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Clojure Networking Concepts, Functions-Methods, Classes, Standard Library and 3rd Party Libraries: In order of most important / popular.

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In Clojure, a dynamic, functional programming language that targets the JVM, networking is an essential aspect for interacting with external systems, handling communications, and performing web-related tasks. Networking in Clojure revolves around using both core libraries and third-party libraries that leverage the Java ecosystem's networking capabilities. Understanding these concepts, functions, and classes can significantly enhance your ability to work on distributed systems, web services, and network-based applications. Furthermore, integration with industry standards such as the various RFC protocols (RFC 2616, RFC 7540, etc.) allows for interoperability and conformance to modern networking standards.

A key concept in Clojure networking is the seamless interoperation with Java's Standard Library. The java.net package provides core networking classes, including Socket, ServerSocket, and URL, which can be utilized directly in Clojure for creating networked applications. Functions such as slurp and spit from Clojure's core library enable simple I/O operations, including reading from URLs and writing to files over a network. These functions are a great entry point for basic networking tasks.

When working with higher-level network communication in Clojure, you often employ HTTP protocols defined by RFC 2616 for HTTP/1.1 and RFC 7540 for HTTP/2. HTTP is a widely used protocol for web services, and libraries like clj-http offer an idiomatic Clojure interface for making HTTP requests. clj-http wraps the underlying Java HttpClient while providing an expressive, functional API for building and parsing requests and responses. This library is essential for interacting with REST APIs, downloading resources, or posting data.

Another critical concept is asynchronous networking. In modern applications, non-blocking, asynchronous operations are crucial for scalability, particularly in handling concurrent connections. Clojure integrates well with Java's NIO (Non-blocking I/O) capabilities, which are defined by RFC 6455 for WebSockets and by RFC 793 for the TCP protocol. Libraries like aleph, built on top of Netty, offer asynchronous, event-driven networking in Clojure. aleph supports a wide range of protocols, including HTTP, TCP, and UDP, allowing for the creation of high-performance networked applications.

For web services and server-side applications, frameworks like Ring and Compojure are popular in the Clojure ecosystem. Ring abstracts the HTTP request-response cycle into a simple map structure, making it easy to manipulate data and headers. The foundation of Ring is based on the HTTP standards described in RFC 2616, ensuring compatibility with modern web practices. Compojure, built on top of Ring, provides routing capabilities that allow developers to define web endpoints with clean syntax.

Security is also a paramount concern in networking, particularly in web applications. Clojure developers often rely on libraries such as buddy to handle authentication, authorization, and encryption. buddy offers support for JWT (JSON Web Tokens), basic auth, and secure password hashing. These features align with security standards like RFC 7519 for JWT and RFC 2617 for HTTP authentication.

Another advanced networking topic is the use of messaging protocols for building distributed systems. Libraries like aleph and manifold enable Clojure applications to work with WebSockets (RFC 6455) and MQTT (RFC 6456), allowing for real-time, bi-directional communication between clients and servers. WebSockets are particularly useful for applications requiring real-time updates, such as chat systems, live notifications, or collaborative tools.

For data serialization and transport over the network, Clojure utilizes formats like JSON, EDN, and Transit. The cheshire library is a popular choice for JSON encoding and decoding in Clojure. cheshire allows you to convert Clojure data structures into JSON and vice versa, which is essential for interacting with web services that rely on the JSON format, a standard defined by RFC 7159.

Another important third-party library for networking is http-kit, which provides a lightweight HTTP client and server in Clojure. http-kit is known for its high performance and low resource consumption, making it suitable for handling a large number of concurrent connections. It is commonly used for building WebSocket servers and clients, enabling real-time communication over the web.

In the context of reactive programming, Clojure developers often use libraries like core.async, which is inspired by Go's CSP (Communicating Sequential Processes). core.async allows you to write asynchronous, non-blocking code using channels, which can be used for handling networking tasks where timing and concurrency are critical. Channels provide a way to pass messages between different parts of an application, making them useful for orchestrating network events.

Lastly, monitoring and debugging are vital aspects of networking. Clojure developers can use tools like clj-profiler and metrics-clojure to monitor network performance, memory usage, and latency. These tools help ensure that networked applications remain performant and scalable, especially under high loads.

In summary, networking in Clojure builds upon the robust Java networking capabilities, augmented by Clojure's functional programming paradigm and its vibrant ecosystem of third-party libraries. Whether you're dealing with simple HTTP requests, building scalable, asynchronous servers, or working with advanced messaging protocols like WebSockets or MQTT, Clojure provides the necessary tools and libraries to meet these demands. Key libraries like clj-http, aleph, Ring, and http-kit play essential roles in enabling modern networked applications. Additionally, adherence to standards like RFC 2616 for HTTP and RFC 6455 for WebSockets ensures that your applications can interoperate effectively with other systems and services. Networking in Clojure is not only about functionality but also about leveraging these standards to create secure, efficient, and scalable applications.

Another foundational concept in Clojure networking is integration with modern cloud architectures and distributed systems. As cloud computing and microservices architectures grow in popularity, the ability to efficiently handle network communication between distributed components is critical. Libraries such as Sente enable Clojure developers to implement real-time bidirectional communication between web clients and servers. Sente leverages both WebSockets (defined by RFC 6455) and fallback mechanisms like long polling to ensure reliable communication, making it a suitable choice for building interactive web applications or dashboards.

Clojure developers working on microservices often integrate with message brokers like RabbitMQ or Kafka. These message brokers allow different services to communicate asynchronously through message queues or topics, decoupling components and improving scalability. Libraries such as langohr provide a Clojure interface to RabbitMQ, allowing for the use of the AMQP protocol (defined by RFC 9140), while libraries like jackdaw offer an idiomatic way to interact with Kafka, which is essential for event-driven architectures.

The trend toward RESTful API design has also influenced networking in Clojure. REST is an architectural style that relies on HTTP (as defined in RFC 2616 and RFC 7540) and is widely used for designing networked systems. In Clojure, frameworks like yada take a resource-oriented approach to building REST APIs. yada automatically handles content negotiation, security, and validation based on the RFCs governing HTTP, making it an excellent tool for quickly developing standards-compliant APIs.

GraphQL is another emerging technology in networking, providing a more flexible alternative to REST. Libraries like lacinia allow Clojure developers to implement GraphQL APIs, offering fine-grained control over data retrieval from networked resources. GraphQL, while not defined by an RFC, is becoming increasingly popular for enabling clients to specify exactly the data they need, reducing over-fetching and under-fetching problems typically encountered with REST.

For networking in the context of the Internet of Things (IoT), Clojure developers may utilize protocols like CoAP (Constrained Application Protocol), which is defined by RFC 7252. CoAP is designed for low-power devices and resource-constrained environments, making it suitable for IoT applications. Libraries such as clj-coap enable Clojure developers to work with CoAP-based devices, allowing for efficient communication in distributed sensor networks and home automation systems.

Another interesting aspect of Clojure networking is peer-to-peer communication. While many applications rely on client-server architectures, there is growing interest in decentralized networks, where peers communicate directly. Libraries like clj-bittorrent enable Clojure developers to interact with the BitTorrent protocol, which is defined by multiple RFCs, including RFC 5050. This allows for the creation of peer-to-peer applications for file sharing, decentralized storage, and even live streaming.

When working with encrypted communication, Clojure can leverage libraries like ssl-utils to handle TLS/SSL encryption, which is crucial for securing data transmitted over the network. SSL/TLS protocols are defined by RFC 5246 and RFC 8446, which describe the mechanisms for establishing secure, encrypted communication channels. Using ssl-utils, Clojure developers can secure both client-side and server-side communications, ensuring data integrity and confidentiality.

In terms of monitoring and analyzing network traffic, the Java ecosystem provides tools like JNetPcap and tcpdump, which can be utilized in Clojure for packet capture and analysis. JNetPcap is a Java wrapper for libpcap, a widely used library for packet sniffing. By integrating these tools into Clojure, developers can capture and analyze network traffic, which is useful for debugging, performance monitoring, and identifying potential security threats.

