pymseed - miniSEED for Python
The pymseed package supports reading and writing of miniSEED formatted data. Both miniSEED version 2 (defined in the SEED standard) and miniSEED version 3 are supported.
The package uses the C-language libmseed for most of the data format and manipulation work.
Installation
Install from PyPI:
pip install pymseed
Or from conda-forge:
conda install -c conda-forge pymseed
Example usage
See the full documentation for a tutorial and complete API reference. Working programs for a variety of use cases can be found in the examples directory of the repository.
Read a file and print details from each record. Each msr is only valid
during its own iteration, since the reader reuses it for the next record;
using it afterwards raises ValueError:
from pymseed import MS3Record, TimeFormat
input_file = "examples/example_data.mseed"
for msr in MS3Record.from_file(input_file):
# Print values directly
print(f' SourceID: {msr.sourceid}, record length {msr.reclen}')
print(f' Start Time: {msr.starttime_str(timeformat=TimeFormat.ISOMONTHDAY_SPACE_Z)}')
print(f' Samples: {msr.samplecnt}')
# Alternatively, use the library print function (print to console)
msr.print()
Read a file into a trace list and print the list:
from pymseed import MS3TraceList
traces = MS3TraceList.from_file("examples/example_data.mseed")
# Print the trace list using the library print function
traces.print(details=1, gaps=True)
# Alternatively, traverse the data structures and print each trace ID and segment
for traceid in traces:
print(traceid)
for segment in traceid:
print(' ', segment)
Simple example of writing multiple channels of data:
import math
from pymseed import MS3TraceList, timestr2nstime
# Generate sinusoid data, starting at 0, 45, and 90 degrees
data0 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(0, 500)))
data1 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(45, 500 + 45)))
data2 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(90, 500 + 90)))
traces = MS3TraceList()
output_file = "output.mseed"
sample_rate = 40.0
starttime = timestr2nstime("2024-01-01T15:13:55.123456789Z")
format_version = 2
max_record_length = 512
# Add generated data to the trace list
traces.add_data(sourceid="FDSN:XX_TEST__B_S_1",
data_samples=data0, sample_type='i',
sample_rate=sample_rate, starttime=starttime)
traces.add_data(sourceid="FDSN:XX_TEST__B_S_2",
data_samples=data1, sample_type='i',
sample_rate=sample_rate, starttime=starttime)
traces.add_data(sourceid="FDSN:XX_TEST__B_S_3",
data_samples=data2, sample_type='i',
sample_rate=sample_rate, starttime=starttime)
traces.to_file(output_file,
format_version=format_version,
max_record_length=max_record_length)
Converting between Source IDs and NSLC codes
miniSEED 3 and FDSN Source Identifiers
use a single string (for example FDSN:IU_COLA_00_B_H_Z) to identify a unique
time series channel. Classic SEED-style identifiers split the same information
into network, station, location, and channel (NSLC) codes. Source IDs are a
superset of SEED v2 codes: all SEED codes can be represented as Source IDs,
but not all Source IDs will fit into SEED codes.
The utility methods nslc2sourceid() and sourceid2nslc() support mapping
between these identifier systems:
from pymseed import nslc2sourceid, sourceid2nslc
# NSLC (four strings) → FDSN source ID
sid = nslc2sourceid("IU", "COLA", "00", "BHZ")
# 'FDSN:IU_COLA_00_B_H_Z'
# Blank location codes are represented as an empty string
sid2 = nslc2sourceid("XX", "TEST", "", "BHZ")
# 'FDSN:XX_TEST__B_H_Z'
# Source ID → (network, station, location, channel)
net, sta, loc, chan = sourceid2nslc("FDSN:IU_COLA_00_B_H_Z")
assert (net, sta, loc, chan) == ("IU", "COLA", "00", "BHZ")
# To accommodate practical identifier conversion `sourceid2nslc()` does not
# strictly require field lengths for SEED v2 conformance, instead converting
# fields to their most SEED-like form. For example single character
# Source ID fields of band, source and subsource are collapsed to a SEED
# channel (B_H_Z -> BHZ); but if the codes cannot form a SEED channel
# they are left in the "extended channel" form of Source IDs. Furthermore,
# larger-than-SEED network, station, and location codes are not truncated
# to fit SEED v2 fields. For example:
nslc = sourceid2nslc("FDSN:NETWORK_STATION_LOCATION_G_SR_1")
assert nslc == ('NETWORK', 'STATION', 'LOCATION', 'G_SR_1')
Invalid source IDs raise ValueError from sourceid2nslc(); invalid NSLC codes
raise ValueError from nslc2sourceid().
Threaded usage
The pymseed package is safe to use with threads as long as the threads
are not sharing data structures, e.g. a MS3TraceList.
The underlying libmseed library uses thread-local storage for logging, so each thread has its own message registry. This is set up automatically the first time a thread makes a pymseed call, so no per-thread initialization is required:
from concurrent.futures import ThreadPoolExecutor
from pymseed import MS3TraceList
def process_file(filename):
traces = MS3TraceList.from_file(filename)
# ... process traces ...
return len(traces)
# A list of files to process (example)
file_list = ["examples/example_data.mseed",
"examples/example_data.mseed"]
with ThreadPoolExecutor(max_workers=4) as executor:
results = executor.map(process_file, file_list)
Call configure_logging() explicitly only to change the log/error prefixes
or the maximum stored message count for the calling thread. A thread that
never calls it uses the settings from the most recent configure_logging()
call made anywhere in the process.
Contributing
Contributions are welcome. Please submit pull requests against the develop
branch. See development.md for details on setting up a
development environment and running tests.
Package design rationale
The package functionality and exposed API are designed to support the most
common use cases of reading and writing miniSEED data using libmseed.
The naming of functions, classes, arguments, etc. often follows the naming
used in the library in order to reference their fundamentals at the C level
if needed; even though this leaves some names distinctly non-Pythonic.
License
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Copyright (C) 2026 EarthScope Data Services
1 maintainer
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Transparency logRelease files / pymseed-1.0.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
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| Tags | CPython 3.10 Linux glibc 2.17+ ARM64 Linux glibc 2.28+ ARM64 |
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BLAKE2b-256 checksum How to use checksums |
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Transparency logRelease files / pymseed-1.0.0-cp310-cp310-macosx_11_0_arm64.whl
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| Size | 315.5 kB |
| Tags | CPython 3.10 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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Transparency logRelease files / pymseed-1.0.0-cp310-cp310-macosx_10_9_x86_64.whl
| Download URL | pymseed-1.0.0-cp310-cp310-macosx_10_9_x86_64.whl |
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| Size | 334.2 kB |
| Tags | CPython 3.10 macOS 10.9+ x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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