Files (CSV, JSON, Excel, Feather, Parquet)
This page contains the setup guide and reference information for the Files source connector.
Prerequisites
- URL to access the file
- Format
- Reader options
- Storage Providers
Setup guide
For Airbyte Cloud:
Setup through Airbyte Cloud will be exactly the same as the open-source setup, except for the fact that local files are disabled.
For Airbyte Open Source:
- Once the File Source is selected, you should define both the storage provider along its URL and format of the file.
- Depending on the provider choice and privacy of the data, you will have to configure more options.
Fields description
- For
Dataset Name
use the name of the final table to replicate this file into (should include letters, numbers dash and underscores only). - For
File Format
use the format of the file which should be replicated (Warning: some formats may be experimental, please refer to the docs). - For
Reader Options
use a string in JSON format. It depends on the chosen file format to provide additional options and tune its behavior. For example,{}
for empty options,{"sep": " "}
for set up separator to one space ' '. - For
URL
use the URL path to access the file which should be replicated. - For
Storage Provider
use the storage Provider or Location of the file(s) which should be replicated.- [Default] Public Web
User-Agent
set to active if you want to add User-Agent to requests
- GCS: Google Cloud Storage
Service Account JSON
In order to access private Buckets stored on Google Cloud, this connector would need a service account json credentials with the proper permissions as described here. Please generate the credentials.json file and copy/paste its content to this field (expecting JSON formats). If accessing publicly available data, this field is not necessary.
- S3: Amazon Web Services
AWS Access Key ID
In order to access private Buckets stored on AWS S3, this connector would need credentials with the proper permissions. If accessing publicly available data, this field is not necessary.AWS Secret Access Key
In order to access private Buckets stored on AWS S3, this connector would need credentials with the proper permissions. If accessing publicly available data, this field is not necessary.
- AzBlob: Azure Blob Storage
Storage Account
The globally unique name of the storage account that the desired blob sits within. See here for more details.SAS Token
To access Azure Blob Storage, this connector would need credentials with the proper permissions. One option is a SAS (Shared Access Signature) token. If accessing publicly available data, this field is not necessary.Shared Key
To access Azure Blob Storage, this connector would need credentials with the proper permissions. One option is a storage account shared key (aka account key or access key). If accessing publicly available data, this field is not necessary.
- SSH: Secure Shell
User
use username.Password
use password.Host
use a host.Port
use a port for your host.
- SCP: Secure copy protocol
User
use username.Password
use password.Host
use a host.Port
use a port for your host.
- SFTP: Secure File Transfer Protocol
User
use username.Password
use password.Host
use a host.Port
use a port for your host.
- Local Filesystem (limited)
Storage
WARNING: Note that the local storage URL available for reading must start with the local mount "/local/" at the moment until we implement more advanced docker mounting options.
- [Default] Public Web
Provider Specific Information
- In case of Google Drive, it is necesary to use the Download URL, the format for that is
https://drive.google.com/uc?export=download&id=[DRIVE_FILE_ID]
where[DRIVE_FILE_ID]
is the string found in the Share URL herehttps://drive.google.com/file/d/[DRIVE_FILE_ID]/view?usp=sharing
- In case of GCS, it is necessary to provide the content of the service account keyfile to access private buckets. See settings of BigQuery Destination
- In case of AWS S3, the pair of
aws_access_key_id
andaws_secret_access_key
is necessary to access private S3 buckets. - In case of AzBlob, it is necessary to provide the
storage_account
in which the blob you want to access resides. Eithersas_token
(info) orshared_key
(info) is necessary to access private blobs. - In case of a locally stored file on a Windows OS, it's necessary to change the values for
LOCAL_ROOT
,LOCAL_DOCKER_MOUNT
andHACK_LOCAL_ROOT_PARENT
in the.env
file to an existing absolute path on your machine (colons in the path need to be replaced with a double forward slash, //).LOCAL_ROOT
&LOCAL_DOCKER_MOUNT
should be the same value, andHACK_LOCAL_ROOT_PARENT
should be the parent directory of the other two.
Reader Options
The Reader in charge of loading the file format is currently based on Pandas IO Tools. It is possible to customize how to load the file into a Pandas DataFrame as part of this Source Connector. This is doable in the reader_options
that should be in JSON format and depends on the chosen file format. See pandas' documentation, depending on the format:
For example, if the format CSV
is selected, then options from the read_csv functions are available.
- It is therefore possible to customize the
delimiter
(orsep
) to in case of tab separated files. - Header line can be ignored with
header=0
and customized withnames
- Parse dates for in specified columns
- etc
We would therefore provide in the reader_options
the following json:
{ "sep" : "\t", "header" : 0, "names": ["column1", "column2"], "parse_dates": ["column2"]}
In case you select JSON
format, then options from the read_json reader are available.