For developers building applications that rely on real-time data streams, Clojure integrates well with streaming frameworks such as Apache Kafka Streams. Libraries like jackdaw provide Clojure bindings to Kafka Streams, allowing for the processing of continuous streams of data in a distributed and fault-tolerant manner. This is particularly useful for applications like financial systems, real-time analytics, and distributed logging.

Clojure's approach to networking also includes support for DNS (Domain Name System) lookups, a critical part of resolving domain names to IP addresses. Using the java.net.InetAddress class, Clojure can perform DNS lookups, which are governed by standards like RFC 1034 and RFC 1035. This allows Clojure applications to resolve hostnames and manage network addresses dynamically.

In distributed computing, Clojure provides support for RPC (Remote Procedure Call) mechanisms, which are important for executing code across networked systems. Libraries like clojure-rpc enable remote method invocations over the network, following standards like RFC 5531 for ONC-RPC. This is especially useful for Clojure applications that need to perform computations on remote machines or interact with external services in a transparent way.

Clojure's interop with Java also extends to SOAP-based web services, which are defined by multiple RFCs and specifications, including RFC 3902. While SOAP has largely been replaced by REST and GraphQL for most web services, some legacy systems still rely on SOAP. Libraries like clj-soap provide Clojure bindings for interacting with SOAP services, enabling developers to integrate with older enterprise systems.

In terms of testing and simulating network conditions, libraries like clj-http-fake are useful for Clojure developers. clj-http-fake allows developers to mock HTTP responses and simulate various network conditions, making it easier to test how an application handles different network scenarios, such as timeouts, errors, and slow connections.

Another critical area is working with databases over the network. Clojure supports a variety of database protocols, including those for PostgreSQL, MySQL, and MongoDB. Libraries like clojure.java.jdbc and next.jdbc provide interfaces for interacting with databases over the network. These libraries handle connection pooling, query execution, and data retrieval, ensuring efficient communication with networked databases.

In distributed systems, consensus algorithms like Raft and Paxos are often used to ensure consistency across nodes in a network. Clojure developers working on distributed databases or coordination services may use libraries like jepsen, which tests and validates distributed systems' behavior under network partitions, as described in RFC 3740 for Paxos.

Clojure also provides facilities for working with email protocols, such as SMTP, IMAP, and POP3. Using libraries like postal, developers can send and receive emails in their applications. These protocols are standardized by RFC 5321 for SMTP and RFC 3501 for IMAP, allowing Clojure applications to integrate with email systems for notifications, alerts, or communication services.

In the context of mobile and IoT networking, Clojure developers can leverage libraries like nrepl to create remote REPL (Read-Eval-Print Loop) sessions over the network. This allows developers to connect to and interact with remote devices or servers in real-time, providing a powerful tool for debugging and live development.

Clojure is also used in applications that rely on peer-to-peer technologies, such as blockchain networks. Libraries like ClojureChain enable Clojure developers to build applications on top of blockchain networks, leveraging the decentralized nature of the P2P communication model, which is governed by multiple RFCs.

Finally, for developers working with real-time audio and video streaming, Clojure integrates with libraries like clj-rtsp, which enables applications to stream media using the RTSP protocol, as defined by RFC 2326. This is useful for building media servers, surveillance systems, or video conferencing applications in Clojure.

In conclusion, Clojure offers a wide array of tools, libraries, and concepts for handling networking across various use cases. Whether you're dealing with real-time web applications, peer-to-peer networks, encrypted communications, or distributed systems, Clojure's flexibility and integration with the Java ecosystem make it a powerful choice. From foundational protocols like HTTP, TCP, and WebSockets to advanced messaging systems like Kafka and RabbitMQ, Clojure provides a robust set of libraries for building networked applications. Understanding how to leverage these tools and adhering to RFC standards is crucial for developing scalable, secure, and efficient networked applications.

In the realm of high-performance networking, one of the primary considerations for developers using Clojure is the ability to handle large volumes of traffic with minimal latency. This becomes particularly important in applications such as trading systems, where milliseconds matter, or in multiplayer gaming where real-time communication is critical. To address this need, Clojure can leverage the Java Netty framework, which is designed for building asynchronous, event-driven applications. By utilizing libraries like aleph, which is built on Netty, developers can build scalable, high-performance networking systems. The non-blocking I/O features of Netty are crucial in allowing servers to handle thousands of concurrent connections efficiently, aligning with the standards set by RFC 793 for TCP.

Clojure networking also includes support for UDP (User Datagram Protocol), which is defined in RFC 768. UDP is a connectionless protocol, making it faster but less reliable than TCP. In cases where speed is more important than guaranteed delivery, such as in video streaming or online gaming, UDP can be an ideal choice. Clojure libraries such as aleph allow developers to use UDP for these kinds of tasks, where low latency and high throughput are more important than error correction.

Another advanced concept in networking with Clojure is the use of gRPC, a high-performance, open-source RPC framework that enables efficient communication between services. gRPC uses Protocol Buffers (protobuf) for serializing structured data, providing a highly efficient format for communication. In Clojure, libraries like clojure-grpc offer support for integrating gRPC into your applications. This technology is particularly useful in microservice architectures, where multiple services need to communicate over the network, and the performance overhead of traditional HTTP-based REST APIs may be too high.

Security in networking is always a concern, and beyond TLS/SSL, Clojure developers often deal with public key infrastructures (PKI) and certificate management. Tools like BouncyCastle, a Java cryptography library, can be easily used within Clojure to handle encryption, decryption, and key management. BouncyCastle supports various encryption standards, including those defined by RFC 5280 for X.509 certificates. This allows Clojure developers to manage secure communications and user authentication across networked systems.

Clojure developers working with microservice architectures also frequently need to handle service discovery and load balancing. Systems like Consul or Eureka provide service discovery mechanisms, while Clojure libraries such as clj-service-discovery offer abstractions to interact with these systems. Service discovery is crucial in distributed networks, allowing services to automatically find and communicate with each other. This process relies on consistent networking standards, such as DNS protocols defined in RFC 1034 and RFC 1035, to map service names to IP addresses.

When dealing with real-time applications, Clojure developers might also work with Message Queues like ZeroMQ, which is a high-performance asynchronous messaging library. ZeroMQ is designed for distributed systems and offers different communication patterns, such as pub-sub, push-pull, and request-reply, all without requiring a dedicated message broker. Libraries like clj-zeromq provide Clojure bindings to ZeroMQ, enabling developers to build highly scalable, fault-tolerant distributed applications that communicate over the network using the ZeroMQ protocol, which is loosely based on multiple networking RFCs.

For applications that need to interoperate with legacy systems or systems written in other languages, Clojure developers often rely on SOAP-based web services, even though this technology has been largely replaced by REST in modern systems. Tools like ClojureSoap provide an interface for interacting with SOAP web services, which follow the WSDL specifications and are standardized by various RFCs like RFC 3902. While not as lightweight as REST or gRPC, SOAP is still prevalent in many enterprise environments, making it necessary for Clojure developers working in those domains.

For developers working on mobile or constrained devices, where lightweight networking protocols are required, Clojure can interact with the MQTT protocol, which is designed for low-bandwidth, high-latency environments such as the Internet of Things (IoT). MQTT is defined by RFC 6456 and is widely used in scenarios where devices need to send small amounts of data over unreliable networks. Libraries like clj-mqtt enable Clojure applications to publish and subscribe to MQTT topics, making it suitable for home automation systems, sensors, and other embedded systems.

Another important networking technology is SSH (Secure Shell), which is used for secure network communication, particularly in server administration and remote system access. SSH is governed by RFC 4251, which defines the protocols for establishing secure communication channels over an unsecured network. Clojure developers can utilize the clj-ssh library to automate tasks such as remote server configuration, file transfers, and executing commands over SSH connections.

