| Name | infi-logger JSON |
| Version |
0.0.7
JSON |
| download |
| home_page | |
| Summary | Logger package for infinity team |
| upload_time | 2023-12-19 12:28:29 |
| maintainer | |
| docs_url | None |
| author | Infinity Team |
| requires_python | |
| license | MIT |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
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|
# infinity-elastic-logs
This project is a Python logging library that integrates with Elasticsearch for centralized logging. It provides a simple and convenient way to send logs to Elasticsearch with different log levels.
## Installation
[The binary installation file](dist/infi_logger-1.0-py3-none-any.whl) attached to this repository should be taken,
Attach to the project where it will be used
and install with:
```bash
pip install path_to_this_project/dist/infi_logger-1.0-py3-none-any.whl
```
Alternatively, you can move in cmd to this project and just write in
```bash
pip install .
```
Replace path_to_this_project with the path where the file is located in your project.
## Usage
To use the logging library, follow these steps:
1. Import the `ElasticLogger` class:
```python
from infi_logger import ElasticLogger
```
2. Create an instance of the ElasticLogger class, providing a service name, host, cert_fingerprint, name and password:
```python
HOST = "${Ip:Port}"
CERT_FINGERPRINT = "${fingerprint}"
NAME = "${Username}"
PASSWORD = "${Password}"
INDEX = "${IndexName}" # Replace with the index you want to work with
# logger = ElasticLogger("my-service")
logger = ElasticLogger("elastic-service", HOST, CERT_FINGERPRINT, NAME, PASSWORD, INDEX)
```
Alternatively, you can create an instance of the ElasticLogger class that will not connect Elastic, providing a service name only:
```python
logger = ElasticLogger("my-service")
```
3. Use the different log levels to send logs:
```python
logger.debug("This is a debug log")
logger.info("This is an info log")
logger.warning("This is a warning log")
logger.error("This is an error log")
logger.critical("This is a critical log")
```
## Configuration
1. **Elasticsearch Connection**
The ElasticsearchConnection class handles the connection to Elasticsearch. Ensure that the environment variables mentioned above are correctly set before running the project. The connect_elasticsearch method establishes a connection to Elasticsearch using the provided credentials. If the connection fails, an exception will be raised.
2. **Log Format**
The logs sent to Elasticsearch have the following format:
```json
{
"timestamp": "<current_timestamp>",
"message": "<log_message>",
"level": "<log_level>",
"service": "<service_name>"
}
```
3. **Environment Variables**
You can set the location of log files in case Elastic failed/not connected by setting global environment of "LOG_FILE".
If not chosen, it will default to "logs/log.log" in your current directory
Raw data
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"description": "# infinity-elastic-logs\r\n\r\nThis project is a Python logging library that integrates with Elasticsearch for centralized logging. It provides a simple and convenient way to send logs to Elasticsearch with different log levels.\r\n\r\n## Installation\r\n\r\n [The binary installation file](dist/infi_logger-1.0-py3-none-any.whl) attached to this repository should be taken,\r\nAttach to the project where it will be used\r\nand install with:\r\n\r\n```bash\r\npip install path_to_this_project/dist/infi_logger-1.0-py3-none-any.whl\r\n```\r\n\r\nAlternatively, you can move in cmd to this project and just write in\r\n\r\n```bash\r\npip install .\r\n```\r\n\r\nReplace path_to_this_project with the path where the file is located in your project.\r\n\r\n## Usage\r\n\r\nTo use the logging library, follow these steps:\r\n\r\n1. Import the `ElasticLogger` class:\r\n\r\n ```python\r\n from infi_logger import ElasticLogger\r\n ```\r\n\r\n2. Create an instance of the ElasticLogger class, providing a service name, host, cert_fingerprint, name and password:\r\n \r\n ```python\r\n HOST = \"${Ip:Port}\"\r\n CERT_FINGERPRINT = \"${fingerprint}\"\r\n NAME = \"${Username}\" \r\n PASSWORD = \"${Password}\"\r\n INDEX = \"${IndexName}\" # Replace with the index you want to work with\r\n\r\n # logger = ElasticLogger(\"my-service\")\r\n logger = ElasticLogger(\"elastic-service\", HOST, CERT_FINGERPRINT, NAME, PASSWORD, INDEX)\r\n\r\n ```\r\n Alternatively, you can create an instance of the ElasticLogger class that will not connect Elastic, providing a service name only:\r\n\r\n ```python\r\n logger = ElasticLogger(\"my-service\")\r\n ```\r\n \r\n\r\n3. Use the different log levels to send logs:\r\n\r\n ```python\r\n logger.debug(\"This is a debug log\")\r\n logger.info(\"This is an info log\")\r\n logger.warning(\"This is a warning log\")\r\n logger.error(\"This is an error log\")\r\n logger.critical(\"This is a critical log\")\r\n ```\r\n\r\n## Configuration\r\n\r\n\r\n1. **Elasticsearch Connection**\r\n\r\n The ElasticsearchConnection class handles the connection to Elasticsearch. Ensure that the environment variables mentioned above are correctly set before running the project. The connect_elasticsearch method establishes a connection to Elasticsearch using the provided credentials. If the connection fails, an exception will be raised.\r\n\r\n2. **Log Format**\r\n\r\n The logs sent to Elasticsearch have the following format:\r\n\r\n ```json\r\n {\r\n \"timestamp\": \"<current_timestamp>\",\r\n \"message\": \"<log_message>\",\r\n \"level\": \"<log_level>\",\r\n \"service\": \"<service_name>\"\r\n }\r\n ```\r\n\r\n3. **Environment Variables**\r\n\r\n You can set the location of log files in case Elastic failed/not connected by setting global environment of \"LOG_FILE\".\r\n If not chosen, it will default to \"logs/log.log\" in your current directory\r\n",
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