For example, you can use the {"orient" : "records"}
to change how orientation of data is loaded (if data is [{column -> value}, … , {column -> value}]
)
If you need to read Excel Binary Workbook, please specify excel_binary
format in File Format
select.
:::warning
This connector does not support syncing unstructured data files such as raw text, audio, or videos.
:::
Supported sync modes
Feature | Supported? |
---|---|
Full Refresh Sync | Yes |
Incremental Sync | No |
Replicate Incremental Deletes | No |
Replicate Folders (multiple Files) | No |
Replicate Glob Patterns (multiple Files) | No |
:::info
This source produces a single table for the target file as it replicates only one file at a time for the moment. Note that you should provide the `dataset_name` which dictates how the table will be identified in the destination (since `URL` can be made of complex characters).
:::
File / Stream Compression
Compression | Supported? |
---|---|
Gzip | Yes |
Zip | No |
Bzip2 | No |
Lzma | No |
Xz | No |
Snappy | No |
Storage Providers
Storage Providers | Supported? |
---|---|
HTTPS | Yes |
Google Cloud Storage | Yes |
Amazon Web Services S3 | Yes |
SFTP | Yes |
SSH / SCP | Yes |
local filesystem | Local use only (inaccessible for Airbyte Cloud) |
File Formats
Format | Supported? |
---|---|
CSV | Yes |
JSON | Yes |
HTML | No |
XML | No |
Excel | Yes |
Excel Binary Workbook | Yes |
Feather | Yes |
Parquet | Yes |
Pickle | No |
YAML | Yes |
Changing data types of source columns
Normally, Airbyte tries to infer the data type from the source, but you can use reader_options
to force specific data types. If you input {"dtype":"string"}
, all columns will be forced to be parsed as strings. If you only want a specific column to be parsed as a string, simply use {"dtype" : {"column name": "string"}}
.
Examples
Here are a list of examples of possible file inputs:
Dataset Name | Storage | URL | Reader Impl | Service Account | Description |
---|---|---|---|---|---|
epidemiology | HTTPS | https://storage.googleapis.com/covid19-open-data/v2/latest/epidemiology.csv | COVID-19 Public dataset on BigQuery | ||
hr_and_financials | GCS | gs://airbyte-vault/financial.csv | smart_open or gcfs | {"type": "service_account", "private_key_id": "XXXXXXXX", ...} | data from a private bucket, a service account is necessary |
landsat_index | GCS | gcp-public-data-landsat/index.csv.gz | smart_open | Using smart_open, we don't need to specify the compression (note the gs:// is optional too, same for other providers) |
Examples with reader options:
Dataset Name | Storage | URL | Reader Impl | Reader Options | Description |
---|---|---|---|---|---|
landsat_index | GCS | gs://gcp-public-data-landsat/index.csv.gz | GCFS | {"compression": "gzip"} | Additional reader options to specify a compression option to read_csv |
GDELT | S3 | s3://gdelt-open-data/events/20190914.export.csv | {"sep": "\t", "header": null} | Here is TSV data separated by tabs without header row from AWS Open Data | |
server_logs | local | /local/logs.log | {"sep": ";"} | After making sure a local text file exists at /tmp/airbyte_local/logs.log with logs file from some server that are delimited by ';' delimiters |
Example for SFTP:
Dataset Name | Storage | User | Password | Host | URL | Reader Options | Description |
---|---|---|---|---|---|---|---|
Test Rebext | SFTP | demo | password | test.rebext.net | /pub/example/readme.txt | {"sep": "\r\n", "header": null, "names": ["text"], "engine": "python"} | We use python engine for read_csv in order to handle delimiter of more than 1 character while providing our own column names. |
Please see (or add) more at airbyte-integrations/connectors/source-file/integration_tests/integration_source_test.py
for further usages examples.
Performance Considerations and Notes
In order to read large files from a remote location, this connector uses the smart_open library. However, it is possible to switch to either GCSFS or S3FS implementations as it is natively supported by the pandas
library. This choice is made possible through the optional reader_impl
parameter.
- Note that for local filesystem, the file probably have to be stored somewhere in the
/tmp/airbyte_local
folder with the same limitations as the CSV Destination so theURL
should also starts with/local/
. - Please make sure that Docker Desktop has access to
/tmp
(and/private
on a MacOS, as /tmp has a symlink that points to /private. It will not work otherwise). You allow it with "File sharing" inSettings -> Resources -> File sharing -> add the one or two above folder
and hit the "Apply & restart" button. - The JSON implementation needs to be tweaked in order to produce more complex catalog and is still in an experimental state: Simple JSON schemas should work at this point but may not be well handled when there are multiple layers of nesting.