The integration of cloud services into networked applications is also a key aspect of Clojure networking. AWS (Amazon Web Services) offers a range of services that require networking capabilities, such as S3 for object storage or EC2 for virtual servers. Clojure libraries like amazonica provide idiomatic access to the AWS API, enabling developers to interact with cloud resources over the network. This includes uploading and downloading files from S3 using HTTPS, which follows the standards outlined in RFC 2818.

For data-intensive applications, streaming data over the network efficiently is crucial. In this context, Clojure developers can use the Apache Flink framework for distributed stream processing. Libraries like flambo provide Clojure bindings to Flink, allowing developers to process large streams of data in real-time across a distributed network. Flink operates on the principles of streaming analytics, enabling developers to build applications that can handle millions of events per second, making it suitable for use cases like financial transaction processing or monitoring sensor data.

Clojure also offers capabilities for building P2P networks, where each node acts as both a client and a server. This decentralized model can be implemented using the libp2p protocol, which provides a modular network stack for peer-to-peer applications. Libraries like clj-libp2p enable Clojure developers to create decentralized applications, such as file-sharing systems or distributed storage networks, which do not rely on a central authority. This aligns with the standards defined in RFC 9153 for P2P networking.

When building networked applications, error handling is an essential consideration, especially when dealing with unreliable networks or remote services. Clojure provides powerful exception-handling mechanisms, and libraries like slingshot allow for more advanced error handling, such as retrying failed network requests or managing timeouts. Ensuring that an application can gracefully handle network failures is critical, particularly in distributed systems where network partitions are common.

Another key area is integrating with social media and external APIs over the network. Clojure developers often need to interact with services like Twitter or Facebook using their respective REST APIs. Libraries like tentacles provide Clojure bindings to the GitHub API, allowing for networked interaction with code repositories, issue tracking, and collaboration tools, which follow HTTP protocols and various RFCs for OAuth authentication.

For applications that require communication between different environments or languages, Clojure can work with the Thrift protocol, developed by Apache. Thrift enables cross-language services development, supporting multiple programming languages and offering high-performance serialization for networked communication. Libraries like clj-thrift provide Clojure bindings to Thrift, making it possible to define services that communicate across diverse systems efficiently.

As we dive deeper into Clojure networking, we find that many distributed systems rely on consensus algorithms like Raft or Paxos to maintain consistency across networked nodes. Clojure libraries like raft-clj provide an implementation of the Raft consensus algorithm, which allows for distributed coordination and state replication across multiple machines in a network, adhering to the standards set by RFC 7054.

Another emerging trend is the integration of Clojure with containerized environments, such as those managed by Docker and Kubernetes. These platforms rely heavily on networking for managing containers, service discovery, and load balancing. Clojure libraries like clj-docker-client enable developers to interact with the Docker engine API over the network, automating tasks like container orchestration, which adheres to networking protocols and standards like RFC 793 for TCP.

Lastly, as Clojure developers build more sophisticated networked applications, tools for monitoring and observability become essential. Libraries like metrics-clojure allow for the collection of real-time metrics on network performance, such as throughput, latency, and error rates. This monitoring data can then be sent to tools like Prometheus over the network,

providing visibility into the health of networked systems and ensuring that performance meets the required service-level agreements (SLAs).

In conclusion, Clojure's networking capabilities continue to expand, offering developers the tools they need to build everything from simple HTTP clients to complex distributed systems. Whether you are working with peer-to-peer networks, high-performance messaging, or secure communication channels, Clojure provides a rich set of libraries and tools that adhere to modern networking standards like those set forth by various RFCs. As the landscape of distributed computing, real-time streaming, and cloud-native applications grows, Clojure remains well-positioned to help developers meet the challenges of modern networking tasks, with a focus on performance, scalability, and security.

In the modern networking landscape, real-time analytics plays a pivotal role, and Clojure integrates effectively with streaming platforms that are crucial for processing continuous streams of data. Clojure developers often turn to Apache Kafka, which provides distributed event streaming capabilities. Using libraries like jackdaw, which offer idiomatic bindings to Kafka, developers can handle real-time event-driven data processing. These systems are integral for applications like monitoring, log aggregation, and event sourcing, where reliable and low-latency communication across a network is critical.

For real-time collaborative applications, networking in Clojure also involves the use of protocols such as WebRTC, defined in RFC 8825. WebRTC enables peer-to-peer communication directly between browsers without needing an intermediary server, allowing for low-latency audio, video, and data transmission. Clojure libraries like cljs-webrtc enable developers to incorporate real-time collaboration features like video conferencing, file sharing, and live chat into web applications, building upon the standards defined by WebRTC.

One of the more advanced networking concepts that Clojure supports is load balancing and failover mechanisms. When building distributed systems, balancing network traffic across multiple servers is essential to ensure scalability and high availability. Clojure developers can utilize libraries like clj-loadbalancer to implement load balancing strategies such as round-robin, least connections, or consistent hashing. These strategies help distribute client requests evenly across a pool of servers, preventing any single server from becoming a bottleneck, and follow the conventions described in RFC 2391.

Clojure is also highly compatible with serverless computing, where networking plays a crucial role in invoking functions over the network in response to events. Services like AWS Lambda, Google Cloud Functions, and Azure Functions allow developers to build applications that scale automatically based on the volume of network traffic. With libraries like apex-clj and aws-lambda-clj, developers can write functions in Clojure that are deployed to serverless environments, invoking them over the network when triggered by an HTTP request, message queue, or cloud event.

In network-heavy applications such as content delivery networks (CDN), where large amounts of data must be served to users around the world, the need for efficient caching mechanisms is critical. Clojure developers can use libraries like clj-memcached and redis-clojure to interact with distributed caching systems like Memcached and Redis, both of which store frequently accessed data in memory to reduce latency. These systems use networking protocols defined in various RFCs, such as RFC 5901 for Memcached and RFC 5950 for Redis.

When it comes to developing applications that require message passing across distributed components, Clojure integrates seamlessly with ActiveMQ and other message brokers. Using libraries like clj-activemq, developers can send and receive messages asynchronously between different components of a distributed system. ActiveMQ follows the JMS (Java Message Service) specification, which is based on various RFC standards that define reliable message delivery over a network.

For container orchestration and managing complex networked applications, Clojure works well with systems like Kubernetes. Kubernetes provides a platform for automating the deployment, scaling, and operation of containerized applications, and it heavily relies on networking for service discovery, load balancing, and communication between containers. Clojure developers can use libraries like clj-kubernetes-client to interact with the Kubernetes API, allowing them to manage containerized network services programmatically.

Clojure also has strong support for building networked real-time data dashboards and monitoring systems. Using tools like Re-frame (for front-end development) and http-kit (for back-end HTTP communication), developers can create dynamic dashboards that receive real-time updates over the network, often via WebSockets or Server-Sent Events (SSE). These dashboards are useful for tracking live metrics, monitoring performance, or visualizing data streams, especially in cloud-based infrastructure monitoring.

Another important networking application is the transfer and synchronization of large files across distributed systems. Protocols like rsync, governed by RFC 5781, allow for efficient file synchronization over a network by only transferring the portions of a file that have changed. Clojure developers can integrate with tools like rsync using clojure.java.shell or other system-level libraries to automate the synchronization of files between servers or across cloud storage services.

As Clojure is frequently used in data science and machine learning applications, networking is also important for distributed computing tasks such as parameter server architectures or federated learning. Using libraries like clj-dl4j, which provides bindings to DeepLearning4j, developers can distribute machine learning workloads across multiple nodes in a cluster over the network, allowing for faster model training and inference by leveraging distributed computing resources.

For developers working with IoT systems, networking is critical for communicating with sensors and actuators deployed in the field. Protocols like Zigbee, Z-Wave, and LoRaWAN define how IoT devices communicate over low-power, wide-area networks. Clojure libraries like clj-zigbee enable developers to interact with Zigbee-based devices, while adhering to the standards set forth by RFC 3968 for low-power networking, ensuring interoperability between different IoT devices and platforms.

