%global _empty_manifest_terminate_build 0
Name: python-airtable-export
Version: 0.7.1
Release: 1
Summary: Export Airtable data to files on disk
License: Apache License, Version 2.0
URL: https://github.com/simonw/airtable-export
Source0: https://mirrors.aliyun.com/pypi/web/packages/d4/4f/897f00a5cc50baccd793027554b5e5b094109e8e69167da22a13316fa34a/airtable-export-0.7.1.tar.gz
BuildArch: noarch
Requires: python3-click
Requires: python3-PyYAML
Requires: python3-httpx
Requires: python3-sqlite-utils
Requires: python3-pytest
Requires: python3-pytest-mock
%description
# airtable-export
[](https://pypi.org/project/airtable-export/)
[](https://github.com/simonw/airtable-export/releases)
[](https://github.com/simonw/airtable-export/actions?query=workflow%3ATest)
[](https://github.com/simonw/airtable-export/blob/master/LICENSE)
Export Airtable data to files on disk
## Installation
Install this tool using `pip`:
$ pip install airtable-export
## Usage
You will need to know the following information:
- Your Airtable base ID - this is a string starting with `app...`
- Your Airtable API key - this is a string starting with `key...`
- The names of each of the tables that you wish to export
You can export all of your data to a folder called `export/` by running the following:
airtable-export export base_id table1 table2 --key=key
This example would create two files: `export/table1.yml` and `export/table2.yml`.
Rather than passing the API key using the `--key` option you can set it as an environment variable called `AIRTABLE_KEY`.
## Export options
By default the tool exports your data as YAML.
You can also export as JSON or as [newline delimited JSON](http://ndjson.org/) using the `--json` or `--ndjson` options:
airtable-export export base_id table1 table2 --key=key --ndjson
You can pass multiple format options at once. This command will create a `.json`, `.yml` and `.ndjson` file for each exported table:
airtable-export export base_id table1 table2 \
--key=key --ndjson --yaml --json
### SQLite database export
You can export tables to a SQLite database file using the `--sqlite database.db` option:
airtable-export export base_id table1 table2 \
--key=key --sqlite database.db
This can be combined with other format options. If you only specify `--sqlite` the export directory argument will be ignored.
The SQLite database will have a table created for each table you export. Those tables will have a primary key column called `airtable_id`.
If you run this command against an existing SQLite database records with matching primary keys will be over-written by new records from the export.
## Request options
By default the tool uses [python-httpx](https://www.python-httpx.org)'s default configurations.
You can override the `user-agent` using the `--user-agent` option:
airtable-export export base_id table1 table2 --key=key --user-agent "Airtable Export Robot"
You can override the [timeout during a network read operation](https://www.python-httpx.org/advanced/#fine-tuning-the-configuration) using the `--http-read-timeout` option. If not set, this defaults to 5s.
airtable-export export base_id table1 table2 --key=key --http-read-timeout 60
## Running this using GitHub Actions
[GitHub Actions](https://github.com/features/actions) is GitHub's workflow automation product. You can use it to run `airtable-export` in order to back up your Airtable data to a GitHub repository. Doing this gives you a visible commit history of changes you make to your Airtable data - like [this one](https://github.com/natbat/rockybeaches/commits/main/airtable).
To run this for your own Airtable database you'll first need to add the following secrets to your GitHub repository:
- AIRTABLE_BASE_ID
- The base ID, a string beginning `app...`
- AIRTABLE_KEY
- Your Airtable API key
- AIRTABLE_TABLES
- A space separated list of the Airtable tables that you want to backup. If any of these contain spaces you will need to enclose them in single quotes, e.g. 'My table with spaces in the name' OtherTableWithNoSpaces
Once you have set those secrets, add the following as a file called `.github/workflows/backup-airtable.yml`:
```yaml
name: Backup Airtable
on:
workflow_dispatch:
schedule:
- cron: '32 0 * * *'
jobs:
build:
runs-on: ubuntu-latest
steps:
- name: Check out repo
uses: actions/checkout@v2
- name: Set up Python
uses: actions/setup-python@v2
with:
python-version: 3.8
- uses: actions/cache@v2
name: Configure pip caching
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-
restore-keys: |
${{ runner.os }}-pip-
- name: Install airtable-export
run: |
pip install airtable-export
- name: Backup Airtable to backups/
env:
AIRTABLE_BASE_ID: ${{ secrets.AIRTABLE_BASE_ID }}
AIRTABLE_KEY: ${{ secrets.AIRTABLE_KEY }}
AIRTABLE_TABLES: ${{ secrets.AIRTABLE_TABLES }}
run: |-
airtable-export backups $AIRTABLE_BASE_ID $AIRTABLE_TABLES -v
- name: Commit and push if it changed
run: |-
git config user.name "Automated"
git config user.email "actions@users.noreply.github.com"
git add -A
timestamp=$(date -u)
git commit -m "Latest data: ${timestamp}" || exit 0
git push
```
This will run once a day (at 32 minutes past midnight UTC) and will also run if you manually click the "Run workflow" button, see [GitHub Actions: Manual triggers with workflow_dispatch](https://github.blog/changelog/2020-07-06-github-actions-manual-triggers-with-workflow_dispatch/).