Changelog
Version | Date | Pull Request | Subject |
---|---|---|---|
0.3.9 | 2023-05-18 | 26275 | add ParserError handling |
0.3.8 | 2023-05-17 | 26210 | Bugfix for https://github.com/airbytehq/airbyte/pull/26115 |
0.3.7 | 2023-05-16 | 26131 | Re-release source-file to be in sync with source-file-secure |
0.3.6 | 2023-05-16 | 26115 | Add retry on SSHException('Error reading SSH protocol banner') |
0.3.5 | 2023-05-16 | 26117 | Check if reader options is a valid JSON object |
0.3.4 | 2023-05-10 | 25965 | fix Pandas date-time parsing to airbyte type |
0.3.3 | 2023-05-04 | 25819 | GCP service_account_json is a secret |
0.3.2 | 2023-05-01 | 25641 | Handle network errors |
0.3.1 | 2023-04-27 | 25575 | Fix OOM; read Excel files in chunks using openpyxl |
0.3.0 | 2023-04-24 | 25445 | Add datatime format parsing support for csv files |
0.2.38 | 2023-04-12 | 23759 | Fix column data types for numerical values |
0.2.37 | 2023-04-06 | 24525 | Fix examples in spec |
0.2.36 | 2023-03-27 | 24588 | Remove traceback from user messages. |
0.2.35 | 2023-03-03 | 24278 | Read only file header when checking connectivity; read only a single chunk when discovering the schema. |
0.2.34 | 2023-03-03 | 23723 | Update description in spec, make user-friendly error messages and docs. |
0.2.33 | 2023-01-04 | 21012 | Fix special characters bug |
0.2.32 | 2022-12-21 | 20740 | Source File: increase SSH timeout to 60s |
0.2.31 | 2022-11-17 | 19567 | Source File: bump 0.2.31 |
0.2.30 | 2022-11-10 | 19222 | Use AirbyteConnectionStatus for "check" command |
0.2.29 | 2022-11-08 | 18587 | Fix pandas read_csv header none issue. |
0.2.28 | 2022-10-27 | 18428 | Add retry logic for Connection reset error - 104 |
0.2.27 | 2022-10-26 | 18481 | Fix check for wrong format |
0.2.26 | 2022-10-18 | 18116 | Transform Dropbox shared link |
0.2.25 | 2022-10-14 | 17994 | Handle UnicodeDecodeError during discover step. |
0.2.24 | 2022-10-03 | 17504 | Validate data for HTTPS while check_connection |
0.2.23 | 2022-09-28 | 17304 | Migrate to per-stream state. |
0.2.22 | 2022-09-15 | 16772 | Fix schema generation for JSON files containing arrays |
0.2.21 | 2022-08-26 | 15568 | Specify pyxlsb library for Excel Binary Workbook files |
0.2.20 | 2022-08-23 | 15870 | Fix CSV schema discovery |
0.2.19 | 2022-08-19 | 15768 | Convert 'nan' to 'null' |
0.2.18 | 2022-08-16 | 15698 | Cache binary stream to file for discover |
0.2.17 | 2022-08-11 | 15501 | Cache binary stream to file |
0.2.16 | 2022-08-10 | 15293 | Add support for encoding reader option |
0.2.15 | 2022-08-05 | 15269 | Bump smart-open version to 6.0.0 |
0.2.12 | 2022-07-12 | 14535 | Fix invalid schema generation for JSON files |
0.2.11 | 2022-07-12 | 9974 | Add support to YAML format |
0.2.9 | 2022-02-01 | 9974 | Update airbyte-cdk 0.1.47 |
0.2.8 | 2021-12-06 | 8524 | Update connector fields title/description |
0.2.7 | 2021-10-28 | 7387 | Migrate source to CDK structure, add SAT testing. |
0.2.6 | 2021-08-26 | 5613 | Add support to xlsb format |
0.2.5 | 2021-07-26 | 4953 | Allow non-default port for SFTP type |
0.2.4 | 2021-06-09 | 3973 | Add AIRBYTE_ENTRYPOINT for Kubernetes support |
0.2.3 | 2021-06-01 | 3771 | Add Azure Storage Blob Files option |
0.2.2 | 2021-04-16 | 2883 | Fix CSV discovery memory consumption |
0.2.1 | 2021-04-03 | 2726 | Fix base connector versioning |
0.2.0 | 2021-03-09 | 2238 | Protocol allows future/unknown properties |
0.1.10 | 2021-02-18 | 2118 | Support JSONL format |
0.1.9 | 2021-02-02 | 1768 | Add test cases for all formats |
0.1.8 | 2021-01-27 | 1738 | Adopt connector best practices |
0.1.7 | 2020-12-16 | 1331 | Refactor Python base connector |
0.1.6 | 2020-12-08 | 1249 | Handle NaN values |
0.1.5 | 2020-11-30 | 1046 | Add connectors using an index YAML file |