The importance of network virtualization has grown with the rise of software-defined networking (SDN) and network function virtualization (NFV). SDN decouples the control plane from the data plane, allowing for more flexible network management. Clojure can be used to interact with OpenFlow controllers in an SDN environment, and libraries like clj-openflow provide an interface for programming network devices through the OpenFlow protocol, as defined by RFC 7426.

In cloud-native applications, the use of service meshes such as Istio and Linkerd introduces additional networking layers that handle service discovery, routing, load balancing, and security between microservices. Clojure developers can configure and manage these service meshes using libraries like clj-istio-client, which interacts with the Istio API to manage traffic rules and apply security policies to microservices within a network.

Clojure networking also extends to the blockchain domain, where decentralized communication is essential. Using libraries like clojure-bitcoin, developers can interact with blockchain networks, sending transactions, querying the blockchain, or creating new blocks. Bitcoin's underlying networking protocol is defined in several RFC-like specifications, which dictate how peers communicate within the network, making it possible for Clojure developers to build applications that interact with distributed ledger systems.

In terms of mobile applications, ClojureScript (a variant of Clojure that compiles to JavaScript) is often used for building networked applications that run in a web browser. Using ClojureScript libraries like cljs-ajax, developers can easily handle HTTP requests and responses, interacting with back-end services over a network. This is particularly important for building mobile-friendly web applications that rely on network communication for retrieving data, submitting forms, or syncing user preferences.

When working with legacy networking protocols, Clojure's interop with Java makes it easy to access lower-level networking APIs that are not directly exposed in Clojure's standard library. For example, Telnet and FTP, while older protocols, are still used in some systems. Libraries like clj-telnet allow developers to interact with these protocols, which are defined by RFC 854 for Telnet and RFC 959 for FTP, enabling developers to automate tasks such as remote system access or file transfers in legacy systems.

Clojure is also suited for integrating with telecommunications networks, where protocols like SIP (Session Initiation Protocol) are used for voice over IP (VoIP) and video communication. SIP is defined by RFC 3261, and Clojure developers can use libraries like clj-sip to handle call initiation, routing, and termination in VoIP applications, enabling the creation of telecommunication services that communicate over IP networks.

For monitoring the health and performance of networked applications, Clojure developers can integrate with Prometheus and Grafana, which are popular monitoring and alerting tools. Libraries like clj-prometheus allow Clojure applications to expose network performance metrics such as latency, throughput, and error rates over HTTP, which can then be scraped by Prometheus and visualized in Grafana for real-time monitoring.

In conclusion, networking in Clojure covers a vast range of technologies and use cases, from real-time data streaming and peer-to-peer communication to integrating with cloud services, distributed systems, and container orchestration platforms. The language’s interoperability with Java provides Clojure developers with access to an extensive ecosystem of networking libraries and tools. By following standards such as those set by various RFCs, developers can ensure that their Clojure applications are compatible with modern networking protocols, scalable across distributed environments, and secure for handling sensitive data over the network.

Clojure networking is not limited to HTTP and RESTful communication but extends into domains such as distributed databases, where networking is integral for replicating data across nodes. Distributed databases like Cassandra and Couchbase use gossip protocols, as defined by RFC 5127, to manage data replication and consistency across networked clusters. Clojure developers can interact with these databases through libraries like clojurewerkz/cassaforte for Cassandra and clj-couchbase for Couchbase, ensuring efficient data replication over the network in large-scale systems.

In enterprise environments, Clojure developers often need to interface with LDAP (Lightweight Directory Access Protocol), which is used for directory-based services like user authentication, contact information management, and permission management. LDAP is defined by RFC 4511, and using libraries like clj-ldap, Clojure applications can authenticate users, retrieve directory entries, and manage access rights over the network. This is especially useful in corporate intranets or when integrating with legacy enterprise systems that rely on directory services.

When working with event-driven architectures, Clojure developers often rely on event processing frameworks like Apache Storm and Apache Pulsar. Libraries like clojure-storm provide an interface to Storm, which processes streams of events in a distributed manner, routing them across a network of workers. Storm is ideal for use cases like real-time analytics, fraud detection, or anomaly detection, where low-latency event processing over a network is crucial.

For developers building applications in the context of geospatial networking, Clojure has libraries like clj-geo and GeoServer integrations that allow for spatial data processing and geographical information system (GIS) support. These libraries enable querying, storing, and visualizing spatial data over a network. GeoServer itself communicates using protocols like WMS (Web Map Service), as defined by OGC standards, which allows for serving georeferenced map images over the network.

In financial services, where secure and reliable networking is a core requirement, Clojure developers might work with protocols like FIX (Financial Information eXchange), which is used for electronic trading and is defined by RFC 4183. Libraries like clj-fix allow Clojure applications to interact with trading platforms, sending and receiving messages over the network in real-time, ensuring that transactions are processed efficiently and securely across a financial network.

For peer-to-peer file sharing, Clojure can be integrated with the IPFS (InterPlanetary File System) protocol, which is a distributed, peer-to-peer network for storing and sharing data. Libraries like clj-ipfs allow developers to interact with the IPFS protocol, which is built on concepts similar to those described in RFC 792 for distributed file systems. IPFS enables decentralized storage, allowing data to be shared across a global network without relying on central servers.

For developers working in video streaming or multimedia applications, Clojure networking extends to the RTMP (Real-Time Messaging Protocol), commonly used for streaming audio, video, and data over the internet. Libraries like clj-rtmp provide an interface for interacting with the RTMP protocol, enabling Clojure developers to build live streaming applications, video conferencing tools, or media servers that handle high-bandwidth video traffic over the network.

Another area of networking in Clojure is related to IoT security. When deploying IoT devices over a network, ensuring secure communication between devices is critical, especially in distributed environments where devices communicate with servers or other devices. Protocols like DTLS (Datagram Transport Layer Security), defined by RFC 6347, can be implemented in Clojure using libraries like clj-dtls, ensuring encrypted communication between devices while using UDP as the underlying transport protocol.

For developers dealing with streaming and processing massive data sets, Clojure networking concepts also involve the use of distributed file systems like Hadoop's HDFS (Hadoop Distributed File System). Libraries like clj-hdfs allow developers to interface with HDFS over the network, enabling data-intensive applications to store and retrieve large volumes of data across distributed nodes. HDFS is critical for applications that rely on parallel processing and large-scale data analytics.

Clojure is also well-suited for building reactive applications that handle asynchronous data streams over the network. Libraries like manifold provide abstractions for handling asynchronous streams of data, allowing Clojure developers to build applications that react to network events, such as incoming WebSocket connections or HTTP requests. This is particularly useful for applications that require real-time feedback and responsiveness, such as stock market dashboards or live gaming platforms.

For developers working on DNS (Domain Name System) applications, Clojure provides easy access to DNS resolution and management libraries. Using java.net.InetAddress or libraries like dns-clj, Clojure applications can resolve domain names to IP addresses or manage custom DNS servers. This capability is crucial for applications that require dynamic hostname resolution or custom domain management, which relies on RFC 1034 and RFC 1035 standards.

In distributed machine learning environments, networking plays a key role in enabling distributed model training across a cluster of machines. Libraries like clojure-tensorflow enable Clojure applications to interface with machine learning frameworks like TensorFlow, allowing data and model parameters to be shared across the network during training. This distributed approach to machine learning improves both the performance and scalability of training large models on big data.

Clojure also excels in networked game development, where libraries like Arcadia enable the development of real-time multiplayer games that rely on network communication. Using protocols like UDP and WebSockets, Clojure developers can create multiplayer games that handle real-time player interaction, synchronization of game states, and live updates across a network of players.

For social networking applications, Clojure developers can integrate with platforms like Twitter and Facebook using their respective APIs. Libraries like tentacles for GitHub and twitter-api for Twitter allow Clojure applications to communicate with social media platforms over the network, enabling features such as posting updates, fetching user data, or interacting with followers in real-time.

