values example, record the evidence you observed rather than treating the rule as a slogan; that note becomes useful when the next Functions and Program Structure exercise changes the conditions.

Review questions for Functions Parameters and Return Values

• Can you define Functions Parameters and Return Values without using the exact wording of an API/reference page?
• Can you identify the boundary where Functions Parameters and Return Values begins and where another concept takes over?
• Can you predict the result of the worked example before running it?
• Can you explain one failure from evidence rather than guessing?
• Can you name one production constraint that the beginner example intentionally simplifies?
• Can you repeat the example from a clean state?

Summary for the next lesson

• Functions Parameters and Return Values is useful because it controls observable behavior, not because it adds another piece of syntax to memorize.
• Verification belongs in the workflow: build/check, run/reproduce, inspect, challenge, and repeat.
• The Functions and Program Structure module uses this lesson as a foundation for the next decisions in the Python learning path.
• Official documentation is the source of truth for version-specific contracts; tutorials should teach you how to read and apply those contracts.

Official references for deeper lookup

The following primary documentation was used as a factual reference map for this lesson. ScrutnLearn's explanation is original synthesis rather than copied documentation prose.

• Python Enhancement Proposals
• Python Packaging User Guide
• Python asyncio
• Python language reference
• Python standard library

Ready.