## Development
To contribute to this tool, first checkout the code. Then create a new virtual environment:
cd airtable-export
python -mvenv venv
source venv/bin/activate
Or if you are using `pipenv`:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
%package -n python3-airtable-export
Summary: Export Airtable data to files on disk
Provides: python-airtable-export
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-airtable-export
# airtable-export
[](https://pypi.org/project/airtable-export/)
[](https://github.com/simonw/airtable-export/releases)
[](https://github.com/simonw/airtable-export/actions?query=workflow%3ATest)
[](https://github.com/simonw/airtable-export/blob/master/LICENSE)
Export Airtable data to files on disk
## Installation
Install this tool using `pip`:
$ pip install airtable-export
## Usage
You will need to know the following information:
- Your Airtable base ID - this is a string starting with `app...`
- Your Airtable API key - this is a string starting with `key...`
- The names of each of the tables that you wish to export
You can export all of your data to a folder called `export/` by running the following:
airtable-export export base_id table1 table2 --key=key
This example would create two files: `export/table1.yml` and `export/table2.yml`.
Rather than passing the API key using the `--key` option you can set it as an environment variable called `AIRTABLE_KEY`.
## Export options
By default the tool exports your data as YAML.
You can also export as JSON or as [newline delimited JSON](http://ndjson.org/) using the `--json` or `--ndjson` options:
airtable-export export base_id table1 table2 --key=key --ndjson
You can pass multiple format options at once. This command will create a `.json`, `.yml` and `.ndjson` file for each exported table:
airtable-export export base_id table1 table2 \
--key=key --ndjson --yaml --json
### SQLite database export
You can export tables to a SQLite database file using the `--sqlite database.db` option:
airtable-export export base_id table1 table2 \
--key=key --sqlite database.db
This can be combined with other format options. If you only specify `--sqlite` the export directory argument will be ignored.
The SQLite database will have a table created for each table you export. Those tables will have a primary key column called `airtable_id`.
If you run this command against an existing SQLite database records with matching primary keys will be over-written by new records from the export.
## Request options
By default the tool uses [python-httpx](https://www.python-httpx.org)'s default configurations.
You can override the `user-agent` using the `--user-agent` option:
airtable-export export base_id table1 table2 --key=key --user-agent "Airtable Export Robot"
You can override the [timeout during a network read operation](https://www.python-httpx.org/advanced/#fine-tuning-the-configuration) using the `--http-read-timeout` option. If not set, this defaults to 5s.
airtable-export export base_id table1 table2 --key=key --http-read-timeout 60
## Running this using GitHub Actions
[GitHub Actions](https://github.com/features/actions) is GitHub's workflow automation product. You can use it to run `airtable-export` in order to back up your Airtable data to a GitHub repository. Doing this gives you a visible commit history of changes you make to your Airtable data - like [this one](https://github.com/natbat/rockybeaches/commits/main/airtable).
To run this for your own Airtable database you'll first need to add the following secrets to your GitHub repository:
- AIRTABLE_BASE_ID
- The base ID, a string beginning `app...`
- AIRTABLE_KEY
- Your Airtable API key
- AIRTABLE_TABLES
- A space separated list of the Airtable tables that you want to backup. If any of these contain spaces you will need to enclose them in single quotes, e.g. 'My table with spaces in the name' OtherTableWithNoSpaces
Once you have set those secrets, add the following as a file called `.github/workflows/backup-airtable.yml`:
```yaml
name: Backup Airtable
on:
workflow_dispatch:
schedule:
- cron: '32 0 * * *'
jobs:
build:
runs-on: ubuntu-latest
steps:
- name: Check out repo
uses: actions/checkout@v2
- name: Set up Python
uses: actions/setup-python@v2
with:
python-version: 3.8
- uses: actions/cache@v2
name: Configure pip caching
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-
restore-keys: |
${{ runner.os }}-pip-
- name: Install airtable-export
run: |
pip install airtable-export
- name: Backup Airtable to backups/
env:
AIRTABLE_BASE_ID: ${{ secrets.AIRTABLE_BASE_ID }}
AIRTABLE_KEY: ${{ secrets.AIRTABLE_KEY }}
AIRTABLE_TABLES: ${{ secrets.AIRTABLE_TABLES }}
run: |-
airtable-export backups $AIRTABLE_BASE_ID $AIRTABLE_TABLES -v
- name: Commit and push if it changed
run: |-
git config user.name "Automated"
git config user.email "actions@users.noreply.github.com"
git add -A
timestamp=$(date -u)
git commit -m "Latest data: ${timestamp}" || exit 0
git push
```
This will run once a day (at 32 minutes past midnight UTC) and will also run if you manually click the "Run workflow" button, see [GitHub Actions: Manual triggers with workflow_dispatch](https://github.blog/changelog/2020-07-06-github-actions-manual-triggers-with-workflow_dispatch/).