Clojure developers working in VoIP (Voice over IP) systems can take advantage of SIP (Session Initiation Protocol) to establish and manage voice and video calls over IP networks. Libraries like clj-sip allow developers to initiate and terminate calls, manage call routing, and handle other SIP-related tasks. SIP is widely used in telecommunications and is governed by standards such as RFC 3261, making it essential for building networked communication systems.

For secure, encrypted networking, Clojure can interface with PKI (Public Key Infrastructure) systems using libraries like bouncycastle. PKI provides the foundation for secure communications over the network, enabling encryption, digital signatures, and certificate management as defined by RFC 5280 for X.509 certificates. Clojure applications can thus implement secure communication channels, ensuring data privacy and authentication.

Networking in Clojure also involves working with API rate limiting and throttling mechanisms, which are essential when building applications that interact with external services. Libraries like clj-throttle allow developers to limit the number of network requests sent to an external service, ensuring compliance with API rate limits imposed by services like GitHub or Twitter. This ensures that Clojure applications can communicate efficiently with external services while avoiding denial-of-service issues.

For time-sensitive applications, Clojure developers might work with NTP (Network Time Protocol) to synchronize time across networked systems. NTP is defined by RFC 5905 and is crucial for ensuring that all nodes in a distributed system have synchronized clocks, which is important for logging, event ordering, and security. Libraries like clj-ntp allow Clojure applications to communicate with NTP servers and maintain accurate timekeeping across a network.

For applications that require interaction with geographic information, Clojure developers can use OGC (Open Geospatial Consortium) standards like WFS (Web Feature Service) and WCS (Web Coverage Service) to serve and retrieve geospatial data over a network. Libraries like clj-ogc allow Clojure applications to integrate with geospatial services, providing tools for querying, processing, and visualizing spatial data in a distributed environment.

In conclusion, Clojure's networking capabilities extend across a vast range of technologies, protocols, and use cases. Whether you're building secure communication channels, working with real-time data, or developing distributed systems, Clojure provides a rich ecosystem of libraries and tools that integrate seamlessly with modern networking standards like those set forth by various RFCs. From geospatial applications to high-performance messaging and peer-to-peer networks, Clojure's versatility makes it an excellent choice for developing networked systems that are scalable, reliable, and secure.

