resource_tracker
resource_tracker
#
Resource Tracker package for monitoring system resources and detecting cloud environments.
Modules:
Name | Description |
---|---|
cloud_info |
Detect cloud environment (provider, region, instance type) via VM metadata services. |
server_info |
Detect server hardware (CPU count, memory amount, disk space, GPU count and VRAM amount) via |
tiny_data_frame |
A very inefficient data-frame implementation for manipulating resource usage data. |
tracker |
Track resource usage of a process or server. |
Classes:
Name | Description |
---|---|
TinyDataFrame |
A very inefficient data-frame implementation with a few features. |
PidTracker |
Track resource usage of a process and optionally its children. |
SystemTracker |
Track system-wide resource usage. |
Functions:
Name | Description |
---|---|
get_cloud_info |
Detect cloud environment and return standardized information on provider, region, and instance type. |
get_server_info |
Collects important information about the Linux server. |
get_cloud_info
cached
#
Detect cloud environment and return standardized information on provider, region, and instance type.
Returns:
Type | Description |
---|---|
dict
|
A dictionary containing standardized cloud information:
|
Source code in resource_tracker/cloud_info.py
get_server_info
#
Collects important information about the Linux server.
Returns:
Type | Description |
---|---|
dict
|
A dictionary containing server information:
|
Source code in resource_tracker/server_info.py
TinyDataFrame
#
A very inefficient data-frame implementation with a few features.
Supported features:
- reading CSV files from a remote URL
- reading CSV files from a local file
- converting a dictionary of lists/arrays to a data-frame
- converting a list of dictionaries to a data-frame
- slicing rows
- slicing columns
- slicing rows and columns
- printing a summary of the data-frame
- printing the data-frame as a human-readable (grid) table
- renaming columns
- writing to a CSV file
Parameters:
Name | Type | Description | Default |
---|---|---|---|
data
|
Optional[dict | list]
|
Dictionary of lists/arrays or list of dictionaries. |
None
|
csv_file_path
|
Optional[str]
|
Path to a properly quoted CSV file. |
None
|
Example:
>>> df = TinyDataFrame(csv_file_path="https://raw.githubusercontent.com/plotly/datasets/refs/heads/master/mtcars.csv")
>>> df
TinyDataFrame with 32 rows and 12 columns. First row as a dict: {'manufacturer': 'Mazda RX4', 'mpg': 21.0, 'cyl': 6.0, 'disp': 160.0, 'hp': 110.0, 'drat': 3.9, 'wt': 2.62, 'qsec': 16.46, 'vs': 0.0, 'am': 1.0, 'gear': 4.0, 'carb': 4.0}
>>> df[2:5][['manufacturer', 'hp']]
TinyDataFrame with 3 rows and 2 columns. First row as a dict: {'manufacturer': 'Datsun 710', 'hp': 93.0}
>>> print(df[2:5][['manufacturer', 'hp']]) # doctest: +NORMALIZE_WHITESPACE
TinyDataFrame with 3 rows and 2 columns:
manufacturer | hp
------------------+------
Datsun 710 | 93.0
Hornet 4 Drive | 110.0
Hornet Sportabout | 175.0
>>> print(df[2:5][['manufacturer', 'hp']].to_csv()) # doctest: +NORMALIZE_WHITESPACE
"manufacturer","hp"
"Datsun 710",93.0
"Hornet 4 Drive",110.0
"Hornet Sportabout",175.0
Methods:
Name | Description |
---|---|
__init__ |
Initialize with either: |
__len__ |
Return the number of rows in the data-frame |
__getitem__ |
Get a single column or multiple columns or a row or a slice of rows. Can be chained. |
__setitem__ |
Set a column with the given key to the provided values. |
head |
Return first n rows as a new TinyDataFrame. |
tail |
Return last n rows as a new TinyDataFrame. |
__repr__ |
Return a string representation of the data-frame. |
__str__ |
Print the first 10 rows of the data-frame in a human-readable table. |
to_csv |
Write the data-frame to a CSV file or return as string if no path is provided. |
rename |
Rename one or multiple columns. |
Source code in resource_tracker/tiny_data_frame.py
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|
__init__
#
Initialize with either:
- Dictionary of lists/arrays
- List of dictionaries
- CSV file path
Source code in resource_tracker/tiny_data_frame.py
__len__
#
__getitem__
#
Get a single column or multiple columns or a row or a slice of rows. Can be chained.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
key
|
Union[str, list[str], int, slice]
|
A single column name, a list of column names, a row index, or a slice of row indexes. |
required |
Returns:
Type | Description |
---|---|
Union[list, dict, TinyDataFrame]
|
A single column as a list, a list of columns as a new TinyDataFrame, a row as a dictionary, or a slice of rows as a new TinyDataFrame. |
Source code in resource_tracker/tiny_data_frame.py
__setitem__
#
Set a column with the given key to the provided values.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
key
|
str
|
Column name (string) |
required |
value
|
list
|
List of values for the column |
required |
Raises:
Type | Description |
---|---|
TypeError
|
If key is not a string |
ValueError
|
If the length of values doesn't match the dataframe length |
Source code in resource_tracker/tiny_data_frame.py
head
#
tail
#
__repr__
#
Return a string representation of the data-frame.
__str__
#
Print the first 10 rows of the data-frame in a human-readable table.