## Development
To contribute to this tool, first checkout the code. Then create a new virtual environment:
cd airtable-export
python -mvenv venv
source venv/bin/activate
Or if you are using `pipenv`:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
%package help
Summary: Development documents and examples for airtable-export
Provides: python3-airtable-export-doc
%description help
# airtable-export
[](https://pypi.org/project/airtable-export/)
[](https://github.com/simonw/airtable-export/releases)
[](https://github.com/simonw/airtable-export/actions?query=workflow%3ATest)
[](https://github.com/simonw/airtable-export/blob/master/LICENSE)
Export Airtable data to files on disk
## Installation
Install this tool using `pip`:
$ pip install airtable-export
## Usage
You will need to know the following information:
- Your Airtable base ID - this is a string starting with `app...`
- Your Airtable API key - this is a string starting with `key...`
- The names of each of the tables that you wish to export
You can export all of your data to a folder called `export/` by running the following:
airtable-export export base_id table1 table2 --key=key
This example would create two files: `export/table1.yml` and `export/table2.yml`.
Rather than passing the API key using the `--key` option you can set it as an environment variable called `AIRTABLE_KEY`.
## Export options
By default the tool exports your data as YAML.
You can also export as JSON or as [newline delimited JSON](http://ndjson.org/) using the `--json` or `--ndjson` options:
airtable-export export base_id table1 table2 --key=key --ndjson
You can pass multiple format options at once. This command will create a `.json`, `.yml` and `.ndjson` file for each exported table:
airtable-export export base_id table1 table2 \
--key=key --ndjson --yaml --json
### SQLite database export
You can export tables to a SQLite database file using the `--sqlite database.db` option:
airtable-export export base_id table1 table2 \
--key=key --sqlite database.db
This can be combined with other format options. If you only specify `--sqlite` the export directory argument will be ignored.
The SQLite database will have a table created for each table you export. Those tables will have a primary key column called `airtable_id`.
If you run this command against an existing SQLite database records with matching primary keys will be over-written by new records from the export.
## Request options
By default the tool uses [python-httpx](https://www.python-httpx.org)'s default configurations.
You can override the `user-agent` using the `--user-agent` option:
airtable-export export base_id table1 table2 --key=key --user-agent "Airtable Export Robot"
You can override the [timeout during a network read operation](https://www.python-httpx.org/advanced/#fine-tuning-the-configuration) using the `--http-read-timeout` option. If not set, this defaults to 5s.
airtable-export export base_id table1 table2 --key=key --http-read-timeout 60
## Running this using GitHub Actions
[GitHub Actions](https://github.com/features/actions) is GitHub's workflow automation product. You can use it to run `airtable-export` in order to back up your Airtable data to a GitHub repository. Doing this gives you a visible commit history of changes you make to your Airtable data - like [this one](https://github.com/natbat/rockybeaches/commits/main/airtable).
To run this for your own Airtable database you'll first need to add the following secrets to your GitHub repository:
- AIRTABLE_BASE_ID
- The base ID, a string beginning `app...`
- AIRTABLE_KEY
- Your Airtable API key
- AIRTABLE_TABLES
- A space separated list of the Airtable tables that you want to backup. If any of these contain spaces you will need to enclose them in single quotes, e.g. 'My table with spaces in the name' OtherTableWithNoSpaces
Once you have set those secrets, add the following as a file called `.github/workflows/backup-airtable.yml`:
```yaml
name: Backup Airtable
on:
workflow_dispatch:
schedule:
- cron: '32 0 * * *'
jobs:
build:
runs-on: ubuntu-latest
steps:
- name: Check out repo
uses: actions/checkout@v2
- name: Set up Python
uses: actions/setup-python@v2
with:
python-version: 3.8
- uses: actions/cache@v2
name: Configure pip caching
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-
restore-keys: |
${{ runner.os }}-pip-
- name: Install airtable-export
run: |
pip install airtable-export
- name: Backup Airtable to backups/
env:
AIRTABLE_BASE_ID: ${{ secrets.AIRTABLE_BASE_ID }}
AIRTABLE_KEY: ${{ secrets.AIRTABLE_KEY }}
AIRTABLE_TABLES: ${{ secrets.AIRTABLE_TABLES }}
run: |-
airtable-export backups $AIRTABLE_BASE_ID $AIRTABLE_TABLES -v
- name: Commit and push if it changed
run: |-
git config user.name "Automated"
git config user.email "actions@users.noreply.github.com"
git add -A
timestamp=$(date -u)
git commit -m "Latest data: ${timestamp}" || exit 0
git push
```
This will run once a day (at 32 minutes past midnight UTC) and will also run if you manually click the "Run workflow" button, see [GitHub Actions: Manual triggers with workflow_dispatch](https://github.blog/changelog/2020-07-06-github-actions-manual-triggers-with-workflow_dispatch/).
## Development
To contribute to this tool, first checkout the code. Then create a new virtual environment:
cd airtable-export
python -mvenv venv
source venv/bin/activate
Or if you are using `pipenv`:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
%prep
%autosetup -n airtable-export-0.7.1
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-airtable-export -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot - 0.7.1-1
- Package Spec generated