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Clojure Programming Language, Clojure REPL, Clojure Leiningen, Clojure Compiler, Clojure JVM Interoperability, Clojure CIDER Integration, Clojure nREPL, Clojure Rich Hickey, Clojure EDN Format, Clojure Persistent Data Structures, Clojure Immutable Collections, Clojure Vars, Clojure Symbols, Clojure Keywords, Clojure Lists, Clojure Vectors, Clojure Maps, Clojure Sets, Clojure Namespaces, Clojure require Macro, Clojure use Macro, Clojure import Macro, Clojure refer Macro, Clojure alias Macro, Clojure ns Macro, Clojure def Form, Clojure defn Macro, Clojure let Macro, Clojure if Form, Clojure do Form, Clojure fn Form, Clojure defmacro Macro, Clojure defmulti Macro, Clojure defmethod Macro, Clojure defonce Macro, Clojure defrecord Macro, Clojure deftype Macro, Clojure defprotocol Macro, Clojure reify Macro, Clojure gen-class Macro, Clojure gen-interface Macro, Clojure proxy Macro, Clojure dot special form, Clojure quote special form, Clojure unquote macro, Clojure syntax-quote, Clojure var special form, Clojure loop Macro, Clojure recur Keyword, Clojure throw Keyword, Clojure try Keyword, Clojure catch Keyword, Clojure finally Keyword, Clojure monitor-enter, Clojure monitor-exit, Clojure binding Macro, Clojure alter-var-root, Clojure intern, Clojure resolve, Clojure find-var, Clojure set! Special Form, Clojure alter-meta!, Clojure merge-meta!, Clojure with-meta, Clojure meta Function, Clojure vary-meta, Clojure prn Function, Clojure println Function, Clojure print Function, Clojure pr Function, Clojure str Function, Clojure format Function, Clojure with-out-str Macro, Clojure read-string Function, Clojure slurp Function, Clojure spit Function, Clojure load-file Function, Clojure load-string Function, Clojure compile Function, Clojure eval Function, Clojure macroexpand, Clojure macroexpand-1, Clojure macroexpand-all, Clojure future Macro, Clojure promise Function, Clojure deliver Function, Clojure deref Function, Clojure @ Reader Macro, Clojure swap! Function, Clojure reset! Function, Clojure compare-and-set! Function, Clojure atom, Clojure ref, Clojure dosync Macro, Clojure commute Function, Clojure alter Function, Clojure ensure Function, Clojure agent, Clojure send Function, Clojure send-off Function, Clojure await Function, Clojure await-for Function, Clojure shutdown-agents Function, Clojure delay Function, Clojure force Function, Clojure lazy-seq Macro, Clojure memoize Function, Clojure trampoline Function, Clojure comp Function, Clojure partial Function, Clojure complement Function, Clojure constantly Function, Clojure identity Function, Clojure juxt Function, Clojure every-pred Function, Clojure some-fn Function, Clojure fnil Function, Clojure apply Function, Clojure map Function, Clojure reduce Function, Clojure filter Function, Clojure remove Function, Clojure keep Function, Clojure keep-indexed Function, Clojure mapcat Function, Clojure for Macro, Clojure doseq Macro, Clojure dorun Function, Clojure doall Function, Clojure run! Function, Clojure into Function, Clojure conj Function, Clojure assoc Function, Clojure dissoc Function, Clojure get Function, Clojure contains, Clojure keys Function, Clojure vals Function, Clojure select-keys Function, Clojure merge Function, Clojure merge-with Function, Clojure update Function, Clojure update-in Function, Clojure assoc-in Function, Clojure dissoc-in Function (not in core, but commonly known pattern), Clojure get-in Function, Clojure nth Function, Clojure first Function, Clojure second Function, Clojure last Function, Clojure rest Function, Clojure next Function, Clojure ffirst Function, Clojure nfirst Function, Clojure fnext Function, Clojure nnext Function, Clojure map-indexed Function, Clojure reduce-kv Function, Clojure group-by Function, Clojure frequencies Function, Clojure partition Function, Clojure partition-all Function, Clojure partition-by Function, Clojure split-at Function, Clojure split-with Function, Clojure take Function, Clojure drop Function, Clojure take-nth Function, Clojure take-while Function, Clojure drop-while Function, Clojure cycle Function, Clojure iterate Function, Clojure repeat Function, Clojure replicate Function, Clojure range Function, Clojure reverse Function, Clojure sort Function, Clojure sort-by Function, Clojure shuffle Function, Clojure distinct Function, Clojure interleave Function, Clojure interpose Function, Clojure flatten Function, Clojure seq Function, Clojure seq, Clojure coll, Clojure vector, Clojure map, Clojure set, Clojure list, Clojure empty Function, Clojure empty, Clojure not-empty Function, Clojure count Function, Clojure conj! Function, Clojure assoc! Function, Clojure dissoc! Function, Clojure pop Function, Clojure peek Function, Clojure hash Function, Clojure = Function, Clojure == Function, Clojure not= Function, Clojure identical, Clojure compare Function, Clojure max Function, Clojure min Function, Clojure + Function, Clojure - Function, Clojure * Function, Clojure / Function, Clojure inc Function, Clojure dec Function, Clojure pos, Clojure neg, Clojure zero, Clojure even, Clojure odd, Clojure mod Function, Clojure rem Function, Clojure quot Function, Clojure bit-and Function, Clojure bit-or Function, Clojure bit-xor Function, Clojure bit-not Function, Clojure bit-shift-left Function, Clojure bit-shift-right Function, Clojure bit-set Function, Clojure bit-clear Function, Clojure bit-flip Function, Clojure bit-test Function, Clojure bit-and-not Function, Clojure unchecked-add Function, Clojure unchecked-subtract Function, Clojure unchecked-multiply Function, Clojure unchecked-divide Function, Clojure unchecked-negate Function, Clojure unchecked-inc Function, Clojure unchecked-dec Function, Clojure ratio, Clojure rational, Clojure integer, Clojure floats, Clojure doubles, Clojure longs, Clojure bigint Function, Clojure bigdec Function, Clojure biginteger, Clojure ratio Function, Clojure numerator Function, Clojure denominator Function, Clojure double Function, Clojure float Function, Clojure long Function, Clojure int Function, Clojure short Function, Clojure byte Function, Clojure char Function, Clojure boolean Function, Clojure unchecked-long, Clojure unchecked-int, Clojure chars Function, Clojure seqable, Clojure indexed, Clojure reversible, Clojure associative, Clojure sequential, Clojure ratio, Clojure rational, Clojure float, Clojure double, Clojure inst, Clojure uuid, Clojure uri, Clojure bigint, Clojure var, Clojure fn, Clojure ifn, Clojure reduced, Clojure reduced Function, Clojure unreduced Function, Clojure ensure-reduced Function, Clojure volatile! Function, Clojure vswap! Function, Clojure vreset! Function, Clojure volatile, Clojure add-watch Function, Clojure remove-watch Function, Clojure watches Function, Clojure agent-error Function, Clojure restart-agent Function, Clojure set-agent-send-executor!, Clojure set-agent-send-off-executor!, Clojure await1 Function (old), Clojure realize (not in core, used in delays), Clojure bound-fn Macro, Clojure bound-fn*, Clojure pvalues Macro (core.async, Clojure pmap Function, Clojure pcalls Function, Clojure pfor Macro, Clojure bean Function, Clojure beval (not standard), Clojure clojure-version Function, Clojure version-string Function, Clojure *clojure-version* Var, Clojure *command-line-args* Var, Clojure *in* Var, Clojure *out* Var, Clojure *err* Var, Clojure *ns* Var, Clojure *warn-on-reflection* Var, Clojure *print-level* Var, Clojure *print-length* Var, Clojure *print-namespace-maps* Var, Clojure *print-meta* Var, Clojure *print-dup* Var, Clojure *compile-path* Var, Clojure *compile-files* Var, Clojure *compile-deps* Var, Clojure *unchecked-math* Var, Clojure *assert* Var, Clojure *1 Var, Clojure *2 Var, Clojure *3 Var, Clojure *e Var, Clojure *file* Var, Clojure *source-path* Var, Clojure *macro-meta* Var (deprecated, Clojure doc Function, Clojure find-doc Function, Clojure apropos Function, Clojure source Function, Clojure pst Function, Clojure stacktrace (in clojure.stacktrace), Clojure ns-publics Function, Clojure ns-interns Function, Clojure ns-imports Function, Clojure ns-resolve Function, Clojure ns-refers Function, Clojure all-ns Function, Clojure loaded-libs Function, Clojure libspecs in ns Macro, Clojure refer-clojure Macro, Clojure in-ns Macro, Clojure create-ns Function, Clojure remove-ns Function, Clojure map, Clojure vector, Clojure list, Clojure set, Clojure sorted, Clojure reduced returns reduced val, Clojure error handling ex-info, Clojure ex-info Function, Clojure ex-data Function, Clojure ex-message Function, Clojure ex-cause Function, Clojure Throwable, Clojure Exception, Clojure Error, Clojure Reader Conditionals, Clojure Tagged Literals, Clojure tagged-literal Function, Clojure default-data-readers Var, Clojure *data-readers* Var, Clojure print-dup Function, Clojure print-method Function, Clojure pprint (from clojure.pprint), Clojure cl-format (clojure.pprint), Clojure code-formatting (tools), Clojure edn/read-string, Clojure edn/write-string, Clojure transit (not core, but widely used), Clojure spec library (clojure.spec.alpha), Clojure s/def (spec), Clojure s/conform (spec), Clojure s/valid, Clojure s/explain (spec), Clojure s/explain-data (spec), Clojure s/gen (spec), Clojure s/keys (spec), Clojure s/or (spec), Clojure s/and (spec), Clojure s/cat (spec), Clojure s/alt (spec), Clojure s/fspec (spec), Clojure s/fdef (spec), Clojure s/assert (spec), Clojure s/instrument (spec), Clojure s/unstrument (spec), Clojure s/stest (spec test), Clojure clojure.test namespace, Clojure deftest Macro, Clojure testing Macro, Clojure is Macro (clojure.test), Clojure are Macro (clojure.test), Clojure run-tests Function, Clojure test-ns Function, Clojure test-all-vars Function, Clojure test-vars Function, Clojure assert-expr multimethod, Clojure clojure.walk namespace, Clojure walk Function, Clojure postwalk Function, Clojure prewalk Function, Clojure macroexpand-all from clojure.walk, Clojure clojure.set namespace, Clojure set/union Function, Clojure set/intersection Function, Clojure set/difference Function, Clojure set/select Function, Clojure set/project Function, Clojure set/join Function, Clojure set/subset, Clojure set/superset, Clojure clojure.string namespace, Clojure str/blank, Clojure str/trim Function, Clojure str/triml Function, Clojure str/trimr Function, Clojure str/split Function, Clojure str/join Function, Clojure str/replace Function, Clojure str/replace-first Function, Clojure str/upper-case Function, Clojure str/lower-case Function, Clojure str/capitalize Function, Clojure str/includes, Clojure str/index-of Function, Clojure str/last-index-of Function, Clojure str/starts-with, Clojure str/ends-with, Clojure str/escape Function, Clojure str/reverse Function, Clojure str/split-lines Function, Clojure str/re-quote-replacement Function, Clojure ClojureScript Integration, Clojure ClojureCLR Integration, Clojure core.async, Clojure async/go Macro (core.async), Clojure async/chan Function, Clojure async/put! Function, Clojure async/take! Function, Clojure async/close! Function, Clojure async/<! Macro, Clojure async/>! Macro, Clojure async/alt! Macro, Clojure async/alt!! Macro, Clojure async/go-loop Macro, Clojure async/pipeline Functions, Clojure async/pipeline-blocking Functions, Clojure async/timeout Function, Clojure core.logic (logic programming) (Not standard, but widely known in Clojure)], Clojure core.match Pattern Matching Library, Clojure match/match Macro, Clojure match/matchv Macro, Clojure match/let Macro (core.match), Clojure tools.deps.alpha for Dependency Management, Clojure deps.edn Configuration, Clojure Clojure CLI Tools, Clojure clj Command, Clojure clojure Command, Clojure clojure.main Namespace, Clojure -M Flag (CLI), Clojure -A Flag (CLI), Clojure -X Flag (CLI), Clojure -T Flag (CLI), Clojure tools.build, Clojure tools.namespace, Clojure tools.logging, Clojure tools.trace, Clojure tools.macro, Clojure tools.analyzer.jvm, Clojure spec.alpha, Clojure spec.gen.alpha, Clojure test.check Property Testing, Clojure transducers, Clojure eduction Function (transducers), Clojure xform variable for transducers, Clojure sequence function with xform, Clojure into with xform, Clojure transduce Function, Clojure reduce with transducer, Clojure map transducer, Clojure filter transducer, Clojure remove transducer, Clojure take transducer, Clojure take-while transducer, Clojure drop transducer, Clojure drop-while transducer, Clojure replace transducer, Clojure mapcat transducer, Clojure distinct transducer, Clojure partition-by transducer, Clojure partition-all transducer, Clojure flatten transducer (not built-in, Clojure stateful transducers with volatile, Clojure completion for transduce, Clojure reduced from transducer step, Clojure conj transducer step, Clojure into transducer pipeline, Clojure interpose transducer, Clojure dedupe transducer, Clojure keep transducer, Clojure keep-indexed transducer, Clojure random functions (rand), Clojure rand-int Function, Clojure rand-nth Function, Clojure shuffle Function repeated, Clojure *default-data-reader-fn* Var, Clojure tagged-literal for custom tags, inst, uuid, "(pattern)", 'symbol, Clojure quoting 'symbol, Clojure unquote ~symbol, Clojure splicing-unquote ~@symbol, Clojure syntax quote `symbol, Clojure gensym Function, Clojure name Function (on keywords/symbols), Clojure namespace Function (for symbols), Clojure keyword Function, Clojure symbol Function, Clojure slurp and spit for I/O, Clojure *read-eval* Var, Clojure binding for dynamic vars, Clojure alter-var-root for changing top-level var, Clojure var-set function (not core, use set!), Clojure thread macros ->, Clojure ->> Thread Macro, Clojure as-> Macro, Clojure some-> Macro, Clojure some->> Macro, Clojure cond-> Macro, Clojure cond->> Macro, Clojure doto Macro, Clojure memfn Macro, Clojure locking Macro, Clojure with-open Macro, Clojure