Source code in resource_tracker/tiny_data_frame.py
to_csv
#
Write the data-frame to a CSV file or return as string if no path is provided.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
csv_file_path
|
Optional[str]
|
Path to write CSV file. If None, returns CSV as string. |
None
|
quote_strings
|
bool
|
Whether to quote strings. |
True
|
Source code in resource_tracker/tiny_data_frame.py
rename
#
Rename one or multiple columns.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
columns
|
dict
|
Dictionary mapping old column names to new column names. |
required |
Returns:
Type | Description |
---|---|
TinyDataFrame
|
Self for method chaining. |
Raises:
Type | Description |
---|---|
KeyError
|
If any old column name doesn't exist in the dataframe. |
Source code in resource_tracker/tiny_data_frame.py
PidTracker
#
Track resource usage of a process and optionally its children.
This class monitors system resources like CPU times and usage, memory usage, GPU and VRAM utilization, I/O operations for a given process ID and optionally its child processes.
Data is collected every interval
seconds and written to the stdout or
output_file
(if provided) as CSV. Currently, the following columns are
tracked:
- timestamp (float): The current timestamp.
- pid (int): The monitored process ID.
- children (int | None): The current number of child processes.
- utime (int): The total user+nice mode CPU time in clock ticks.
- stime (int): The total system mode CPU time in clock ticks.
- cpu_usage (float): The current CPU usage between 0 and number of CPUs.
- pss (int): The current PSS (Proportional Set Size) in kB.
- read_bytes (int): The total number of bytes read from disk.
- write_bytes (int): The total number of bytes written to disk.
- gpu_usage (float): The current GPU utilization between 0 and GPU count.
- gpu_vram (float): The current GPU memory used in MiB.
- gpu_utilized (int): The number of GPUs with utilization > 0.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pid
|
int
|
Process ID to track. Defaults to current process ID. |
getpid()
|
interval
|
float
|
Sampling interval in seconds. Defaults to 1. |
1
|
children
|
bool
|
Whether to track child processes. Defaults to True. |
True
|
autostart
|
bool
|
Whether to start tracking immediately. Defaults to True. |
True
|
output_file
|
str
|
File to write the output to. Defaults to None, print to stdout. |
None
|
Methods:
Name | Description |
---|---|
__call__ |
Dummy method to make this class callable. |
diff_stats |
Calculate stats since last call. |
start_tracking |
Start an infinite loop tracking resource usage of the process until it exits. |
Source code in resource_tracker/tracker.py
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|
__call__
#
diff_stats
#
Calculate stats since last call.
Source code in resource_tracker/tracker.py
start_tracking
#
Start an infinite loop tracking resource usage of the process until it exits.
A CSV line is written every interval
seconds.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
output_file
|
Optional[str]
|
File to write the output to. Defaults to None, printing to stdout. |
None
|
print_header
|
bool
|
Whether to print the header of the CSV. Defaults to True. |
True
|
Source code in resource_tracker/tracker.py
SystemTracker
#
Track system-wide resource usage.
This class monitors system resources like CPU times and usage, memory usage, GPU and VRAM utilization, disk I/O, and network traffic for the entire system.
Data is collected every interval
seconds and written to the stdout or
output_file
(if provided) as CSV. Currently, the following columns are
tracked:
- timestamp (float): The current timestamp.
- processes (int): The number of running processes.
- utime (int): The total user+nice mode CPU time in clock ticks.
- stime (int): The total system mode CPU time in clock ticks.
- cpu_usage (float): The current CPU usage between 0 and number of CPUs.
- memory_free (int): The amount of free memory in kB.
- memory_used (int): The amount of used memory in kB.
- memory_buffers (int): The amount of memory used for buffers in kB.
- memory_cached (int): The amount of memory used for caching in kB.
- memory_active_anon (int): The amount of memory used for anonymous pages in kB.
- memory_inactive_anon (int): The amount of memory used for inactive anonymous pages in kB.
- disk_read_bytes (int): The total number of bytes read from disk.
- disk_write_bytes (int): The total number of bytes written to disk.
- disk_space_total_gb (float): The total disk space in GB.
- disk_space_used_gb (float): The used disk space in GB.
- disk_space_free_gb (float): The free disk space in GB.
- net_recv_bytes (int): The total number of bytes received over network.
- net_sent_bytes (int): The total number of bytes sent over network.
- gpu_usage (float): The current GPU utilization between 0 and GPU count.
- gpu_vram (float): The current GPU memory used in MiB.
- gpu_utilized (int): The number of GPUs with utilization > 0.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
interval
|
float
|
Sampling interval in seconds. Defaults to 1. |
1
|
autostart
|
bool
|
Whether to start tracking immediately. Defaults to True. |
True
|
output_file
|
str
|
File to write the output to. Defaults to None, print to stdout. |
None
|
Methods:
Name | Description |
---|---|
__call__ |
Dummy method to make this class callable. |
diff_stats |
Calculate stats since last call. |
start_tracking |
Start an infinite loop tracking system resource usage. |
Source code in resource_tracker/tracker.py
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|
__call__
#
diff_stats
#
Calculate stats since last call.
Source code in resource_tracker/tracker.py
start_tracking
#
Start an infinite loop tracking system resource usage.
A CSV line is written every interval
seconds.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
output_file
|
Optional[str]
|
File to write the output to. Defaults to None, printing to stdout. |
None
|
print_header
|
bool
|
Whether to print the header of the CSV. Defaults to True. |
True
|