with-local-vars Macro, Clojure var-get Function, Clojure var-set Macro (no direct, set! used), Clojure ns-map Function, Clojure ns-name Function, Clojure ns-aliases Function, Clojure ns-unmap Function, Clojure ns-unalias Function, Clojure test successful, Clojure test summary (Clojure.test result), Clojure test use-fixtures, Clojure test join-fixtures, Clojure test composed-fixtures, Clojure test deftest macro repeated, Clojure test are macro repeated, Clojure test use-fixtures macro, Clojure *clojure-version* map with version keys, Clojure Stacktraces printing with *e var, Clojure loading code with load and require, Clojure clojure.core ServerSocket (not standard use java interop), Clojure reflection with reflect (clojure.reflect), Clojure *warn-on-reflection* to avoid reflection, Clojure printed representation of objects, Clojure definline Macro (deprecated, Clojure definterface Macro, Clojure memfn macro for method calls, Clojure re-find Function (clojure.string/regex), Clojure re-seq Function, Clojure re-matches Function, Clojure load and load-file difference, Clojure require and use difference, Clojure refer-clojure to manage clojure.core symbols, Clojure positional destructuring, Clojure map destructuring, Clojure seq destructuring, keys destructuring, strs destructuring, syms destructuring, or destructuring key, as destructuring key, Clojure & rest param in fn, Clojure &env in macros, Clojure &form in macros, Clojure gensym for unique symbols in macros, Clojure macro hygiene via syntax-quote, Clojure macro generating macros, Clojure tools.namespace for reloading, Clojure tools.logging for logging macros, Clojure *print-fn* Var, Clojure *print-fn-bodies* Var (not standard), Clojure clojure.main main function, Clojure with-precision macro (bigdec), Clojure rationalize Function, Clojure numerator/denominator again repeated, if, do, let, quote, var, recur, fn*, loop*, monitor-enter, monitor-exit, throw, try, catch, finally, new, set!, deftype*, defrecord*, . (dot), Clojure chunked sequences, Clojure chunk-first Function, Clojure chunk-rest Function, Clojure chunk-next Function, Clojure chunk-buffer Function, Clojure chunk-append Function, Clojure chunk-cons Function, Clojure chunk Function, Clojure enchunk (not standard), Clojure line-seq Function, Clojure file-seq Function, Clojure resource Function, (), Clojure reader Macro % symbol in anonymous fn, ' for var quote, 'functionName, inst, uuid for UUID, js for CLJS JavaScript literals (ClojureScript), Clojure reagent (not core, but widely used in CLJS), Clojure pedestal (not in core, widely used web), Clojure ring (HTTP library), Clojure compojure (routing), Clojure clj-http (HTTP client), Clojure core.async go macro again, Clojure tools.cli, Clojure tools.deps API, Clojure tools.build build-clj, Clojure babashka Integration, Clojure SCI interpreter, Clojure HoneySQL (SQL gen), Clojure clojure.java.io namespace, Clojure io/reader Function, Clojure io/writer Function, Clojure io/input-stream Function, Clojure io/output-stream Function, Clojure io/copy Function, Clojure io/file Function, Clojure io/resource Function, Clojure line-seq over io/reader, Clojure with-open over io resources, Clojure bean for Java interop, Clojure doto macro repeated, Clojure memfn macro repeated, Clojure future-call Function, Clojure future-cancel Function, Clojure future-cancelled, Clojure future-done, Clojure future, Clojure clojure.java.shell/sh Function, Clojure *unchecked-math* true in ns, Clojure clj-kondo linting, Clojure Eastwood linter, Clojure *print-dup* var, Clojure *print-meta* var, Clojure *print-length* var, Clojure *print-level* var, Clojure printer control vars, Clojure print-str Function, Clojure pr-str Function, Clojure print-err], [[Clojure print-fn custom setting, Clojure add-classpath (deprecated), Clojure RT class (java interop), Clojure Compiler class (java interop), Clojure IFn interface (java interop), Clojure ISeq interface, Clojure IPersistentMap interface, Clojure IPersistentVector interface, Clojure IPersistentSet interface, Clojure IPersistentList interface, Clojure ILookup interface, Clojure IKeywordLookup interface, Clojure ITransientCollection interface, Clojure ITransientMap interface, Clojure ITransientVector interface, Clojure IEditableCollection interface, Clojure IChunk interface, Clojure IChunkedSeq interface, Clojure IChunkedNext interface, Clojure IDeref interface, Clojure IAtom interface, Clojure IRef interface, Clojure IVar interface, Clojure IBlockingDeref interface, Clojure IMeta interface, Clojure IObj interface, Clojure java interop (.method obj) syntax, Clojure doto macro repeated to show interop usage, Clojure .. macro (threading java calls), Clojure memfn macro repeated for method calls, Clojure bean function repeated for bean properties, Clojure Class/forName call java interop, Clojure setAccessor (not core), Clojure getAccessor (not core), Clojure var-get var-set repeated concept, Clojure gen-interface repeated concept, Clojure gen-class multiple options, Clojure reify inline implementation, Clojure deftype fields definition, Clojure defrecord fields definition, Clojure definterface no body, Clojure protocol method dispatch, Clojure SExpression style code, Clojure Lisp Dialect identity, Clojure structural editing (paredit), Clojure cider-nrepl middleware, Clojure piggieback for CLJS REPL, Clojure adzerk/boot-reload (not standard), Clojure tools.logging macros info,debug,warn,error,fatal, Clojure Timbre logging (3rd party), Clojure Cheshire JSON library, Clojure clj-time (deprecated in favor of java-time), Clojure java-time library, inst again, Clojure re-matcher Function, Clojure re-groups Function, Clojure symbol, Clojure number, Clojure fn, Clojure seqable, Clojure associative, Clojure counted, Clojure indexed, Clojure reducible, Clojure coll, Clojure empty, Clojure juxt function repeated, Clojure partial function repeated, Clojure comp function repeated, Clojure complement function repeated, Clojure constantly function repeated, Clojure identity function repeated, Clojure memoize repeated, Clojure repeatedly function, Clojure repeatedly with function arg, Clojure iterate function repeated, Clojure re-seq function repeated, Clojure re-find repeated, if, do, let*, quote, var, fn*, loop*, recur, throw, try, catch, finally, set!, new, monitor-enter, monitor-exit, deftype*, defrecord*, . (dot) again, Clojure *fn-loader* var maybe internal, Clojure *compile-files* var repeated, Clojure *compile-path* var repeated, Clojure *command-line-args* repeated, Clojure *macroexpand-vars* no standard, Clojure load-libs function, Clojure *ns* repeated, Clojure *file* repeated, Clojure *warn-on-reflection* repeated, Clojure *print-namespace-maps* repeated, Clojure -main function convention in ns, Clojure with-redefs Macro, Clojure assert function macro (core), Clojure cond Macro, Clojure condp Macro, Clojure case Macro, Clojure while loop (no direct, use loop/recur), Clojure doseq Macro repeated, Clojure dotimes Macro, Clojure when Macro, Clojure when-not Macro, Clojure when-let Macro, Clojure when-first Macro, Clojure when-some Macro, Clojure if-let Macro, Clojure if-not Macro, Clojure if-some Macro, Clojure cond-> Macro, Clojure cond->> Macro repeated, Clojure some-> Macro repeated, Clojure some->> Macro repeated, Clojure as-> Macro repeated, Clojure letfn Macro, Clojure delay and force repeated, Clojure promise, deliver repeated, Clojure future-calls repeated, complement repeated, Clojure biginteger from BigInt (coercion), Clojure deftype inline fields initialization, Clojure defrecord inline fields initialization, Clojure extend-protocol Macro, Clojure extend-type Macro, Clojure satisfies, Clojure supers function (class hierarchy), Clojure bases function (class hierarchy), Clojure ancestors function, Clojure descendants function, Clojure parents function, Clojure isa, Clojure derive Function, Clojure underive Function, Clojure prefer-method Function, Clojure methods Function on multi, Clojure remove-method Function, Clojure remove-all-methods Function, Clojure default-dispatch-val, Clojure alter-var-root repeated, Clojure set-validator! Function, Clojure get-validator Function, Clojure *1,*2,*3,*e repl vals repeated, Clojure break (no direct break, use loop/recur or exception), Clojure continue (no direct continue), Clojure Clojars Repository (used widely in clojure community), Clojure Gitlibs in tools.deps, Clojure XForms library (transducer utils), Clojure spec instrumentation, Clojure spec explain-data repeated, Clojure coercion from string to int (Integer/parseInt), Clojure to-array function, Clojure to-array-2d function, Clojure int-array function, Clojure long-array function, Clojure double-array function, Clojure char-array function, Clojure byte-array function, Clojure object-array function, Clojure alength function, Clojure aget function, Clojure aset function, Clojure aset-int function, Clojure aset-long function, Clojure aset-double function, Clojure aset-float function, Clojure aset-char function, Clojure aset-short function, Clojure aset-byte function, Clojure aset-boolean function, Clojure subvec function, Clojure vec function, Clojure vector function, Clojure vector-of function, Clojure persistent! function, Clojure transient function, Clojure conj! function repeated for transients, Clojure pop! function for transients, Clojure disj! function for transients, Clojure assoc! function repeated for transients, Clojure dissoc! repeated for transients, Clojure select-keys repeated, Clojure merge repeated, Clojure zipmap function, Clojure keys repeated, Clojure vals repeated, Clojure rseq function, Clojure subseq function (for sorted collections), Clojure rsubseq function, Clojure sorted-set function, Clojure sorted-set-by function, Clojure sorted-map function, Clojure sorted-map-by function, Clojure compare function repeated, Clojure comp comparator example, Clojure conj on map returns map with added kv pair, Clojure disj function removes element from set, Clojure boolean function (coerce to boolean), Clojure rationalize repeated, Clojure test.check (property testing library), Clojure orchard (cider), Clojure clj-reflector, Clojure Fipp pretty printer, inst repeated, =(...) read-eval (disabled by default), Clojure *read-eval* false recommended, Clojure *compile-path* repeated, Clojure compilation via AOT, Clojure *data-readers* map, Clojure default-data-readers (var) repeated, myapp/foo custom, Clojure xml parsing clojure.xml, Clojure xml/parse function, Clojure xml/emit function, Clojure bean repeated, Clojure doto repeated, Clojure locking repeated, Clojure memoize repeated, Clojure future repeated, Clojure promise repeated, Clojure delay repeated, Clojure with-in-str macro, Clojure with-out-str repeated, Clojure with-err-str macro, Clojure with-open repeated, Clojure time (no built-in, use java-time), Clojure System/getProperty (java interop), Clojure System/getenv (java interop), Clojure Double/NaN (java interop), Clojure Double/POSITIVE_INFINITY, Clojure Double/NEGATIVE_INFINITY, Clojure (set! *warn-on-reflection* true), Clojure (set! *print-length* 50), Clojure (set! *print-level* 3), Clojure binding to dynamic vars repeated, Clojure special form docstrings, Clojure *assert* var repeated, Clojure with-bindings macro (not in core, with-bindings*, Clojure (Thread.) creation via interop, Clojure future-call function, Clojure delay, Clojure realized, Clojure custom macro expansions, Clojure clojure.core server REPL (not standard), Clojure key function (used in sort-by), Clojure val function (used in sort-by), Clojure compare fn for sorting, Clojure doc-string in defn, Clojure metadata on vars, dynamic metadata, private metadata, const metadata, _ reader macro for comment, Clojure comment macro, Clojure *clojure-load-path* var (not standard), Clojure clojure.repl namespace, Clojure clojure.java.io namespace repeated, Clojure clojure.java.jdbc (3rd party), Clojure compojure routes (3rd party), Clojure ring adapter jetty (3rd party), Clojure cider jack-in command, Clojure shadow-cljs (ClojureScript build), Clojure figwheel-main (ClojureScript dev), Clojure reagent atoms (CLJS), Clojure re-frame (CLJS FRP), Clojure tools.trace trace macro, Clojure spec instrument fdef, Clojure spec test/check, Clojure code runner clj, Clojure mapv function, Clojure filterv function, Clojure reduce-kv repeated, Clojure into-array function, Clojure vec repeated, Clojure subvec repeated, Clojure pop on vector, Clojure peek on vector, Clojure conj on vector appends, Clojure conj on list prepends, Clojure transient performance, Clojure persistent! to finalize, Clojure Java array interop, Clojure run! function repeated, Clojure dedupe function, Clojure random-sample function, Clojure eduction for transducer pipeline, Clojure sequence function for transducers, Clojure transducer xf param, Clojure ephemeral performance var *warn-on-reflection*, Clojure (doc *ns*) usage, Clojure (source println) usage, Clojure clojure.instant read-instant-date, Clojure clojure.instant read-instant-timestamp, Clojure clojure.instant read-instant-calendar, Clojure override data readers, =(eval ...) disabled, Clojure future-cancelled, Clojure *compile-files* repeated, Clojure apply-to function (internal), Clojure seq, int etc., Clojure booleans as true/false, Clojure ratio from (/ 1 2), Clojure MVars (java interop), Clojure add-classpath (deprecated) repeated, Clojure resolved artifact with tools.deps, Clojure doping a stable item - no meaning discard, Clojure conj on map vector key pair, Clojure signature of defn [name doc-string, Clojure ^type hints, Clojure unchecked arithmetic repeated, Clojure reflect on classes, Clojure *assert* true/false, Clojure alter-var-root to change a var, Clojure dynamic vars *ns* etc., inst "2012-09-10T12:00", uuid "f81d4fae-7dec-11d0-a765-00a0c91e6bf6", _commentedOutCode, Clojure with-precision macro big decimals

Clojure: Effective Clojure, Clojure Best Practices, Clojure Fundamentals, Clojure Inventor - Clojure Language Designer: Rich Hickey in October 2007; ClojureScript, Maven-Gradle, JVM, Clojure on JVM, Clojure keywords, Clojure data structures - Clojure algorithms, Clojure syntax, Clojure OOP, Clojure installation (Leiningen, choco install lein, sdk install leiningen), Clojure containerization, Clojure configuration, Clojure compiler, Clojure IDEs - Clojure editors - JetBrains Clojure REPL Plugin, Clojure development tools, Clojure DevOps - Clojure SRE, Clojure data science - Clojure DataOps, Clojure machine learning, Clojure deep learning, Functional Clojure, Clojure concurrency, Clojure history, Clojure bibliography, Manning Clojure Series, Clojure Glossary - Glossaire de Clojure - French, Clojure topics, Clojure courses, Clojure Standard Library, Clojure libraries, Clojure frameworks, Clojure research, Clojure GitHub, Written in Clojure, Clojure popularity, Clojure Awesome list, Clojure Versions. (navbar_clojure - see also navbar_clojure_networking, navbar_clojure_standard_library, navbar_clojure_libraries, navbar_clojure_reserved_words, navbar_clojure_functional, navbar_clojure_concurrency)